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We examine whether the hedging effectiveness of crude oil futures is affected by asymmetry in the return distribution by applying tail-specific metrics to compare the hedging effectiveness of both short and long hedgers. The hedging effectiveness metrics we use are based on lower partial moments (LPM), value at risk (VaR) and conditional value at risk (CVaR). Comparisons are applied to a number of hedging strategies including ordinary least square (OLS), and both symmetric and asymmetric GARCH models. We find that OLS provides consistently better performance across different measures of hedging effectiveness as compared with GARCH models, irrespective of the characteristics of the underlying distribution.

The purpose of this paper is to ascertain the effectiveness of major deterministic and stochastic volatility-based option pricing models in pricing and hedging exchange-traded dollar–rupee options over a five-year period since the launch of these options in India.

The paper examines the pricing and hedging performance of five different models, namely, the Black–Scholes–Merton model (BSM), skewness- and kurtosis-adjusted BSM, NGARCH model of Duan, Heston’s stochastic volatility model and an ad hoc Black–Scholes (AHBS) model. Risk-neutral structural parameters are extracted by calibrating each model to the prices of traded dollar–rupee call options. These parameters are used to generate out-of-sample model option prices and to construct a delta-neutral hedge for a short option position. Out-of-sample pricing errors and hedging errors are compared to identify the best-performing model. Robustness is tested by comparing the performance of all models separately over turbulent and tranquil periods.

The study finds that relatively simpler models fare better than more mathematically complex models in pricing and hedging dollar–rupee options during the sample period. This superior performance is observed to persist even when comparisons are made separately over volatile periods and tranquil periods. However the more sophisticated models reveal a lower moneyness-maturity bias as compared to the BSM model.

The study concludes that incorporation of skewness and kurtosis in the BSM model as well as the practitioners’ approach of using a moneyness-maturity-based volatility within the BSM model (AHBS model) results in better pricing and hedging effectiveness for dollar–rupee options. This conclusion has strong practical implications for market practitioners, hedgers and regulators in the light of increased volatility in the dollar–rupee pair.

Existing literature on this topic has largely centered around either US equity index options or options on major liquid currencies. While many studies have solely focused on the pricing performance of option pricing models, this paper examines both the pricing and hedging performance of competing models in the context of Indian currency options. Robustness of findings is tested by comparing model performance across periods of stress and tranquility. To the best of the author’s knowledge, this paper is one of the first comprehensive studies to focus on an emerging market currency pair such as the dollar–rupee.

This study empirically compares the hedging performances of the newly listed Japanese yen (JPY) and European euro (EUR) currency futures in the KRX relative to that of the us dollar (USD) currency futures. For this purpose, assuming the situation of foreign-asset investment the minimum variance hedging models based on OLS and ECM are compared with a simple 1: 1 hedge. The difference between previous studies and this one is in that the latter uses various kinds of hedging performance measures and analyzes the hedging performances by different hedging horizon. According to the empirical results, the USD currency futures outperforms the JPY and EUR currency futures when considering the risk only.

However, the results are reversed wilen incorporating the return as well as the risk. With respect to the comparative advantages among hedging types, the ECM-hedge turns out to be better than the others for evaluating the risk only, and the 1: 1 hedge proves to be superior to the others when considering both of the return and risk aspects. Based on the risk-reduction aspect. the hedging performances are gradually improving as the length of hedging period increases, while they deteriorate for considering both the return and risk aspects.

The depth and breadth of the market for contingent claims, including exotic options, has expanded dramatically. Regulators have expressed concern regarding the risks of exotics to the financial system, due to the difficulty of hedging these instruments. Recent literature focuses on the difficulties in hedging exotic options, e.g., liquidity risk and other violations of the standard Black‐Scholes model. This article provides insight into hedging problems associated with exotic options: 1) hedging in discrete versus continuous time, 2) transaction costs, 3) stochastic volatility, and 4) non‐constant correlation. The author applies simulation analysis of these problems to a variety of exotics, including Asian options, barrier options, look‐back options, and quanto options.

