Top 10 Forex Trading Rules - Investopedia

Former investment bank FX trader: some thoughts

Former investment bank FX trader: some thoughts
Hi guys,
I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert.
I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning.
When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions.
The first topic is Risk Management and we'll cover it in three parts
Part I
  • Why it matters
  • Position sizing
  • Kelly
  • Using stops sensibly
  • Picking a clear level

Why it matters

The first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.”
You have to keep it before you grow it.
Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around.
The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices.
Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.

Capital and position sizing

The first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose.
Position sizing is what ensures that a losing streak does not take you out of the market.
A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples.
So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000.
We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be?
We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator".

https://preview.redd.it/y38zb666e5h51.jpg?width=1200&format=pjpg&auto=webp&s=26e4fe569dc5c1f43ce4c746230c49b138691d14
So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital.
You should be using this calculator (or something similar) on every single trade so that you know your risk.
Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later.
The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work.
As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you.
Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints.
For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly:

https://preview.redd.it/q2ea6rgae5h51.png?width=1200&format=png&auto=webp&s=4332cb8d0bbbc3d8db972c1f28e8189105393e5b
To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you.
Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown.
It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance.
Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k.
Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money.
Do not let this happen to you. Use position sizing discipline to protect yourself.

Kelly Criterion

If you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number?
The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round.
This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet.
Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin.
Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips.
Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds.
Applying the formula to forex trading looks like this:
Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio
If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically.
If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss.
So that’s 0.3 - (1 - 0.3) / 3 = 6.6%.
Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit!
With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not.
Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account.
Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see.
This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders.
Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
  • How many live trades have you done? Often they’ll have done only a handful of real trades and the rest are simulated backtests, which are overfitted. The model will soon die.
  • What is your risk-reward ratio on each trade? If you have a take profit $3 away and a stop loss $100 away, of course most trades will be winners. You will not be making money, however! In general most traders should trade smaller position sizes and less frequently than they do. If you are going to bias one way or the other, far better to start off too small.

How to use stop losses sensibly

Stop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them.
A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter.
The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’.
This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK.
Why are stop losses so important? Well, there is no other way to manage risk with certainty.
You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter.
Learning to take a loss and move on rationally is a key lesson for new traders.
A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not.
Bruce Kovner, founder of the hedge fund Caxton Associates
There is an old saying amongst bank traders which is “losers average losers”.
It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong.
Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.

Picking a clear level

Where you leave your stop loss is key.
Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible.

If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop
You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200.
The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up.
Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD.

https://preview.redd.it/moyngdy4f5h51.png?width=1200&format=png&auto=webp&s=91af88da00dd3a09e202880d8029b0ddf04fb802
If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend.
So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level.
There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section.
There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high.

https://preview.redd.it/ygy0tko7f5h51.png?width=1200&format=png&auto=webp&s=34af49da61c911befdc0db26af66f6c313556c81
Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument.
Here are some guidelines that can help:
  1. Use technical analysis to pick important levels (support, resistance, previous high/lows, moving averages etc.) as these provide clear exit and entry points on a trade.
  2. Ensure that the stop gives your trade enough room to breathe and reflects your timeframe and typical volatility of each pair. See next section.
  3. Always pick your stop level first. Then use a calculator to determine the appropriate lot size for the position, based on the % of your account balance you wish to risk on the trade.
So far we have talked about price-based stops. There is another sort which is more of a fundamental stop, used alongside - not instead of - price stops. If either breaks you’re out.
For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.

