Manual Back-Testing; Practicing the Art of Trading

H1 Backtest of ParallaxFX's BBStoch system

Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are.
TL;DR at the bottom for those not interested in the details.
This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.

Background

For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX!
I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose.
This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem.
I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.

System Details

I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:

And now for the fun. Results!

As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker.
EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.

A Note on Spread

As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits.
Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way).
However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades.
You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term.
Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.

Time of Day

Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either.
On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate.
That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.

Moving stops up to breakeven

This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers.
Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability.
One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)?
Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right?
Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert.
I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall.
The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.

2-Candle vs Confirmation Candle Stops

Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it.
Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL.
Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.

Correlated Trades

As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular.
Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system.
This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here).
Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses.
Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels).
Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant.
One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak.
EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much.
I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system.
This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions.
There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated.
I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful.
Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.

What I will trade

Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
Looking at the data for these rules, test results are:
I'll be sure to let everyone know how it goes!

Other Technical Details

Raw Data

Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.)
I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.

Insanely detailed spreadsheet notes

For you real nerds out there. Here's an explanation of what each column means:

Pairs

  1. AUD/CAD
  2. AUD/CHF
  3. AUD/JPY
  4. AUD/NZD
  5. AUD/USD
  6. CAD/CHF
  7. CAD/JPY
  8. CHF/JPY
  9. EUAUD
  10. EUCAD
  11. EUCHF
  12. EUGBP
  13. EUJPY
  14. EUNZD
  15. EUUSD
  16. GBP/AUD
  17. GBP/CAD
  18. GBP/CHF
  19. GBP/JPY
  20. GBP/NZD
  21. GBP/USD
  22. NZD/CAD
  23. NZD/CHF
  24. NZD/JPY
  25. NZD/USD
  26. USD/CAD
  27. USD/CHF
  28. USD/JPY

TL;DR

Based on the reasonable rules I discovered in this backtest:
submitted by ForexBorex to Forex [link] [comments]

Everything You Always Wanted To Know About Swaps* (*But Were Afraid To Ask)

