Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...

This survey reviews the growing literature on pairs trading frameworks, i.e., relative-value arbitrage strategies involving two or more securities. The available research is categorized into five groups: The distance approach uses nonparametric distance metrics to identify pairs trading...

The strategy of buying and holding “net nets” has been advocated by deep value investors for decades, but systematic studies of the returns to such a strategy are few. We detail the returns generated from a net nets strategy implemented from 1984 - 2008, and then attempt to explain the...

This paper proves a class of static fund separation theorems, valid for investors with a long horizon and constant relative risk aversion, and with stochastic investment opportunities. An optimal portfolio decomposes as a constant mix of a few preference-free funds, which are common to all...

In this study, the well-known pairs trading strategy, one of typical market neutral strategies, is modified to be able to utilize high frequency equity data, and it is applied to the constituent shares of the KOSPI (Korea Composite Stock Price Index) 100 index. This study is distinguished from...

We propose a new approach to constructing inflation tracking portfolios. The key to this approach is the insight that asset returns track expected inflation far better than they track current realized inflation. Thus, we can construct portfolios that track next month's inflation much more...

We propose an alternative investment strategy for pairs trading using Archimedean copulas in order to cover a wider range of tail dependence patterns and apply it to the S&P 500 stocks from 1990 to 2015. Empirical results show that our mixed copula approach generates higher average and risk...