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The article discusses the VIX futures indexes and key statistics and the dynamic capital asset pricing model (CAPM). Topics discussed include application of portfolio construction method to several indexes such as VIX short-term and midterm futures indexes; induction of greater transaction costs that leads to reduced performance; presentation of graphs and charts related to the same.

This article presents an automated forecasting system that provides a macroeconomic forecasting approach that some hedge funds may find useful. The authors describe the structure of an econometric forecasting system designed to produce multiequation econometric forecasting models of national macroeconomies. They also describe the func­tioning of an automatic model-building system that builds the forecasting equation for each series submitted and pro­duces forecasts of the series without hum an intervention. The automatic model-building system employs informa­tion criteria and cross-validation in the equation building process, and it uses Bayesian model averaging to combine forecasts of individual series. The system outperforms stan­dard benchmarks for a variety of macroeconomic datasets. To demonstrate its use, the automatic system is used to build a fixed-income macro trading system. [ABSTRACT FROM AUTHOR]

In this article, the authors replicate major Hedge Fund Research, Inc., style indexes using alternative methods. These methods include stepwise regression, ridge regression, the lasso method, the elastic net, dynamic linear regression, principal component regression, and partial least squares regression. They find generally that, across the major hedge fund style indexes, the best replication results are obtained with methods that employ shrinkage of parameters. [ABSTRACT FROM AUTHOR]

Many hedge funds attempt to achieve high returns b employing leverage. However, it is difficult to track the degree of leverage used by hedge funds over time becausse detailed timely information about their positions in asset markets is generally unavailable. This article discusses how to combine shrinkage variable selection methods with dynamic regression to compute and track hedge fund leverage on a time-varying basis. The authors argue that their methodology measures leverage as well as hedge fund sensitivity markets arising from other sources. The authors' approach employs the lasso variable selection method to select the independent variables in equations of hedge fund excess returns. With the independent variables selected by the lasso method, a state space model generates the parameter estimates dynamically. The hedge fund market sensitivity indicator is the average of the absolute values of the parameters in the excess return equations. The indicator peaks a the time of the Long Term Capital Management meltdown in 1998 and again at a critical time in the 2008 financial crisis. In the absence of direct information from hedge fund balance sheets, this approach could serve as an important tool for monitoring market sensitivity and financial distress in the hedge fund industry. [ABSTRACT FROM AUTHOR]