Hello, dummies
It's your old pal, Fuzzy.
As I'm sure you've all noticed, a lot of the stuff that gets posted here is - to put it delicately - fucking ridiculous. More backwards-ass shit gets posted to wallstreetbets than you'd see on a Westboro Baptist community message board. I mean, I had a look at the daily thread yesterday and..... yeesh. I know, I know. We all make like the divine Laura Dern circa 1992 on the daily and stick our hands deep into this steaming heap of shit to find the nuggets of valuable and/or hilarious information within (thanks for reading, BTW). I agree. I love it just the way it is too. That's what makes WSB great.
What I'm getting at is that a lot of the stuff that gets posted here - notwithstanding it being funny or interesting - is just... wrong. Like, fucking your cousin wrong. And to be clear, I mean the fucking your *first* cousin kinda wrong, before my Southerners in the back get all het up (simmer down, Billy Ray - I know Mabel's twice removed on your grand-sister's side). Truly, I try to let it slide. I do my bit to try and put you on the right path. Most of the time, I sleep easy no matter how badly I've seen someone explain what a bank liquidity crisis is. But out of all of those tens of thousands of misguided, autistic attempts at understanding the world of high finance, one thing gets so consistently - so *emphatically* - fucked up and misunderstood by you retards that last night I felt obligated at the end of a long work day to pull together this edition of Finance with Fuzzy just for you. It's so serious I'm not even going to make a u/pokimane gag. Have you guessed what it is yet? Here's a clue. It's in the title of the post.
That's right, friends. Today in the neighborhood we're going to talk all about hedging in financial markets - spots, swaps, collars, forwards, CDS, synthetic CDOs, all that fun shit. Don't worry; I'm going to explain what all the scary words mean and how they impact your OTM RH positions along the way.
We're going to break it down like this. (1) "What's a hedge, Fuzzy?" (2) Common Hedging Strategies and (3) All About ISDAs and Credit Default Swaps.
Before we begin. For the nerds and JV traders in the back (and anyone else who needs to hear this up front) - I am simplifying these descriptions for the purposes of this post. I am also obviously not going to try and cover every exotic form of hedge under the sun or give a detailed summation of what caused the financial crisis. If you are interested in something specific ask a question, but don't try and impress me with your Investopedia skills or technical points I didn't cover; I will just be forced to flex my years of IRL experience on you in the comments and you'll look like a big dummy.
TL;DR? Fuck you. There is no TL;DR. You've come this far already. What's a few more paragraphs? Put down the Cheetos and try to concentrate for the next 5-7 minutes. You'll learn something, and I promise I'll be gentle.
Ready? Let's get started.
1. The Tao of Risk: Hedging as a Way of Life
The simplest way to characterize what a hedge 'is' is to imagine every action having a binary outcome. One is bad, one is good. Red lines, green lines; uppie, downie. With me so far? Good. A 'hedge' is simply the employment of a strategy to mitigate the effect of your action having the wrong binary outcome. You wanted X, but you got Z! Frowny face. A hedge strategy introduces a third outcome. If you hedged against the possibility of Z happening, then you can wind up with Y instead. Not as good as X, but not as bad as Z. The technical definition I like to give my idiot juniors is as follows:
Utilization of a defensive strategy to mitigate risk, at a fraction of the cost to capital of the risk itself.
Congratulations. You just finished Hedging 101. "But Fuzzy, that's easy! I just sold a naked call against my 95% OTM put! I'm adequately hedged!". Spoiler alert: you're not (although good work on executing a collar, which I describe below). What I'm talking about here is what would be referred to as a 'perfect hedge'; a binary outcome where downside is totally mitigated by a risk management strategy. That's not how it works IRL. Pay attention; this is the tricky part.
You can't take a single position and conclude that you're adequately hedged because risks are fluid, not static. So you need to constantly adjust your position in order to maximize the value of the hedge and insure your position. You also need to consider exposure to more than one category of risk. There are micro (specific exposure) risks, and macro (trend exposure) risks, and both need to factor into the hedge calculus.
That's why, in the real world, the value of hedging depends entirely on the design of the hedging strategy itself. Here, when we say "value" of the hedge, we're not talking about cash money - we're talking about the intrinsic value of the hedge relative to the the risk profile of your underlying exposure. To achieve this, people hedge dynamically. In wallstreetbets terms, this means that as the value of your position changes, you need to change your hedges too. The idea is to efficiently and continuously distribute and rebalance risk across different states and periods, taking value from states in which the marginal cost of the hedge is low and putting it back into states where marginal cost of the hedge is high, until the shadow value of your underlying exposure is equalized across your positions. The punchline, I guess, is that one static position is a hedge in the same way that the finger paintings you make for your wife's boyfriend are art - it's technically correct, but you're only playing yourself by believing it.
Anyway. Obviously doing this as a small potatoes trader is hard but it's worth taking into account. Enough basic shit. So how does this work in markets?
2. A Hedging Taxonomy
The best place to start here is a practical question. What does a business need to hedge against? Think about the specific risk that an individual business faces. These are legion, so I'm just going to list a few of the key ones that apply to most corporates. (1) You have commodity risk for the shit you buy or the shit you use. (2) You have currency risk for the money you borrow. (3) You have rate risk on the debt you carry. (4) You have offtake risk for the shit you sell. Complicated, right? To help address the many and varied ways that shit can go wrong in a sophisticated market, smart operators like yours truly have devised a whole bundle of different instruments which can help you manage the risk. I might write about some of the more complicated ones in a later post if people are interested (CDO/CLOs, strip/stack hedges and bond swaps with option toggles come to mind) but let's stick to the basics for now.
(i) Swaps
A swap is one of the most common forms of hedge instrument, and they're used by pretty much everyone that can afford them. The language is complicated but the concept isn't, so pay attention and you'll be fine. This is the most important part of this section so it'll be the longest one.
Swaps are derivative contracts with two counterparties (before you ask, you can't trade 'em on an exchange - they're OTC instruments only). They're used to exchange one cash flow for another cash flow of equal expected value; doing this allows you to take speculative positions on certain financial prices or to alter the cash flows of existing assets or liabilities within a business. "Wait, Fuzz; slow down! What do you mean sets of cash flows?". Fear not, little autist. Ol' Fuzz has you covered.
The cash flows I'm talking about are referred to in swap-land as 'legs'. One leg is fixed - a set payment that's the same every time it gets paid - and the other is variable - it fluctuates (typically indexed off the price of the underlying risk that you are speculating on / protecting against). You set it up at the start so that they're notionally equal and the two legs net off; so at open, the swap is a zero NPV instrument. Here's where the fun starts. If the price that you based the variable leg of the swap on changes, the value of the swap will shift; the party on the wrong side of the move ponies up via the variable payment. It's a zero sum game.
I'll give you an example using the most vanilla swap around; an interest rate trade. Here's how it works. You borrow money from a bank, and they charge you a rate of interest. You lock the rate up front, because you're smart like that. But then - quelle surprise! - the rate gets better after you borrow. Now you're bagholding to the tune of, I don't know, 5 bps. Doesn't sound like much but on a billion dollar loan that's a lot of money (a classic example of the kind of 'small, deep hole' that's terrible for profits). Now, if you had a swap contract on the rate before you entered the trade, you're set; if the rate goes down, you get a payment under the swap. If it goes up, whatever payment you're making to the bank is netted off by the fact that you're borrowing at a sub-market rate. Win-win! Or, at least, Lose Less / Lose Less. That's the name of the game in hedging.
There are many different kinds of swaps, some of which are pretty exotic; but they're all different variations on the same theme. If your business has exposure to something which fluctuates in price, you trade swaps to hedge against the fluctuation. The valuation of swaps is also super interesting but I guarantee you that 99% of you won't understand it so I'm not going to try and explain it here although I encourage you to google it if you're interested.
Because they're OTC, none of them are filed publicly. Someeeeeetimes you see an ISDA (dsicussed below) but the confirms themselves (the individual swaps) are not filed. You can usually read about the hedging strategy in a 10-K, though. For what it's worth, most modern credit agreements ban speculative hedging. Top tip: This is occasionally something worth checking in credit agreements when you invest in businesses that are debt issuers - being able to do this increases the risk profile significantly and is particularly important in times of economic volatility (ctrl+f "non-speculative" in the credit agreement to be sure).
(ii) Forwards
A forward is a contract made today for the future delivery of an asset at a pre-agreed price. That's it. "But Fuzzy! That sounds just like a futures contract!". I know. Confusing, right? Just like a futures trade, forwards are generally used in commodity or forex land to protect against price fluctuations. The differences between forwards and futures are small but significant. I'm not going to go into super boring detail because I don't think many of you are commodities traders but it is still an important thing to understand even if you're just an RH jockey, so stick with me.
Just like swaps, forwards are OTC contracts - they're not publicly traded. This is distinct from futures, which are traded on exchanges (see The Ballad Of Big Dick Vick for some more color on this). In a forward, no money changes hands until the maturity date of the contract when delivery and receipt are carried out; price and quantity are locked in from day 1. As you now know having read about BDV, futures are marked to market daily, and normally people close them out with synthetic settlement using an inverse position. They're also liquid, and that makes them easier to unwind or close out in case shit goes sideways.
People use forwards when they absolutely have to get rid of the thing they made (or take delivery of the thing they need). If you're a miner, or a farmer, you use this shit to make sure that at the end of the production cycle, you can get rid of the shit you made (and you won't get fucked by someone taking cash settlement over delivery). If you're a buyer, you use them to guarantee that you'll get whatever the shit is that you'll need at a price agreed in advance. Because they're OTC, you can also exactly tailor them to the requirements of your particular circumstances.
These contracts are incredibly byzantine (and there are even crazier synthetic forwards you can see in money markets for the true degenerate fund managers). In my experience, only Texan oilfield magnates, commodities traders, and the weirdo forex crowd fuck with them. I (i) do not own a 10 gallon hat or a novelty size belt buckle (ii) do not wake up in the middle of the night freaking out about the price of pork fat and (iii) love greenbacks too much to care about other countries' monopoly money, so I don't fuck with them.
(iii) Collars
No, not the kind your wife is encouraging you to wear try out to 'spice things up' in the bedroom during quarantine. Collars are actually the hedging strategy most applicable to WSB. Collars deal with options! Hooray!
To execute a basic collar (also called a wrapper by tea-drinking Brits and people from the Antipodes), you buy an out of the money put while simultaneously writing a covered call on the same equity. The put protects your position against price drops and writing the call produces income that offsets the put premium. Doing this limits your tendies (you can only profit up to the strike price of the call) but also writes down your risk. If you screen large volume trades with a VOL/OI of more than 3 or 4x (and they're not bullshit biotech stocks), you can sometimes see these being constructed in real time as hedge funds protect themselves on their shorts.
(3) All About ISDAs, CDS and Synthetic CDOs
You may have heard about the mythical ISDA. Much like an indenture (discussed in my post on $F), it's a magic legal machine that lets you build swaps via trade confirms with a willing counterparty. They are very complicated legal documents and you need to be a true expert to fuck with them. Fortunately, I am, so I do. They're made of two parts; a Master (which is a form agreement that's always the same) and a Schedule (which amends the Master to include your specific terms). They are also the engine behind just about every major credit crunch of the last 10+ years.
First - a brief explainer. An ISDA is a not in and of itself a hedge - it's an umbrella contract that governs the terms of your swaps, which you use to construct your hedge position. You can trade commodities, forex, rates, whatever, all under the same ISDA.
Let me explain. Remember when we talked about swaps? Right. So. You can trade swaps on just about anything. In the late 90s and early 2000s, people had the smart idea of using other people's debt and or credit ratings as the variable leg of swap documentation. These are called credit default swaps. I was actually starting out at a bank during this time and, I gotta tell you, the only thing I can compare people's enthusiasm for this shit to was that moment in your early teens when you discover jerking off. Except, unlike your bathroom bound shame sessions to Mom's Sears catalogue, every single person you know felt that way too; and they're all doing it at once. It was a fiscal circlejerk of epic proportions, and the financial crisis was the inevitable bukkake finish. WSB autism is absolutely no comparison for the enthusiasm people had during this time for lighting each other's money on fire.
Here's how it works. You pick a company. Any company. Maybe even your own! And then you write a swap. In the swap, you define "Credit Event" with respect to that company's debt as the variable leg . And you write in... whatever you want. A ratings downgrade, default under the docs, failure to meet a leverage ratio or FCCR for a certain testing period... whatever. Now, this started out as a hedge position, just like we discussed above. The purest of intentions, of course. But then people realized - if bad shit happens, you make money. And banks... don't like calling in loans or forcing bankruptcies. Can you smell what the moral hazard is cooking?
Enter synthetic CDOs. CDOs are basically pools of asset backed securities that invest in debt (loans or bonds). They've been around for a minute but they got famous in the 2000s because a shitload of them containing subprime mortgage debt went belly up in 2008. This got a lot of publicity because a lot of sad looking rednecks got foreclosed on and were interviewed on CNBC. "OH!", the people cried. "Look at those big bad bankers buying up subprime loans! They caused this!". Wrong answer, America. The debt wasn't the problem. What a lot of people don't realize is that the real meat of the problem was not in regular way CDOs investing in bundles of shit mortgage debts in synthetic CDOs investing in CDS predicated on that debt. They're synthetic because they don't have a stake in the actual underlying debt; just the instruments riding on the coattails. The reason these are so popular (and remain so) is that smart structured attorneys and bankers like your faithful correspondent realized that an even more profitable and efficient way of building high yield products with limited downside was investing in instruments that profit from failure of debt and in instruments that rely on that debt and then hedging that exposure with other CDS instruments in paired trades, and on and on up the chain. The problem with doing this was that everyone wound up exposed to everybody else's books as a result, and when one went tits up, everybody did. Hence, recession, Basel III, etc. Thanks, Obama.
Heavy investment in CDS can also have a warping effect on the price of debt (something else that happened during the pre-financial crisis years and is starting to happen again now). This happens in three different ways. (1) Investors who previously were long on the debt hedge their position by selling CDS protection on the underlying, putting downward pressure on the debt price. (2) Investors who previously shorted the debt switch to buying CDS protection because the relatively illiquid debt (partic. when its a bond) trades at a discount below par compared to the CDS. The resulting reduction in short selling puts upward pressure on the bond price. (3) The delta in price and actual value of the debt tempts some investors to become NBTs (neg basis traders) who long the debt and purchase CDS protection. If traders can't take leverage, nothing happens to the price of the debt. If basis traders can take leverage (which is nearly always the case because they're holding a hedged position), they can push up or depress the debt price, goosing swap premiums etc. Anyway. Enough technical details.
I could keep going. This is a fascinating topic that is very poorly understood and explained, mainly because the people that caused it all still work on the street and use the same tactics today (it's also terribly taught at business schools because none of the teachers were actually around to see how this played out live). But it relates to the topic of today's lesson, so I thought I'd include it here.
Work depending, I'll be back next week with a covenant breakdown. Most upvoted ticker gets the post.
*EDIT 1\* In a total blowout, $PLAY won. So it's D&B time next week. Post will drop Monday at market open.
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When will we bottom out?

