We use simple linear models all the time in investment; they are actually quite good. Best of all they are robust. Like Owen I would love to discuss this.
For example, today I was trying to predict some property of companies. I came up with 5 signals I can easily calculate which all capture some information about the underlying property, turned them into 5 binary indicators, and just added them together for a composite signal. No attempt at producing weights, but for various reasons I’m pretty happy with this approach, and I’m confident my boss would endorse it too if we went into details.
It looks like there’s evidence for using them to predict continuous variables using continuous inputs, which might be your case. Also, if you’re using it to supplement your personal decision-making, then on the face of it, that’s more likely to work well than using it as a substitute.
We use simple linear models all the time in investment; they are actually quite good. Best of all they are robust. Like Owen I would love to discuss this.
For example, today I was trying to predict some property of companies. I came up with 5 signals I can easily calculate which all capture some information about the underlying property, turned them into 5 binary indicators, and just added them together for a composite signal. No attempt at producing weights, but for various reasons I’m pretty happy with this approach, and I’m confident my boss would endorse it too if we went into details.
It looks like there’s evidence for using them to predict continuous variables using continuous inputs, which might be your case. Also, if you’re using it to supplement your personal decision-making, then on the face of it, that’s more likely to work well than using it as a substitute.
http://effective-altruism.com/ea/fo/announcing_effective_altruism_ventures/2te