Obviously you should do some parameter averaging, e.g. you could compute the signal using various speeds from 5-15 days and average the positions over each parameter choice, to make the strategy robust.
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This is just an example so I'll use the 7 day moving avg. Chart below shows performance of this strategy. Need to remember that we picked the best parameter in-sample plus there will be transaction costs so real world performance will not be this good, but it looks promising!pic.twitter.com/ZgmfUymkwV
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With some additional robustness checks and careful implementation of a simulator for fill prices, commissions etc you are well on your way to launching your first quant strategy.
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Only problem is that the price series is one I generated using 100% random noise, it is completely unpredictable by any signal. Congratulations, you now know how to overfit a backtest. Welcome to quant research.
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Replying to @macrocephalopod
This is Shannon's Demon - you can get meaningfully positive ER by volatility pumping. Sure, it has issues (its basically short gamma) but what you found is "legit" and not an overfit.
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Replying to @macrocephalopod
The fact you chose 7 days is an overfit. However, the fact you see positive Sharpe at any horizon is because of Shannon's demon.
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Replying to @zzzrrrzzz12 @breakingthemark
This is further proof to me that the “shannon’s demon” crowd are actually insane.
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Shannon’s demon needs +ve arithmetic return but flat or negative geometric return. I generated this data myself so I know it has zero arithmetic return! The fact that you would argue with me about data *that I made up* is simply a confirmation that you are an idiot.
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Replying to @macrocephalopod @zzzrrrzzz12
To be fair, you started the thread portraying the data as a real stock, and not a random stream you made up. What's the volatility of the actual data, and I assume it's daily data?
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The entire point is that it’s a bait and switch! There is absolutely no way that you can read the entire thread and conclude “yes, it would be possible to make money from this” unless you are a moron. It’s 1%/day volatility zero arithmetic drift geometric brownian motion.
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Well, I'd like to think I'm not a moron, and it wasn't clear to me the arithmetic mean was 0 until you explicitly said so. Maybe that was immediately clear to non-morons before you said so?
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Mean zero is the *best case* for the strategy I described! If mean > 0 then a reversion strategy is short more often than long so it would lose money. If mean < 0 then a reversion strategy is long more than it is short so it would lose money.
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