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.

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.

Volatility Forecast by Volatility Index and Its Use as a Risk Management Tool Under a Value-at-Risk Approach

2018 ◽  
Vol 21 (02) ◽  
pp. 1850010 ◽  
Author(s):  
Yam Wing Siu
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Risk Premium ◽  
Value At Risk ◽  
Realized Volatility ◽  
Management Tool ◽  
Spot Price ◽  
Pricing Options ◽  
Significance Levels ◽  
Risk Approach

This paper examines the predicting power of the volatility indexes of VIX and VHSI on the future volatilities (or called realized volatility, [Formula: see text] of their respective underlying indexes of S&P500 Index, SPX and Hang Seng Index, HSI. It is found that volatilities indexes of VIX and VHSI, on average, are numerically greater than the realized volatilities of SPX and HSI, respectively. Further analysis indicates that realized volatility, if used for pricing options, would, on some occasions, result in greatest losses of 2.21% and 1.91% of the spot price of SPX and HSI, respectively while the greatest profits are 2.56% and 2.93% of the spot price of SPX and HSI, respectively, making it not an ideal benchmark for validating volatility forecasting techniques in relation to option pricing. Hence, a new benchmark (fair volatility, [Formula: see text] that considers the premium of option and the cost of dynamic hedging the position is proposed accordingly. It reveals that, on average, options priced by volatility indexes contain a risk premium demanded by the option sellers. However, the options could, on some occasions, result in greatest losses of 4.85% and 3.60% of the spot price of SPX and HSI, respectively while the greatest profits are 4.60% and 5.49% of the spot price of SPX and HSI, respectively. Nevertheless, it can still be a valuable tool for risk management. [Formula: see text]-values of various significance levels for value-at-risk and conditional value-at-value have been statistically determined for US, Hong Kong, Australia, India, Japan and Korea markets.

scholarly journals Risk management of risk under the Basel Accord: forecasting value‐at‐risk of VIX futures

2011 ◽  
Vol 37 (11) ◽  
pp. 1088-1106 ◽  
Author(s):  
Chia‐lin Chang ◽  
Juan‐Ángel Jiménez‐Martín ◽  
Michael McAleer ◽  
Teodosio Pérez‐Amaral
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Basel Accord ◽  
Vix Futures ◽  
Management Of Risk

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

Optimal Reciprocal Reinsurance under VaR or TVaR Constraint

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hung-Hsi Huang ◽  
Ching-Ping Wang
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Moral Hazard ◽  
Value At Risk ◽  
Incentive Compatibility ◽  
Regular Form ◽  
Optimal Reinsurance ◽  
The Common ◽  
Risk Constraint ◽  
Management Requirement

Abstract Most existing researches on optimal reinsurance contract are based on an insurer’s viewpoint. However, the optimal reinsurance contract for an insurer is not necessarily to be optimal for a reinsurer. Hence, this study aims to develop the optimal reciprocal reinsurance which satisfies the benefits of both the insurer and reinsurer. Additionally, due to legislative restriction or risk management requirement, the wealth of insurer and reinsurer are frequently imposed upon a VaR (Value-at-Risk) or TVaR (Tail Value-at-Risk) constraint. Therefore, this study develops an optimal reciprocal reinsurance contract which maximizes the common benefits (evaluated by weighted addition of expected utilities) of the insurer and reinsurer subject to their VaR or TVaR constraints. Furthermore, for avoiding moral hazard problem, the developed contract is additionally restricted to a regular form or incentive compatibility (both indemnity schedule and retained loss schedule are continuously nondecreasing).

The Value-at-Risk Methodology of Basel II and Basel III

2014 ◽  
pp. 100-114 ◽  
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Basel Ii ◽  
Risk Measurement ◽  
Capital Adequacy ◽  
Basel Iii ◽  
Regulatory Capital ◽  
Advantages And Disadvantages ◽  
Risk Methodology

This chapter examines the advantages and disadvantages of the risk estimate approach—Value-at-Risk (VaR) which has been extensively embraced by regulators and practitioners in financial markets under the Basel II & III framework as the basis of risk measurement, both for the purpose of ensuring regulatory capital adequacy, and risk management and strategic planning at industry level.

Arbor City Community Foundation (A): The Foundation

2017 ◽  
pp. 1-3 ◽  
Author(s):  
Karl Schmedders ◽  
Russell Walker ◽  
Michael Stritch
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Management Policy ◽  
City Region ◽  
Portfolio Rebalancing ◽  
City Community ◽  
Portfolio Returns ◽  
The Impact ◽  
Community Foundation

The Arbor City Community Foundation (ACCF) was a medium-sized endowment established in Illinois in the late 1970s through the hard work of several local families. The vision of the ACCF was to be a comprehensive center for philanthropy in the greater Arbor City region. ACCF had a fund balance (known collectively as “the fund”) of just under $240 million. The ACCF board of trustees had appointed a committee to oversee investment decisions relating to the foundation assets. The investment committee, under the guidance of the board, pursued an active risk-management policy for the fund. The committee members were primarily concerned with the volatility and distribution of portfolio returns. They relied on the value-at-risk (VaR) methodology as a measurement of the risk of both short- and mid-term investment losses. The questions in Part (A) of the case direct the students to analyze the risk inherent in both one particular asset and the entire ACCF portfolio. For this analysis the students need to calculate daily VaR and monthly VaR values and interpret these figures in the context of ACCF's risk management. In Part (B) the foundation receives a major donation. As a result, the risk inherent in its portfolio changes considerably. The students are asked to evaluate the risk of the fund's new portfolio and to perform a portfolio rebalancing analysis.Understanding the concept of value at risk (VaR); Calculating daily and monthly VaR by two different methods, the historical and the parametric approach; Interpreting the results of VaR calculations; Understanding the role of diversification for managing risk; Evaluating the impact of portfolio rebalancing on the overall risk of a portfolio.

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