Coming up in part II

EDIT: part II here
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Risk:reward ratios
Risk-adjusted returns

Coming up in part III

Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

[Strategies] Here is My Trading Approach, Thought Process and Execution

Hello everyone. I've noticed a lot of us here are quite secretive about how we trade, especially when we comment on a fellow trader's post. We're quick to tell them what they're doing isn't the "right way" and they should go to babypips or YouTube. There's plenty of strategies we say but never really tell them what is working for us. There's a few others that are open to share their experience and thought processes when considering a valid trade. I have been quite open myself. But I'm always met with the same "well I see what you did is quite solid but what lead you to deem this trade valid for you? "
The answer is quite simple, I have a few things that I consider which are easy rules to follow. I realized that the simpler you make it, the easier it is for you to trade and move on with your day.
I highlight a few "valid" zones and go about my day. I've got an app that alerts me when price enters the zone on my watchlist. This is because I don't just rely on forex trading money, I doubt it would be wise to unless you're trading a 80% win rate strategy. Sometimes opportunities are there and we exploit them accordingly but sometimes we are either distracted by life issues and decide to not go into the markets stressed out or opportunities just aren't there or they are but your golden rules aren't quite met.
My rules are pretty simple, one of the prime golden rules is, "the risk is supposed to be very minimal to the reward I want to yield from that specific trade". i.e I can risk -50 pips for a +150 and more pips gain. My usual target starts at 1:2 but my most satisfying trade would be a 1:3 and above. This way I can lose 6/10 trades and still be profitable.
I make sure to keep my charts clean and simple so to understand what price does without the interference of indicators all over my charts. Not to say if you use indicators for confluence is a complete no-no. Each trader has their own style and I would be a narcissistic asshole if I assumed my way is superior than anybody else's.
NB: I'm doing this for anybody who has a vague or no idea of supply and demand. Everything here has made me profitable or at least break even but doesn't guarantee the same for you. This is just a scratch on the surface so do all you can for due diligence when it comes to understanding this topic with more depth and clear comprehension.
Supply and Demand valid zones properties; what to me makes me think "oh this zone has the potential to make me money, let me put it on my watchlist"? Mind when I say watchlist, not trade it. These are different in this sense.
👉With any zone, you're supposed to watch how price enters the zone, if there's a strong push in the opposite direction or whatever price action you're observing...only then does the zone becomes valid. YOU TRADE THE REACTION, NOT THE EXPECTATION Some setups just fail and that's okay because you didn't gamble. ✍
!!!IMPORTANT SUBJECT TO LEARN BEFORE YOU START SUPPLY AND DEMAND!!!
FTR. Failure to Return.(Please read on these if you haven't. They are extremely important in SnD). Mostly occur after an impulse move from a turning point. See attached examples: RBR(rally base rally)/DBD(drop base drop). They comprise of an initial move to a certain direction, a single candle in the opposite direction and followed by 2 or more strong candles in the initial direction. The opposite candle is your FTR(This is your zone) The first time price comes back(FTB) to a zone with an FTR has high possibilities to be a strong zone.
How to identify high quality zones according to my approach:
  1. Engulfing zones; This is a personal favorite. For less errors I identify the best opportunities using the daily and 4H chart.
On the example given, I chose the GBPNZD trade idea I shared here a month ago I believe. A double bottom is easily identified, with the final push well defined Bullish Engulfing candle. To further solidify it are the strong wicks to show strong rejection and failure to close lower than the left shoulder. How we draw our zone is highlight the whole candle just before the Engulfing Candle. That's your zone. After drawing it, you also pay attention to the price that is right where the engulfing starts. You then set a price alert on your preferred app because usually price won't get there immediately. This is the second most important part of trading, PATIENCE. If you can be disciplined enough to not leave a limit order, or place a market order just because you trust your analysis...you've won half the battle because we're not market predictors, we're students. And we trade the reaction.
