Pitfalls in linear models for style analysis

We discuss the statistical properties of return-based OLS style analysis introduced by Sharpe (1992). The aim of style analysis is to infer a fund managers investment decisions using only publicly available data on the fund performance and on the time evolution of market indexes. We show that the model proposed by Sharpe suffers of relevant drawbacks, most notably that it fails to yield correct results even in the simple case of a buy-and-hold strategy that only invests in the market indexes. Under this hypothesis we show that a model linear in index levels, as opposed to index returns, estimated via a Kalman filter avoids Sharpes model drawbacks. We further extend our analysis to strategies where the fund manager policy changes with time and the asset classes in which the fund manager invests are not known exactly. In this last case we show that a style analysis is possible only conditional to either an orthogonality hypothesis on the active investment strategy, or by the introduction of suitable instrumental variables.The authors are grateful to the editor and an anonymous referee for many comments which greatly helped in improving the paper. The authors are, obviously, fully responsible for any remaining error.     

A new approach to stock price modelling and the efficiency of the Italian stock exchange

In this paper, we propose a new model of asset prices which takes account of the investment strategies of three different kinds of agents: the market-makers, who operate rationally on the basis of the asset fundamentals, the smart buy-and-sell agents, who intervene when the prices reach particular levels and the non-smart buy-and-sell agents, who trade infrequently, mainly following psychological motivations. The different behavior of these groups of agents can determine temporary inefficiences on financial markets and we show that, by considering these inefficiences, it is possible to improve forecasting of asset prices.     

Fundamentals and asset price dynamics

The relation between fundamentals and asset returns is analyzed by means of Markov-switching regression models with time-varying transition probabilities. By referring to the Italian Stock Exchange over the 1973-2002 period, we find that (i) returns switch between a zero-expected return/low volatility state and a high expected return/high volatility state; (ii) states are persistent and hence state changes can be forecast to some extent; (iii) the probability of state changes can be explained in terms of changes in the fundamentals; (iv) fundamentals do not have a direct impact on the expected returns but they only affect the transition probability matrix. Overall, our results show that a non-linear relation between market price changes and market fundamentals can be caught within the framework of (Markov) switching regession models.A previous draft of the paper was presented at the XL Scientific Meeting of The Italian Statistical Society, Firenze, April 2000. We would like to thank Maurizio Vichi (the editor) and several anonymous referees for important suggestions. A special thank to Lorenzo Sevini for valuable research assistance. Partial financial support by Italian M.I.U.R. grants is gratefully acknowledged.     

The role of passing network indicators in modeling football outcomes: an application using Bayesian hierarchical models

AStA Advances in Statistical Analysis - Passes are undoubtedly the more frequent events in football and other team sports. Passing networks and their structural features can be useful to evaluate...