In my last post I introduced Fundamental Return Moment Estimation. This short post applies the resulting estimates to build superior minimum variance portfolios. Both standard mean-variance-, as well as minimum variance portfolio optimization suffer from…
Continue readingStock returns are notoriously noisy and as a result, little can be learned from historical data. One of the major buidling blocks of academic finance, the Markowitz portfolio optimization with its mean-variance framework is rarely...
Continue readingIn this post, I want to introduce local effects in the cross-section of stock returns. Different from risk factors/ market anomalies, calculated using raw (global) measures, local measures that relate single stocks to their peers...
Continue readingWe overcome the low performance of standard portfolio optimization by modeling portfolio weights as functions of stock characteristics. Instead of predicting asset returns in a first step and subsequently modeling portfolio weights in a second step, we...
Continue readingRecently, I presented two new concepts related to risk factor cross-correlations. Namely, I showed you cross-correlation time-series factor momentum and I used deep neural networks to predict the returns of the value factor. Today I...
Continue readingIn the last post, I showed you cross-correlation time-series factor momentum. This strategy times factors by utilizing auto-cross-correlations in factor data (see Gupta & Kelly (2019) for a comprehensive study). This week, I will extract...
Continue readingLet me introduce you to time-series factor momentum, a strategy that attempts to harness the auto-correlation in factor returns (see Gupta & Kelly (2019) for a comprehensive study). Factor returns are frequently significantly auto-correlated, which...
Continue readingMarkowitz Portfolio Optimization is haunted by estimation errors in mean and covariance estimates. Instead of optimizing the Sharpe ratio out-of-sample, the optimizers tend to maximize the estimation Error (Michaud 1989). The estimation error maximization property...
Continue readingFactor momentum is persistent and observable in global equity markets (Gupta & Kelly (2019)). We take the perspective of a value investor that faces disappointing returns in domestic markets and attempts to chase positive value returns over the world. A strategy that buys winning international...
Continue readingThe factor zoo challenges financial research and raised doubts regarding post-publication robustness and data snooping. Feng et al. (2020) find that only a few new anomalies are enough to explain the cross section of stock returns, while the other factors are redundant. Another way...
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