On the given example, price had already reached the zone of interest. Price action observed was, there was a rejection that drove it out of the zone, this is the reaction we want. Soon as price returns(retests)...this is your time to fill or kill moment, going to a 4H or 1H to make minimum risk trades. (See GBPNZD Example 1&2)
  1. Liquidity Run; This approach looks very similar to the Engulfing zones. The difference is, price makes a few rejections on a higher timeframe level(Resistance or support). This gives the novice trader an idea that we've established a strong support or resistance, leading to them either selling or buying given the opportunity. Price then breaks that level trapping the support and resistance trader. At this point, breakout traders have stop orders below or above these levels to anticipate a breakout at major levels with stops just below the levels. Now that the market has enough traders trapped, it goes for the stop losses above or below support and resistance levels after taking them out, price comes back into the level to take out breakout traders' stop losses. This is where it has gathered enough liquidity to move it's desired direction.
The given example on the NZDJPY shows a strong level established twice. With the Bearish Engulfing movement, price leaves a supply zone...that's where we come in. We go to smaller timeframes for a well defined entry with our stops above the recent High targeting the next demand zone.
The second screenshot illustrates how high the reward of this approach is as well. Due diligence is required for this kind of approach because it's not uncommon but usually easily misinterpreted, which is why it's important it's on higher timeframes.
You can back test and establish your own rules on this but the RSI in this case was used for confluence. It showed a strong divergence which made it an even easier trade to take.
...and last but definitely not least,
  1. Double Bottom/Top. (I've used double bottoms on examples because these are the only trades I shared here so we'll talk about double bottoms. Same but opposite rules apply on double tops).
The first most important rule here is when you look to your left, price should have made a Low, High and a Lower Low. This way, the last leg(shoulder) should be lower than the first. Some call this "Hidden Zones". When drawing the zones, the top border of the zone is supposed to be on the tip of the Low and covering the Lower Low. **The top border is usually the entry point.
On the first given example I shared this week, NZDCAD. After identifying the structure, you start to look for zones that could further verify the structure for confluence. Since this was identified on the 4H, when you zoom out to the daily chart...there's a very well defined demand zone (RBR). By now you should know how strong these kind of zones are especially if found on higher timeframes. That will now be your kill zone. You'll draw another zone within the bigger zone, if price doesn't close below it...you've got a trade. You'll put your stop losses outside the initial zone to avoid wicks(liquidity runs/stop hunts)
On the second image you'll see how price closed within the zone and rallied upwards towards your targets.
The second example is CHFJPY; although looking lower, there isn't a rally base rally that further solidifies our bias...price still respected the zone. Sometimes we just aren't going to get perfect setups but it is up to us to make calculated risks. In this case, risk is very minimal considering the potential profit.
The third example (EURNZD) was featured because sometimes you just can't always get perfect price action within your desired zone. Which is why it's important to wait for price to close before actually taking a trade. Even if you entered prematurely and were taken out of the trade, the rules are still respected hence a re entry would still yield you more than what you would have lost although revenge trading is wrong.
I hope you guys learnt something new and understand the thought process that leads to deciding which setups to trade from prepared supply and demand trade ideas. It's important to do your own research and back testing that matches your own trading style. I'm more of a swing trader hence I find my zones using the Daily and 4H chart. Keeping it simple and trading the reaction to your watched zone is the most important part about trading any strategy.
Important Note: The trade ideas on this post are trades shared on this sub ever since my being active only because I don't want to share ideas that I may have carefully picked to make my trading approach a blind pick from the millions on the internet. All these were shared here.
Here's a link to the trade ideas analyzed for this post specifically
Questions are welcome on the comments section. Thank you for reading till here.
submitted by SupplyAndDemandGuy to Forex [link] [comments]

