I am not a quant, but have some related background. (Those who know this area best, may not be inclined to say.)
”Real traders” have many ways to avoid getting front-run to the extreme degree suggested in (c), including limit orders and “trying not to be that predictable” by disguising action to look like other forms of flow.
The amount of pain you experience from (b) depends on whether you think your strategy’s value decays rapidly or slowly.
But there is is a more general problem: it is not just HFT’s but the market as a whole that reacts to your actions: your impact will shift the demand curve for the stock. the size of that impact depends on the information leaked by your actions, information leaked by passage of time, and time allowed for new liquidity to arrive.
but predicting actual impact is hard for a number of reasons (limited data, causality issues)
Knowledge of what other players can and can’t infer from your execution, and modeling impact patterns well, is a multiplier on the value of strategies, hence worth spending a lot to get right.
I am not a quant, but have some related background. (Those who know this area best, may not be inclined to say.)
”Real traders” have many ways to avoid getting front-run to the extreme degree suggested in (c), including limit orders and “trying not to be that predictable” by disguising action to look like other forms of flow.
The amount of pain you experience from (b) depends on whether you think your strategy’s value decays rapidly or slowly.
But there is is a more general problem: it is not just HFT’s but the market as a whole that reacts to your actions: your impact will shift the demand curve for the stock. the size of that impact depends on the information leaked by your actions, information leaked by passage of time, and time allowed for new liquidity to arrive.
there is academic work on theoretical “square-root laws of market impact”
https://mfe.baruch.cuny.edu/wp-content/uploads/2012/09/Chicago2016OptimalExecution.pdf
but predicting actual impact is hard for a number of reasons (limited data, causality issues)
Knowledge of what other players can and can’t infer from your execution, and modeling impact patterns well, is a multiplier on the value of strategies, hence worth spending a lot to get right.