Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility

This paper investigates the impacts of News-based Implied Volatility (NVIX) on the long-term volatility of five cryptocurrencies using the GARCH-MIDAS model. We also evaluate the hedging effectiveness of cryptocurrencies against the S&P 500 index after incorporating NVIX. The empirical results show that NVIX has a negative and significant impact on the long-term volatility of five cryptocurrencies. The impact of NVIX remains robust even after controlling for Global Economic Policy Uncertainty (GEPU) and Realized Volatility (RV). The uncertainty derived from investor perception is more important than the uncertainty of economic fundamentals in predicting cryptocurrency volatility. The hedging effectiveness of Bitcoin against the S&P 500 index is improved due to consideration of NVIX. This paper provides new evidence concerning the impacts of uncertainty on the volatility of cryptocurrencies.     

Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?

We assess whether the long-run volatilities of Bitcoin, global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results provide evidence supporting this hypothesis, except in the case of bonds. For Bitcoin investors, the results imply the ability to use information about the state of global economic uncertainty to enhance the predictions of Bitcoin volatility. We further examine whether the correlation between Bitcoin and global equities, commodities, and bonds are affected by global economic policy uncertainty. Empirical results reveal that global economic policy uncertainty has a negative significant impact on the Bitcoin-bonds correlation and a positive impact on both Bitcoin-equities and Bitcoin-commodities correlations, suggesting the possibility of Bitcoin acting as a hedge under specific economic uncertainty conditions. Interestingly, the hedging effectiveness of Bitcoin for both global equities and global bonds enhances slightly after considering the level of global economic policy uncertainty. Such a weak effect of the state of global economic uncertainty on the hedging ability of Bitcoin implies that investors cannot substantially enhance the hedging performance of Bitcoin under different economic uncertainty conditions.     

Robustly Hedging Variable Annuities With Guarantees Under Jump and Volatility Risks

Recent variable annuities offer participation in the equity market and attractive protection against downside movements. Accurately quantifying this additional equity market risk and robustly hedging options embedded in the guarantees of variable annuities are new challenges for insurance companies. Due to sensitivities of the benefits to tails of the account value distribution, a simple Black–Scholes model is inadequate in preventing excessive liabilities. A model which realistically describes the real world price dynamics over a long time horizon is essential for the risk management of the variable annuities. In this article, both jump risk and volatility risk are considered for risk management of lookback options embedded in guarantees with a ratchet feature. We evaluate relative performances of delta hedging and dynamic discrete risk minimization hedging strategies. Using the underlying as the hedging instrument, we show that, under a Black–Scholes model, local risk minimization hedging can be significantly better than delta hedging. In addition, we compare risk minimization hedging using the underlying with that of using standard options. We demonstrate that, under a Merton's jump diffusion model, hedging using standard options is superior to hedging using the underlying in terms of the risk reduction. Finally, we consider a market model for volatility risks in which the at‐the‐money implied volatility is a state variable. We compute risk minimization hedging by modeling at‐the‐money Black–Scholes implied volatility explicitly; the hedging effectiveness is evaluated, however, under a joint model for the underlying price and implied volatility. Our computational results suggest that, when implied volatility risk is suitably modeled, risk minimization hedging using standard options, compared to hedging using the underlying, can potentially be more effective in risk reduction under both jump and volatility risks.     

Pricing methods and hedging strategies for volatility derivatives

We explore the valuation and hedging of discretely observed volatility derivatives using three different models for the price of the underlying asset: Geometric Brownian motion with constant volatility, a local volatility surface, and jump-diffusion. We begin by comparing the effects on valuation of variations in contract design, such as the differences between specifying log returns or actual returns and incorporating caps on the level of realized volatility. We then focus on the difficulties associated with hedging these products. Delta hedging strategies are ineffective for hedging volatility derivatives since they require very frequent rebalancing. Moreover, they provide limited protection in the jump-diffusion context. We study the performance of a hedging strategy for volatility swaps that establishes small, fixed positions in vanilla options at each volatility observation.     