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80+ FREE Udemy & Few Discounted

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Top 5 Most Famous Traders Of All Time

In all industries there are people credited to being the simplest .
In design, the late Steve Jobs is credited to being the simplest in his industry. In boxing, Muhammad Ali was credited to being the simplest boxer of all time.
In U.S. politics, there's a consensus that Lincoln was the nation’s greatest President by every measure applied.
In the trading world, a variety of traders are known worldwide for his or her skills. From Jesse Livermore to George Soros, we are sharing these tales of past and present traders who had to claw their thanks to the highest .
Here, we'll check out the five most famous traders of all time and canopy a touch bit about each trader and why they became so famous.
Jesse Livermore
Jesse Livermore jumped into the stock exchange with incredible calculations at the age of 15, amassed huge profits, then lost all of them , then mastered two massive crises and came out the opposite side while following his own rules, earning him the nickname “The Great Bear of Wall Street.”
Livermore was born in 1877 in Shrewsbury, Massachusetts.
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He is remembered for his incredible risk taking, his gregarious method of reading the potential moves within the stock exchange , derivatives and commodities, and for sustaining vast losses also as rising to fortune.
He began his career having run far away from home by carriage to flee a lifetime of farming that his father had planned for him, instead choosing city life and finding work posting stock quotes at Paine Webber, a Boston stockbroker.
Livermore bought his first share at 15 and earned a profit of $3.12 from $5 after teaching himself about trends.
George Soros
George Soros has a fantastic backstory.
Born in Hungary in 1930 to Jewish parents, Soros survived the Holocaust and later fled the country when the Communists took power. He went on to become one among the richest men and one among the foremost famous philanthropists within the world.
Most day traders know him for his long and prolific career as a trader who famously “broke the Bank of England” in 1992. Soros made an enormous bet against British Pound, which earned him $1 billion in profit in only 24 hours.
Along with other currency speculators, he placed a bet against the bank’s ability to carry the road on the pound. He borrowed pounds, then sold them, helping to down the worth of the currency on forex markets and ultimately forcing the united kingdom to crash out of the ecu rate of exchange Mechanism.
It was perhaps the quickest billion dollars anyone has ever made and one among the foremost famous trades ever taken, which later became referred to as “breaking the Bank of England”.
Soros is believed to have netted a complete of about $44 billion through financial speculation. And he has used his fortune to find thousands of human rights, democracy, health, and education projects.
Richard Dennis
There are only a couple of traders which will take a little amount of cash and switch it into millions and Richard Dennis was one among them.
Known as the “Prince of the Pit”, Dennis is claimed to have borrowed $1,600 when he was around 23 years old and turned it into $200 million in about 10 years trading commodities. Even more interesting to notice , he only traded $400 of the $1,600.
Not only did he achieve great success as a commodities trader, he also went on to launch the famous “Turtle Traders Group”. Using mini contracts, Dennis began to trade his own account at the Mid America commodities exchange .
He made a profit of $100,000 in 1973. The subsequent year, he capitalized on a runway soybean market to earn $500,000 in profits. He became an impressive millionaire at the top of the year.
However, he incurred massive losses within the Black Monday stock exchange crash in 1987 and therefore the dot-com bubble burst in 2000.
While he's famous for creating and losing tons of cash , Dennis is additionally famous for something else – an experiment. He and his friend William Eckhardt recruited and trained traders, a couple of men and ladies, the way to trade futures. These so-called Turtle Traders went on to form profits of $175 million in 4 years, consistent with a former student.
Paul Tudor Jones
Paul Tudor Jones thrust into the limelight within the 80s when he successfully predicted the 1987 stock exchange , as shown within the riveting one hour documentary called “Trader”.
The legendary trader was born in Memphis, Tennessee in 1954. His father ran a financial and legal trade newspaper. While he was in college, he want to write articles for the newspaper under the pseudonym, “Eagle Jones”.
Jones began his journey within the finance business by trading cotton. He started trading on his own following 4 years of non-trading experience, made profits from his trades but got bored, and later hired people to trade for him so he would not get bored.
But the trade that shot him to fame came on Black Monday in 1987, when he made an estimated $100 million whilst the Dow Jones Industrial Average plunged 22%.
He became a pioneer within the area of worldwide macro investing and was an enormous player within the meteoric growth of the hedge fund industry. He's also known for depending on currencies and interest rates.
He founded his hedge fund, Tudor Investment Corp, in 1980. The fund currently has around $21 billion in assets under management and he himself has an estimated net worth of nearly $5.8 Billion.
John Paulson
Super-trader John Paulson built a private fortune worth $4.4 billion from managing other people’s money. Born in 1955, Paulson made his name and far of his money betting a huge amount of money against the U.S. housing market during the worldwide financial crisis of 2007–2008.
Paulson bought insurance against defaults by subprime mortgages before the market collapse in 2007. He netted an estimated $20 billion on the collapse of the subprime mortgage market, dubbed the best trade ever.
However, his diary since that bet has been patchy at the best . Within the years following the financial crisis, Paulson struggled to match this success.
Failed bets on gold, healthcare and pharmaceutical stocks caused investors to escape his hedge fund Paulson & Co, cutting its assets under management to $10 billion as of January 2020 from a high of $36 billion in 2011.
Earlier this year, Paulson announced the fund would stop managing money for outdoor clients and switch it into a family office. He launched the fund in 1994.
submitted by equiti-me to u/equiti-me [link] [comments]