This study seeks to examine the effectiveness of controlling the currency risk for international diversified mixed‐asset portfolios via two different hedge instruments, currency forwards and currency options. So far, currency forward has been the most common hedge tool, which will be compared here with currency options to control the foreign currency exposure risk. In this regard, several hedging strategies are evaluated and compared with one another.

Owing to the highly skewed return distributions of options, the application of the traditional mean‐variance framework for portfolio optimization is doubtful. To account for this problem, a mean lower partial moment model is employed. An in‐the‐sample as well as an out‐of‐the sample context is used. With in‐sample analyses, a block bootstrap test has been used to statistically test the existence of any significant performance improvement. Following that, to investigate the consistency of the results, the out‐of‐sample evaluation has been checked. In addition, currency trends are also taken into account to test the time‐trend dependence of currency movements and, therefore, the relative potential gains of risk‐controlling strategies.

Results show that European put‐in‐the‐money options have the potential to substitute the optimally forward‐hedged portfolios. Considering the composition of the portfolio in using in‐the‐money options and forwards shows that using any of these hedge tools brings a much more diversified selection of stock and bond markets than no hedging strategy. The optimal option weights imply that a put‐in‐the‐money option strategy is more active than at‐the‐money or out‐of‐the‐money put options, which implies the dependency of put strategies on the level of strike price. A very interesting point is that, just by dedicating a very small part of the investment in options, the same amount of currency risk exposure can be hedged as when one uses the optimal forward hedging. In the out‐of‐sample study, the optimally forward‐hedged strategy generally presents a much better performance than any types of put policies.

The research shows the risk and return implications of different currency hedging strategies. The finding could be of interest for asset managers of internationally diversified portfolios.

Considering the findings in the out‐of‐sample perspective, the optimally forward‐hedged minimum risk portfolio dominates all other strategies, while, in the depreciation of the local currency, this, together with the forward‐hedged tangency portfolio selection, would characterize the dominant portfolio strategies.

This paper investigates the predictive impact of Financial Stress on hedging between the oil market and the GCC stock and bond markets from January 1, 2007, to December 31, 2020. The authors also compare the hedging performance of in-sample and out-of-sample analyses.

For the modeling purpose, the authors combine the GARCH-BEKK model with the machine learning approach to predict the transmission of shocks between the financial markets and the oil market. The authors also examine the hedging performance in order to obtain well-diversified portfolios under both Financial Stress cases, using a One-Dimensional Convolutional Neural Network (1D-CNN) model.

According to the results, the in-sample analysis shows that investors can use oil to hedge stock markets under positive Financial Stress. In addition, the authors prove that oil hedging is ineffective in reducing market risks for bond markets. The out-of-sample results demonstrate the ability of hedging effectiveness to minimize portfolio risk during the recent pandemic in both Financial Stress cases. Interestingly, hedgers will have a more efficient hedging performance in the stock and oil market in the case of positive (negative) Financial Stress. The findings seem to be confirmed by the Diebold-Mariano test, suggesting that including the negative (positive) Financial Stress in the hedging strategy displays better out-of-sample performance than the in-sample model.

This study improves the understanding of the whole sample and positive (negative) Financial Stress estimates and forecasts of hedge effectiveness for both the out-of-sample and in-sample estimates. A portfolio strategy based on transmission shock prediction provides diversification benefits.

The purpose of this paper is to deeply study and compare the dual and single hedging strategy, from the direct and cross hedging perspective.

The authors not only first consider the dual hedge of integrated risks in this oil prices and foreign exchange rates setting but also make a novel comparison between the dual and single hedging strategy from a direct and cross hedging perspective. In total, six econometric models (to conduct one-step-ahead out-of-sample rolling estimation of the optimal hedge ratio) and two hedging performance criteria are employed in two different hedging backgrounds (direct and cross hedging).

Results show that in the direct hedging background, a dual hedge cannot outperform the single hedge. But in the cross dual hedging setting, a dual hedge performs much better, possibly because the dual hedge brings different levels of advantages and disadvantages in the two different settings and the superiority of the dual hedge is more obvious in the cross dual hedging setting.

