Hedging Effectiveness Research Articles

How do crude oil futures hedge crude oil spot risk after the COVID-19 outbreak? A wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method

In the current paper, we investigate the problem of how do crude oil futures hedge crude oil spot risk after the COVID-19 outbreak. Specifically, given that noise, conditional higher moments and asymmetric tail dependence may exist in crude oil markets, a Wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method is proposed to construct hedging portfolios in crude oil markets during the epidemic period. Based on the in-sample and out-of-sample results, the hedging roles of Brent futures and Shanghai crude oil (SC) futures for light and medium crude spots after the COVID-19 outbreak are further researched. The empirical results demonstrate that noise, conditional higher moments and asymmetric tail dependence do exist in crude futures and spots, which have impact on the precision of modeling results. Secondly, the Wavelet denoising-GARCHSK-SJC Copula hedge ratio estimation method outperforms all control groups, obtaining the best in-sample and out-of-sample hedging effectiveness. Finally, it is reported in the in-sample and out-of-sample hedging results that Brent is the optimal futures to hedge light oil, while SC is the optimal futures to hedge medium oil. The paper provides substantial recommendations for policymakers and investors.

Analysis of the Frequency-Based Relationship between Inflation Expectations and Gold Returns in Turkey

This paper explores the relationship between inflation expectations and gold returns of monthly and annual maturities in Turkey from 2006 to 2020 with 177 monthly observations through the application of wavelet cohesion and causality tests. The findings reveal significantly negative cohesion in the short term and significantly positive cohesion in the long term, indicating that the hedging ability of gold prices exists only in the long term during crisis periods. Therefore, the findings provide evidence for the validity of the expected inflation effect hypothesis in Turkey. The ordinary least squares results, on the other hand, show that the ongoing COVID-19 pandemic is the most prominent factor in the movement of inflation and gold at all wavelet scales for the two types of maturities. The continuous wavelet transformation based Granger-causality test provides little evidence for out-of-phase and unidirectional causality running from the inflation expectations to gold returns in the higher and medium frequency bands. Furthermore, the QQR results show an asymmetrical impact on each other—implying a hedging effectiveness of gold against inflation expectations—and reveal that its size and magnitude change significantly under different economic conditions and data frequencies. The results have significant implications for portfolio and risk management during normal market conditions as well as hedging and speculation activities during crises in short term and long term periods, respectively. 

Can bonds hedge stock market risks? Green bonds vs conventional bonds

Growing concerns about climate change have generated several ecofriendly investments, including green bonds. This study investigates the impacts of geopolitical, economic and climate policy risks (GPR, EPU and CPU, respectively) on the long-term conventional/energy stock and conventional/green bond correlations using the DCC-MIDAS-X model. We determine that GPR, EPU and CPU impact the correlations between these stock and bond markets differently. Both conventional and green bonds have a safe-haven function when GPR levels are high, while green bonds outperform conventional bonds as a safe haven when EPU and CPU levels are high. Moreover, incorporating green bond assets into diversified portfolios provides the best hedging effectiveness, particularly for assets with a high carbon footprint.

