Which do you think is the most profitable in HFT among market making, event driven and stat arb?
Many think HFT is profitable, but few only know which is the most profitable. Let’s discuss a piece of the fact.
Interesting question! I think market making used to be a great form of income, yet now they are getting gamed by faster and more sophisticated predatory algorithms which take advantage of the rules they are forced to abide by. We are actually working to help market makers get their edge back with what we call combative algorithms. Event driven trading can really be limited to a couple firms that have the money for Ultra low latency algo’s, and unless you have that you are getting in the market while they are getting out! For the most part I would vote stat arb as being the “most profitable”, just because that is what majority of trading strategies
I found in Wikipedia that two HFT butiques occupy 15~20% of the whole equity transactions in the USA, which is surprising. They started as a market maker and made huge money in 2008. The profitability of market making seems to be dependent on market volatilities. In terms of HFT stat arb, are there giants like the market makers?
they are GETCO and TradeBot.
In what sense most profitable? Return on investment? Absolute profits? The question could be formulated better.
Having said that, if I had to put my last savings into either of the HFT firms, I would choose market making. The source of income for market maker is the spread (and rebates). Only uninformed traders will give you the spread if the prices are predictable. If the prices are unpredictable you can prove that as a market maker you are guaranteed profit (in theory).
Event-driven arbitrage and statistical arbitrage require research and predicting. You are betting on statistical relationships, which acutally can break down. Profit is not guaranteed.
Finally, many market makers do in fact engage in statistical and event-driven arbitrage: they are not mutually exclusive. For example, your stat arb system tells you that the spread between Google and Apple is too large and you should short one and buy the other. You take these instructions to your market making part and adjust your quotes (price and size).
On my part, firstly absolute profits, then return on investment. If it’s small profits with high return of investment, it’s not enough for me. If its return of investment is very low despite huge profits, it’s not attractive for me, either.
As you said, a market maker seems to be guaranteed. But he still has a risk to be a uninformed trader in the case of trading with/against an informed (institutional) investor. In order to be more informed, what does he have to do? Research, accurate forecasting and brushing up trading techniques easily pop up. In reality, it’s rare to have all skills in one company. So some company has competents in one area and other has them in another area. That’s my general thought, so I asked “are there giants like the market makers?”. The giant market makers may do well in stat arb or event driven. If you know how they do well in both ereas, please let me know.
I don’t know many giants. I know RenTec is a giant in statistical aribtrage. They have to have world’s highest average IQ of an employee. Without a numerical phd you don’t have a chance with them.
Then there is Citadel. I think they’re big in market making, but I’m not sure. Googling will definately give you some answers.
You are correct that market makers have to reseach something, but it is still different that if you trade purely stat arb. Besides, if price are random, then there is nothing to research and you are guaranteed a profit.
I checked out RecTec webpages and reached to Job Openings page. They want quantitative finance candidates who they say ideally have “A Ph.D. in Computer Science, Mathematics, Physics, Statistics, or a related discipline”. There is no word “a phd in finance”. It seems like computer science is the most important for them. Then I understood the reason why they are a top runner in HFT field.
In terms of how they trade, I didn’t get a clue in the pages unfortunately, cause I couldn’t log in. But time is changing. In1980s, a high IQ guy dropped out from Turtles training course. Nowadays, high IQ guys seem to be successful. Things on the earth must not differ so much from the broard perspective. I am curious what kind of skills they, phds in non finance, have in general.
This thread at Nuclear Phynance is the best source on RenTec:
Also, search for Jim Simmons, the RenTec’s founder. He does not like to give out info about his hedge fund, but there are some interesting interviews with him floating the interwebs.
Would PhDs in RenTec use regression to grasp a price behavior or pattern? Kinds of regression vary from ols (ordinary least square) to ridge. But almost all of them are based on the assumptions of normal distribution, which looks like to have relatively big estimate errors when implementing into practice. I have heard from some statistician that another methods could be better to forecast the future than statistical methods.
In a sense, PhDs in mathematics or physics are advantageous in utilizing regression, cause they understand the fundermentals on the mathematical ( or statistical ) tool. So they could modify or improve it to gain less estimate errors. But nobody knows how. Is there somebody who plays or will play a roll that Donchains did on Turtles.
I found another article about HFT houses and other players. A bit interesting.
thanks for the article. We know the race to zero is occupied by the few firms mentioned in this article and above. Going forward, the only way to compete is to have more flexible algorithms. The ability to change your parameters to tweak your algorithms real time, will ultimately be a longer term solution for success.
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