VAR-BASED OPTIMAL PARTIAL HEDGING

2013 ◽  
Vol 43 (3) ◽  
pp. 271-299 ◽  
Author(s):  
Jianfa Cong ◽  
Ken Seng Tan ◽  
Chengguo Weng

AbstractHedging is one of the most important topics in finance. When a financial market is complete, every contingent claim can be hedged perfectly to eliminate any potential future obligations. When the financial market is incomplete, the investor may eliminate his risk exposure by superhedging. In practice, both hedging strategies are not satisfactory due to their high implementation costs, which erode the chance of making any profit. A more practical and desirable strategy is to resort to the partial hedging, which hedges the future obligation only partially. The quantile hedging of Föllmer and Leukert (Finance and Stochastics, vol. 3, 1999, pp. 251–273), which maximizes the probability of a successful hedge for a given budget constraint, is an example of the partial hedging. Inspired by the principle underlying the partial hedging, this paper proposes a general partial hedging model by minimizing any desirable risk measure of the total risk exposure of an investor. By confining to the value-at-risk (VaR) measure, analytic optimal partial hedging strategies are derived. The optimal partial hedging strategy is either a knock-out call strategy or a bull call spread strategy, depending on the admissible classes of hedging strategies. Our proposed VaR-based partial hedging model has the advantage of its simplicity and robustness. The optimal hedging strategy is easy to determine. Furthermore, the structure of the optimal hedging strategy is independent of the assumed market model. This is in contrast to the quantile hedging, which is sensitive to the assumed model as well as the parameter values. Extensive numerical examples are provided to compare and contrast our proposed partial hedging to the quantile hedging.

2019 ◽  
Vol 56 (3) ◽  
pp. 787-809 ◽  
Author(s):  
Paolo Di Tella ◽  
Martin Haubold ◽  
Martin Keller-Ressel

AbstractWe introduce variance-optimal semi-static hedging strategies for a given contingent claim. To obtain a tractable formula for the expected squared hedging error and the optimal hedging strategy we use a Fourier approach in a multidimensional factor model. We apply the theory to set up a variance-optimal semi-static hedging strategy for a variance swap in the Heston model, which is affine, in the 3/2 model, which is not, and in a market model including jumps.


2020 ◽  
Vol 14 (2) ◽  
Author(s):  
Jan Bauer

AbstractI study dynamic hedging for variable annuities under basis risk. Basis risk, which arises from the imperfect correlation between the underlying fund and the proxy asset used for hedging, has a highly negative impact on the hedging performance. In this paper, I model the financial market based on correlated geometric Brownian motions and analyze the risk management for a pool of stylized GMAB contracts. I investigate whether the choice of a suitable hedging strategy can help to reduce the risk for the insurance company. Comparing several cross-hedging strategies, I observe very similar hedging performances. Particularly, I find that well-established but complex strategies from mathematical finance do not outperform simple and naive approaches in the context studied. Diversification, however, could help to reduce the adverse impact of basis risk.


Risks ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 76
Author(s):  
Saswat Patra ◽  
Malay Bhattacharyya

This paper investigates the risk exposure for options and proposes MaxVaR as an alternative risk measure which captures the risk better than Value-at-Risk especially. While VaR is a measure of end-of-horizon risk, MaxVaR captures the interim risk exposure of a position or a portfolio. MaxVaR is a more stringent risk measure as it assesses the risk during the risk horizon. For a 30-day maturity option, we find that MaxVaR can be 40% higher than VaR at a 5% significance level. It highlights the importance of MaxVaR as a risk measure and shows that the risk is vastly underestimated when VaR is used as the measure for risk. The sensitivity of MaxVaR with respect to option characteristics like moneyness, time to maturity and risk horizons at different significance levels are observed. Further, interestingly enough we find that the MaxVar to VaR ratio is higher for stocks than the options and we can surmise that stock returns are more volatile than options. For robustness, the study is carried out under different distributional assumptions on residuals and for different stock index options.


2020 ◽  
Vol 21 (5) ◽  
pp. 543-557
Author(s):  
Modisane Bennett Seitshiro ◽  
Hopolang Phillip Mashele

Purpose The purpose of this paper is to propose the parametric bootstrap method for valuation of over-the-counter derivative (OTCD) initial margin (IM) in the financial market with low outstanding notional amounts. That is, an aggregate outstanding gross notional amount of OTC derivative instruments not exceeding R20bn. Design/methodology/approach The OTCD market is assumed to have a Gaussian probability distribution with the mean and standard deviation parameters. The bootstrap value at risk model is applied as a risk measure that generates bootstrap initial margins (BIM). Findings The proposed parametric bootstrap method is in favour of the BIM amounts for the simulated and real data sets. These BIM amounts are reasonably exceeding the IM amounts whenever the significance level increases. Research limitations/implications This paper only assumed that the OTCD returns only come from a normal probability distribution. Practical implications The OTCD IM requirement in respect to transactions done by counterparties may affect the entire financial market participants under uncleared OTCD, while reducing systemic risk. Thus, reducing spillover effects by ensuring that collateral (IM) is available to offset losses caused by the default of a OTCDs counterparty. Originality/value This paper contributes to the literature by presenting a valuation of IM for the financial market with low outstanding notional amounts by using the parametric bootstrap method.