Economic imperatives of financialization of agricultural commodity markets

Purpose. The purpose of the article is to substantiate the theoretical and methodological foundations and economic feasibility of intensifying the processes of financialization of the business model of Ukrainian grain producers, in particular through the formation of the grain futures market and the creation of commodity exchange in Ukraine. 
 Methodology / approach. In the article, it is clarified the concept of financialization as one of the global trends of economic development that provides deep integration of financial and real economy on macro- and micro levels. Hedge effectiveness of price risks for Ukrainian grain (wheat and corn) using futures contracts traded on CME Group and Euronext is evaluated using regression analysis. Ukrainian wheat and corn FOB price volatility for 2016–2021 marketing years is estimated. The dynamics and volatility of the basis for Ukrainian wheat and corn and respective futures contracts traded on CME Group and Euronext are analyzed. 
 Results. The analysis of securitization index of global agricultural markets has shown an increase of its financialization rate. The main reasons for this process were the deepening of financial and commodity markets integration, deregulation of financial markets and introduction of new financial instruments. The structure of the grain market in Ukraine is analyzed, particularly the role of agricultural holdings and international companies. The tendencies and determinants of wheat and corn market prices in Ukraine during marketing year are revealed. Regression analysis of hedge effectiveness has shown that all considered futures contracts are suitable for wheat and corn CPT and FOB price hedging in Ukraine. The highest hedge effectiveness was revealed for Black Sea Corn Financially Settled (Platts) Futures) (CME Group) and Milling Wheat / Ble de Meunerie (Euronext Matif). Short hedge efficiency of CME Group futures contracts was supported by analysis of basis dynamics for Ukrainian wheat and corn and respective futures contracts. 
 Originality / scientific novelty. Based on the analysis of the theoretical foundations of financialization, the positive and negative consequences of the strengthening of financialization of global commodity markets and the peculiarities of the functioning of the modern grain market in Ukraine, the economic imperatives of the development of the Ukrainian market of grain derivatives, as an objectively determined trend of agricultural commodity market, are substantiated. The evaluation of the effectiveness of hedging price risks on the Ukrainian grain markets using derivatives traded on global exchanges has gained further development.
 Practical value / implications. It is proposed to intensify market tools usage for risk hedging in Ukraine in order to cover interests of all market participants. Risk management instruments available for Ukrainian agricultural producers are discussed.

Volatility Forecasting of Copper Futures Based on HAR-RV Model

As an important part of the international futures market, copper price prediction is important for international financial market research. This paper selects the high-frequency data every 5 minutes from the database and uses the HAR-RV model based on realized volatility. By introducing investor sentiment and the day of week effects, we have established three new types of non-uniform autoregressive models. Empirical analysis shows that the weekly and monthly fluctuations of copper futures prices are relatively small, while the daily fluctuations are relatively large. The prediction model is more accurate when predicting the long-term volatility, and the stability test shows that the HAR-RV model is relatively stable when predicting the long-term volatility. Investor sentiment has a negative impact on the price volatility of copper futures in the medium and long-term forecasts. Weekend effects have a negative impact on the medium and long-term forecasts of copper futures. This paper complements the existing literature and improves the prediction ability of copper price fluctuations, which is very important to promote effective hedging, risk transfer, and price discovery in the futures market.

Bitcoin, Ether, Tether and Gold: Do these assets reduce losses or profits in the US stock market during the COVID-19 pandemic?

The effectiveness of an optimal hedging for a drop in the S&P500 using gold and cryptocurrencies in the COVID-19 pandemic is considered. Based on Value at Risk a new dynamic measure of relative benefit from the hedging strategy is proposed in the paper which allows us to compare the loss reduction and profit sacrifice. We find gold as good shelter for the US stock market. It effectively lowers volatility and downside risk. Moreover, gold reduces extreme losses more intensively than corresponding profits. Hedging with optimal weights for cryptocurrencies is not recommended since it establishes weights close to zero for Bitcoin and Ether and close to one for Tether.

Can social capital and reputation mitigate political and market competition risk?

We assess whether social capital, captured by CSR, is an effective hedge against risks arising from political and market competition risk. Having a higher CSR score significantly reduces stock return volatility during political uncertainty, but not cash flow volatility. Meanwhile, CSR is also an effective hedge against stock return volatility that arises from peer competition. Finally, the hedging effect of CSR on stock return volatility is transient, but has a positive effect on firms’ future performance and growth opportunities.

When is gold an effective hedge against inflation?

Using threshold and piecewise regression models on monthly data (January 1969–March 2021), we examine the asymmetric effects of inflation and the US ten-year Treasury bond interest rate on gold price returns, identifying two distinct regimes. Inter alia, it is found that the responsiveness of gold returns to changes in inflation and interest rate depends on the magnitude of monthly inflation itself. Given the recent multi-trillion-dollar stimulus packages, the US is likely to switch into a ‘high’ inflation regime (as defined by our endogenously determined threshold), leading to gold once again becoming a potent hedge against inflation. The results support the view that when monthly inflation in the US exceeds 0.55%, gold exhibits significant responses to changes in both inflation and the ten-year Treasury interest rate. However, when inflation is moderate or low, gold remains somewhat non-responsive. We thus argue that such asymmetric and size-dependent responses are the main causes of the lack of consensus in the literature regarding the hedging capability of gold.

