Academic literature on the topic 'Stochastic dominance, VaR, CVaR'

AbstractBased on the notions of value-at-risk and conditional value-at-risk, we consider two functionals, abbreviated VaR and CVaR, which represent the economic risk capital required to operate a risky business over some time period when only a small probability of loss is tolerated. These functionals are consistent with the risk preferences of profit-seeking (and risk averse) decision makers and preserve the stochastic dominance order (and the stop-loss order). This result is used to bound the VaR and CVaR functionals by determining their maximal values over the set of all loss and profit functions with fixed first few moments. The evaluation of CVaR for the aggregate loss of portfolios is also discussed. The results of VaR and CVaR calculations are illustrated and compared at some typical situations of general interest.

This paper proposes an improved procedure for stochastic volatility model estimation with an application to Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) estimation. This improved procedure is composed of the following instrumental components: Fourier transform method for volatility estimation, and importance sampling for extreme event probability estimation. The empirical analysis is based on several foreign exchange series and the S&P 500 index data. In comparison with empirical results by RiskMetrics, historical simulation, and the GARCH(1,1) model, our improved procedure outperforms on average.

The goal of this paper is to continue our investigation of the heuristic approaches of solving thestochastic quadratic assignment problem (StoQAP) and provide additional insight into the behavior of di erentformulations that arise through the stochastic nature of the problem. The deterministic Quadratic AssignmentProblem (QAP) belongs to a class of well-known hard combinatorial optimization problems. Working with severalreal-world applications we have found that their QAP parameters can (and should) be considered as stochasticones. Thus, we review the StoQAP as a stochastic program and discuss its suitable deterministic reformulations.The two formulations we are going to investigate include two of the most used risk measures - Value at Risk(VaR) and Conditional Value at Risk (CVaR). The focus is on VaR and CVaR formulations and results of testcomputations for various instances of StoQAP solved by a genetic algorithm, which are presented and discussed.

The purpose of this article is to develop a new stochastic multi objective optimization model to mitigate disruption risks while simultaneously addressing operational risks as well. Indeed, this model considers five objective functions for selecting a set of suppliers considering disruption risk and stochastic demand, quality, and delay time. The authors use two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Two examples are given to illustrate our model and two solution methods are compared and tested.

This paper used different risk management indicators applied to the investment optimization performed by consumers in Distributed Generation (DG). The objective function is the total cost incurred by the consumer including the energy and capacity payments, the savings, and the revenues from the installation of DG, alongside the operation and maintenance (O&M) and investment costs. Probability density function (PDF) was used to model the price volatility in the long-term. The mathematical model uses a two-stage stochastic approach: investment and operational stages. The investment decisions are included in the first stage and which do not change with the scenarios of the uncertainty. The operation variables are in the second stage and, therefore, take different values with every realization. Three risk indicators were used to assess the uncertainty risk: Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Expected Value (EV). The results showed the importance of migration from deterministic models to stochastic ones and, most importantly, the understanding of the ramifications of every risk indicator.

Cette thèse a pour objectif d’évaluer et de comparer la performance des stratégies d’assurance de portefeuille pour tenter de définir quelles stratégies doivent être privilégiées par les investisseurs. Nous comparons de nombreuses stratégies d’assurance (OBPI, CPPI, put synthétique et Stop-loss) entre elles mais également avec quelques autres stratégies de référence. Nous utilisons différents critères de comparaison qui comprennent: 1. Les distributions de pay-off, le niveau de protection, la dominance stochastique et le coût d’assurance dans différentes conditions de marché identifiées par des modèles à changements de régime markovien. 2. Les mesures de la performance ajustée au risque qui peuvent refléter les préférences des investisseurs vis-à-vis du risque et de la rentabilité. 3. Les préférences des investisseurs en intégrant la théorie cumulative des perspectives (TCP). Nos résultats semblent mettre en évidence une dominance des stratégies CPPI dans la majorité des cas et pour la majorité des critères de comparaison
This thesis is set out with the objective of evaluating and comparing the performance of portfolio insurance strategies. We try to figure out when and why one portfolio insurance strategy should be preferred by investors in practice. To meet this objective, main portfolio insurance strategies (OBPI, CPPI, Synthetic put and Stop-loss) are compared relatively to each other and to some benchmark strategies. Portfolio insurance strategies are applied within different implementation scenarios and compared according to various criteria that include:1. The payoff functions, stochastic dominance, the level of protection and the cost of insurance under bull and bear market conditions. 2. Various risk adjusted performance measures that reflect different investors’ preferences toward risk and return. 3. The preferences of investors who act according to cumulative prospect theory (CPT). Our results reveal a dominant role of CPPI strategy at the majority of cases and according to the majority of comparison criteria

