Nonmyopic optimal portfolios in viable markets

Cvitanić, Jakša; Malamud, Semyon

doi:10.1007/s11579-013-0109-6

Cited by 4 publications

(4 citation statements)

References 62 publications

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“…This remark indicates that the corporation believes there is a less than 1% possibility that it will lose $2 million the next day. A high VaR for an investing firm indicates that the firm's investments are overly hazardous, and there should be a structural adjustment [15].…”

Section: Research Approaches Of Varmentioning

confidence: 99%

Asymmetric Laplace Distribution Models for Financial Data: VaR and CVaR

2022

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In the field of financial risk measurement, Asymmetric Laplace (AL) laws are used. The assumption of normalcy is used in traditional approaches for calculating financial risk. Asymmetric Laplace distribution, on the other hand, reveals the properties of empirical financial data sets much better than the normal model by leptokurtosis and skewness. According to recent financial data research, the regularity assumption is frequently broken. As a result, Asymmetric Laplace laws offer a simple, creative, and useful option to normal distributions when it comes to modeling financial data. We here engage AL distribution to explore specific formulas for the two commonly used risk measures, Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). The currency exchange rates data are used to and worked out to illustrate the proposed methodologies.

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Section: Research Approaches Of Varmentioning

confidence: 99%

Asymmetric Laplace Distribution Models for Financial Data: VaR and CVaR

2022

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“…The measurement of investors preferences are described in the form of utility functions. For the financial-related terms, see [3,8]. Next, the commodity spot price and convenience yield are assumed to follow the Schwartz two-factor model.…”

Section: Chapter II Preliminarymentioning

confidence: 99%

“…According to a description in [3,11], the rational investors are typically being able to compare between different situations and to decide which one is better. This kind of preferences of investors is the basic idea for a measurement tool called utility function.…”

Section: Investor's Preferences and Utility Functionmentioning

confidence: 99%

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Numerical Simulation for an Optimal Fixed Ratio of Investment in Hedged Portfolio of Commodities and Their Futures Under Schwartz Pricing Model

Tangcharoen

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In this thesis, we are interested in a portfolio maximization problem and a numerical method solving for the optimal investment solution associated with our problem. Accordingly, we first present a specific kind of portfolio model which consisted of only two assets, one is a commodity asset, and another one is a futures contract written on this commodity. Through out this study, we assume that the behavior of commodity price in a perfect market is described by the Schwartz two-factor pricing model. In additions, by no-arbitrage assumption, the close-form formula of fair price can be used to derive an instantaneous futures price. In the first part of this study we formulate the portfolio model by considering the generating of portfolio incomes. We give an emphasize on a tradeoff between a proportion of commodities and commodity futures in the portfolio. In order to solve this problem, we employ Monte Carlo technique to simulate the process generating the return on our portfolio model and to approximate the fixed ratio solution of an investment that maximizes the portfolio final wealth. Some numerical examples are given to illustrate the procedure and additional applications are suggested.

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Portfolio Theory for Squared Returns Correlated Across Time

Eberlein

Madan

2015

SSRN Journal

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Nonmyopic optimal portfolios in viable markets

Cited by 4 publications

References 62 publications

Asymmetric Laplace Distribution Models for Financial Data: VaR and CVaR

Asymmetric Laplace Distribution Models for Financial Data: VaR and CVaR

Numerical Simulation for an Optimal Fixed Ratio of Investment in Hedged Portfolio of Commodities and Their Futures Under Schwartz Pricing Model

Portfolio Theory for Squared Returns Correlated Across Time

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