Evaluating the performance of futures hedging using factors-driven realized volatility

The complexity and uncertainty of the financial market mainly stem from the rich market internal transaction information and a wide range effect of external factors. To this end, this paper proposes the combination factors-driven forecasting method to predict realized volatilities of the CSI 300 index and index futures. Based on the volatilities predicted by the proposed method, we further evaluate the ex-ante hedging performance in comparison to the conventional HAR model as well as GARCH-type models. The empirical results indicate that the factors-driven realized volatility model significantly dominates the other commonly used models in terms of hedging effectiveness. Furthermore, the superiority of the proposed method is robust in different market conditions, including significant rising or falling and abnormal market fluctuations in the COVID-19 pandemic, and in different index markets. Therefore, this paper improves the prediction accuracy of volatility by integrating market internal transaction information and external factor information, and the proposed method in this paper can be used by investors to obtain an excellent hedging effect.     

Some Issues in Corporate Hedging Policy

The increased volatility of financial markets in recent years has led to a corresponding increase in the volatility of corporate earnings. This has, in turn, led to a surge of interest in hedging. At first sight, it may seem that, to the extent it can reduce volatility, hedging is a worthwhile activity. However, we argue that the issue is less clear-cut than meets the eye. In the process of developing our arguments, we shall look at some of the financial instruments available for hedging and shall show how they can be used for various hedging and non-hedging purposes.     

Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection

During the recent European sovereign debt crisis, returns on EMU government bond portfolios experienced substantial volatility clustering, leptokurtosis and skewed returns as well as correlation spikes. Asset managers invested in European government bonds had to derive new hedging strategies to deal with changing return properties and higher levels of uncertainty. In this environment, conditional time series approaches such as GARCH models might be better suited to achieve a superior hedging performance relative to unconditional hedging approaches such as OLS. The aim of this study is to test innovative hedging strategies for EMU bond portfolios for non-crisis and crisis periods. We analyze single and composite hedges with the German Bund and the Italian BTP futures contracts and evaluate the hedging effectiveness in an out-of-sample setting. The empirical analysis includes OLS, constant conditional correlation (CCC), and dynamic conditional correlation (DCC) multivariate GARCH models. We also introduce a Bayesian composite hedging strategy, attempting to combine the strengths of OLS and GARCH models, thereby endogenizing the dilemma of selecting the best estimation model. Our empirical results demonstrate that the Bayesian composite hedging strategy achieves the highest hedging effectiveness and compares particularly favorable to OLS during the recent sovereign debt crisis. However, capturing these benefits requires low transactions cost and efficiently functioning futures markets.     

Mitigating Interest Rate Risk in Variable Annuities: An Analysis of Hedging Effectiveness under Model Risk

Variable annuities are investment vehicles offered by insurance companies that combine a life insurance policy with long-term financial guarantees. These guarantees expose the insurer to market risks, such as volatility and interest rate risks, which can be managed only with a hedging strategy. The objective of this article is to study the effectiveness of dynamic delta-rho hedging strategies for mitigating interest rate risk in variable annuities with either a guaranteed minimum death benefit or guaranteed minimum withdrawal benefit rider. Our analysis centers on three important practical issues: (1) the robustness of delta-rho hedging strategies to model uncertainty, (2) the impact of guarantee features (maturity versus withdrawal benefits) on the performance of the hedging strategy, and (3) the importance of hedging interest rate risk in either a low and stable or rising interest rate environment. Overall, we find that the impact of interest rate risk is equally felt for the two types of products considered, and that interest rate hedges do lead to a significant risk reduction for the insurer, even when the ongoing low interest rate environment is factored in.     

Risk management and market conditions

In this paper, we investigate the relation between hedging activity by commercial/merchant/producers to commodity prices and commodity market volatility using Commitments of Traders reports from commodity futures markets exchanges. Qualifying the body of literature which attributes hedging activity to departures from Modigliani-Miller theory, market imperfections and transactions cost, we address the paradoxes of hedging which is not value creating and the absence of hedging when firms might benefit, arguing that it may be related to the market conditions and risk appetite. We discover that prices and volatility are generally statistically significant contributors to hedging activity by commercial/merchant/producers’ users but with marked differences in their elasticities. For some commodities, price levels alone and not volatility are significant. We demonstrate that analysis of hedging in commodity markets should take cognisance of conditions and the degree of risk aversion, otherwise the implicit assumption is that hedging is invariant to such matters. Through considering both market conditions and the degree of risk aversion, understanding the motivation for hedging may be enhanced.     