PART 2 : https://www.reddit.com/wallstreetbets/comments/g0sd44/what_is_the_bottom/
PART 3: https://www.reddit.com/wallstreetbets/comments/g2enz2/why_the_printer_must_continue/
Edit: By popular demand, the too long didn't read is now at the top
TL;DR
SPY 220p 11/20
This will likely be a multi-part series. It should be noted that I am no expert by any means, I'm actually quite new to this, it is just an elementary analysis of patterns in price and time. I am not a financial advisor, and this is not advice for a person to enter trades upon.
The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this DD, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. We will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The market is technically open 24-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy.
Some important terms to keep in mind:
§ Discrete – terminal points at the extremes of ranges
§ Secondary Discrete – quantified retracement or correction between two discrete
§ Longs (asset appreciation) and shorts (asset depreciation)
- Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
§ Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes because of levels of fear. Allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation.
Therefore, due to the relatively high volume on the 23rd of March, we can safely determine that a low WAS NOT reached.
§ VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend is imminent.
– Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw an uptrend line on the SPY chart, but it is possible to correctly draw a downtrend – indicating that the overall trend is downwards.
Now that we have determined that the overall trend is downwards, the next issue is the question of when SPY will bottom out.
Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will complete our analysis of time by measuring it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
Yearly Lows: 12/31/2000, 9/21/2001, 10/9/2002, 3/11/2003, 8/2/2004, 4/15/2005, 6/12/2006, 3/5/2007, 11/17/2008, 3/9/2009, 7/2/10, 10/3/11, 1/1/12, 1/1/13, 2/3/14, 9/28/15, 2/8/16, 1/3/17, 12/24/18, 6/3/19
Months: 1, 1, 1, 2, 2, 3, 3, 3, 4, 6, 6, 7, 8, 9, 9, 10, 10, 11, 12, 12
Days: 1, 1, 2, 2, 3, 3, 3, 3, 5, 8, 9, 9, 11, 12, 15, 17, 21, 24, 28, 31
Monthly Lows: 3/23, 2/28, 1/27, 12/3, 11/1, 10/2, 9/3, 8/5, 7/1, 6/3, 5/31, 4/1
Days: 1, 1, 1, 2, 3, 3, 3, 5, 23, 27, 27, 31
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points*.*
We see that SPY tends to have its lows between three major month clusters: 1-4, primarily March (which has actually occurred already this year), 6-9, averaged out to July, and 10-12, averaged out to November. Following the same methodology, we get the third and tenth days of the month as the likeliest days. However, evaluating the monthly lows for the past year, the end of the month has replaced the average of the tenth. Therefore, we have four primary dates for our histogram.
7/3/20, 7/27/20, and 11/3/20, 11/27/20 .
How do we narrow this group down with any accuracy? Let us average the days together to work with two dates - 7/15/20 and 11/15/20.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model – states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is April 14th of 2022. However, we can time-shift to other peaks and troughs to determine a date for this year. If we consider 1/28/2018 as a localized high and apply this model, we get 3/23/20 as a low - strikingly accurate. I have chosen the next localized high, 9/21/2018 to apply the model to. We achieve a date of 11/14/2020.
The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of the bear market - roughly speaking.
Therefore, our timeline looks like:
As we move forward in time, our predictions may be less accurate. It is important to keep in mind that this analysis will likely change and become more accurate as we factor in Terry Laundry’s T-Theory, the Bradley Cycle, a more sophisticated analysis of Bull and Bear Market Cycles, the Fundamental Investor Cyclic Approach, and Seasons and Half-Seasons.
I have also assumed that the audience believes in these models, which is not necessary. Anyone with free time may construct histograms and view these time models, determining for themselves what is accurate and what is not. Take a look at 1/28/2008, that localized high, and 2.15 years (1/4th of the sinusoidal wave of the model) later.
The question now is, what prices will SPY reach on 11/14? Where will we be at 7/28? What will happen on 4/14/22?
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Where is Bitcoin Going and When?

Where is Bitcoin Going and When?

The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.

Stock Market Crash

The Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.

Economic Analysis of Bitcoin

The reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.

Trading or Investing?

The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.

Technical Indicator Analysis of Bitcoin

Technical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
  • Volume – derived from the market itself, it is mostly irrelevant. The major problem with volume for stocks is that the US market open causes tremendous volume surges eradicating any intrinsic volume analysis. This does not occur with BTC, as it is open twenty-four-seven. At major highs and lows, the market is typically anemic. Most traders are not active at terminal discretes (peaks and troughs) because of levels of fear. Volume allows us confidence in time and price symmetry market inflection points, if we observe low volume at a foretold range of values. We can rationalize that an absolute discrete is usually only discovered and anticipated by very few traders. As the general market realizes it, a herd mentality will push the market in the direction favorable to defending it. Volume is also useful for swing trading, as chances for swing’s validity increases if an increase in volume is seen on and after the swing’s activation. Volume is steadily decreasing. Lows and highs are reached when volume is lower.
Therefore, due to the relatively high volume on the 12th of March, we can safely determine that a low for BTC was not reached.
  • VIX – Volatility Index, this technical indicator indicates level of fear by the amount of options-based “insurance” in portfolios. A low VIX environment, less than 20 for the S&P index, indicates a stable market with a possible uptrend. A high VIX, over 20, indicates a possible downtrend. VIX is essentially useless for BTC as BTC-based options do not exist. It allows us to predict the market low for $SPY, which will have an indirect impact on BTC in the short term, likely leading to the yearly low. However, it is equally important to see how VIX is changing over time, if it is decreasing or increasing, as that indicates increasing or decreasing fear. Low volatility allows high leverage without risk or rest. Occasionally, markets do rise with high VIX.
As VIX is unusually high, in the forties, we can be confident that a downtrend for the S&P 500 is imminent.
  • RSI (Relative Strength Index): The most important technical indicator, useful for determining highs and lows when time symmetry is not availing itself. Sometimes analysis of RSI can conflict in different time frames, easiest way to use it is when it is at extremes – either under 30 or over 70. Extremes can be used for filtering highs or lows based on time-and-price window calculations. Highly instructive as to major corrective clues and indicative of continued directional movement. Must determine if longer-term RSI values find support at same values as before. It is currently at 73.56.
  • Secondly, RSI may be used as a high or low filter, to observe the level that short-term RSI reaches in counter-trend corrections. Repetitions based on market movements based on RSI determine how long a trade should be held onto. Once a short term RSI reaches an extreme and stay there, the other RSI’s should gradually reach the same extremes. Once all RSI’s are at extreme highs, a trend confirmation should occur and RSI’s should drop to their midpoint.

Trend Definition Analysis of Bitcoin

Trend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.

Time Symmetry Analysis of Bitcoin

Time is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
  • Yearly Lows (last seven years): 1/1/13, 4/10/14, 1/15/15, 1/17/16, 1/1/17, 12/15/18, 2/6/19
  • Monthly Mode: 1, 1, 1, 1, 2, 4, 12
  • Daily Mode: 1, 1, 6, 10, 15, 15, 17
  • Monthly Lows (for the last year): 3/12/20 (10:00pm), 2/28/20 (7:09am), 1/2/20 (8:09pm), 12/18/19 (8:00am), 11/25/19 (1:00am), 10/24/19 (2:59am), 9/30/19 (2:59am), 8/29,19 (4:00am), 7/17/19 (7:59am), 6/4/19 (5:59pm), 5/1/19 (12:00am), 4/1/19 (12:00am)
  • Daily Lows Mode for those Months: 1, 1, 2, 4, 12, 17, 18, 24, 25, 28, 29, 30
  • Hourly Lows Mode for those Months (Military time): 0100, 0200, 0200, 0400, 0700, 0700, 0800, 1200, 1200, 1700, 2000, 2200
  • Minute Lows Mode for those Months: 00, 00, 00, 00, 00, 00, 09, 09, 59, 59, 59, 59
  • Day of the Week Lows (last twenty-six weeks):
Weighted Times are repetitions which appears multiple times within the same list, observed and accentuated once divided into relevant sections of the histogram. They are important in the presently defined trading time period and are similar to a mathematical mode with respect to a series. Phased times are essentially periodical patterns in histograms, though they do not guarantee inflection points
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
  • 2/14/20 – yearly high ($10372 USD)
  • 3/12/20 – yearly low thus far ($3858 USD)
  • 5/9/20 – T-Theory true yearly low (BTC between 4863 and 3569)
  • 5/26/20 – hashrate difficulty halvening
  • 11/14/20 – stock market low
  • 1/15/21 – yearly low for BTC, around $8528
  • 8/19/21 – end of stock bear market
  • 11/26/21 – eighteen months from halvening, average peak from halvenings (BTC begins rising from $3000 area to above $23,312)
  • 4/23/22 – all-time high
Taken from my blog: http://aliamin.info/2020/
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Forex Trading - Getting Started