Your Pre Market Brief for 07/16/2020

Pre Market Brief for Thursday July 16th 2020

You can subscribe to the daily 4:00 AM Pre Market Brief on The Twitter Link Here . Alerts in the tweets will direct you to the daily 4:00 AM Pre Market Brief in this sub.
Updated as of 4:45 AM EST
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Stock Futures:
Wednesday 07/15/2020 News and Markets Recap:
Thursday July 16th 2020 Economic Calendar (All times are in EST)
(JOBLESS CLAIMS TODAY)
News Heading into Thursday July 16th 2020:
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Upcoming Earnings:
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Subscribe to This Brief and the daily 4:00 AM Pre Market Brief on The Twitter Link Here . Alerts in the tweets will direct you to the daily brief in this sub
submitted by Cicero1982 to pennystocks [link] [comments]

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:

Demo Trading Results

Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc).
A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade.
I'm heading out of town next week, then after that it'll be time to take this sucker live!

Live Trading Results

I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
submitted by ForexBorex to Forex [link] [comments]

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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Stop-Loss and the Hunger For New Capital

Stop-Loss and the Hunger For New Capital

Stop-Loss and the Hunger For New Capital


Stop-Loss and the Hunger For New Capital


Ever wonder why when you trade your stop gets tagged? Although you put it in a spot where "There's no way price will want to reach my stop level for sure this time"
As a trader, particularly a new trader – I've always wondered why my stops were only tagged for the price of running briefly the area that I've ever so carefully researched ... hit my stop point ..... then move on in the direction of my original study and run to the point where my profit should have been taken.
Everything leaving me wondering ...... In the hell for what did this do??? Obviously this is a common issue that has plagued most traders. At least, I know that I have faced this very problem for years.

What I noticed was that there was a very distinctive pattern going on, and it was repeating itself again and again. I noticed that the traditional supply and demand theory, support and resistance zones, or double top / double bottom trading patterns that I have been told time and time again that price has always covered these regions, was not really a real thing.

The argument had been, ..... Put me into the shoes of the major investment banks vs. the home-trading fighter who was going to conquer the markets every day. If you were a large company with an infinite supply of money and you decided to bring a massive chunk of it into the game, you can't just dump the whole lot into the game and demand all your orders to be filled out at once, then take off the price in the direction you want .... no ..... That is not exactly the way it operates.All these major organizations need to do is pair orders.

And they match that order by sending the markets to areas where liquidity is high .... The stops AKA!

Let 's say you 're evaluating the markets, for example, and deciding that price wants to go higher than an old regular target as it's in a bullish uptrend at the moment. And you see price for the past day, or so, not willing to go any lower.
What looks like a bit of a demand shelf or support level where the demand is all in a nice tight clustered row that just doesn't seem to want to go down and you know for sure this time price won't go under that heavily protected area ..... only for the price to run down quickly and refuse to go up (in this case a long position).
And I started to note that these "secure zones" or places where price is certainly not going to come up / down to be simply used by these large entities as feeding grounds for harvesting liquidity and adding more positions to include them in a larger movement.

They need a lot of money to buy in and just to do so, your sell stop is great. Many traders put their stops below this tight pack range of candles a few pips / ticks / cents believing they 're secure as price obviously doesn't want to come down below them. And most traders have their positions liquidated by the hungry major capital banks to feed the whole push higher than you were originally right about.

