StatArb

I find HPCA is a v useful tool for feature selection. Makes the clusters where you need to choose between features much more clear than a correlation grid

Unit tests are an admission that your code might have errors. Real manual HFT developers don’t use them

ChatGPT 让原本无能为力的人能够生成漂亮的图表，这彻底改变了量化交易领域的空间

I have seen some commentary about orderbook vs RFQ. Some thoughts of mine as someone who’s quoted both:
1. RFQ is inherently taker only and as such you hit a limit with costs and cannot ever reach ultra low cost execution required for higher turnover strategies via making into positions.
2. Orderbook will generally be better cost for anything that isn’t explicitly ultra large size
3. RFQ can outperform in situations where the net risk of the position is significantly different than the gross risk. This is multi leg positions and options structures (you pay for the gross of the Greeks when exec

For those who are not good at coding looking to try out quant strategies, I think: is a great product for researching and deploying strategies. Early stage but very cool! Worth trying :)
[This is a genuine endorsement, I have no financial interest here]

I met Stoikov on call once and thought he was a complete retard.
Don’t believe in academics too much

Latest article on the blog (free for all readers): The Industry
How desks, funds, and pods are structured, typical compensation ranges, cost attributions, and smart choices to make as a manager.

Knowledge Snippet
What is a factor?
I feel I never quite understood this idea until I started trading them very actively.
Factors are not anything special, they are just important alphas - NOTHING MORE.
You use factors to say:
Hey these alphas explain a large chunk of the variance and I don’t want to find them again. In crypto that might be a momentum factor so to avoid finding 20 versions of the same effect we use a xs regression to remove our momentum feature from returns and can then test against specific factor returns (returns minus the returns explained by factors basically).
The first

Effects:
1h reversal (crypto)
5-21 day momentum (crypto)
decay effect (crypto)
Small cap anti-premium (crypto)
1-7 day reversal (equities)
long term behaviour characteristics (ts argmax) (ie who had the largest volume spike in the last 3 years) (equities)
Momentum (9-18 months) ( equities)
A lot of the same effects, different timeframes

Crypto alphas tend to work in equities but not equities alpha in crypto I find.
** specifically price/volume alphas, alt datasets don’t compare **

Digging through WQ training material online for new transforms and found this gem from a scam network copy pasting alphas between them as WQ consultants