Forex Trading: a Beginner's Guide
The forex market is the world's largest international currency trading market operating non-stop during the working week. Most forex trading is done by professionals such as bankers. Generally forex trading is done through a forex broker - but there is nothing to stop anyone trading currencies. Forex currency trading allows buyers and sellers to buy the currency they need for their business and sellers who have earned currency to exchange what they have for a more convenient currency. The world's largest banks dominate forex and according to a survey in The Wall Street Journal Europe, the ten most active traders who are engaged in forex trading account for almost 73% of trading volume.
However, a sizeable proportion of the remainder of forex trading is speculative with traders building up an investment which they wish to liquidate at some stage for profit. While a currency may increase or decrease in value relative to a wide range of currencies, all forex trading transactions are based upon currency pairs. So, although the Euro may be 'strong' against a basket of currencies, traders will be trading in just one currency pair and may simply concern themselves with the Euro/US Dollar ( EUUSD) ratio. Changes in relative values of currencies may be gradual or triggered by specific events such as are unfolding at the time of writing this - the toxic debt crisis.
Because the markets for currencies are global, the volumes traded every day are vast. For the large corporate investors, the great benefits of trading on Forex are:

From the point of view of the smaller trader there's lots of benefits too, such as:

How the forex Market Works
As forex is all about foreign exchange, all transactions are made up from a currency pair - say, for instance, the Euro and the US Dollar. The basic tool for trading forex is the exchange rate which is expressed as a ratio between the values of the two currencies such as EUUSD = 1.4086. This value, which is referred to as the 'forex rate' means that, at that particular time, one Euro would be worth 1.4086 US Dollars. This ratio is always expressed to 4 decimal places which means that you could see a forex rate of EUUSD = 1.4086 or EUUSD = 1.4087 but never EUUSD = 1.40865. The rightmost digit of this ratio is referred to as a 'pip'. So, a change from EUUSD = 1.4086 to EUUSD = 1.4088 would be referred to as a change of 2 pips. One pip, therefore is the smallest unit of trade.
With the forex rate at EUUSD = 1.4086, an investor purchasing 1000 Euros using dollars would pay $1,408.60. If the forex rate then changed to EUUSD = 1.5020, the investor could sell their 1000 Euros for $1,502.00 and bank the $93.40 as profit. If this doesn't seem to be large amount to you, you have to put the sum into context. With a rising or falling market, the forex rate does not simply change in a uniform way but oscillates and profits can be taken many times per day as a rate oscillates around a trend.
When you're expecting the value EUUSD to fall, you might trade the other way by selling Euros for dollars and buying then back when the forex rate has changed to your advantage.
Is forex Risky?
When you trade on forex as in any form of currency trading, you're in the business of currency speculation and it is just that - speculation. This means that there is some risk involved in forex currency trading as in any business but you might and should, take steps to minimise this. You can always set a limit to the downside of any trade, that means to define the maximum loss that you are prepared to accept if the market goes against you - and it will on occasions.
The best insurance against losing your shirt on the forex market is to set out to understand what you're doing totally. Search the internet for a good forex trading tutorial and study it in detail- a bit of good forex education can go a long way!. When there's bits you don't understand, look for a good forex trading forum and ask lots and lots of questions. Many of the people who habitually answer your queries on this will have a good forex trading blog and this will probably not only give you answers to your questions but also provide lots of links to good sites. Be vigilant, however, watch out for forex trading scams. Don't be too quick to part with your money and investigate anything very well before you shell out any hard-earned!
The forex Trading Systems
While you may be right in being cautious about any forex trading system that's advertised, there are some good ones around. Most of them either utilise forex charts and by means of these, identify forex trading signals which tell the trader when to buy or sell. These signals will be made up of a particular change in a forex rate or a trend and these will have been devised by a forex trader who has studied long-term trends in the market so as to identify valid signals when they occur. Many of the systems will use forex trading software which identifies such signals from data inputs which are gathered automatically from market information sources. Some utilise automated forex trading software which can trigger trades automatically when the signals tell it to do so. If these sound too good to be true to you, look around for online forex trading systems which will allow you undertake some dummy trading to test them out. by doing this you can get some forex trading training by giving them a spin before you put real money on the table.
How Much do you Need to Start off with?
This is a bit of a 'How long is a piece of string?' question but there are ways for to be beginner to dip a toe into the water without needing a fortune to start with. The minimum trading size for most trades on forex is usually 100,000 units of any currency and this volume is referred to as a standard "lot". However, there are many firms which offer the facility to purchase in dramatically-smaller lots than this and a bit of internet searching will soon locate these. There's many adverts quoting only a couple of hundred dollars to get going! You will often see the term acciones trading forex and this is just a general term which covers the small guy trading forex. Small-scale trading facilities such as these are often called as forex mini trading.
Where do You Start?
The single most obvious answer is of course - on the internet! Online forex trading gives you direct access to the forex market and there's lots and lots of companies out there who are in business just to deal with you online. Be vigilant, do spend the time to get some good forex trading education, again this can be provided online and set up your dummy account to trade before you attempt to go live. If you take care and take your time, there's no reason why you shouldn't be successful in forex trading so, have patience and stick at it!
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Making the jump: how to leave day job and concentrate on trading instead

Hi everyone...
I've been thinking about this topic for a while now but never really addressed it with some serious thought.
Currently I'm employed full time by a consulting firm and it's a nice job indeed (well payed, nice benefits, great colleagues, soon-to-become junior partner). Nevertheless I still feel it doesn't tick all the boxes for me:
That said, I'm starting to think a regular job will never fit with these requirements and I'm looking at alternatives: this is where trading comes in. I've been interested in trading for a few years now and my current situation on the topic is the following:
On one end I feel if only I could have enough time to focus and concentrate on this I think I might be successful, on the other end not I'm well aware I could easily lose all my money and the uncertainty of the income scares me.
As of now, I'm defining something that resambles a plan to jump ship and it looks like the following:
  1. Define starting capital i need before quitting my job (probably around 20k€ for the markets + 5k€ as rainy days fund)
  2. Define how much I need to make each month to survive and keep on trading (somewhere between 1.5k€/2k€ at least)
  3. Define "point of no return" (how much of said capital I'm ok to burn before reverting back to searching for a regular job)
  4. Feasibility check
  5. Define exit plan from current job
So, in order to converge to a conclusion, I need advice from people that may have found themeselves in my same spot. How did you make the jump? How did you cope with fear and uncertainty? How did you prepare to switch? Is there something major I'm missing?
Thanks for all your feedbacks!
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All You Need To Know About DochCoin As An Investment Scheme

All You Need To Know About DochCoin As An Investment Scheme


Doch Llc is a “FINTECH” company based out of Usa, which is into Fintech service, E — commerce, Crypto Exchanges, Direct selling and Forex trading. The DOTCH team is powered by tech savy enterpreneurs and its main objective is to make global footprint in a time bound manner, Doch management team is committed to provide its investors and clients unique global platform to explore financial world in a single click
Doch Concept To Commercialization
Birth Of A Concept : Discussion that defined the concept.
What are the performance parameters?
What are the technical requirements?
Can it be done successfully?
Development : We begin to move toward development where concepts are tested, theories and algorithms are validated .
Live Testing Phase : Live testing on exchanges to verify real life feasibility. This provides further validation which further reduce risk
Optimization & Continuous Product Improvement : Further work in understanding , Optimizing and improving the technology to reduce risks and provide for a more profit.

https://www.techng.com.ng/2020/05/all-you-need-to-know-about-dochcoin.html
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Overview of Algorithmic Trading Strategies

