Suchergebnisse

AbstractMarket events of the past ten years have sparked an interest in tactical asset allocation. In the current study we develop and test a model that incorporates currently available information into the tactical asset allocation process. The model provides an estimate of the probabilities that the upcoming market period will be bullish or bearish. Logit analysis is employed to determine which of the various timely and readily available data significantly affect these probabilities. These estimated probabilities are used to suggest the optimal allocations of funds over time between the risk‐free asset and the market portfolio. Then, several timing strategies are compared with a buy‐and‐hold portfolio. An asset allocation strategy based on the probabilities assigned by the logit model appears to achieve greater terminal wealth with less variability of returns. Similar results are obtained for both an initial sample (1962–76 in our model) and a holdout sample (1977–88).

This book covers each step in the asset allocation process, addressing as many of the relevant questions as possible along the way. How can we formulate expectations about long-term returns? How relevant are valuations? What are the challenges to optimizing the portfolio? Can factor investing add value and, if so, how can it be implemented? Which are the key performance drivers for each asset class, and what determines how they are correlated? How can we apply insights about the business cycle to tactical asset allocation? The book is aimed at finance professionals and others looking for a coherent framework for decision-making in asset allocation, both at the strategic and tactical level. It stresses analysis rather than pre-conceived ideas about investments, and it draws on both empirical research and practical experience to give the reader as strong a background as possible.--