Asset allocation is the most influential factor driving investment performance. While researchers have made substantial progress in the field of asset allocation since the introduction of mean-variance framework by Markowitz, there is little agreement about appropriate portfolio choice for multi-period long horizon investors. Nowhere this is more evident than trustees of retirement plans choosing different asset allocation strategies as default investment options for their members. This doctoral dissertation consists of four essays each of which explores either a novel or an unresolved issue in the area of asset allocation for individual retirement plan participants. The goal of the thesis is to provide greater insight into the subject of portfolio choice in retirement plans and advance scholarship in this field. The first study evaluates different constant mix or fixed weight asset allocation strategies and comments on their relative appeal as default investment options. In contrast to past research which deals mostly with theoretical or hypothetical models of asset allocation, we investigate asset allocation strategies that are actually used as default investment options by superannuation funds in Australia. We find that strategies with moderate allocation to stocks are consistently outperformed in terms of upside potential of exceeding the participant’s wealth accumulation target as well as downside risk of falling below that target by very aggressive strategies whose allocation to stocks approach 100%. The risk of extremely adverse wealth outcomes for plan participants does not appear to be very sensitive to asset allocation. Drawing on the evidence of the previous study, the second essay explores possible solutions to the well known problem of gender inequality in retirement investment outcomes. Using non-parametric stochastic simulation, we simulate iv and compare the retirement wealth outcomes for a hypothetical female and male worker under different assumptions about breaks in employment, superannuation contribution rates, and asset allocation strategies. We argue that modest changes in contribution and asset allocation strategy for the female plan participant are necessary to ensure an equitable wealth outcome in retirement. The findings provide strong evidence against gender-neutral default contribution and asset allocation policy currently institutionalized in Australia and other countries. In the third study we examine the efficacy of lifecycle asset allocation models which allocate aggressively to risky asset classes when the employee participants are young and gradually switch to more conservative asset classes as they approach retirement. We show that the conventional lifecycle strategies make a costly mistake by ignoring the change in portfolio size over time as a critical input in the asset allocation decision. Due to this portfolio size effect, which has hitherto remained unexplored in literature, the terminal value of accumulation in retirement account is critically dependent on the asset allocation strategy adopted by the participant in later years relative to early years. The final essay extends the findings of the previous chapter by proposing an alternative approach to lifecycle asset allocation which incorporates performance feedback. We demonstrate that strategies that dynamically alter allocation between growth and conservative asset classes at different points on the investment horizon based on cumulative portfolio performance relative to a set target generally result in superior wealth outcomes compared to those of conventional lifecycle strategies. The dynamic allocation strategy exhibits clear second-degree stochastic dominance over conventional strategies which switch assets in a deterministic manner as well as balanced diversified strategies.

Title: Almost stochastic dominance Author: Adam Štefánik Department: Probability and Mathematical Statistics Supervisor: RNDr. Ing. Miloš Kopa, PhD. Department of Probability and Mathematical Statistics, MFF UK Abstract: In the presented work we study the almost stochastic dominance and it's properties. Almost stochastic dominance is a relaxation of stochastic dominance. Almost stochastic dominance also deals with paradox situations occurring in case of stochastic dominance. This is a situation when stochastic dominance determines indifferent relation- ship between two portfolios, but in fact almost all investors can choose the better one. The original almost stochastic dominance presented by Leshno and Levy (2002) is compu- tationally expensive. Lizyayev and Ruszczy'nski (2012) suggested an alternative approach. This work introduces both approaches. The most interesting part of this work is a search for efficient portfolio with respect to the almost stochastic dominance by the simple linear programming. Lizyayev and Ruszczy'nski (2012) approach is applied to Kopa and Chovanec (2008) quantile approach for portfolio efficiency testing with respect to second order stochastic dominance. Keywords: almost stochastic dominance, efficiency, CVaR