What does the autocorrelation structure of your alphas have to do with running market makers over? 1/9
In general, as a taker going after an edge you need to be more right than the market maker does to requote.
For example, you as an aggressor have a 2 bps taker fee looking for 2 bps of edge over fair. Maker has 0 bps maker fee and is trying to keep their ask 2 bps over fair. 2/9
Aug 23, 2021 • 9 tweets • 2 min read
This fox has been receiving some messages about optimizing C++ code, FPGA's, etc. Allow me to somewhat rigorously explain why this is mostly worthless in crypto. (a thread) 1/9
Fluctuations in latency are primarily a function of two things: exchange congestion and jitter. Let's assume that instantaneously exchange congestion is held constant, and i.i.d normal jitter is the sole source of variance in latency. 2/9
Aug 22, 2021 • 4 tweets • 1 min read
A simple microstructure insight to apply is paying attention to your queue position on a given price level.
Having a resting limit order at the back of the queue with no size behind it is like signing up for an immediate small unrealized loss if your order gets filled. 1/4
Even if you are click trading, this can save you a few bps on execution in thicker tick, slower moving markets like those in some altcoins.
Although in a busier market like BTC or ETH, a human generally can’t react to their queue position fast enough. 2/4
Jul 22, 2021 • 8 tweets • 2 min read
A thread on microstructure on high rebate/high taker fee crypto-derivatives exchanges. E.g. BitMEX, Bybit. This may be common sense to some, but I explained this to a tradfi trader and they found it helpful. (1/8)
Stylized fact #1: Despite a relatively thin tick in BTC, these markets trade one tick wide 99% of the time.
Stylized fact #2: When the price moves, it often moves by 20-40 ticks at a time instantaneously. (2/8)
Jul 16, 2021 • 7 tweets • 2 min read
Figured I would compliment the shitposting with some thoughts. This meme was based completely on a true story. People talk a lot about mental game for discretionary traders, but mental biases for quants are under discussed in my opinion. (1/n)
1. Confirmation bias w.r.t simulations: How often do you look for bugs in your backtesting framework when performance looks good vs bad? When performance looks bad the inclination is to peruse the code. When things look good, ignorance is bliss. (2/n)
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