2016 ◽  
Vol 32 (2) ◽  
Author(s):  
Michał Barski

AbstractThe issue of constructing a risk minimizing hedge under an additional almost-surely type constraint on the shortfall profile is examined. Several classical risk minimizing problems are adapted to the new setting and solved. In particular, the bankruptcy threat of optimal strategies appearing in the classical risk minimizing setting is ruled out. The existence and concrete forms of optimal strategies in a general semimartingale market model with the use of conditional statistical tests are proven. The quantile hedging method applied in [Finance Stoch. 3 (1999), 251–273; Finance Stoch. 4 (2000), 117–146] as well as the classical Neyman–Pearson lemma are generalized. Optimal hedging strategies with shortfall constraints in the Black–Scholes and exponential Poisson model are explicitly determined.


2018 ◽  
Vol 8 (2) ◽  
pp. 7-40
Author(s):  
Everton Dockery ◽  
Miltiadis Efentakis Miltiadis Efentakis ◽  
Mamdouh Abdulaziz Saleh Al-Faryan

We study the performance of range-based models over varying market conditions and compare their performance against a set of alterative risk measurement models, including the more widely used techniques in practice for measuring the Value-at-Risk (VaR) of seven financial market indices. In particular, we focus on model accuracy in estimated VaRs over quiet and volatile moments utilizing loss functions and likelihood ratio tests for coverage probability. The empirical estimates based on these two criteria find that the range based-model of Yang and Zhang (2000) shows some success in estimated VaR risk measure, especially during quiet periods, than is the case for the other range based models considered. Also, we find that the EWMA and RiskMetrics models have an inconsistent marginal edge over the widely used GARCH and historical simulation specifications and that there is validity in the use of the EWMA and RiskMetrics models over range-based approaches as both capture and thus provide more accurate estimated VaR risk measure of market risk.


2018 ◽  
Vol 5 (331) ◽  
pp. 185-203
Author(s):  
Dominik Krężołek

 Risk analysis in the financial market requires the correct evaluation of volatility in terms of both prices and asset returns. Disturbances in quality of information, the economic and political situation and investment speculations cause incredible difficulties in accurate forecasting. From the investor’s point of view, the key issue is to minimise the risk of huge losses. This article presents the results of using some selected GARCH‑type models, ARMA‑GARCH and ARMA‑APARCH, in evaluating volatility of asset returns in the metals market. To assess the level of risk, the Value‑at‑Risk measure is used. The comparison between real and estimated losses (in terms of VaR) is made using the backtesting procedure. 


2021 ◽  
Vol 6 (4) ◽  
pp. 343
Author(s):  
Alexander Melnikov ◽  
Hongxi Wan

<p style='text-indent:20px;'>This paper analyzes Conditional Value-at-Risk (CVaR) based partial hedging and its applications on equity-linked life insurance contracts in a Jump-Diffusion market model with transaction costs. A nonlinear partial differential equation (PDE) that an option value process inclusive of transaction costs should satisfy is provided. In particular, the closed-form expression of a European call option price is given. Meanwhile, the CVaR-based partial hedging strategy for a call option is derived explicitly. Both the CVaR hedging price and the weights of the hedging portfolio are based on an adjusted volatility. We obtain estimated values of expected total hedging errors and total transaction costs by a simulation method. Furthermore,our results are implemented to derive target clients’ survival probabilities and age of equity-linked life insurance contracts.</p>


2011 ◽  
Vol 2011 ◽  
pp. 1-23
Author(s):  
Norman Josephy ◽  
Lucia Kimball ◽  
Victoria Steblovskaya

We present a method of optimal hedging and pricing of equity-linked life insurance products in an incomplete discrete-time financial market. A pure endowment life insurance contract with guarantee is used as an example. The financial market incompleteness is caused by the assumption that the underlying risky asset price ratios are distributed in a compact interval, generalizing the assumptions of multinomial incomplete market models. For a range of initial hedging capitals for the embedded financial option, we numerically solve an optimal hedging problem and determine a risk-return profile of each optimal non-self-financing hedging strategy. The fair price of the insurance contract is determined according to the insurer's risk-return preferences. Illustrative numerical results of testing our algorithm on hypothetical insurance contracts are documented. A discussion and a test of a hedging strategy recalibration technique for long-term contracts are presented.


Author(s):  
Dandes Rifa

The main objective of risk management is to minimize the potential for losses (risk) arising from unexpected changes in currency rates, credit, commodities and equities. One of the risks faced by companies is market risk (value at risk). This article aims to explain that risk management can be one of them by using derivative products. Derivative transactions is very useful for business people who want to hedge (hedging) against a commodity, which always experience price changes from time to time. There are three strategies that can be used to hedge the balance sheet hedging strategy, operational hedging strategies and contractual hedging strategies. Staregi contractual hedging is a form of protection that is done by forming a contractual hedging instruments in order to provide greater flexibility to managers in managing the potential risks faced by foreign currency. Most of these contractual hedging instrument in the form of derivative products. The management can enhance shareholder value by controlling risk. -Party investors and other interested parties hope that the financial manager is able to identify and manage market risks to be faced. If the value of the firm equals the present value of future cash flows, then risk management can be justified. 


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