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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.

Trading through an ECN is a good idea, FXALL is probably a bad choice since they have such a small market share. Currenex and Hotspot are both better. EBS (in EUR, JPY, and CHF) and Reuters (in GBP, AUD, CAD) have the largest market shares, but they both are expensive to set up and require monthly fees regardless of how much you trade, their liquidity in ...

I'm not really sure what your question is, you appear to answer it yourself... If I'm understanding you correctly you are making 2 transactions at 0.6% cost, so then your profit = pred * d_price - pred*(trans) - pred/(1+d_price)*trans That is just your raw profit minus your transaction costs at your opening and closing prices

Your aggregator should be coding not just to the FIX feeds but the specialized protocols. FIX just gives the bare minimum. For example, Hotspot's FIX certainly works but is throttled and doesn't have the full market data detail. You need their Itch. For Currenex, you need their Itch and Ouch. Your aggregator provider should also give impartial advice ...

Find out yourself? -> why not solving for alpha as a function of the difference between the model delta and your true market impact of past trades and subsequent market impact. You obviously need the accompanying data to run such computation but it should be rather straight forward. From my own research I have not found "stiff" formulae to fit the bill at ...