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We cannot give you a relative bid-ask spread that would make sense. The reason for that is that it really depends on several parameters: The type of financial asset you invest in (futures, funds, index, options, ...) The period during which you're trading (I think the liquidity in markets hasn't been the same over time). If you trade intraday, it depends ...


When I simulate, I can usually narrow my trades down to the minute. So I set my Open price at the HIGHEST price for the minute, and my close price to the LOWEST price for the minute. The goals is to be as conservative as possible. You don't want to go live and find that you were too optimistic in your fills. If you cannot narrow it down to smaller than a ...


Other answers all give helpful advice, but none actually answer your question, so I will try. First off, backtesting based on close is reasonable only as a poor-man's first approximation, and before committing serious capital I would recommend collecting some higher frequency data. Having said that, it is actually quite common to investigate ideas quickly ...


The bid/offer spread is informative about a narrow range of transaction sizes, i.e. the quote depth. E.g. if we see a bid/offer of 99/101 with quantities of 1000/1500 shares respectively then we know that doing a trade to sell upto 1000 shares will get an execution of 99 and doing a trade to buy upto 1500 will get an execution of 101. But the trades that ...


We discussed the validity of using bid-ask spreads as transaction costs in this post. Essentially the bid-ask spread represents the cost of liquidity which can be seen only as part of the transaction cost you will have to pay in live trading. There are a lot of things to be considered if you want to include transaction cost in your backtest. The main ...


For the brokerage fee, consider coding a system that calculates the fees for several brokerages (so that you can compare brokerages). For the slippage (and other issues), consider coding that in as well. Adjust prices based on the slippage percentage. Once you do that, you can vary the slippage and determine how much slippage will break your algo.


IMO, there is only one satisfactory answer to your question. You must measure the actual total cost of implementation. Spread, slippage, comish. Test what you trade/trade what you test.

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