scholarly journals Value at Risk Incorporating Dynamic Portfolio Management

2000 ◽  
Author(s):  
Stephen Lawrence
Keyword(s):  
At Risk ◽  
Portfolio Management ◽  
Value At Risk ◽  
Dynamic Portfolio

scholarly journals Copula-based agricultural conditional value-at-risk modelling for geographical diversifications in wheat farming portfolio management

2018 ◽  
Vol 21 ◽  
pp. 76-89 ◽  
Author(s):  
Thong Nguyen-Huy ◽  
Ravinesh C. Deo ◽  
Shahbaz Mushtaq ◽  
Jarrod Kath ◽  
Shahjahan Khan
Keyword(s):  
At Risk ◽  
Portfolio Management ◽  
Value At Risk ◽  
Conditional Value At Risk ◽  
Risk Modelling

DRAWDOWN MEASURE IN PORTFOLIO OPTIMIZATION

2005 ◽  
Vol 08 (01) ◽  
pp. 13-58 ◽  
Author(s):  
ALEXEI CHEKHLOV ◽  
STANISLAV URYASEV ◽  
MICHAEL ZABARANKIN
Keyword(s):  
At Risk ◽  
Portfolio Management ◽  
Asset Allocation ◽  
Value At Risk ◽  
Risk Measures ◽  
Sample Path ◽  
Real Life ◽  
Optimization Techniques ◽  
Conditional Value At Risk ◽  
Excess Loss

A new one-parameter family of risk measures called Conditional Drawdown (CDD) has been proposed. These measures of risk are functionals of the portfolio drawdown (underwater) curve considered in active portfolio management. For some value of the tolerance parameter α, in the case of a single sample path, drawdown functional is defined as the mean of the worst (1 - α) * 100% drawdowns. The CDD measure generalizes the notion of the drawdown functional to a multi-scenario case and can be considered as a generalization of deviation measure to a dynamic case. The CDD measure includes the Maximal Drawdown and Average Drawdown as its limiting cases. Mathematical properties of the CDD measure have been studied and efficient optimization techniques for CDD computation and solving asset-allocation problems with a CDD measure have been developed. The CDD family of risk functionals is similar to Conditional Value-at-Risk (CVaR), which is also called Mean Shortfall, Mean Excess Loss, or Tail Value-at-Risk. Some recommendations on how to select the optimal risk functionals for getting practically stable portfolios have been provided. A real-life asset-allocation problem has been solved using the proposed measures. For this particular example, the optimal portfolios for cases of Maximal Drawdown, Average Drawdown, and several intermediate cases between these two have been found.

scholarly journals INTEGRATED MANAGEMENT OF MARKETING RISK AND EFFICIENCY / INTEGRUOTAS MARKETINGO RIZIKOS IR EFEKTYVUMO VALDYMAS

2011 ◽  
Vol 12 (1) ◽  
pp. 5-23 ◽  
Author(s):  
Aleksandras Vytautas Rutkauskas ◽  
Adomas Ginevičius
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Portfolio Management ◽  
Value At Risk ◽  
Integrated Management ◽  
Management Strategies ◽  
Optimization Methods ◽  
Integrated Analysis ◽  
Marketing Risk ◽  
Marketing Efficiency

There are two principal problems arising for marketing management: first—the increase of marketing ability to use effectively its resources, and second—to inventory the risks influencing marketing activity in order to develop their management strategy. Considering exceptional riskiness of marketing, the solution of marketing efficiency problems is not separable from identification of risks, influencing marketing, and their management strategies development. Integrated analysis of marketing efficiency and risk management problems is performed in two ways. First, a marketing risks portfolio management situation is analysed in such a way that resources, intended for risk management, are distributed among the means of decreasing value at risk in such a manner that the overall value of risk, i.e. the resultant of all risk values, would be minimal. Second, based on the expert efficiency estimates for a unit of costs in every element of marketing structure, a distribution of costs is pursued which would uphold the best increase of marketinggenerated marginal utility. To find the solution, imitative modeling and stochastic optimization methods are used. Santrauka Kyla dvi pagrindines marketingo valdymo problemos: pirma—tai marketingo gebejimo efektyviai naudoti jam skirtus išteklius didinimas, antra—inventorizuoti marketingo veiklai itak daranèias rizikas, siekiant parengti ju valdymo strategij. Atsižvelgiant i išskirtini marketingo rizikingum, jo efektyvumo problemu sprendimas neatsiejamas nuo riziku, daranèiu poveiki marketingui, identifikavimo ir ju valdymo strategiju sukurimo. Straipsnyje marketingo efektyvumas ir rizikos valdymo problemos nagrinejamos dviem budais. Pirmas—nagrinejama marketingo riziku portfelio valdymo situacija, kai ištekliai, skirti rizikai valdyti, dalijami tarp priemoniu, skirtu riziku vertei mažinti (Value at Risk), taip, kad bendroji rizikos verte, t. y. visu rizikos verèiu atstojamoji, butu minimali. Antras—remiantis ekspertu efektyvumo iverèiais snaudu vienetui kiekviename marketingo strukturos elemente, ieškomas toks snaudu padalijimas, kuris puoseletu naudingiausi marketingo sukuriamo ribinio naudingumo prieaugi. Sprendimams rasti pasitelkti imitacinio modeliavimo ir stochastinio optimizavimo metodai.

Stability analysis of portfolio management with conditional value-at-risk

2007 ◽  
Vol 7 (4) ◽  
pp. 397-409 ◽  
Author(s):  
Michal Kaut ◽  
Hercules Vladimirou ◽  
Stein W. Wallace ◽  
Stavros A. Zenios
Keyword(s):  
At Risk ◽  
Stability Analysis ◽  
Portfolio Management ◽  
Value At Risk ◽  
Conditional Value At Risk

scholarly journals VALUE-AT-RISK BASED APPROACH FOR CURRENCY HEDGING

2021 ◽  
Vol 5 (1) ◽  
pp. 23-37
Author(s):  
Rachna Khurana ◽  
Umang Khetan
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Portfolio Management ◽  
Value At Risk ◽  
Efficient Frontier ◽  
Jel Classification ◽  
Currency Hedging ◽  
Hedge Ratios ◽  
Cost Of Hedging ◽  
Historical Methods

Corporate FX risk management has gained complexity with an increased number of currencies involved and varying correlations among them. Existing literature has highlighted the need to account for cross-currency correlations when optimizing hedge ratios for portfolio management (Dowd, 1999). In this paper, we propose a Value-at-Risk (VaR) based model to estimate the optimal hedge ratio for a multi-national corporate that aims to minimize the cost of hedging at a given tolerance level of expected loss arising out of FX movement. The paper illustrates both parametric and historical methods of VaR estimation at a portfolio level as the first step in risk management. As a second step, an efficient-frontier is derived based on the expected VaR level at various hedge ratios and compared with associated hedge cost. The benefits of this approach include: identification of net exposures after correlations among currencies are accounted for in order to avoid duplication of hedges, and condensation of the parameters governing hedging decision into a single, intuitively-appealing number. The paper also highlights the need to frequently update the model’s assumptions as currency correlations and corporate exposures remain dynamic.   JEL Classification Codes: C10, F31, G32, M20.

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