Robot James πŸ€–πŸ– Profile picture
Mar 18, 2021 β€’ 15 tweets β€’ 3 min read β€’ Read on X
How do I know if I have an edge?

A thread... πŸ‘‡πŸ‘‡πŸ‘‡πŸ‘‡

I've been helping a family friend with his trading. I've given him a simple systematic strategy to trade by hand.

We can plot the distribution of historic trade returns from past trading or a backtest as a histogram.

1/n
The trade P&L is on the x-axis and the frequency (# of trades with that P&L) on the y-axis.

This is useful because it gives us a hint as to what the "edge" of our strategy might be - if we could ever truly *know* such a thing.

2/n
In this case, our strategy had positive mean and negative skew.

We saw winning trades about 58% of the time but losers were bigger, on average, than winners.

(As many things that make money tend do, regrettably)

3/n
Now, when we make a trade, we're really just taking a random sample from a bucket of returns.

You might think of it like we're picking observations out of the bucket described by the histogram we just made.

BUT....

4/n
The histogram doesn't show us the true nature of the distribution of returns in the bucket - just the returns that occurred in the past.

The "true distribution" changes with time (it is stochastic) and cannot be observed directly. We can only infer it from the past.

5/n
So the best we can know is that, in the past, it looked like we had an edge.

We might run rolling stats to try to observe the time-varying nature of things - but we'd be working with only a few samples and the variance of our trade return is large.

6/n
So we do our best to estimate what the "true process" looks like, by inferring it from past observations and our understanding of market dynamics.

Now we have set reasonable expectations about the P&L distribution, my friend starts trading...

7/n
My friend has placed about 20 trades and he's starting to try to make some distinctions based on individual trades.

"I've learned to exit later when momentum is in my favour" etc...

This is what humans do. They look for patterns in noise.

8/n
Ultimately, however, analysis at the individual trade level is meaningless.

He's just fitting stories to random data. Individual trade P&L carries no useful information.

9/n
Think about the trade p&l histogram we made at the start.

Imagine we're building that up trade by trade, observation by observation.

How many points would you need before it had a meaningful shape?

10/n
All analysis needs to be undertaken in the aggregate, ideally over as many stable observations as possible.

But everything is non-stationary (it changes with time) so our observations always arrive later than we want them to, and there are never enough of them.

11/n
This is why trading is hard and you don't get much feedback (on edge) from observing your own trades.

You get plenty of useful quick feedback on things such as market impact, but the data on "edge" takes forever to collect and stuff is constantly changing underneath you

12/n
You're extremely unlikely to make much sense of this kind of probabilistic thinking by watching the market - unless you are trading extremely fast and disciplined.

You need a quantitative approach. You need to analyze in aggregate. You need an understanding of stats

13/n
You need a critical mind. You need to understand why something works, and track whether those conditions are still in place - so you can try to pre-empt the change in the return process.

You need to understand you can never *know* if you have an edge right now.

14/n
As @AgustinLebron3 pointed out the other day, this is not something to be feared... this is what makes trading awesome!πŸ˜€

You never know if you have an edge right now, but when you think you do - sample from it as much as you can in the simplest, most robust way possible.

15/15

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More from @therobotjames

Jul 8
one of the most important things i tell people over and over again, like a stuck record, is that their trading should look like a useful thing that sucks.
you know that there are extremely sophisticated trading firms out there with ultra-low latency infrastructure and sophisticated modeling techniques.

and you might reasonably ask how you, as an individual, could possibly compete with that.
and the answer is that you can’t.

but you don’t have to.

you shouldn't even try.

so, why then, can many small speculators do ok and make money?
Read 9 tweets
May 21
nearly everything that is a good repeatable trading idea looks like:

"under <some circumstances> this thing is likely to be too cheap/rich because <some people> are being forced or greedy or stupid... so the thing is more likely to go up/down in the future" Image
your job as trader, operating in an efficient, competitive market, is to tell yourself that your idea about that is probably bullshit.

and quickly prove to yourself that it is indeed bullshit.

destroy those hopes and dreams quickly... and move onto something more productive. Image
you can show that something is a BAD idea way quicker than you can show yourself that it's a good idea.

and showing yourself quickly that something is a bad idea is a GOOD thing...
Read 16 tweets
Sep 30, 2024
all active etfs are trash.

under the premise that all active etfs are trash, i looked at what it would look like if you could shorta bunch of them against an equivalent SPY long.

the legs are sized to equal volatility based on 120 day rolling realized vol. Image
highlighly scientifically, i looked at etfdb and picked 15 active / tactical ETFs based on their name and category. Image
here's the performance of the long SPY / short ETF pairs individually.

some did less bad than others, but all the ETFs underperformed SPY, risk-adjusted.

FIG, HFND, MOOD look especially bad. Image
Read 6 tweets
May 17, 2024
andy's top didn't last all year, but it lasted 32 days.

is that a lot or a little?

it's a lot

if you called a top on every new 252-day high, most of the time, the call would fail the next day

the expected length a top would have held is 9 days

andy's top is 95% percentile Image
that the median case is to fail straight away should be self-evident.

if the market was 50/50 up or down on a given day, half of the time the top call would fail the next day.

but, as you know, the market prefers to go up, so the most common outcome is it failing the next day.
the mean of 9 days is pushed up by a few very long tops - such as the 1375 day one that started in october 2007.

here's what the histogram would look like if i didn't truncate the x-axis Image
Read 7 tweets
Apr 30, 2024
i think people new to markets massively underestimate how noisy everything is.

your job as trader is to try to work out when stuff is likely to go up or down, right?

then you can bet.

any trade might not make money but do enough good trades and you're likely to over time.
the problem you have, is that things go up or down for a million different reasons.

and the massive majority of those reasons are unknowable before they happen.

why?

cos tons of people are betting on this stuff, so all the obvious stuff gets priced in beforehand.
if we know something is gonna be trading $100 tomorrow, where's it trading today?

well, $100, give or take.

it trades for the price where you can't make any money trading on obvious shit everyone knows, right?
Read 8 tweets
Apr 23, 2024
trading is hard.

if you disagree, that's cos you haven't done it for long enough.

you can get lucky for a while - but your luck will inevitably turn

you can find yourself doing the right thing at the right time for a while - but markets adapt quicker than you can, typically.
extracting returns from the market, persistently, over years and decades is tough.

it requires pragmatism and flexibility.

it requires you to be decisive about trade-offs, in a world of incomplete information and massive uncertainty.
if the responsibility of turning money into more money incites a certain amount of anxiety in you, that is the good and natural and correct response.

financial markets are highly competitive.

that's because they are competitive, they are highly adaptive.
Read 18 tweets

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