Aug

24

 Should one follow a purely Quant approach, as seems increasingly popular today, or should one on the contrary combine quantitative and qualitative ideas for best results in trading? 

Intuitively mixing qualitative judgment with quantitative signals matches pension funds' desire to blame someone if something goes wrong, so intuitively it should command higher fees and more assets. Less cynically qualitative judgment is harder to replicate. Theoretically. In reality I find most people's qualitative judgment is just a randomly executed quant system.

For similar reasons I can imagine purely quantitative processes performing better, when the sole mandate of the manager was to define methodologies to turn systems on then subsequently turn them off. But it's hard to ignore the effect of AQR on fees and industry events like Cohen plowing into Quantopian, as both worsening pricing and increasing competition in the quant space.

I'm trying to figure out what method is the best to pursue. Should I be reading the earnings transcripts, talking to management, using the software companies make and ad platforms of tech companies, doing my best to make a robust qualitative view? Or should I be improving my use of machine learning models and getting more proprietary data sets?

More simply, does the next 20 years in have asset management have a stronger bid for the qualitative, the quantitative or the hybrid?

I would be most grateful for your wisdom.

Bill Rafter writes: 

Let's say you have a quant "system" that you have tested and it has a positive expected value that is of interest. Adding some qualitative/anecdotal tinkering on top of your tested program has a real risk of lowering your expected value (assuming you have no ability to test your tinkering.) So why tinker? Well, it's human nature to do so, and by tinkering you might find something better. Okay, then put 90 percent of the capital into the program with the tested positive expected value and experiment with 10 percent, or just hold that latter capital back for when you positively test another system.

BTW you might want to read Ralph's thoughts on how much to bet.

The tougher part is coming up with the "system". Obviously test everything, especially your assumptions. From reading your note I see that you might have some untested assumptions. For example do you think earnings are important, something which I myself do not know? I'm not saying they are unimportant, just that I don't know. For example we do a lot of macroeconomic forecasting, but we never trade based on it because we have learned that the market does what it wants to do, and not necessarily what the economic numbers suggest. And also we know that a lot of the macro releases are fudged.

One thing you should give serious consideration to is which time venue you will target. Unless you have the right infrastructure it will not be high frequency trading. So will it be days, weeks, or much longer? That will dictate the type of approach you pursue and your research. If it will be very long term, then you have to get deep into company research.

The people who care about earnings tend to look at the much longer time frame. Meaning that your capital is exposed for a long time during which lots of randomness can work their evil ways. [The factors that we are most capable of dealing with are momentum and sentiment, and consequently our time frame of interest is shorter, say 4 days to 6 months.] So identify your strengths and go with them, particularly if those strengths differ from that of the crowd. If you don't know what your strengths are, be prepared to put in a lot of time on research. Minimize your trading during that period otherwise you will not have seed capital to trade when you acquire the skills. You know that, but it bears repeating.

Be prepared for the counterintuitive. For example, when we first acquired the computer skills to do the research we did "test 1". Test 1 was "if you know the market is going to go up, which stocks do you buy?" We assumed it would be the high beta stocks, as they would go up more. But they didn't. Turns out that beta is backward-looking and going forward the high-beta moniker just means higher volatility, which is a negative. So test everything and assume nothing.


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