![]() The return from this policy turns out to have other stochastic dominance properties as well. For example, the mean return on investment is maximized by the same strategy that maximizes logarithmic utility, which is also known to maximize the exponential rate at which wealth grows. This limit theorem allows for comparisons of different strategies. Among other results, we prove that the limiting distribution of this measure of return is a gamma distribution. In this paper we study the rate of return on investment, defined here as the net gain in wealth divided by the cumulative investment, for such investment strategies in continuous time. The paper suggests a systematization of this new approach, which is subsequently used to conduct a state-of-the-art literature survey and an evaluation of evolutionary finance research.ĭynamic asset allocation strategies that are continuously rebalanced so as to always keep a fixed constant proportion of wealth invested in the various assets at each point in time play a fundamental role in the theory of optimal portfolio strategies. Evolutionary finance suggests a model of portfolio selection and asset price dynamics that is explicitly based on the ideas of investors’ heterogeneity, dynamics and changes, learning and a natural selection of strategies. However, the traditional, new institutional and the behavioral finance models all share one important feature: They are all based on the notion of a representative agent even though this mythological figure is dressed differently. In contrast, behavioral finance completely challenges the rationality assumption and aims to improve the understanding of financial markets by assuming that, due to psychological factors, investors’ decisions will contradict the expected utility theory. By comparison, the new institutional economics approach attempts to provide a more realistic picture of economic processes, even in financial markets, by postulating several market imperfections, including the agents’ limited rationality. The traditional financial paradigm seeks to understand financial markets by using models in which markets are perfect, which includes agents who are “rational” and update their beliefs correctly based on new information. Using the University of Massachusetts hedge fund database, we show some funds with superior records and from this evaluation learn more about the properties of the DSSR and the modified downside symmetric information ratio (DISR). This measure only counts losses and is useful in evaluating superior investors such as the Renaissance Medallion hedge fund which has a high rating by the modified downside symmetric Sharpe ratio as opposed to a modest rating with the ordinary Sharpe ratio. Earlier, Ziemba (2005), following an idea in Ziemba and Schwartz (1991), proposed a modification of the ordinary normal distribution based Sharpe ratio to evaluate right skewed great investor portfolios. These include some Kelly criterion investors such as Buett, Keynes and Soros who have concentrated portfolios with few asset positions. Some investors prefer high long run growth and accept bumps, rather than smooth wealth paths and lower growth. Their graphs of wealth over time leads us to a search for smooth monotone paths and how we might fairly evaluate superior as opposed to average investors. We discuss the records of some great investors and hedge fund managers. ![]() Therefore, strategic asset allocation approaches that rely on such an economic foundation are evolutionarily advantageous for multi-asset investors. This paper shows that yield-based strategies generate asset allocations that outperform competing alternatives. While traditional mean/variance optimization is static and concerned with finding the optimal asset allocation, evolutionary portfolio theory is dynamic and its focus is on finding the optimal investment strategy. Requiring little more than dividend and interest rate data, it facilitates an interesting glimpse into the inner workings of financial markets and provides a valuable guide to this class of models. ![]() This paper develops a multi-asset evolutionary finance model. Evolutionary finance accounts for this and endogenizes asset prices. However, returns are not generated in a vacuum but are the result of the market's price discovery mechanism which is driven by investors' investment strategies. Standard strategic asset allocation procedures usually neglect market interaction.
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