Strategies are a natural way to get the maximum benefit out of algorithmic Trading. Based on the duration of holding the investment, Algo Trading Strategies are classified as Long term and short-term strategies. Automated TradingTrading has been enhanced with specific rule-based decision making.
Long Term Strategies
  1. Pricing Strategies are more focused on the expected returns
  2. Mathematical model-based Strategies are developed purely based on mathematical calculations, models.
  3. Trend Based Strategies follow market trends. By using the statistics, patterns are studied, and further strategies are developed.
  4. Arbitrage strategies use algorithms to figure out price differences and trade according to opportunities for profit.
  5. VWAP (Volume Weighted Average Price) & strategies, break the large volume of stock into smaller and later issues them according to market conditions to earn more yield.
  6. Implementation shortfall strategy uses algorithms to target involvement in dealing when stock prices are high and vice versa.
Short-Term Strategies
Short term strategies are generally executed in Intraday Trading strategies, where assets are bought and sold on the same day. Here stocks are not purchased for investment purpose but to earn the profit by connecting with the stock market trend. Algo trading strategies are incorporated in Intraday Trading to reap more benefits. Following are the Intraday trading strategies using algorithmic TradingTrading:
  1. Reversal trading strategies use algorithms to find out the highest and lowest points of the day. Based on these points as the secure time, price and quantity start reversing; it gives alerts to either buy or sell the assets.
  2. Trend based strategies analyse the trends using Algorithms, and further strategy is developed.
  3. Bull flag trading strategy based on the highest peak and steady decrease in trend during the day. To get the target prices on the patterns of bull flag shape, algorithms are used. Based on these trends, ' strategies are developed.
  4. Pullback Trading Strategy develops the low-risk buying opportunity.
  5. Breakout trading strategy enables us to enter the market when prices change outside a specific range.
3 Efficient Intraday Trading Strategies Used in Algorithmic Trading
Algo trading is an automated practical approach to TradingTrading. Strategies make the trading process very fast and much more result-oriented. The trades can be executed to the point of specified price and volume in minimal time. It reduces the losses due to the time lag between the sale and purchase of securities.
When the algo trading is used with specific intraday trading strategies, it works amazingly well.
Here are a few back-tested strategies used by successful traders as a part of Algo trading. These strategies can undoubtedly lead to maximize profits with the correct execution.
1. Momentum and Trend Based Strategy:
It is the most commonly used and most straightforward strategy. There are no complex interpretations or predictions to be made. It is the momentum and trend-based strategy. You need to follow the trends, and the energy in the market and the trades will be executed accordingly. Trade will be based on technical indicators - the moving averages, the price level movements, channel breakouts, etc. If a set of conditions is fulfilled, then automated trading is generated.
2. Arbitrage Strategy:
When there is a difference in the cost of the securities on different stock exchanges, Arbitrage profits take place. The algorithm identifies the price difference immediately using the computers and executes a trade to enable buying on the low-priced exchange and sell on the high-priced exchange. Although the cost difference is not too much, here, we can compare the speed and accuracy of Algo trading and manual TradingTrading.
This strategy is mostly applicable to forex trading. Once the trade gets executed, arbitrage profits will be credited to the trader.
3. Weighted Average Price Strategy:
This is also one of the most popular and efficient strategies. The objective of this strategy is to quick-execute the order to the volume-weighted average price or the time-weighted average price. The orders are executed in small parts. The order is based at either volume-weighted average price or the time-weighted average price in specific opening price in defined time slots.
The algorithms are successful in releasing the orders in small parts with efficiency and accuracy in nanoseconds, which may not be possible by human traders.
To know more strategies, refer to our Algorithmic Trading Strategies - Part 1.
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So you wanna trade Forex? - tips and tricks inside

Let me just sum some stuff up for you newbies out there. Ive been trading for years, last couple of years more seriously and i turned my strategies into algorithms and i am currently up to 18 algorithms thats trading for me 24/7. Ive learned alot, listened to hundreds of podcasts and read tons of books + research papers and heres some tips and tricks for any newbie out there.

  1. Strategy - How to... When people say "you need a trading strategy!!" Its because trading is very hard and emotional. You need to stick to your rules at all times. Dont panic and move your stop loss or target unless your rules tell you to. Now how do you make these rules? Well this is the part that takes alot of time. If your rules are very simple (for example: "Buy if Last candles low was the lowest low of the past 10 candles." Lets make this a rule. You can backtest it manually by looking at a chart and going back in time and check every candle. or you can code it using super simple software like prorealtime, MT4 ++ Alot of software is basicly "click and drag" and press a button and it gives you backtest from 10-20-30 years ago in 5 seconds. This is the absolute easiest way to backtest rules and systems. If your trading "pure price action" with your drawn lines and shit, the only way to truly backtest that kind of trading is going in a random forex pair to a random point in time, could be 1 year ago, 1 month ago, 5 years ago.. and then you just trade! Move chart 1 candle at a time, draw your lines and do some "actual trading" and look at your results after moving forward in the chart. If you do not test your strategy your just going in blind, which could be disaster.. Maybe someone told u "this is the correct way to trade" or "this strategy is 90% sure to win every trade!!!" If you think you can do trading without a strategy, then your most likely going to look back at an empty account and wonder why you moved that stop loss or why you didnt take profit etc.. and then your gonna give up. People on youtube, forums, interwebz are not going to give you/sell you a working strategy thats gonna make you rich. If they had a working strategy, they would not give it away/sell it to you.
  2. Money management - How to.... Gonna keep this one short. Risk a small % of your capital on each trade. Dont risk 10%, dont risk 20%. You are going to see loosing trades, your probably gonna see 5-10 loss in a row!! If your trading a 1000$ account and your risking 100$ on each trade (10%) and you loose 5 in a row, your down -50% and probably you cant even trade cus of margin req. Game over.. Now how does one get super rich, super fast, from risking 1-3% of your account on each trade?? Well heres the shocking message: YOU CANT GET RICH FAST FROM TRADING UNLESS YOUR WILLING TO GO ALL IN! You can of course go all in on each trade and if you get em all right, you might get 1000%, then you go all in 1 more time and loose it all... The whole point of trading is NOT going bust. Not loosing everything, cus if you loose it all its game over and no more trading for you.
  3. Find your own trading style.... Everyone is different. You can have an average holding period of 1 month or you could be looking at a 1 min chart and average holding time = 10 minutes. For some, less volatility helps them sleep at night. For others, more volatility gives them a rush and some people crave this. There is no "correct" timeframes, or holding periods, or how much to profit or how much to loose. We are all individuals with different taste in risk. Some dont like risk, others wanna go all in to get rich over night. The smart approach is somewhere in the middle. If you dont risk anything, your not gonna get anything. If you risk everything, your most likely going to loose everything. When people are talking about trading style, this is kinda what that means.
  4. There are mainly 2 ways to trade: Divergence and Convergence. Or in other words: Mean reversion or trend following. Lets talk about them both: Trend following is trying to find a trend and stay with the trend until its over. Mean reversion is the belief that price is too far away from the average XX of price, and sooner or later, price will have to return to its average/mean (hence the name: MEAN reversion). Trend following systems usually see a lower winrate (30-40% winrate with no money management is not uncommon to see when backtesting trend following systems.. You can add good money management to get the winrate % higher. Why is the % winrate so low? Well a market, whatever that market is, tend to get real choppy and nasty right after a huge trend. So your gonna see alot of choppy fake signals that might kill 5-6 trades in a row, until the next huge trend starts which is going to cover all the losses from the small losses before the trend took off. Then you gotta hold that trade until trade is done. How do you define "when trend starts and stops"? Well thats back to point 1, find a strategy. Try defining rules for an entry and exit and see how it goes when you backtest it. For mean reversion the win % is usually high, like 70-90% winrate, but the average winning trade is alot smaller than the average loosing trade. this happens because you are basicly trying to catch a falling knife, or catch a booming rocket. Usually when trading mean reversion, waiting for price to actually reverse can very often leave you with being "too late", so you kinda have to find "the bottom" or "the top" before it actually has bottomed/ topped out and reversed. How can you do this you ask? Well your never going to hit every top or every bottom, but you can find ways to find "the bottom-ish" or "the top-ish", thens ell as soon as price reverts back to the mean. Sometimes your gonna wish you held on to the trade for longer, but again, back to point 1: Backtest your rules and figure that shit out.

Read these 4 points and try to follow them and you are at least 4 steps closer to being a profitable trader. Some might disagree with me on some points but i think for the majority, people are going to agree that these 4 points are pretty much universal. Most traders have done or are doing these things every day, in every trade.
Here is some GREAT material to read: Kevin Davey has won trading championship multiple times and he has written multiple great books, from beginner to advanced level. Recommend these books 100%, for example: Building winning algorithmic trading systems" will give you alot to work with when it comes to all 4 of the above points. Market wizards, Reminiscences of a stock operator are 2 books that are a great read but wont give you much "trading knowledge" that you can directly use for your trading. Books on "The turtles" are great reading. Then you have podcasts and youtube. I would stay away from youtube as much as possible when it comes to "Heres how to use the rsi!!!" or "this strategy will make you rich!!". Most youtube videoes are made by people who wanna sell you a course or a book. Most of this is just pure bullshit. Youtube can very harmfull and i would honestly advice about going there for "strategy adivce" and such. Podcasts tho are amazing, i highly recommend: Better systems trader, Chat with traders, Top traders unplugged, We study billionairs, to name a few :)
Also, on a less funny note.. Please realize that you are, and i am, real fucking stupid and lazy compared to the actual pro's out there. This is why you should not go "all in" on some blind stupid strategy youve heard about. This is why this is indeed VERY FUCKING HARD and most, if not everyone has busted an account or two before realizing just this. Your dumb.. your not going to be super rich within 1 year.. You can not start with 500$ account and make millions! (some might have been able to do this, but know that for every winner, theres 999 loosers behind him that failed... Might work fine first 5 trades, then 1 fuckup tho and ur gone..
And lastly: Try using a backtesting software. Its often FREE!!! (on a demo account) and often so simple a baby could use it. If your trading lines and such there exists web broweser "games" and softwares that lets you go "1 and 1 candle ahead" in random forex pairs and that lets you trade as if its "real" as it goes.
A big backtesting trap however is backtesting "losely" by just drawing lines and looking at chart going "oh i would have taken this trade FOR SURE!! I would have made so much money!!" however this is not actually backtesting, its cherry picking and its biased beyond the grave, and its going to hurt you. Try going 1 candle at a time doing "real and live" trades and see how it goes.

