Portfolio diversification based on stochastic dominance under incomplete probability information

Identifying efficient portfolio diversification strategies subject to stochastic dominance (SD) criteria usually assumes that the state-space of future asset returns can be captured by a fixed sample of equally probable historical returns. This paper relaxes this assumption by developing SD criteria under incomplete information on state probabilities. Specifically, we identify portfolios that dominate a given benchmark for any state probabilities in a given set. The proposed approach is applied to analyze if industrial diversification can be utilized to outperform the market portfolio. The results from this application demonstrate that the use of set-valued state probabilities can help to improve out-of-sample performance of SD-based portfolio optimization

Diversification Preferences in the Theory of Choice

Diversification represents the idea of choosing variety over uniformity. Within the theory of choice, desirability of diversification is axiomatized as preference for a convex combination of choices that are equivalently ranked. This corresponds to the notion of risk aversion when one assumes the von-Neumann-Morgenstern expected utility model, but the equivalence fails to hold in other models. This paper studies axiomatizations of the concept of diversification and their relationship to the related notions of risk aversion and convex preferences within different choice theoretic models. Implications of these notions on portfolio choice are discussed. We cover model-independent diversification preferences, preferences within models of choice under risk, including expected utility theory and the more general rank-dependent expected utility theory, as well as models of choice under uncertainty axiomatized via Choquet expected utility theory. Remarks on interpretations of diversification preferences within models of behavioral choice are given in the conclusion

Information asymmetries and securitization design

The strong growth in collateralized debt obligation transactions raises the question how these transactions are designed. The originator designs the transaction so as to maximize her benefit subject to requirements imposed by investors and rating agencies. An important issue in these transactions is the information asymmetry between the originator and the investors. First Loss Positions are the most important instrument to mitigate conflicts due to information asymmetry. We analyse the optimal size of the First Loss Position in a model and the actual size in a set of European collateralized debt obligation transactions. We find that the asset pool quality, measured by the weighted average default probability and the diversity score of the pool, plays a predominant role for the transaction design. Characteristics of the originator play a small role. A lower asset pool quality induces the originator to take a higher First Loss Position and, in a synthetic transaction, a smaller Third Loss Position. The First Loss Position bears on average 86 % of the expected default losses, independent of the asset pool quality. This loss share and the asset pool quality strongly affect the rating and the credit spread of the lowest rated tranche.Securitization, collateralized debt obligations, asset pool quality, First Loss Position, synthetic transactions, tranching

Portfolio optimization models for project valuation

This dissertation presents (i) a framework for selecting and managing a portfolio of risky multi-period projects, called Contingent Portfolio Programming (CPP), and (ii) an inverse optimization procedure that uses this framework to compute the value of a single project. The dissertation specifically examines a setting where the investor can invest both in private projects and securities in financial markets, but where the replication of project cash flows with securities is not necessarily possible. This setting is called a mixed asset portfolio selection (MAPS) setting. The valuation procedure is based on the concepts of breakeven selling and buying prices, which are obtained by first solving an optimization problem and then an inverse optimization problem. In the theoretical part of the dissertation, it is shown that breakeven prices are consistent valuation measures, exhibiting sequential consistency, consistency with contingent claims analysis (CCA), and sequential additivity. Due to consistency with CCA, the present approach can be regarded as a generalization of CCA to incomplete markets. It is also shown that, in some special cases, it is possible to derive simple calculation formulas for breakeven prices which do not require the use of inverse optimization. Further, it is proven that breakeven prices for a mean-variance investor converge towards the prices given by the Capital Asset Pricing Model (CAPM) as the investor's risk tolerance goes to infinity. The numerical experiments show that CPP is computationally feasible for relatively large portfolios both in terms of projects and states, and illustrate the basic phenomena that can be observed in a MAPS setting.reviewe

HETEROGENEOUS CONSTRAINTS, INCENTIVES AND INCOME DIVERSIFICATION STRATEGIES IN RURAL AFRICA

A burgeoning recent literature emphasizes "livelihood" diversification among smallholder populations (Chambers and Conway 1992, Davies 1993, Ellis 1998, Bryceson 1999, Ellis 2000, Little et al. 2001). While definitions vary within this literature, the concept of livelihoods revolves around the opportunity set afforded an individual or household by their asset endowment and their chosen allocation of those assets across various activities to generate a stream of benefits, most commonly measured as income. This holistic perspective has the potential to enhance our understanding of the strategies that farm households pursue to ensure food and income security given the natural and economic environment in which they operate. Diversification patterns reflect individuals' voluntary exchange of assets and their allocation of assets across various activities so as to achieve an optimal balance between expected returns and risk exposure conditional on the constraints they face (e.g., due to missing or incomplete markets for credit, labor, or land). Because it offers a glimpse as to what people presently consider their most attractive options, given the incentives and constraints they face, the study of diversification behavior offers important insights as to what policy or project interventions might effectively improve either the poor's asset holdings or their access to higher return or lower risk uses of the assets they already possess. Since diversification is not an end unto itself, it is essential to connect observed livelihood strategies back to resulting income distributions and poverty. Not all diversification into off-farm or non-farm income earning activities offers the same benefits and not all households have equal access to the more lucrative diversification options. Yet the livelihoods literature offers little documentation or explanation of important differences between observed diversification strategies. This paper addresses that gap by offering a comparative analysis using data from three different countries, Cote d'Ivoire, Kenya and Rwanda. Like Dercon and Krishnan (1996) and Omamo (1999), we emphasize that interhousehold heterogeneity in constraints and incentives must factor prominently in any sensible explanation of observed diversification behaviors. Indeed, section 4 demonstrates that at a very fundamental level - the choice of basic livelihood strategy - households would prefer locally available livelihood strategies other than those they choose, were they not constrained from doing so. A simple appeal to the principle of revealed preference thus suggests that heterogeneous constraints and incentives play a fundamental role in determining livelihood diversification patterns manifest in income diversification data. The plan for the remainder of this paper is as follows. The next section presents the basic conceptual foundation from which we operate. Section 3 then introduces the data sets and definitions employed in the analysis. Section 4 presents findings relating to the observed variation in income sources across the income distribution, to distinct livelihood strategies pursued by rural African households, to the determinants of strategy choice, and to the effects of alternative livelihood strategies on income dynamics. These findings point especially to significant rural markets failures - especially with respect to finance and land - that force poorer subpopulations to select strategies offering demonstrably lower returns while wealthier subpopulations are able to enjoy higher return strategies to which entry is at least partly impeded by fixed costs and lower marginal costs of participation. Section 5 concludes.Labor and Human Capital, O & Q12,

The History of the Quantitative Methods in Finance Conference Series. 1992-2007

This report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.

Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections

This paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas