The three major hurdles between backtesting and live trading: slippage worsens execution prices, price limits and trading suspensions make fills impossible, and capacity prevents large capital from getting in—all of which are effectively “assumed not to exist” in backtests. The approach: actively add slippage assumptions, reduce fill rates, and estimate capacity during backtesting; subtract the as…
When conducting quantitative backtesting, applying the same set of factors to all stocks is not only meaningless but also affects the strategy’s performance on individual stocks. After all, different stocks have different characteristics, so so-called universally applicable strategy parameters should not be forced onto them. It is therefore necessary to perform rough screening and group stocks, bu…
The core of quantitative investing is factors. A factor translates stock-selection logic into a computable number: buy stocks with high factor scores and sell those with low scores, then backtest the results. On the surface, this process is mathematical, but behind it lies a deeper question: why are factors able to work? Factors are not truths; they are hypotheses. The premise that a factor is eff…
The core of quantitative investing is data plus factors plus strategy: data is the raw material, factors are the processing, and strategy is the decision-making. The more data you have and the richer its variety, the more accurate the strategy should intuitively be—the more complete the information, the more accurate the judgment, which aligns with common sense. But common sense does not necessari…
Can anyone make Chan theory unique? Or, more specifically, which school of Chan theory can make the stroke segments unique? The pivots unique? The trends unique?
Quantitative hedge funds are becoming increasingly dominant. This is an undeniable fact. Leading institutions have data sources extending down to Level 2, tick-by-tick trades, and alternative data; computing power running backtests around the clock on thousands of machines; and talent pools packed with math and science PhDs from Tsinghua, Peking, Fudan, and SJTU. Individuals cannot compete on a si…
The essence of quantitative investing is data plus factors plus strategy: data is the raw material, factors are the processing, and strategy is the decision-making. The three build on one another, with data at the bottom—factors are calculated from data, and strategies make decisions based on factors. But data quality does not determine the upper limit of a strategy; it determines its lower limit:…
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