Bonus point!!
many people misunderstands what indicators like the RSI is telling you. Indeed something is "overbought" or "oversold" but only compared to the last average of xx amounts of bars/candles.
It doesn't tell you that RIGHT NOW is a great time to sell or buy. It only tells you that the math formula that is RSI, gives you a number between 1-100, and when its above 70 its telling you that momentum is up compared to the last average 14 candles. This is not a complete buy/sell signal. Its more like a filter if anything. This is true for MOST indicators. They INDICATE stuff. Dont use them as pure buy/sell signals.. At least backtest that shit first! Your probably gonna be shocked at the shitty results if you "buy wehn rsi is undeer 30 and sell when RSI is above 70".

Editedit: Huge post already, why not copy paste my comment with an example showing the difference in trend following vs mean reversion:
The thing about trend following is that we never know when a trade starts and when it ends. So what often happens is that you have to buy every breakout going up, but not every breakout is a new trend. Lets do an example. Check out the photo i included here: https://imageshost.eu/image/image.RcC

THE PHOTO IS JUST AN EXAMPLE THAT SHOWS WHY A TYPICAL TREND FOLLOWING STRATEGY HAVE A "LOW" WINRATE.
THE PHOTO IS NOT SHOWING AN EXAMPLE OF MY STRATEGIES OR TRADING.

  1. We identify the big orange trend up.
  2. We see the big break down (marked with the vertical red line) this is telling us we are not going higher just yet. Our upwards trend is broken. However we might continue going up in a new trend, but when will that trend come?
  3. We can draw the blue trend very earyly using highs and lows, lines up and down. Then we begin to look for breakouts of the upper blue line. So every time price breaks upper blue line we have to buy (cus how else are we going to "catch the next trend going up?)
As you can see we get 5 false breakouts before the real breakout happens!
Now if you could tell fake breakouts from real breakouts, your gonna be rich hehe. For everyone else: Take every signal you can get, put a "tight" stop loss so in case its a fake signal you only loose a little bit. Then when breakout happens as you can clearly see in chart, your going to make back all the small losses.
So in this example we fail 5 times, but get 1 HUGE new trend going further up. This 1 huge trade, unless we fuck it up and take profits too early or shit like that, is going to win back all those small losses + more.
This is why trend following has a low winrate. You get 5 small loss and 1 big win.

Now lets flip this! Imagine if your trading Mean reversion on all the same red arrows! So every time price hits the blue line, we go short back to the bottom (or middle) again! You would have won 5 trades with small profits, but on that last one you would get stopped out so hard. Meaning 5 small wins, 1 big loss (as some have pointed out in comments, if you where trading mean reverting you would wanna buy the lows as well as short the tops - photo was suppose to show why trend following strategies have a lower % winrate.)

Final edit: sorry this looks like a wall of text on ur phones.
submitted by RipRepRop to Forex [link] [comments]

Taking a break from FIRE to go backpacking

Hi everyone! Taken a few big life decisions lately and thought I would share them here as they have a lot to do with FIRE. I guess you could call me CoastFI.

Mid-30s DINK couple working in Mumbai, have been in India all my working life. No NRI story here! Spouse and I are both MBAs.

The personal bit
Have dreamed about taking a year off to go backpacking ever since I was 25. Given the corporate culture – was too afraid to do that till now. I have not yet reached my FIRE target the way I defined it 3 years ago. But I’ve decided to take a break and resign to go backpacking for a year.

Had dreamed of a few trips for years – plan on travelling from Bombay to Beijing completely overland – through trains and buses. This was not possible till 2018 when Myanmar opened up their visa policy. Also dream of doing the Camino Santiago – it is a 500 km pilgrimage that starts from France and ends in western Spain. Both these trips will take a few months minimum so there was no way I could do them while working in the corporate world. I also want to travel to South America.

I resigned from my job last week. My organization is trying to retain me by offering a new role. They have also offered to give me a 3 month sabbatical. Let’s see how it goes – I am not going to accept anything unless it is in writing. The sabbatical is being promised with too many conditions so I don’t think I am going to accept it – for example they are asking that I go on the sabbatical from April 2020 – unfortunately that means I won’t be able to do the Bombay to Beijing trip because it will be very bad weather in Myanmar at the time – so am going to wait and watch without having too high expectations. I will come back in a year and find a job. Got a call from a few recruiters and I explained my situation – they asked me to contact them once I am back so they can share any opportunities. My boss from my old company now works in E-com and has offered me a job on my return as well.

My spouse will continue to work here – they recently rejoined their old boss and mentor at a job that really excites them. Till a few months ago we planned on taking the trip together but now that they got this job offer we took the joint decision for me to take this trip solo. Maybe we will take a joint trip together at 40! My spouse is incredibly supportive and has always been. I’m very very grateful that I have them on my side.

The financial bit

We are at 35X of normal expenses (current expenses – some buffer for Mumbai rents) and 44X of LeanFire expenses (normal expenses – discretionary travel expenses). My target is 45X of normal expenses for final FIRE. I also want to save up for a medical emergency corpus for me and my spouse, as well as for my spouse's parents who are dependent on us. The split is about 65:35 between me : my spouse (mainly because I saved about 75% right from my first job). All our corpus is from our savings from our job – no inheritance, no side hustles, no off-site, nothing.

Most of our funds are in equity and debt funds, with a big chunk in VPF. Due to some past mistakes I have too much in debt (little more than 60%) and am slowly moving into equity. Not included in this corpus – my spouse also has a house in Tier 3 city bought for their parents (about 30 lacs).

No plans on buying a house – we have both my spouse’s house and my parent’s house (I am an only child). We are consciously childfree, so no kid’s marriage and education goals as well.

I plan on funding the trip mainly through my holdings in arbitrage funds (have a fair amount in this because I had invested in these pre-LTCG). I have got myself a NiYo card as it has zero forex fees. Will keep a few other cards as backup as well. I still have not found a good travel insurance which will cover me for such a long period. I also do not have clarity on how my VPF will be taxed in this period.

A very rough estimate yields a cost of about 1.5 lacs per month for my trip. It can go lower as well because a lot of my trip is overland and I am used to budget travel – however since I am solo, would not like to compromise on safety either. This will be a dent on our corpus – but since my spouse will continue to earn and save in this period, that’s not too bad.

I have personally always been a good student, Type A personality, very risk averse by nature. I can be a bit of a workaholic as well. Lately have decided to relax a bit, not be so hard on myself and enjoy life a little. This felt like the right time to do something I had dreamed about for more than a decade. I am honestly a bit nervous – what If I don’t enjoy it! What if I don’t get a good job on my return! But this is a good test run for FIRE. My HR jokingly asked me if this was a midlife crisis and I said that this was a midlife celebration instead!

I have been working towards FIRE from 2010. I may not be exactly there, but the time for me to take a new step is here. Wish me luck!
submitted by caffeinewasmylife to FIREIndia [link] [comments]

What factors predict the success of a Steam game? (An analysis)

What factors predict the success of a Steam game?

