How do you assess if a spread is (relatively) large or small? - page 2
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There can be all sorts of solutions, but as the market is dynamic, here's how I see things. Write an optimiser that runs through a week's time series data looking at each tick. Run this optimiser only once a week to get new optimised data. The optimization process itself is simple. It is necessary to go through the data only one time to calculate the average spread. Anything below the average is low and anything above the average is high spread. For a more detailed categorization of high and low spread, you can calculate additional metrics. For example, at the same time, You can calculate incrementally standard deviation or mean absolute deviation based on the running mean. Now you can set your transaction filter. Additionally, if you want to trade during the news and look for the best place to enter with a spread, then it gets a bit more complicated, but that too can be done by incorporating statistical values into Your spread calculations.
However, here i only wonder if every tick of historical dickdata contains real recorded bid and ask data or also derived data. (Someone who is competent could inform). If it is the second option then collect the data in the optimizer in real time and keep it to the extent necessary.
Now, coming back to the original topic question - of course, such an optimizer should be run on a per-instrument basis because spread of each trading instrument is different.