A new book by a University of Luxembourg Professor provides new insights, ideas and empirical evidence that will improve tools and methods at our disposal for fund performance analysis.
Associate-Professor Virginie Terraza, from the Centre for Research in Economics and Management, in the Faculty of Law, Economics and Finance together with Associate-Professor Hery Razafitombo from the University of Lorraine, have written «Understanding Investment Funds : Insights from performance and risk analysis» which is published by Palgrave Macmillan.
Since the beginning of the decade, the frequency and impact of financial crises have gained magnitude and traditional risk protection practices are no longer sufficient for modern risk management practice. With the multiplication of both investment funds and available information across categories such as stocks, bonds, money market products and alternative investments, there is a necessity to classify funds in order to inform investors about each fund's specific risk profile as precisely as possible.
Terraza said : « In the past crises used to be limited to singular markets or specific asset classes. In today's crises, many different asset classes are affected simultaneously and globally. Given this new context, our traditional methods must be adapted with the overall objective to strengthen the scientific knowledge of investment funds. «
The book discusses the theoretical basis and a number of implementation issues related to the evaluation of the financial performance of funds systems. These include the prediction of fund's failure and the discussion of appropriate performance measures where risks control constitutes an essential tool to face up to future uncertainties.
The authors propose a new asset allocation scheme that complements the traditional portfolio optimization approach. To do this, the portfolio allocation process is revised first to test conditional market stability and bivariate contagion risk between single assets and then to perform portfolio optimization on the subset of assets that passed the first layers of filters.
This approach is applied on a synthetic Fund of Hedge Funds and the efficiency of this multivariate extreme risk management complement is tested in practice. Simulation results indicate that the exposure to extreme risk can be significantly reduced for a portfolio monitored at daily frequency and that crisis-resilient portfolios can be constructed in a robust manner for all portfolio management schemes.
The book also proposes two portfolio optimization models with a multi-fractional approach and a dynamic approach using risk aversion signals; an alternative benchmark for mutual funds, a fuzzy approach to estimate performance measures and a symbolic data approach to compare fund ratings systems.
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