I've seen quite a few discussions, comments and questions on /gamedev about what determines a game's success. How much does quality matter? Is establishing market awareness before launch the only thing that matters? Does a demo help or hurt? If your game has a poor launch, how likely is it to recover? Is it possible to roughly predict the sales of a game before launch?
In preparation for my game's launch, I spent a lot of time monitoring upcoming releases trying to find the answer to these questions. I compiled a spreadsheet, noted followers, whether it was Early Access or not, and saw how many reviews it received in the first week, month and quarter.
I'm sharing this data now in the hopes that it helps other developers understand and predict their games' sales.
First some notes on the data:
Game Price Launch Discount Week Guess Week actual 3 Month 3 Month/week Followers Early Access Demo Review Score
Pit of Doom 9.99 0 7 27 43 1.592592593 295 Y N 0.8
Citrouille 9.99 0.2 16 8 12 1.5 226 N N
Corspe Party: Book 14.99 0.1 32 40 79 1.975 1015 N N 0.95
Call of Cthulhu 44.99 0 800 875 1595 1.822857143 26600 N N 0.74
On Space 0.99 0.4 0 0 0 4 N N
Orphan 14.99 0 50 0 8 732 N N
Black Bird 19.99 0 20 13 34 2.615384615 227 N N
Gloom 6.99 0 20 8 17 2.125 159 N N
Gilded Rails 5.99 0.35 2 3 7 2.333333333 11 N Y
The Quiet Man 14.99 0.1 120 207 296 1.429951691 5596 N N 0.31
KartKraft 19.99 0.1 150 90 223 2.477777778 7691 Y N 0.84
The Other Half 7.99 0 2 3 27 9 91 N Y 0.86
Parabolus 14.99 0.15 0 0 0 16 N Y
Yet Another Tower Defense 1.99 0.4 20 22 38 1.727272727 396 N N 0.65
Galaxy Squad 9.99 0.25 8 42 5.25 3741 Y N 0.87
Swords and Soldiers 2 14.99 0.1 65 36 63 1.75 1742 N N 0.84
SpitKiss 2.99 0 3 1 2 2 63 N N
Holy Potatoes 14.99 0 24 11 22 2 617 N N 0.7
Kursk 29.99 0.15 90 62 98 1.580645161 2394 N N 0.57
SimpleRockets 2 14.99 0.15 90 142 272 1.915492958 3441 Y N 0.85
Egress 14.99 0.15 160 44 75 1.704545455 7304 Y N 0.67
Kynseed 9.99 0 600 128 237 1.8515625 12984 Y N 0.86
11-11 Memories 29.99 0 30 10 69 6.9 767 N N 0.96
Rage in Peace 12.99 0.1 15 10 42 4.2 377 N N 0.85
One Hour One Life 19.99 0 12 153 708 4.62745098 573 N N 0.81
Optica 9.99 0 0 2 3 1.5 18 N N
Cybarian 5.99 0.15 8 4 18 4.5 225 N N
Zeon 25 3.99 0.3 3 11 12 1.090909091 82 Y N
Of Gods and Men 7.99 0.4 3 10 18 1.8 111 N Y
Welcome to Princeland 4.99 0.1 1 15 55 3.666666667 30 N N 0.85
Zero Caliber VR 24.99 0.1 100 169 420 2.485207101 5569 Y N 0.73
HellSign 14.99 0 100 131 334 2.549618321 3360 Y N 0.85
Thief Simulator 19.99 0.15 400 622 1867 3.001607717 10670 N N 0.81
Last Stanza 7.99 0.1 8 2 4 2 228 N Y
Evil Bank Manager 11.99 0.1 106 460 4.339622642 8147 Y N 0.78
Oppai Puzzle 0.99 0.3 36 93 2.583333333 54 N N 0.92
Hexen Hegemony 9.99 0.15 3 1 5 5 55 Y N
Blokin 2.99 0 0 0 0 0 10 N N
Light Fairytale Ep 1 9.99 0.1 80 23 54 2.347826087 4694 Y N 0.89
The Last Sphinx 2.99 0.1 0 0 1 0 17 N N
Glassteroids 9.99 0.2 0 0 0 0 5 Y N
Hitman 2 59.99 0 2000 2653 3677 1.385978138 52226 N N 0.88
Golf Peaks 4.99 0.1 1 8 25 3.125 46 N N 1
Sipho 13.99 0 24 5 14 2.8 665 Y N
Distraint 2 8.99 0.1 40 104 321 3.086538462 1799 N N 0.97
Healing Harem 12.99 0.1 24 10 15 1.5 605 N N
Spark Five 2.99 0.3 0 0 0 0 7 N N
Bad Dream: Fever 9.99 0.2 30 78 134 1.717948718 907 N N 0.72
Underworld Ascendant 29.99 0.15 200 216 288 1.333333333 8870 N N 0.34
Reentry 19.99 0.15 8 24 78 3.25 202 Y N 0.95
Zvezda 5.99 0 2 0 0 0 25 Y Y
Space Gladiator 2.99 0 0 1 2 2 5 N N
Bad North 14.99 0.1 500 360 739 2.052777778 15908 N N 0.8
Sanctus Mortem 9.99 0.15 3 3 3 1 84 N Y
The Occluder 1.99 0.2 1 1 1 1 13 N N
Dark Fantasy: Jigsaw 2.99 0.2 1 9 36 4 32 N N 0.91
Farming Simulator 19 34.99 0 1500 3895 5759 1.478562259 37478 N N 0.76
Don't Forget Our Esports Dream 14.99 0.13 3 16 22 1.375 150 N N 1
Space Toads Mayhem 3.99 0.15 1 2 3 1.5 18 N N
Cattle Call 11.99 0.1 10 19 53 2.789473684 250 Y N 0.71
Ralf 9.99 0.2 0 0 2 0 6 N N
Elite Archery 0.99 0.4 0 2 3 1.5 5 Y N
Evidence of Life 4.99 0 0 2 4 2 10 N N
Trinity VR 4.99 0 2 8 15 1.875 61 N N
Quiet as a Stone 9.99 0.1 1 1 4 4 42 N N
Overdungeon 14.99 0 3 86 572 6.651162791 77 Y N 0.91
Protocol 24.99 0.15 60 41 117 2.853658537 1764 N N 0.68
Scraper: First Strike 29.99 0 3 3 15 5 69 N N
Experiment Gone Rogue 16.99 0 1 1 5 5 27 Y N
Emerald Shores 9.99 0.2 0 1 2 2 12 N N
Age of Civilizations II 4.99 0 600 1109 2733 2.464382326 18568 N N 0.82
Dereliction 4.99 0 0 0 0 #DIV/0! 18 N N
Poopy Philosophy 0.99 0 0 6 10 1.666666667 6 N N
NOCE 17.99 0.1 1 3 4 1.333333333 35 N N
Qu-tros 2.99 0.4 0 3 7 2.333333333 4 N N
Mosaics Galore. Challenging Journey 4.99 0.2 1 1 8 8 14 N N
Zquirrels Jump 2.99 0.4 0 1 4 4 9 N N
Dark Siders III 59.99 0 2400 1721 2708 1.573503777 85498 N N 0.67
R-Type Dimensions Ex 14.99 0.2 10 48 64 1.333333333 278 N N 0.92
Artifact 19.99 0 7000 9700 16584 1.709690722 140000 N N 0.53
Crimson Keep 14.99 0.15 20 5 6 1.2 367 N N
Rival Megagun 14.99 0 35 26 31 1.192307692 818 N N
Santa's Workshop 1.99 0.1 3 1 1 1 8 N N
Hentai Shadow 1.99 0.3 2 12 6 14 N N
Ricky Runner 12.99 0.3 3 6 13 2.166666667 66 Y N 0.87
Pro Fishing Simulator 39.99 0.15 24 20 19 0.95 609 N N 0.22
Broken Reality 14.99 0.1 60 58 138 2.379310345 1313 N Y 0.98
Rapture Rejects 19.99 0 200 82 151 1.841463415 9250 Y N 0.64
Lost Cave 19.99 0 3 8 11 1.375 43 Y N
Epic Battle Fantasy 5 14.99 0 300 395 896 2.26835443 4236 N N 0.97
Ride 3 49.99 0 75 161 371 2.304347826 1951 N N 0.74
Escape Doodland 9.99 0.2 25 16 19 1.1875 1542 N N
Hillbilly Apocalypse 5.99 0.1 0 1 2 2 8 N N
X4 49.99 0 1500 2638 4303 1.63115997 38152 N N 0.7
Splotches 9.99 0.15 0 2 1 0.5 10 N N
Above the Fold 13.99 0.15 5 2 6 3 65 Y N
The Seven Chambers 12.99 0.3 3 0 0 #DIV/0! 55 N N
Terminal Conflict 29.99 0 5 4 11 2.75 125 Y N
Just Cause 4 59.99 0 2400 2083 3500 1.680268843 50000 N N 0.34
Grapple Force Rena 14.99 0 11 12 29 2.416666667 321 N Y
Beholder 2 14.99 0.1 479 950 1.983298539 16000 N N 0.84
Blueprint Word 1.99 0 12 15 1.25 244 N Y
Aeon of Sands 19.99 0.1 20 12 25 2.083333333 320 N N
Oakwood 4.99 0.1 32 68 2.125 70 N N 0.82
Endhall 4.99 0 4 22 42 1.909090909 79 N N 0.84
Dr. Cares - Family Practice 12.99 0.25 6 3 8 2.666666667 39 N N
Treasure Hunter 16.99 0.15 200 196 252 1.285714286 4835 N N 0.6
Forex Trading 1.99 0.4 7 10 14 1.4 209 N N
Ancient Frontier 14.99 0 24 5 16 3.2 389 N N
Fear the Night 14.99 0.25 25 201 440 2.189054726 835 Y N 0.65
Subterraneus 12.99 0.1 4 0 3 #DIV/0! 82 N N
Starcom: Nexus 14.99 0.15 53 119 2.245283019 1140 Y N 0.93
Subject 264 14.99 0.2 25 2 3 1.5 800 N N
Gris 16.9 0 100 1484 4650 3.133423181 5779 N N 0.96
Exiled to the Void 7.99 0.3 9 4 11 2.75 84 Y N
Column Explanations
For the columns that are not self-explanatory:

Question 1: Does Quality Predict Success?

