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This is just the observed variance. Which means that you assume that this will be the variance in the future. Don’t make decisions for evolving systems based o
by whatever1 11mo ago
This is just the observed variance. Which means that you assume that this will be the variance in the future.
Don’t make decisions for evolving systems based on statistics.
Insider info on the other hand works much better.
- JohnCClarke 11mo agoUpvoting b/c this comment is true, obviously I disapprove of insider trading.
- energy123 11mo agoThis is why Markowitz isn't used much in the industry, at least not in a plug-and-play fashion. Empirical volatility, and the variance -covariance matrix more generally speaking, is a useful descriptive statistic, but the matrix has high sampling variance, which means Markowitz is garbage in garbage out. Unlike in other fields, you can't just make/collect more data to reduce the sampling variance of the inputs. So you want to regularize the inputs or have some kind of hybrid approach that has a discretionary overlay.
- pinkmuffinere 11mo agoI have some familiarity with the Markowitz model, but certainly not as much as you do about the practical use — could you share notes/articles/talks on the practical use? I’m super interested to learn more.
- energy123 11mo agoBlack-Litterman model is an example of how to address the shortcoming of unreliable empirical inputs. You'll also see more ad hoc approaches, such as simulating hypothetical scenarios to determine worst case scenarios. It's not math heavy. Math heavy is a smell. Expect to see fairly simple monte carlo simulations, but with significant thought put into the assumptions.
- pinkmuffinere 11mo agoOooooh this is cool, thanks!
- mhh__ 11mo agoRead "Advanced portfolio management" by Paleologo (ironically it's actually the introductory one of his two books), or "Active portfolio management" for a more thorough, older, longer book on the topic. Markowitz isn't really used at all, but Markowitz-like reasoning is used extremely heavily in finance, by which I basically mean factor modelling of various kinds - effectively the result of taking mean-variance as a concept and using some fairly aggressive dimensionality reduction to cope with the problems of financial data, and the fact that one has proprietary views about things ("alpha" and so on)
- pinkmuffinere 11mo agoThanks, just bought the book! Some nice reading for the holidays!
- kgwgk 11mo ago> This is why Markowitz isn't used much in the industry This may be one reason but the return part is much more problematic than the risk part.
- energy123 11mo agoVery true, although the off-diagonal terms in the variance-covariance matrix are also hard to estimate, which is a problem, especially when simulating worst case scenarios, which is often when correlations tend to break down.
- ijidak 11mo agoDoesn't it make more sense to measure and minimize the variance of the underlying cash flows of the companies one is investing in, rather than the prices? Price variance is a noisy statistic not based on any underlying data about a company, especially if we believe that stock prices are truly random.
- mhh__ 11mo agoVolatility is fairly predictable. Or at least much more predictable than returns
- CGMthrowaway 11mo agoThat's the first thing I thought of. I read the opening of this article and thought "oh this could be applied to a load balancing problem" but it immediately becomes obvious that you can't assume the variance is going to be uniform over time