We propose an innovative methodology for decomposing the value added generated by a money manager within a given assessment interval into the contributions of the manager's investment decisions made in the various periods, in order to identify the most (and the least) impactful period decisions....

We build regression trees to determine which firm characteristics are most likely to drive future returns. Out of 30 attributes, those related to momentum appear to have, by far, the most marked impact. This prominence is verified at the sector level as well. The second order effects are...

This paper introduces a model-free decomposition of S&P 500 forward market index returns in terms of realized and implied dispersion, downside, and tail risk using option portfolios. The decomposition lends itself by construction to learn about the different sources of risk in the market return,...

For years, research has been conducted to correctly model and predict the risk and return structures of Private Equity (PE) funds. Although past research has revealed valuable insight into the features of those funds, most risk and return model struggle with the dispersion of PE funds' returns,...

A great deal of research has examined comovements between commercial real estate returns and macroeconomic variables in the US economy. These relationships have attracted less research interest for the UK real estate market, despite this being the largest European Market. This cross-sectional...

The aggregate portfolio of Chinese actively managed stock mutual funds exhibits a large and significantly positive alpha. Results from bootstrap simulations indicate that most Chinese active stock mutual fund managers have skill. A substantial amount of their outperformance can be attributed to...

This paper introduces new money-weighted metrics for investment performance analysis, based on arithmetic means of holding period rates weighted by the investment's market values. This approach generates rates of return which measure a fund's or portfolio's performance and a fund manager's...

Return chasing is often cited as one of the primary behavioral foibles of investors, resulting in sub-par returns. Surprisingly, the literature does not provide a generally accepted and testable description of return chasing. This paper proposes a simple definition. It then describes how return...

We give explicit algorithms and source code for extracting factors underlying Treasury yields using (unsupervised) machine learning (ML) techniques, such as nonnegative matrix factorization (NMF) and (statistically deterministic) clustering. NMF is a popular ML algorithm (used in computer...

You're probably familiar, at least in passing, with the 'convexity' of long-term bonds - i.e. that yields dropping 1% produce a bigger price move than yields rising 1%. A significant amount of brainpower has gone into understanding all the ramifications of this convexity in the fixed income...