There was a recent blog post stating that the #1 metric for indie games' success is how good it is.
Quality is obviously a subjective metric. The most obvious objective measure of quality for Steam games is their % Favorable Review score. This is the percentage of reviews by purchasers of the game that gave the game a positive rating. I excluded any game that did not have at least 20 user reviews in the first month, which limited the sample size to 56.
The (Pearson) correlation of a game's review score to its number of reviews three months after its release was -0.2. But 0.2 (plus or minus) isn't a very strong correlation at all. More importantly, Pearson correlation can be swayed if the data contains some big outliers. Looking at the actual games, we can see that the difference is an artifact of an outlier. Literally. Valve's Artifact by far had the most reviews after three months and had one of the lowest review scores (53% at the time). Removing this game from the data changed the correlation to essentially zero.
Spearman's Rho, an alternative correlation model that correlates rank position and minimizes the effect of huge outliers produced a similar result.
Conclusion: If there is correlation between a game's quality (as measured by Steam review score) and first quarter sales (as measured by total review count), it is too subtle to be detected in this data.

Question 2: Do Demos, Early Access or Launch Discounts Affect Success/Failure?

Unfortunately, there were so few games that had demos prior to release (10) that only a very strong correlation would really tell us anything. As it happens, there was no meaningful correlation one way or another.
There were more Early Access titles (28), but again the correlation was too small to be meaningful.
More than half the titles had a launch week discount and there was actually a moderate negative correlation of -0.3 between having a launch discount and first week review count. However it appears that this is primarily the result of the tendency of AAA titles (which sell the most copies) to not do launch discounts. Removing the titles that likely grossed over a $1 million in the first week reduced the correlation to basically zero.
Conclusion: Insufficient data. No clear correlation between demos, Early Access or launch discount and review counts: if they help or hurt the effect is not consistent enough to be seen here.

Question 3: Does pre-launch awareness (i.e., Steam followers) predict success?

You can see the number of "followers" for any game on Steam by searching for its automatically-created Community Group. Prior to launch, this is a good rough indicator of market awareness.
The correlation between group followers shortly before launch and review count at 3 months was 0.89. That's a very strong positive correlation. The rank correlation was also high (0.85) suggesting that this wasn't the result of a few highly anticipated games.
Save for a single outlier (discussed later), the ratio of 3 month review counts to pre-launch followers ranged from 0 (for the handful of games that never received any reviews) to 1.8, with a median value of 0.1. If you have 1000 followers just prior to launch, then at the end of the first quarter you should expect "about" 100 reviews.
One thing I noticed was that there were a few games that had follower counts that seemed too high compared to secondary indicators of market awareness, such as discussion forum threads and Twitter engagement. After some investigation I came to the conclusion that pre-launch key activations are treated as followers by Steam. If a game gave away a lot of Steam keys before launch (say as Kickstarter rewards or part of beta testing) this would cause the game to appear to have more followers than it had gained "organically."
Conclusion: Organic followers prior to launch are a strong predictor of a game's eventual success.

Question 4: What about price?

The correlation between price and review count at 3 month is 0.36, which is moderate correlation. I'm not sure how useful that data point is: it is somewhat obvious that higher budget games have larger marketing budgets.
There is a correlation between price and review score of -0.41. It seems likely that players do factor price into their reviews and a game priced at $60 has a higher bar to clear to earn a thumbs up review than a game priced at $10.

Question 5: Do first week sales predict first quarter results?

The correlation between number of reviews after 1 week and number of reviews after 3 months was 0.99. The Spearman correlation was 0.97. This is the highest correlation I found in the data.
Excluding games that sold very few copies (fewer than 5 reviews after the first week), most games had around twice as many reviews after 3 months as they did after 1 week. This suggests that games sell about as many copies in their first week as they do in the next 12 weeks combined. The vast majority of games had a tail ratio (ratio of reviews at 3 months to 1 week) of between 1.3 to 3.2.
I have seen a number of questions from developers whose game had a poor launch on Steam and wanted to know what they can do to improve sales. While I'm certain post-launch marketing can have an effect on continuing sales, your first week does seem to set hard bounds on your results.
Conclusion: ALL SIGNS POINT TO YES

Question 6: Does Quality Help with a Game's "Tail"?

As discussed in the last question while first week sales are very strongly correlated with first quarter, there's still quite a wide range of ratios. Defining a game's Tail Ratio as the ratio of reviews after 3 months to after 1 week, the lowest value was 0.95 for "Pro Fishing Simulator" which actually managed to lose 1 review. The highest ratio was 6.9, an extreme outlier that I'll talk about later. It is perhaps not a coincidence that the worst tail had a Steam score of 22% and the best tail had a Steam score of 96%.
The overall correlation between the Tail Ratio and Steam score was 0.42.
Conclusion: Even though there is no clear correlation between quality and overall review count/sales, there is a moderate correlation between a game's review score and its tail. This suggests that "good games" do better in the long run than "bad games," but the effect is small compared to the more important factor of pre-launch awareness.

Question 7: Is it possible to predict a game's success before launch without knowing its wishlists?

While I was compiling the data for each game, sometime prior to its scheduled launch date, I would make a prediction of how many reviews I thought it would receive in its first week and add that prediction to the spreadsheet.
The #1 factor I used in making my prediction was group follower count. In some cases I would adjust my prediction if I thought that value was off, using secondary sources such as Steam forum activity and Twitter engagement.
The correlation between my guess and the actual value was 0.96, which is a very strong correlation. As you can see in the data, the predictions are, for the most part, in the right ballpack with a few cases where I was way off.
Based on my experience, multiplying the group follower count by 0.1 will, in most cases, give you a ballpark sense of the first week quarter review count. If a game doesn't have at least one question in the discussion forum for every 100 followers, that may indicate that there are large number of "inorganic" followers and you may need to adjust your estimate.
Conclusion: Yes, with a few exceptions, using follower data and other indicators you can predict first week results approximately. Given the strong correlation between first week and quarter sales, it should also be possible to have a ballpark idea of first quarter results before launch.

Final Question: What about the outliers you mentioned?

There were a few games in the data that stood out significantly in one way or another.
Outlier #1: Overdungeon. This game had 77 group followers shortly before launch, a fairly small number and based solely on that number I would have expected fewer than a dozen reviews in the first week. It ended up with 86. Not only that, it had a strong tail and finished its first quarter with 572 reviews. This was by a wide margin the highest review count to follower ratio in the sample.
Based on the reviews, it appears to basically be Slay the Spire, but huge in Asia. 90% of the reviews seem to be in Japanese or Chinese. If anyone has some insight to this game's unusual apparent success, I'm very curious.
This seems to be the only clear example in the data of a game with minimal following prior to launch going on to having a solid first quarter.
Outlier #2: 11-11 Memories Retold. This game had 767 group followers shortly before launch, ten times as many as Overdungeon. That's still not a large number for even a small indie title. It had a fair amount going for it, though: it was directed by Yoan Fanise, who co-directed the critally acclaimed Valiant Hearts, a game with a similar theme. It was animated by Aardman Studios of "Wallace and Gromit" fame. Its publisher was Bandai Namco Europe, a not inexperienced publisher. The voice acting was by Sebastian Koch and Elijah Wood. It has dozens of good reviews in both gaming and traditional press. It currently has a 95% positive review rating on Steam.
Despite all that, nobody bought it. 24 hours after it came out it had literally zero reviews on Steam. One week after it came out it had just 10. Three months later it had demonstrated the largest tail in the data, but even then it had only climbed to 69 reviews. Now it's at about 100, an incredible tail ratio, but almost certainly a commercial failure.
This is a solid example that good game + good production values does necessarily equal good sales.

Final notes:
The big take-aways from this analysis are:
Thanks for reading!
submitted by justkevin to gamedev [link] [comments]

Live Sinyal Forex dan Binary 17072020 - YouTube Forex Signals  Forex Signal Review  Forex Signals Providers Forex Trading The Best Time Frame To Trade The Shark Out ... FLM Intro To Forex Feat. David Mock Forex Robot EURUSD for 15-Minute Time Frame

Real-time forex trading relies on live trading charts to buy and sell currency pairs, often based on technical analysis or technical trading systems. more Forex Analysis Definition and Methods Forex trading involves substantial risk of loss and is not suitable for all investors. Please do not trade with borrowed money or money you cannot afford to lose. Any opinions, news, research, analysis, prices, or other information contained on this website is provided as general market commentary and does not constitute investment advice. Manual back-testing simulates the live environment using past data and performance, this can enhance your trading and increase your probability for success. nial this is the most accurate of your forex analysis that youve ever published. Its true that whenever trading, though one is using the daily chart candle signals, as entry should and must be done in the lower chart frames, one can never enter based on the signal of the daily chart alone as ive noticed but also on all the lower chart frames, specifically the hourly and 15 charts combined. Forex strategy is a special technique or trading technique traders use to determine whether they should buy or sell a currency pair at a given time. Strategies based on technical analysis require the use of indicators, while strategies based on fundamental analysis require business data and economic news.

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Live Sinyal Forex dan Binary 17072020 - YouTube

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