Dynamic frequency volatility spillovers and connectedness between strategic commodity and stock markets: US-based sectoral analysis

This study examines the time-varying frequency spillovers and connectedness between U.S. sector stock markets and both crude oil and gold and their implications on portfolio management. Using the methodology of Diebold and Yilmaz (2012) and Baruník and Křehlík (2018), the results show that oil, gold, financials, utilities, communications services, consumer staples (at short term), and health care are net receivers of spillovers in the system, and the remaining sectors are net contributors regardless of the frequencies. The extent of spillover reduces when both gold and oil assets are added to sector portfolio. Furthermore, the connectedness among markets is heterogeneous and depends on time horizons and market conditions. Oil offers a higher hedging effectiveness in both the short and long term as well as over different turbulent periods compared to oil. The hedging effectiveness is higher in the long term compared to the short term.

Can precious metals hedge geopolitical risk? Fresh sight using wavelet coherence analysis

Based on wavelet coherence analysis, this paper explores whether precious metals can be used to hedge geopolitical risk (GPR) and whether there is an asymmetry in the hedging effect when GPR rises or falls in time and frequency domains. In addition, we obtain the lead-lag relationship between precious metals and GPR under different time-frequency effects. The main findings are summarized as follows. First, gold and silver are good assets to hedge against GPR in the short and medium term. Second, the relationship between GPR and precious metals shows a significant asymmetry when GPR rises and falls. Third, all four precious metals can hedge both GPR and the negative change of GPR in the medium term. Finally, it is worth noting that both gold and silver are leaders in GPR changes. These new findings in this paper provide an essential reference for investors and policymakers from different time scale perspectives.

Effect of summer hedging on return bloom, yield, tree growth, and juice quality of apples grown for cider

Effect of summer hedging on return bloom, yield, tree growth, and juice quality of apples grown for cider

Commodity futures hedge ratios: A meta-analysis

The derivative accounting standard requires hedging to satisfy the 80–125 rule to be eligible to apply the hedge accounting treatment. This means the hedging relationship should achieve hedging effectiveness within the 80%–125% level to qualify for hedge accounting. The appropriateness of this screening criterion is questioned in the existing literature, and there is hardly any empirical evidence to justify the suitability of this threshold level of hedge effectiveness. By applying meta-analysis methodology for 1699 hedge ratios collected from previous academic studies in commodity futures hedging, we show that the average optimal hedge ratio in commodity futures hedging in the academic literature mostly overlaps with the 80–125 threshold.

State-dependent hedge strategy for crude oil spot and futures markets

Relying on the hidden Markov model improved by the particle swarm optimization algorithm (PSO-HMM), we develop a dual-decision method to address the issue of state-dependent futures hedging. Our approach is attractive in two ways. First, it uses the PSO algorithm to overcome the shortcomings of the traditional algorithm, which can easily fall into the local optima to estimate parameters in a hidden Markov mode. Second, this paper proposes a new hedge position adjustment method based on the identified market states, instead of sticking to the hedge position calculated by the commonly used GARCH-type models to achieve a better trade-off between risk hedging and return acquisition. Specifically, we first improve the accuracy of parameter measurement and employ the PSO-HMM to identify two market states, bear and bull, and fully illustrate the rationality and effectiveness of the proposed model. Based on the market states identified, we then adjust the hedge ratio estimated by GARCH-type models and compare the hedging effects of no hedge, model-driven, and state-dependent strategies. Our empirical results show that the PSO-HMM method can improve the accuracy of state identification over the classical HMM. The market state-dependent hedging strategy has better performance than other strategies when it comes to the trade-off between the return and the risk of a hedged portfolio. Furthermore, robustness checks under different conditions confirm that the state-dependent hedging strategy outperforms the model-driven hedging and no hedge strategies. Thus, our research sheds new light on conventional hedging models.

