1) Trading fees. If the house takes a cut of 0.1% on every transaction, then on average those who trade more lose more money.
2) Risk/reward tradeoff. If you buy deep out-of-the-money options, you might have a 5% chance of profitability, but expected return of $0 (neither positive nor negative). 95% of the time you lose $X, and 5% of the time you make $19X. If traders are pursuing riskier strategies, you'd expect most of them to lose money.
For point 2, if there is an expected return of 0, then on average this should push the portfolio toward 50% chance of profitability.
It is the psychological factors combined with a non-random market that ensure most traders lock in losses (usually after riding them too long or not long enough).
If you trade derivatives, fees can be very low (because these are highly-leveraged products but if you are smart you know you shouldn't take any leverage). This can save substantial money if you trade frequently.
> Risk/reward tradeoff. If you buy deep out-of-the-money options, you might have a 5% chance of profitability, but expected return of $0 (neither positive nor negative). 95% of the time you lose $X, and 5% of the time you make $19X. If traders are pursuing riskier strategies, you'd expect most of them to lose money.
There is more to trading than predicting the direction of a stock/currency. You can provide liquidity and arbitrage a stock and its derivatives. Having traded for a while, arbitrage opportunities do exist; though sometimes you might have to be patient and cut off trading until an opportunity arise. This can be quite a time (like a year with no trading opportunity) and will require a lot of self-control.
It exist due to "absorption barriers", due to the ergodicity of the process - betting too big and hitting "uncle points".
It's a bias present in most people, especially otherwise intelligent people: not understanding that there is a huge difference between expected value and ergodic properties. Between expected returns and risk. Just look up what VaR is, the concept is ridiculous, yet so widely used.
How much should the win (5/6) value be in a game of Russian roulette for you to play the game? The answer is that for most people it is not any number, that value doesn't exist.
Can you expand on this? Are you claiming that the stock market is ergodic, or that it is not?
https://medium.com/incerto/the-logic-of-risk-taking-107bf410...
Though I suppose even if you broaden "the market" even to all of civilization - it is also non-ergodic, at least since nukes and hydrogen bombs were created.
I've spent a lot of time on a automated trading side project of mine but haven't found the strategy yet.
In retrospect time has been spent in completely the wrong areas ( setup a solid backrest platform first, duh )
Warning: it is a lot of fun, thrilling, but hard to make money. My winning algos took a while to research, longer to automate, and often lost alpha quickly.
Backtesting is great for validating ideas initially. Especially, to see if it holds up through abnormal markets like '08, or the volpocalypse, or the recent crash. Watch out for curve fitting, though.
Do you apply ml techniques? I don't suppose you could point a little in a good direction to follow
Something like using NLP on SEC filings the second they come out to catch an initial jump in the underlying would be cool to try out.
Tech stack: I love Ruby, but use Python and a custom language that interfaces with the broker I'm using for execution. More and more decent broker API's are starting to pop up out there. So, you can likely use whatever you're most comfortable with. Alpaca has a decent web API, for example.
I honestly wouldn't recommend getting into it, though, unless you really enjoy geeking out over this stuff and have a decent breadth of knowledge to find your edge. You're also competing against some brilliant PhD types who are just as obsessed and hard working as you. My stuff works in part because it's taking advantage of some things that are too small for the big boys to pay attention to.
They need to compete like a human - using their pattern matching skills and reason on the fundamentals. Algorithmic traders that attempt sentiment analysis get fooled into doing things like buying Nintendo stock because female Bowser art was trending.
The main reason why 90% lose money is costs. That is it. Most people probably are optimised for losing money but the main issue is really costs/overtrading.
But related to this, most people believe that edge on profitable trades is very large...but in most markets, institutional-grade costs will still be a big chunk of your edge i.e. costs matter hugely.
The fees are baked into quoted price ("the spread") but the execution cannot be worst than the NBBO (National Best Bid Offer).
They are making money on the spread for sure, probably crossing some trades internally as well. They also make money on the margin rates.
You don't think it's at all strange that 80% of share volume coming out of Robinhood is sold off to broker-dealers attached to large systematic hedge funds?
I'm sure you could think of a thing or two to do with terabytes of retail trade logs and behavioral advertising data.
The rule is that at the time of the execution, the execution cannot be worse than the NBBO.
I'm dont work at a broker dealer anymore, i'm a retail investor. I think where we are is awesome. Ten years ago, these trades cost $7 to $20 ($1 for iB) + spread.
Twenty years ago, they cost $10 to $50 + spread.
Twenty five years ago they cost $35+ + spread.
These numbers are not even inflation adjusted. In think where we are is awesome and a big win for customers.
I'm just saying that systematic hedge funds make directional bets and hold positions overnight. These activities move the midpoint.
That is a hidden cost not visible in spreads or commissions. The SEC can't even measure that cost, only the intermediaries themselves can.
Only if the humans were making decision to buy and sell randomly.
This seems highly unlikely
Sure, there are people that have the skillset and capital to earn a living from day trading that don't have the skillset or interest in running a business who'll be better off trading. But successful businesses selling products or services can consistently earn very large multiples of their initial investment, and day traders can't. Short term financial bets are much closer to a zero sum game than starting businesses. And we've already established that 90% of day traders fail, just like startup businesses. More than 90% since the criteria in this study is beat the index, not earn a living.
This is likely a controversial opinion: 90% of the time, someone who wants to break out of the "rat race" or achieve wealth for some future vision should go the startup route, or if the wealth part is not as important, do freelance/consulting. However, I believe there are 10% of people where trading the markets provide the better way to achieve the same goal. The reason being that for certain personality types (you need to be smart, disciplined, and creative to beat the market, and it still requires a lot of time), I suspect trading offers a higher expected value of return than starting a bootstrapped company. Startups, especially those not started by someone wealthy, have a higher failure rate than day traders. If you are not passionate about anything you can get funding for (would SpaceX have been successful if it were Elon's first company?), and you fit the criteria, trading is not as terrible an option as its reputation suggests.