The existing literature that deals with oil prices and foreign exchange rates mostly concentrates on their relationship and comovements, while the dual hedge of integrated risks in this setting remains underresearched. Besides, the existing literature that deals with dual hedge gets its conclusions only based on a single specific background (direct or cross hedging) and lacks deeper investigation. In this paper, the authors expand the width and depth of the existing literature. Results and implications are revealing.

This paper studies hedging strategies that use the KOSDAQ50 index futures to hedge the price risk of the KOSDAQ50 index spot portfolio. This study uses the minimum variance hedge model and bivariate ECT-GARCH (1,1) model as hedging models, and analyzes their hedging performances. The sample period covers from January 31, 2001 to December 31, 2002. The most important findings may be summarized as follows. First, both the risk-minimization and GARCH model exhibit hedge ratios that are substantially lower than one. Hedge ratios of the risk-minimization tend to be higher than those of GARCH model. Second, for the in-sample data, hedging effectiveness of GARCH model is higher than that of the risk-minimization, while for the out-of-sample data, hedging effectiveness of the risk-minimization with constant hedge ratios is not far behind the GARCH model in its hedging performance. Third, the hedging performance of KOSDAQ50 index futures is lower than that of KOSPI200 index futures, but higher than that of KTB futures. In conclusion, in the KOSDAQ50 index market, investors are encouraged to use the simple risk-minimization model to hedge the price risk of KOSDAQ50 spot portfolios.

This study aims to investigate the benefits of commodity hedging in the global stock index, bond and foreign currency (FX) portfolios.

The authors compare various hedging strategies and factor transaction costs. The authors analyze equally weighted, dynamic hedging ratio, risk parity and reward to risk timing strategies. Volatilities are estimated using historical, GARCH(1,1), and APARCH(1,1) methods. In addition, the authors evaluate the portfolio's hedging performance (HP) based on four different dimensions: volatility (annualized standard deviation), Sharpe ratio (SR), HP, and high-low ratio (HL).

The authors observe different benefits of the commodity hedging strategy among financial assets (stocks, bonds or FX).The authors find that commodity hedging in the stock markets is the best option, if the authors optimize the hedging ratio using dynamic hedging from historical data. The authors also document that for stock portfolio managers, adding commodities will generate a more conservative strategy, whereas for bond and/or FX portfolio managers, adding commodities will generate a more aggressive strategy.

This study contributes to the literature by investigating commodity hedging in the global stock index, bond and FX portfolios. First, the authors provide details on the diversification benefits in the commodities. Second, the authors document the hedging strategy that is the best as a part of the diversification strategy by adding commodities. Third, the authors provide a practical analysis by reporting the financial assets portfolio that is appropriate for commodity hedging following the portfolio managers' objectives (e.g. reducing risks or improving the risk-reward ratio).

This paper seeks to shed light on the question whether German real estate investment vehicles provide an effective hedge against inflation. To do so it aims to investigate open‐end real estate funds, special funds and real estate stocks.

Traditional approaches as well as cointegration and causality tests are applied to monthly and quarterly index data from 1992:04 to 2009:12 for the subject investment vehicles.

There is strong evidence that real estate returns are almost independent from inflation in the short run. None of the investigated investment vehicles provide a hedge against expected and unexpected inflation at different lags. In contrast, cointegration tests show that real estate stocks, open‐end funds and special funds do provide a hedge against inflation in the long term. Likewise, causality tests suggest that real estate performance is influenced by inflation in the long term.

The study still could not investigate closed‐end funds and G‐REITs. Yet, it does capture the most and comprehensive part of the indirect German real estate investment market.

Inflation‐hedging capabilities are of particular interest in periods of economic instability. Especially institutional investors with large asset portfolios seek to adjust their asset allocation to changing conditions.

To date, research papers on the subject of inflation‐hedging capabilities of real estate almost exclusively focus on REITs in the USA and in the UK. Research about the German real estate market and alternative investment vehicles is rare – partly due to a lack of transparency over the past – although international investors more and more adhere to the German real estate investment market.