Category Archives: Portfolio Probe

Release of Portfolio Probe version 1.05 plus blog problems

June has been a good month for releases of Portfolio Probe and a bad month for disseminating the blog. Version 1.05 This is a minor release, primarily to fix some bugs, but a little sugar slipped in as well. bug: when forced trades created a portfolio that satisfied all of the constraints, then all “random” … Continue reading

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Newsletter sign-up problems

There have been some issues with the sign-up process for the Portfolio Probe newsletter and the Portfolio Probe user’s list.  The issues may or may not be in the past tense. The way the process is supposed to work is: You sign up for one or both lists You get a message from us saying … Continue reading

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Rebalancing the low vol cohorts

How much turnover is required to get portfolios back to their constraints? Previously “Low (and high) volatility strategy effects” created 6 sets of random portfolios as of 2007 and showed their performance up to about a month ago.  This post explores how much turnover it takes to get the portfolios to obey their constraints at … Continue reading

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Linear constraints with risk fractions

A different sort of generalization of variance partitions. Previously The post “Generalizing risk fractions” described additional (to version 1.04 of Portfolio Probe) ways of dividing the variance among the assets.  This post describes the other major addition in the new version. Linear constraints Linear constraints on sectors, industries and countries are quite common.  These constrain … Continue reading

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Generalizing risk fractions

More ways of constraining the variance attributable to individual assets. Introduction This post describes some additions to the 1.04 version of Portfolio Probe.  A beta of that version was released last week. We’ve also added Linux 32-bit and 64-bit as platforms on which Portfolio Probe is for sale.  Unfortunately demo and academic versions are still … Continue reading

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A different take on random portfolios and optimization

In which random portfolios are used as the vehicle for portfolio optimization. The paper The author is William Shaw.  The paper goes by the succinct title of “Portfolio Optimization for VAR, CVaR, Omega and Utility with General Return Distributions: A Monte Carlo Approach for Long-Only and Bounded Short Portfolios with Optional Robustness and a Simplified … Continue reading

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