I have a mean reversion strategy based on the comparing the results of several types of sentiment analysis in real time. It earns between 3 - 15% in options trading every few days with a win rate of around 70% and an average holding time of a few hours. Stop losses are at -70% or so.
Algorithmic trading is very difficult, but it is empirical. Information asymmetry exists in the market, and if you can capture it you profit. I don't know how capacity constrained my strategy is (I think it would be difficult to work this strategy profitably with over $10M depending on how much effort you put into execution; my execution is unsophisticated and I'm working with two orders of magnitude less than that), but it's working.
Am I reading that right, you lose one trade you lose 70% of your capital? Sounds like a very very dangerous strategy with a near 100% certainty of blowing up the account. The optimal trade size for equity growth (which is itself hugely risky) is vastly smaller than that.
Hah, no that's a typo, sorry my mind was a bit scattered in this thread. I meant to type that stop losses are at -15% or so (of the position, not the portfolio).
There is a separate risk management metric in play that automatically closes positions and pauses the strategy after a specific number of losses in a row, or after the strategy's capital allocation drops below a certain percentage (whichever comes first).
> -15% or so (of the position, not the portfolio).
Oh... HUGE difference. What percentage of the portfolio is the position? How long have you run this strategy; I ask because those are huge returns that indicate to me you're taking huge risk which can work short term but nearly always wipes you out over a sufficient amount of time.
> It earns between 3 - 15% in options trading every few days with a win rate of around 70% and an average holding time of a few hours.
If those returns could be held for any length of time you'd be wealthy in no time.
> Oh... HUGE difference. What percentage of the portfolio is the position? How long have you run this strategy; I ask because those are huge returns that indicate to me you're taking huge risk which can work short term but nearly always wipes you out over a sufficient amount of time.
No single position can be more than 10% of the portfolio, there is no limit on concurrent positions, and the strategy cannot use more than 20% of the account's capital. Each position has a profit target, normally a 5% increase on the cost basis, and when it's opened a GTC order is immediately submitted to flip it. But this isn't a market-making algorithm or something that requires serious latency considerations - the target holding period for each position is less than five days, after which if the position is still open it's flagged. The strategy has been running continuously for only eight months; prior to that it was backtested with historical data before launching live. It used to be that the mean holding time was around 2 days, but lately it's been flipping positions in fairly short intraday scales (an hour or less), which means I'll be adding more risk accountability to it.
> If those returns could be held for any length of time you'd be wealthy in no time.
Yes...however this strategy has generated less than $30,000 in profits since its launch (on an initial outlay of $10,000), and I don't reinvest profits.
This is an options trading algorithm, and I don't think there is enough liquidity available in the targets to significantly ramp up capital from here without adding on more leverage (and risk). The other difficulty is that a confluence of factors needs to happen somewhat simultaneously in order for a candidate equity to become a target.
Due to this, it's more accurate to say that the strategy generates a few hundred dollars weekly to biweekly (on average). I may be overcautious, but this is primarily a research project for me. I would not actually be trading with real capital were it not for the fact that I'd like to demonstrate the results in the future.
I use Interactive Brokers (the Python TWS API), with a trading system I've written in mostly Python and C++. Yes, I'm charged per trade (occasionally there are rebates, but the strategy doesn't optimize for adding liquidity). I don't have the trading volume to negotiate flat commission rates (nor is that really high on my list of priorities).
Algo trading typically utilises technical analysis which is basically patterns proven to repeat in markets for a variety of fundamental reasons, or fundamental analysis (e.g. algorithmically valuing and pricing options based on underlying fundamental data, sentiment analysis, etc.), and buying/shorting as appropriate. It is based on scientific methods: empirical evidence being used to validate hypothesis that produce results that can be shared and repeated by others.
Astrology is story-telling with no scientific grounding.
> technical analysis which is basically patterns proven to repeat in markets for a variety of fundamental reasons
Technical analysis is merely another name for hindsight bias. Those patterns only look like they repeat in hindsight because you're ignoring all the failed patterns that setup right but failed to play out and thus don't look like the pattern in hindsight.
Technical analysis is exactly like astrology and is in no way grounded in science. Quantitative analysis is based in the scientific process, technical analysis is superstition created by visual traders who think they see patterns but fail to understand biases. You are confusing the two, technical analysis is a pattern library of nonsense like "head and shoulders" or "dead cat bounce" based purely on visual patterns in price data that only "appear" to repeat due to hindsight bias. It is in no way remotely scientific.
I've spend thousands of hours testing trading patterns in Forex, they're all nonsense that lose as much as they win over any decent sample size which equates to random.
Edit: to the guy below, You should ask for sources that back up the claims that it does work. You won't find any, it's trader superstition, not science. You don't have to prove things don't work; you have to prove they do. At least if you want to call it based in science. However, the field of quantitative analysis itself is proof technical analysis doesn't work; it's what happened with people who actually knew math got into trading and discovered the technical analysis superstition that visual traders who lack math skills made up.
Well they are obviously fundamental type of investors, and I have no doubts this type of investment is superior to pattern matching and chart gazing. But I see all those guys doing their pretty technical analysis charts in stocks and bitcoins and even though I think it's all BS, I wonder, is it? I mean, can you get a small edge? why would they be at it all day if it wasn't making them money?
> I mean, can you get a small edge? why would they be at it all day if it wasn't making them money?
It's gambling, they win randomly and falsely attribute the wins to tech analysis and dismiss all the losses as them "reading" it wrong. The random wins attribute to an addiction and superstition but they'd win just as much flipping a coin to decide whether to buy or sell. These people are very bad at math, if they were any good they'd be doing quantitative analysis and looking for actual patterns in the data that stand up to real scientific inquiry. Technical analysis is to quantitative analysis what alternative medicine is to actual medicine.
If this was the case...if there was way to make money off of scientifically proven, reliably reproducible 'stock market patterns' everyone would be a billionaire.
When filing for its IPO in March 2014, it was disclosed that during five years Virtu Financial made profit 1,277 out of 1,278 days, losing money just one day.
They don't rely on technical analysis. They are arbitrage trading across different markets, where there's zero chance of losing money if you're fast enough and doing it right. That's why HFT is so popular, if you're doing it right you can't lose money.
Nothing can be predicted because there's way too many confounding factors.