And how can you stop this pitfall happening to you is the million-dollar question? There are a few ways to handle this and keep your hard-earned money from being ripped away from you in an moment, which you have at risk in the markets.

Stop-Hunting and the Hunger For New Capital

I found that you would do much better in your trading career if you look at these areas (in the above example a long position) as a chance rather than a safe zone to put your stop. What I mean by that is, anticipate them coming down under those equal lows and try to get far below it instead of getting long above the area of consolidation. Yeah, that means you're going to have to go long when the competition runs against you and I know , I know, it feels really uncomfortable and wrong and goes against all you've been taught ... but believe me that this approach can give you the very best possible entries.
Imagine: getting into the day 's low and riding price action all the way up to the top of everyday scale!!! Wouldn't this be terrific?

Well, if your quantitative skills are timely and your business research tells you to go a long way, then all you need to do is wait for the perfect entry. Let the price build up and create "demand shelf" or support areas for that. Let the market shift sideways and bounce around like a pinball mocking all the other traders who were at the top of these stuff for a long time and put their stops just below them in hopes that the price would not come down and stop them. All the while playing with and holding their emotions on the cliff of –Will this be a winner, or a trade loser? So when price does the unimaginable and runs below the support area and scoops up all the traders stops you can then go long and take part in the glorious upside of being right – and of course make some money doing it.

Notice facile? Well, that is not so. It takes patience and timing and experience to catch all those eager participants who keep their stops on a silver platter for the fat and thirsty banks to suck them up, as the markets normally send price south of the border.
Stop-Loss and the Hunger For New Capital (meme)

You have to define the times of the day when the wrong move is made apparent.
Or when they make that low of the day – typically within the 1st 1 – 4 hours
of the trading day, and I don't mean either when the banks come online at 8 a.m. NY.
I mean 12 am, at the beginning of the day.
So yes you 're definitely going to have to be awake if you like watching
price do its thing and don't trust the process of buying into those down candles.
And use a limit order like me-then go to sleep and trust your overall analysis to be right and wake up to your morning with a nice little start.
But the trick is-where are you going to shop under the lows?

And where does your stop then go when you buy?

Those are all interesting questions that I should seek to answer clearly here – but alas, all markets are different.

Yet general rule of thumb as follows:

  1. You should predict that such stop-sweeps will occur in grades 5 and 10. The average is usually about 10, cents, pips, ticks or otherwise. The bigger the step down the more likely it is not a stop raid and potentially a reversal of the pattern. And you can prevent too much danger and keep the stop fairly secure.
Your stop will need to go low on the 1hr map below the next move. As a minimum, and yes, that may mean a greater risk level that you are usually prepared to take.
However if that is the case then try to turn your power back.
You don't need to make every trade worth a million dollars.
This is about continuity, when dealing, not winning the draw.
In your research you need to be sure the price will push higher as this is how the overall trend directions point it.
I am not recommending trade in these types of trades against the trend.
You need to be in full agreement with the direction of the total daily level.
And bringing it in.

Also, a great way to place the maximum risk reward for your take profit:

Attempt to position it in places above the market where short-sellers will stop.

And in a nutshell, with a bit of analysis, all the knowledge I described above can be readily found, I didn't come up with it on my own and these ideas are not unique. Yet how you adapt them to your particular trading style is up to you and relies on your interpretation of these principles for your success and/or failure. Price is fractal and would want to return to markets it has previously sold before – if you accept the basic fact you ought to be doing very well in your business career.

Eva " Forex " Canares .
Cheers and Profitable Trading to All.

About FTMO -
They fund forex traders. Just Pass their risk management rules and begin trading for their company. They'll provide you capital up to $300k USD for trading the financial markets. 70% of profits you keep and losses are covered by them. How does it work?
How to Become a Funded Forex ,Stocks or CryptoCurrency Trader?
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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/
submitted by aibnsamin1 to Bitcoin [link] [comments]

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