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So it's clear that the length of the backtest, and the size of the search space, are absolutely critical things to know to assess the backtest. With a short time period and a large search space you can find a backtest which is arbitrarily good
You also want to know about the assumptions being made, particularly about when the data is available to trade on, how quickly you can execute trades, and what slippage you expect to experience (in terms of fill rate and implementation shortfall)
The simplest explanation for a Sharpe 5 backtest is look-ahead. Many variants of this but essentially it means the backtest assumes some data is available before it would be in reality, i.e. the strategy is allowed to see the future.
Another mistake is to assume that you can observe a signal and instantly trade on it at the observed market price. In reality there is a lag between observing a signal and trading on it, and the market moves in that time. If the signal is good, the move is normally against you.
You are also likely to experience slippage which is correlated with your alpha, i.e. conditional on your signal being large, you will have a lower fill rate and will get filled further from mid than if you traded randomly. If not modeled, this inflates backtest performance.
Third I want to know about the style of the strategy, e.g. number of markets trading, average holding period, whether it is simulated using daily data, minute bins, L2 tick data etc.
It's simply not plausible to have a strategy with a > 1 day holding period that has a Sharpe of 5. It's not even plausible to have a >1 hour holding period with a Sharpe of 5, this is the realm of high frequency trading.
Obviously can't cover anywhere close to everything in ~10 tweets but these are the 2-3 most important questions to ask about any simulated strategy, **especially one that you came up with yourself**
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