MFT & HFT | Views my own. Not financial advice.
Zug
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It follows an auto regression process - you can fit a recursive AR (X) model to forecast funding out. It’s fairly easy and beats an EWMA of funding. It’s not the biggest of questions to answer in quant finance but nonetheless it’s an easy incremental boost
How sticky is funding?
I compared today with tomorrow, then the previous 3 days with the next 3, and 7 with 7.
Higher funding tended to stay higher, especially one day ahead.
That gave me a reason to keep looking. The price move still matters.
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I once posted an order of options by accident to sell something with mid priced at 10k for 1k and nobody hit it until I cancelled it an hour later. #ilovemycounterparties
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I think maybe 3 times so far someone has posted on Twitter which led me to finding a very profitable feature in my own research :)🧐
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To somewhat defend Kalshi:
As seen in the fee schedule. Maker rebate + taker fee net to 0 for eligible participants. It’s more likely to be another trader who wants to pump their own volume than Kalshi themselves.
Regarding the 1 cent bet being counted as a whole dollar - using notional volume is very common in options. Usually you just count premium traded and notional traded as different numbers. This doesn’t feel so bad to me, they just picked the prettier number and haven’t done anything very uncommon in the options world.
This said they probably should be banning people who wash trade and adding an asterisk to the volume number. I think it’s gone a bit far to imply they are wash trading themselves which is much less likely and very different than failing to ban / detect those who do it.
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Need a large universe to work with this many factors. Would be too much of the cross section explained away for even S&P500. Need roughly N/5 as upper limit. 153*5=765 min cross section.
jkpfactors.com is a great library of the factor landscape, 153 factors that make up 13 clusters.
The mean strategies of these clusters cluster again:
Quality: quality, profitability, profit growth. momentum is also attached here, as it correlates to profit growth.
Value: investment, value, low risk. short-term reversal is loosely attached.
Leftovers: accruals, size, debt issuance, low leverage. their common feature is being mostly anti-correlated with the first two groups.
seasonality is its own odd thing, even its constituents don't correlate with each other.
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It’s in rotatingsandwiches.com so I’d say yes
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Check out the site @Vertox_DF made for practicing for quant prep:
eigenscore.com
First contest is tomorrow
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Important question, what are we naming our exchange adapter ‼️‼️‼️
32%
OkexClient
68%
OkxClient
142 votes • Final results
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I know extremely profitable desks (9 figs PnL) where they don’t check the Sharpe unless it’s a systematic strategy. It’s simply is the PnL positive every quarter. Seen multiple desks like this (often very discretionary) print like crazy. Not everyone runs quant books @ 3+ Sharpe
Quant says literally no successful trader sells a course.
I call him out to put skin in the game.
Quant says sure. Then defines success as “15m/yr in PNL for at least 3 years.”
Well, I guess 99.999% of traders and humans are unsuccessful. Great post as always from the quants.
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At a lot of Chicago style shops, it’s just don’t hit your DD and how much PnL did you make.
There’s very profitable teams out there which consistently have done very well for themselves and their firms without having infinite sharpes. Sometimes being willing to stomach some risk, and be convinced in your views, is a core part of the edge itself.
I know extremely profitable desks (9 figs PnL) where they don’t check the Sharpe unless it’s a systematic strategy. It’s simply is the PnL positive every quarter. Seen multiple desks like this (often very discretionary) print like crazy. Not everyone runs quant books @ 3+ Sharpe
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Stat Arb retweeted
Quant says literally no successful trader sells a course.
I call him out to put skin in the game.
Quant says sure. Then defines success as “15m/yr in PNL for at least 3 years.”
Well, I guess 99.999% of traders and humans are unsuccessful. Great post as always from the quants.
A good trader can generate high $ returns and high risk-adjusted returns, consistently over a good chunk of time. So I’d propose something like, over the most recent four year period (2023-26)
- Total P&L over $60m (ie $15m/year)
- Sharpe ratio over 3
I’d probably accept a shorter period with a higher Sharpe, or lower PnL with a higher sharpe, or higher PnL with a lower Sharpe. Can discuss details if you’re happy to go ahead.
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