Dynamic dependence and hedging strategies in BRICS stock markets with oil during crises

This paper discusses the asymmetric volatility spillovers between these two markets of BRICS’ countries during different financial and economic circumstances from 2010 until 2021, using the ARFIMA-FIAPARCH to model the dynamics of the marginal distribution. We study the feasibility of hedging stocks with oil, risk measurement functions allow financial practitioners to calculate the optimal hedge ratios and the corresponding to hedge portfolio returns. A dual long memory model is adopted to estimate the conditional mean and the conditional variance. Thereafter, a VaR,CVaR and ΔCVaR are applied to assess oil price exposure. Furthermore, to evaluate the optimal portfolio, we adopted the optimal portfolio weight, the optimal hedge ratio and the hedge effectiveness oil. Our results show that there are distinct economic benefits from hedging stocks with oil, although the effectiveness of hedging is both time-varying and market-state-dependent. We determine that the volatility transmission was time-varying and that influence from the Asian crisis, the bursting of the dot com bubble, the 2008 global financial crisis, the recent oil-price crash, and COVID 19 alternated between negative and positive values, over the entire studied period. During times of global financial uncertainty, investors reduce stock positions more than commodity positions, thus crude oil prices shock negatively affect the portfolio returns of stock-oil hedges. all stock market–oil pairs display the highest hedging effectiveness during the COVID-19 pandemic, which proved that the oil market can assist as a hedge for stock market in a portfolio.

Financing renewables in the age of falling technology costs

Cost of renewable energies have dropped, approaching wholesale power price levels. As a result, the role of renewable energy policy design is shifting – from covering incremental costs towards facilitating risk-hedging. An analytical model of the financing structure of renewable investment projects is developed to assess this effect und used to compare different policy design choices: contracts for differences, sliding premia, fixed premia and a setting without dedicated remuneration mechanism. The expected benefit for electricity consumers from reduced risk and financing costs is approximated at the example of a 2030 scenario for Germany. Policies like sliding premia, previously evaluated as providing low-risk investment environments, provide for less risks hedging, when technology costs approach wholesale power prices. Contracts for differences provide in all scenarios the most effective hedge for investors against power prices uncertainty, enabling low-cost financing and reducing costs for consumers, while also hedging electricity consumers against high power prices.

Time-frequency spillovers and connectedness between precious metals, oil futures and financial markets: Hedge and safe haven implications

This paper examines the time-frequency spillovers and connectedness between the major precious metals futures markets (gold, palladium, platinum, and silver), the West Texas Intermediate (WTI) oil futures, the US stock market, the US 10-year Treasury Bond (T-Bond) market, and the US dollar index. Applying Barunik and Krehlik’s (2018) novel framework, the results show that spillovers across markets strengthens in the short-term, suggesting that diversification opportunities are lower in the short-term than the long-term. Furthermore, we find that the net transmitter/receiver of spillover is dependent on the frequency being analyzed, thereby indicating asymmetric spillovers among markets. Moreover, gold and silver (platinum, T-Bonds, and US dollar index) are net transmitters (receivers) of spillover regardless of the time horizon. Palladium is the net transmitter of spillover to the other markets in the short-term period (1–8 days); in contrast, in the long-term period (8–256 days), the S&P 500 index is the net transmitter of spillover. Precious metals futures, crude oil, and T-Bond assets are diversifiers for the US stock market for short-term and the long-term investments. The US dollar index is a strong hedge regardless of the time horizon and a strong (weak) safe haven asset in the short (long) term. Precious metals are a safe haven in the short-term and long-term periods. Crude oil and T-Bonds are not a safe haven for US equity investors. Finally, our result support evidence of diversification benefits and better hedging effectiveness by adding precious metals, WTI, T-Bond, and USDX to S&P500 index, which is higher in the long-term than in the short-term. WTI offers the highest hedging effectiveness, regardless the time investment horizons.

Risk Connectedness Between Green and Conventional Assets with Portfolio Implications.

