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So what's your point? Sure, you can mess up your test -- does that mean you shouldn't trade? Does that mean you shouldn't run validation tests at all?

by consz 11y ago

dschiptsov 11y ago
My point is that there are more faith and wishful thinking than science in all these "models". Moreover, the very nature of the markets are too complex to model, especially using such data sources. The result would be some naive description of reality, like pre-scientific religious cosmology, a wrong but sophisticated enough 'model' based on 'current consensus'.)
- consz 11y ago
  Have you worked in a variety of quant funds? What makes you think markets are too complex to model? What evidence do you have that the models used at successful shops are not sufficiently rigorous?
  - dschiptsov 11y ago
    Because all one needs is to bullshit one's boss or sponsor. I gave an example of a religion for a reason. And bullshitting is much more efficient strategy than actual modeling and rigorous research. Group thinking is much easier and cheaper than proper science, especially when even the best economists are full of doubts. I took Yale's financial markets courses, so I know what ideas they might have. This is the Nobel laureate's course.
    - consz 11y ago
      The bosses in the typical quant firm are also quants themselves, and have no trouble following the rigor used to justify the validity of a trading strategy. Sure, at a certain point in the chain, you're talking with someone (eg. COO) who isn't allowed to see the details of the modeling procedure, but this is the point of scaling up and having risk/pnl limits -- no HFT firm, for example, is at risk of blowing out from lack of statistical rigor. I doubt taking Yale's financial markets courses is sufficient to understand or be exposed to what is currently being used in quantitative finance. I took Stanford's financial markets and statistics classes, and those are far behind and unaware of what's currently being used in the industry (I've worked in two highly successful HFT groups since Stanford).

So what's your point? Sure, you can mess up your test -- does that mean you shouldn't trade? Does that mean you shouldn't run validation tests at all?

by consz 11y ago

So what's your point? Sure, you can mess up your test -- does that mean you shouldn't trade? Does that mean you shouldn't run validation tests at all?

dschiptsov 11y ago

My point is that there are more faith and wishful thinking than science in all these "models". Moreover, the very nature of the markets are too complex to model, especially using such data sources. The result would be some naive description of reality, like pre-scientific religious cosmology, a wrong but sophisticated enough 'model' based on 'current consensus'.)

consz 11y ago
Have you worked in a variety of quant funds? What makes you think markets are too complex to model? What evidence do you have that the models used at successful shops are not sufficiently rigorous?
- dschiptsov 11y ago
  Because all one needs is to bullshit one's boss or sponsor. I gave an example of a religion for a reason. And bullshitting is much more efficient strategy than actual modeling and rigorous research. Group thinking is much easier and cheaper than proper science, especially when even the best economists are full of doubts. I took Yale's financial markets courses, so I know what ideas they might have. This is the Nobel laureate's course.
  - consz 11y ago
    The bosses in the typical quant firm are also quants themselves, and have no trouble following the rigor used to justify the validity of a trading strategy. Sure, at a certain point in the chain, you're talking with someone (eg. COO) who isn't allowed to see the details of the modeling procedure, but this is the point of scaling up and having risk/pnl limits -- no HFT firm, for example, is at risk of blowing out from lack of statistical rigor. I doubt taking Yale's financial markets courses is sufficient to understand or be exposed to what is currently being used in quantitative finance. I took Stanford's financial markets and statistics classes, and those are far behind and unaware of what's currently being used in the industry (I've worked in two highly successful HFT groups since Stanford).