Here is an interesting (although heavily contrived) experiment that is very helpful in *actually understanding* path dependency and, done often enough, can lead to some very good ideas.
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Take three markets that, on a close to close basis, tend to have a correlated ‘sign’ (+ or -).
Put another way, all three tend to close in the same direction over time.
Maybe EURUSD, GBPUSD & AUDUSD. What’s intriguing from a research angle is the different paths...
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that they take between the opening and the close. (Or any two points in time really)
Things worth trying to quantify:
* Leads and lags between them.
* Absolute and relative sizes of moves.
* Reactions to ‘X’ time period highs and lows.
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* Is EURUSD more likely to lead because it is ‘more important’ than the AUDUSD.
* If all three move in lockstep with one another is that predictive of anything.
* If one currency plays catchup to the other two late in the session, is that predictive of anything.
And on...
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Not suggesting any of the above have any relationship to anything, rather these are a few things that come to one’s mind straight away as measureable, testable and replicable.
You might pick three stocks in the same sector also.
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Ed. Note- one more dimension lower into the microstructure and it is quite evident to see cross hedging activities by liquidity providers that provide much nourishment for the HFT community (amongst many other morsels).
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I need to think about the next big strategy and the possibility (indeed the likelihood) that I won’t discover it.
I have posted about a massive ML/AI experiment that didn’t succeed (not giving up but… tik tok, tik tok).
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Despite my background and quant trading bona fides, I am increasingly drawn to the Idea that the highest future returns will come from quantitative trading rules applied by experienced discretionary traders.
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For my sins, I am ‘experienced’ enough to have seen all of ‘Macro’, ‘L/S Equity’ and ‘Trend Following’ implode inward to varying degrees (Clearly, firms have survived in all three).
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One notes, regrettably, that it is beginning in the ‘Quant’ space. I believe I am qualified to state with some measure of certainty, the reasons-
* Most new entrants come from the same echo chamber schools with the same knowledge.
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* Very, very few have actually bought or sold anything in their lives.
* A completely baffling belief that being a world class programmer means they will find better systematic alpha than a ‘non programmer’ given excellent testing software.
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My lasting memory as an incredibly fortunate Junior trader on the Proprietary Trading desk at a shiny US IB in the late 90’s was watching the best and brightest traders of their generation throw it all away betting against the internet and all of its late 90’s manifestations.
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They were, of course, eventually proved correct but none survived. The almost tangible hatred of the market’s incredible advance came through in increasingly poor sizing and trade structure.
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It accelerated my move to rules based and then fully quantitative trading in a holding period time frame where I found real Alpha.
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Some things to think about regardless of the level of your participation in markets:
* Every time that you leave a traditionally scripted order on any DMA connectivity apparatus, you are providing information to others.
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* The Financial markets are set up to take money from the weak and give it to the strong via volatility AND the rules of engagement (agreements, exchange rules etc.)
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* If you apply the techniques (and the published extensions thereof) gifted you from a high level technical education, then know this - you will lose when the distributions change. And they always do!
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I would like to share with those wishing to hear, the basic experiments that I did that led to finding phenomena and regularities that I was able to systematise and apply in markets...
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It is important to understand that there are no advanced concepts to be applied in the embryonic stage of alpha research and so "some will be frustrated at the simplicity".
Experiment No. 1 We need to understand the difference between reversion and momentum.
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The easiest way to think about this is to look at runs and sequences of consecutive transactions in a market. It is instructive to study what is happening as run lengths increase and change sign.
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