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by stagehn
2117 days ago
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What's deadweight loss? Trading is zero sum dollars (gross fees) and positive sum utility. If execution flow is paying more slippage in large tick stocks then that PnL must be going to someone's pocket (market maker or short term scalper or prop firm) I don't agree that flow execution is going to be queueing much more than hitting in larger tick stocks relative to smaller tick stocks especially in US equities where the largest tick size is 100 bps and low price stocks have larger volatility. Most of these stocks have multi tick spreads anyway so reducing the tick size does nothing but increase complexity of order management. The bid ask volume imbalance is often skewed in these stocks and you get less slippage by just lifting the entire queue (when the BBO imabalance points in your direction) and being bid-over with half of the average queue size and being front of queue even if you have a low information order you're trying to execute. I can actually make a theoretical argument that large tick stocks is actually better for flow execution as follows: if the tick size is sufficiently large then I can be bid-over with size and not get dimed. Queue position is mine and can't be effectively stolen by market maker algos. I think it's mostly a myth that execution slippage is lower when queueing versus hitting for these large tick names. The average slippage from VWAP from randomly queueing in a stock with a 20 bps tick size will be about 10 bps, roughly the same as if you're just crossing the spread with a large order. But of course this slippage can be massively reduced in both the queueing and hitting execution strategies with some simple heuristics. You can get some market data and backtest this slippage yourself. |
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The key is the total volume of execution flow is not fixed, but elastic to spread sizes. The total slippage captured by market makers and prop traders is higher in 2020 than it was in 1985. HFT firms make more more in aggregate than old school floor traders.
Yet, I think both you and I can agree that by any reasonable measure, tradings costs are orders of magnitude lower in 2020 than 1985. You have to be careful not to confuse an aggregate amount (total industry profit) with an unit cost (average cost to trade $X). The former can rise, even while the latter is falling. When demand is elastic (as it is for liquidity), suppliers make up for lower costs with higher volumes.
> being bid-over with half of the average queue size and being front of queue
This is a tangent, but I don’t think that works for ordinary traders in US equities. Even if you manage to simultaneously sweep the touch at every exchange, SIP is still going to lag and show a stale NBBO. Without an ISO (which civilians don’t have) the exchange is obligated to route the order to the stale liquidity. By the time NBBO updated, an HFT would have already grabbed the queue. I could be wrong though, so let me know if I’m missing something.