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Most portfolios offer positive returns, and minimum variance portfolios are not exceptions to this rule. But by offering "minimum variance," they also offer the lowest possibility of a negative deviation large enough to pull the actual return (expected return minus deviation), into negative territory.


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My experience in statistical arbitrage desks (primarily equities) and CTAs is somehow different than @Simon's. From my perspective, I have used and seen plenty of portfolio optimization tools. However, I have most often operated in a layered architecture. A layered architecture is an architecture where independent automated traders are stacked, each and ...


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Most money is not quantitatively managed, as you point out. If those managers don't use any quantitative methods in their process then it doesn't really matter if MVO is a 50+ or 500+ year old concept. Also, since there are many subtleties to proper application of these techniques to a particular strategy, it is unlikely that a manager would use them if she ...


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Portfolio optimization techniques are used quite a bit by hedge funds. I think you misunderstand how portfolio optimization operates in the context of an active trading strategy. Your question suggests a view of portfolio optimization as a tool to adjust portfolio weights arrived at by a separate, active strategy. Under that approach, you are correct, the ...


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Well, given that either LM or BHHH is supposed to stop when the Kuhn-Tucker condition is satisfied, I infer it has to be stepwise. I would say otherwise if, say, they were potentially using something like SALO (simulated annealing with local optimization), where one algorithm could profitably run in full as a sub-step of the other.


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An AR(1), once the time series and lags are aligned and everything is set-up, is in fact a standard regression problem. Let's look, for simplicity sake, at a "standard" regression problem. I will try to draw some conclusions from there. Let's say we want to run a linear regression where we want to approximate $y$ with $$h_(x) = \sum_0^n \theta_i x_i = ...


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I work on Quant hedge fund. My answer is: YES and NO:) Advanced optimization techniques are popular in academia but less useful on the street. Specifically, the answer really depends on which type of strategies you are trading. For equities long-short portfolios, some level of optimization is needed, partly because they need to trade on large sizes on ...


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I made a micro-test and the trinomial tree seems to be fast enough. (From my original comment) As described in Brigo & Mercurio illustrate, a numerical procedure to evaluate the Black and Karasinki model has been presented in Hull and White, "Branching Out", Risk magazine, 1994. Hull and White make use of a trinomial tree, which may indeed more ...



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