Tagged “strategies”
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What a Reddit Sentiment Feature Actually Measures
Scraping a subreddit is easy; the feature you build from it is a model you never validated, sampled from a population that keeps changing.
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Running More Than One Strategy at Once
Two strategies that each work can be worse together. How correlation, overlapping exposure, and capital allocation decide whether combining helps.
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What to Compare a Strategy Against
A performance figure alone means nothing. How to choose a benchmark, build null models, and match them to a strategy so the comparison is fair.
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Is Algorithmic Trading Profitable?
The honest answer is that it is profitable for some participants and not most retail ones. What the question leaves out, and what the real costs are.
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Regime Change and Why Strategies Decay
Strategies stop working for four distinguishable reasons. How to tell decay from a normal drawdown, and why the distinction has to be defined in advance.
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Multiple Testing: Why Your Best Result Is Probably Noise
The maximum of many noisy estimates is biased upward. Why the count of strategies you tested changes what the winner means, and how to account for it.
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Momentum vs. Mean-Reversion, Explained
Two opposite bets about what price does next. What momentum and mean-reversion assume, the market regimes each needs, and how they fail.
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Sortino vs. Sharpe: Two Ways to Divide by Risk
Sortino replaces Sharpe's standard deviation with downside deviation. What changes, what doesn't, and when the distinction is worth the extra complexity.
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How Overfitting Hides in a Trading Strategy
Overfitting rarely looks like overfitting. The forms it takes in strategy research, the tells that give it away, and the habits that limit it.
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How Walk-Forward Validation Works
Walk-forward validation tunes on a window and tests on the window after it, rolling forward. How to structure it, and what it does and doesn't prove.