Author: tom_anichini
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How to model new ETFs? Use Matrix Returns
I recently delved into the new Russell stability indices and started inspecting the related Russell Factor ETFs. The ETFs began to trade toward the end of May. If you’ve spent any time researching the so-called “low volatility anomaly” you’re well aware that empirically we have little evidence that investment returns are related to risk.. This…
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Reverse Optimization: A Glimpse into an Investor’s Expected Returns?
Investment professionals who know what “reverse optimization” means typically know of two methods. The more widely used method is known as the Black-Litterman method. That approach is well covered elsewhere, especially on StyleAdvisor. The less widely-used method, described by Bill Sharpe in 1974 in “Imputing Expected Security Returns from Portfolio Composition,” (linked at bottom of…
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Introducing the “
MatrixReconstructed Return” – a Handy Shortcut for Estimating BetaFor anyone building and managing equity portfolios for clients, I have two pieces of advice. 1. Use a fundamental risk model. One of the first advantages of fundamental risk models is they afford easier portfolio optimization. When you have thousands of stocks to choose from, in order to model them completely using returns you would…
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Why it’s so easy to loathe high frequency traders: you can see them profit
This morning Tyler Cowen wrote again about High Frequency Trading. His post has to do with the idea that our economic intuition breaks down at small scales. I don’t think small scale is the matter; I think transparency is. Middlemen have been loathed for a long time, even though they provide a useful function. But…
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Risk parity: Why it belongs in your toolkit
Risk Parity portfolios are also known as Equal Risk or Balanced Risk portfolios, because their portfolio risk is balanced equally among their components. If you build investment products, manage client assets, or advise clients on asset allocation, chances are there is a place for Risk Parity among your portfolios. Risk Parity fits best wherever you…
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Predict beta more accurately by using imaginary returns
Updated October 2014, replacing the word “imaginary” with “reconstructed.” – TMA If you’re managing portfolios without using a risk model, you’re probably relying on regression statistics of asset returns to estimate risk characteristics such as Beta. For reporting purposes or for the purpose of measuring sensitivity to a broad index whose constituents don’t change drastically…
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What does portfolio diversification have to do with fake fireplaces?
Before getting to fake fireplaces, consider the question: Does portfolio diversification work? That is not a rhetorical question. I’ve heard plenty of people declare that portfolio diversification doesn’t work. Not just any people, mind you, but I’ve heard plenty of investment professionals decry portfolio diversification as useless. “It doesn’t work,” they say. Their evidence? The…
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Contribution to Risk: the key to unlocking portfolio solutions
Whether you’re trying to maximize Sharpe ratio or information ratio, building a risk parity portfolio, or inferring an investor’s expected returns her given portfolio weights, the key component to each goal is contribution to portfolio risk. The Modern Portfolio Theory formula for variance of a portfolio with n assets is: i=1,n j=1,n wi wj ijij…