The increasing concerns of investors toward green bonds and their appealing nature of diversification has motivated the current research to study the risk connectedness between green and conventional assets spanning from August 2014 to December 2020. We first estimate the dynamic equi-correlations through DECO-GARCH. Next, we assess the dynamic and static risk connectedness in the median, extreme low, and extreme high quantiles arguing that spillovers vary across different time periods particularly during economically intense time periods. Finally, we analyzed the hedge ratio and hedge effectiveness between green bonds and other assets. We find that equi-correlations are intense during economic shocks such as the Shale oil crisis, Brexit, US interest rate hike, and COVID-19 pandemic. The volatility analysis at average, lower, and upper quantiles also validate time-varying attributes of green and conventional assets. Further, network figures of green and conventional assets identify potential diversification opportunities. Meanwhile, the hedge effectiveness indicates that green bonds are effective hedge for precious metals and cryptocurrencies. Our findings draw multiple implications for policymakers, green investors, financial market participants, and regulatory authorities regarding flight-to-safety during crisis times and maintaining a diverse portfolio to escape potential losses.

The impact of cryptocurrencies on China's carbon price variation during COVID-19: A quantile perspective

We aim to document the impact of cryptocurrencies on China's carbon price variation using some quantile techniques during COVID-19 with the daily data spanning from August 7, 2015 to April 30, 2021. In this paper, we show that cryptocurrencies have a very strong explanation power for carbon market with the non-parametric causality-in-quantiles method. In addition, cryptocurrencies can work as a good hedging candidate for carbon market at different investment horizons with the quantile coherency approach. Using hedging effectiveness measure, we further show that COVID-19 can reverse the optimal hedging ratios in our portfolio specification in cryptocurrencies‑carbon emission trading pairs while this pandemic does not have effects on the trading effectiveness. Finally, the heterogeneity and asymmetry features in the dynamic quantile-on-quantile effects are detected and the effects on carbon efficient index show relatively strong fluctuation while on carbon emission trading market are relatively strong in magnitude. Our empirical results conclude with many potential applications for policymakers and investors.

Understanding e-commerce customer behaviors to use drone delivery services: A privacy calculus view

Drone delivery is an emerging service at the early adoption stage. It is imperative to understand what it takes for the public to accept such emerging services. This study asks what mechanism influences people’s switching intention in e-commerce drone delivery services. A 7 points Likert scale questionnaire were developed after the two rounds of pretest and a total of 83 surveys were collected from a business school in USA. This study applies privacy calculus theory and technology anxiety in innovation to develop a research model. An empirical survey and structural equation modeling analysis with SmartPLS and a consistent PLS algorithm are used to understand the hedging effect of relative advantages of drone delivery services and technology anxiety on the switching intention of e-commerce consumers. Theoretically, this research adds the e-commence literature, suggesting that people appreciate drone delivery’s speed and environmental protection advantages. However, privacy risk severity and vulnerability are not significant predictors of technology anxiety, negatively impacting switching intention. This study also provided practical contribution to improve the service development of e-commerce company to deliver their products to their customers with the most efficient resources being used.

Blue hydrogen and industrial base products: The future of fossil fuel exporters in a net-zero world

Is there a place for today's fossil fuel exporters in a low-carbon future? This study explores trade channels between energy exporters and importers using a novel electricity-hydrogen-steel energy systems model calibrated to Norway, a major natural gas producer, and Germany, a major energy consumer. Under tight emission constraints, Norway can supply Germany with electricity, (blue) hydrogen, or natural gas with re-import of captured CO 2 . Alternatively, it can use hydrogen to produce steel through direct reduction and supply it to the world market, an export route not available to other energy carriers due to high transport costs. Although results show that natural gas imports with CO 2 capture in Germany is the least-cost solution, avoiding local CO 2 handling via imports of blue hydrogen (direct or embodied in steel) involves only moderately higher costs. A robust hydrogen demand would allow Norway to profitably export all its natural gas production as blue hydrogen. However, diversification into local steel production, as one example of easy-to-export industrial base products, offers an effective hedge against the possibility of lower European blue hydrogen demand. Looking beyond Europe, the findings of this study are also relevant for the world's largest energy exporters (e.g., OPEC+) and importers (e.g., developing Asia). Thus, it is recommended that large hydrocarbon exporters consider a strategic energy export transition to a diversified mix of blue hydrogen and climate-neutral industrial base products.