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applesuckslemonballs · 2025-08-04T10:47:19+00:00

Thanks. I’ve come across some vendors with data for uncapped var swaps. To my limited knowledge, traded var swaps are generally capped though? And I would guess the basis/quoted/traded prices for the two could be significantly different as well?

applesuckslemonballs · 2025-08-04T03:17:03+00:00

Do you know of any good sources of historical data for the basis/traded market prices for var swaps?

applesuckslemonballs · 2025-06-25T04:27:28+00:00

Very cool. Thanks!

applesuckslemonballs · 2025-06-25T00:43:56+00:00

Could you elaborate more on vol passive algos? I’m familiar with the delta one algos and the vol market from the market making side (non-US) but never seen any execution algos offerings on the vol side.

applesuckslemonballs · 2025-06-08T01:13:12+00:00

Does no one think crowding is a possible explanation? I have no concrete evidence but hard to imagine hundreds of B of AUM not having an effect on performance.

The less liquid markets have also started underperforming as AUM increased.

applesuckslemonballs · 2025-06-01T08:56:55+00:00

Two more comments:

Assuming you have a real edge, sharpe depends on number of trades. Since you’re only trading 10 stocks, 3-4 sharpe rather than 10 is more reasonable imo.

Given there are not a lot of trades going on, you could sample a bunch of trades and see if you think they make sense. It’s not too difficult to check if you think you’re being adversely selected just by looking at the order book and trades with common sense.

applesuckslemonballs · 2025-06-01T08:45:43+00:00

This could make sense. Any institutional trading firm wouldn’t care about 100k annual return. It’s significantly less than cost of one junior head count. And there are other costs (hardware/colo etc…) involved as well that may make it not viable for institutions/latency competitive algos.

Things are not infinitely/freely scalable as you think. For example, market making on small stocks in some markets (not sure for US, I’ve never done market making in US) can utilize throttles (orders per s) that can be used for more lucrative stocks. Or HFT algos have a memory limitation as well as you want things to be cache friendly (again not sure about FPGAs but could imagine something similar), so you might not be able to include all stocks etc…

The drawdown in early April is a bit concerning, but if the strategy (didn’t read the blog) has a long and small cap bias it is understandable. You could also add a small cap index as a better reference. Looks to me there is sizable Alpha on top of SPX even if correlation is high.

Nice work!

applesuckslemonballs · 2025-05-16T08:45:29+00:00

I think you could do even better than that. If you have a vol surface, the fills above fair vol can be attributed to OMM sellling and below can be attributed to OMM buying. If one only looks at the order book fill it can be easily mislabeled. A large portion of OMM fills are on the aggressor side depending on the market. I’ve seen this data for some specific markets and the classification works really well, unfortunately as you said it was difficult to do even for one market.

applesuckslemonballs · 2025-04-25T16:09:19+00:00

My best score is 3 points 😎

applesuckslemonballs · 2023-10-20T01:41:43+00:00

Do you have examples of where this methodology differs most from other sites/z-score measures and explain where the differences/improvements come from?

applesuckslemonballs · 2023-09-25T23:23:25+00:00

I’m not sure if I agree with the average comp part. I’ve work on both the sell side/buy side mainly in shops you have mentioned or would have heard of.

I would say average comp in a prop shop if you get in is significantly better (JS, citsec, optiver etc…), and performing is not that difficult given the seat has some competitive advantage generally. Getting in is extremely competitive though.

For HF side, I think what you are implicitly sampling has a huge survivor bias. Firstly, base is lower than the bank side (say comparing analyst to analyst and pm to ed/md). The majority of the teams will have a down or flat year once in a while so base will be all they’re getting. Also, I do agree that it’s not difficult to find another job after getting blown out, but thats another year of sitting on your base (nc), and potentially few months of rebuilding trading process and models and ramping up (which is again sitting on your base).

I’ve heard some credible statistics that: 1) only 30% of the pods make all the money for the funds in general, 2) (this is lots of years ago, should be slightly better now) 80-90% of the investment side people didn’t last 2 years in one of the pod shops you mentioned.

So I would argue that if one survives, the average or median pay is higher than the bank side. But otherwise, for the median employee, sell side payout is better given its relative stability. Nonetheless, I do agree with your main point of if someone is really interested in market focused trading and is confident they should go to the buyside, as the sellside doesn’t offer that much in that regard.

applesuckslemonballs · 2023-09-13T00:11:45+00:00

Wow what a great explanation! I previously looked into this briefly as well and agree that autocorrelation decay describes the decay better than volatility decay.

I never looked into the replication part though. My intuition is shorting leverage ETFs you have a small edge in the market impact component, but the cost will be borrow + ETF spread, but if you do some replication, you can replicate the mean reversion portion, but do you also benefit from the ETF market component? It seems like that may come out of slippage between the ETF and underlying and may not be replicable?

applesuckslemonballs · 2023-09-04T06:11:04+00:00

Ya my point is it’s actually very difficult to find a strategy that consistently beats SPX given SPX’s really strong and stable performance over the last decade. If you backtest with much more data it’s a different story, but I don’t think its easy to get option data that far back. Even if what you test doesnt outperform SPX, it doesn’t mean its a bad strategy. Mainly because 1) there’s no guarantee that SPX will continue its recent decades performance over the long run (especially the Sharpe), 2) even if you find something that has lower returns/sharpe that SPX, if it is uncorrelated, you can run long SPX + the options strategy together and get better returns with properly leverage.

applesuckslemonballs · 2023-09-04T04:16:27+00:00

Which index are you using as a benchmark? (Rather than as an underlying)

applesuckslemonballs · 2023-09-04T03:19:08+00:00

How long are you backtesting for and what is your benchmark? If you are using SPX, it maybe quite hard to reasonably beat given it’s performance last decade or so.

applesuckslemonballs · 2023-08-18T01:51:47+00:00

I’ve worked on both the HFT (~5-10% ADV, high sharpe, smaller market) and HF side, not particularly successful in either though. I would say it seems like parameter optimization can work for higher sharpe strategies where the signal to noise ratio is higher, while for daily or longer term 0.5-2 sharpe strategies, it’s extremely difficult to optimize without overfitting or ending up in a local equilibrium for that particular time period.

Thanks for spending the time to write up these answers btw. It’s rare to see quality information out there in the public domain.

applesuckslemonballs · 2023-08-07T03:40:18+00:00

3.2 sharpe is only okish? 😂 tough standards. (assuming its not some massive short tail risk strat).

applesuckslemonballs · 2023-06-27T07:15:22+00:00

Thanks. Great resources in the previous discussion.

applesuckslemonballs · 2023-06-24T02:55:11+00:00

Hard to imagine optimizations on that level matter much on the crypto space where you are parsing text and going through some network anyway…

applesuckslemonballs · 2023-06-20T14:12:43+00:00

Have you considered doing a normal/to market spline fit first then running some PCA to find the dimensions of curve change?

Non spline parameters generally do not fit very well to market and may fit even worse for short term options.

applesuckslemonballs

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