Managing earnings risk under SFAS 133/IAS 39: the case of cash flow hedges

Whereas empirical studies suggest that firm hedging is influenced by accounting standards such as SFAS 133 and IAS 39, the nature of earnings risk management remains a puzzle. I develop a model that shows how non-financial firms that prefer predictable earnings jointly optimize their hedging strategy and the choice between fair-value and hedge accounting. I also examine the implications of these decisions for earnings predictability under SFAS 133/IAS 39. In this model, which has two accounting periods, earnings uncertainty arises from economic shocks and accounting mismatches. The specific influence of accounting mismatches is isolated with two benchmarks, one for firm hedging (cash flow hedging) and another for an accounting system that fully complies with the matching principle. In this forward-looking analysis, most firms significantly decrease the hedging of long-term earnings when faced with persistent price dynamics. Under non-persistent price dynamics, the levels of long-term earnings hedging are only slightly reduced. Therefore, the influence of accounting mismatches on firm hedging is highly dependent on the economic environment in which a firm operates, which suggests that the potential influence of accounting on firm hedging may be difficult to identify in archival studies. The analysis also offers a forward-looking perspective on the changing properties of earnings since the late 1970s that supplements the existing body of archival accounting studies. For example, under persistent price dynamics, forward-looking short-term earnings volatility may increase tenfold or more for cash flow hedging under fair-value accounting compared with a perfectly matched accounting system.     

THE ECONOMIC VALUE OF USING REALIZED VOLATILITY IN FORECASTING FUTURE IMPLIED VOLATILITY

We examine the economic benefits of using realized volatility to forecast future implied volatility for pricing, trading, and hedging in the S&P 500 index options market. We propose an encompassing regression approach to forecast future implied volatility, and hence future option prices, by combining historical realized volatility and current implied volatility. Although the use of realized volatility results in superior performance in the encompassing regressions and out-of-sample option pricing tests, we do not find any significant economic gains in option trading and hedging strategies in the presence of transaction costs.     

Information,hedging demand,and institutional investors: Evidence from the Taiwan Futures Exchange

This paper examines the effect of hedging demand by various types of institutional investor on subsequent returns and volatility. Using data from the Taiwan Futures Exchange, empirical results indicate that the hedging demand of foreign investors has a significant negative impact on subsequent returns and volatility. In addition, trading strategies based on the extreme hedging demand of foreigners are positively correlated with trading performance. Furthermore, there is evidence to show that returns (volatility) also affect the subsequent hedging demand of foreign investors, suggesting a feedback relation. Finally, the hedging demand of foreign investors has a greater impact on subsequent returns and volatility after global financial turmoil. Accordingly, this paper concludes that foreign investors are informed hedgers in the Taiwan futures market, especially after global financial turmoil.     

Empirical Performance of Alternative Option Pricing Models

Substantial progress has been made in developing more realistic option pricing models. Empirically, however, it is not known whether and by how much each generalization improves option pricing and hedging. We fill this gap by first deriving an option model that allows volatility, interest rates and jumps to be stochastic. Using S&P 500 options, we examine several alternative models from three perspectives: (1) internal consistency of implied parameters/volatility with relevant time-series data, (2) out-of-sample pricing, and (3) hedging. Overall, incorporating stochastic volatility and jumps is important for pricing and internal consistency. But for hedging, modeling stochastic volatility alone yields the best performance.     

Hedging with Chinese Aluminum Futures: International Evidence with Return and Volatility Spillover Indices Under Structural Breaks

This paper examines the hedging performance of the Shanghai futures market, with the London futures market acting as the channel for volatility spillover. Taking into consideration structural change, basis effects, and return and volatility spillover effects, the authors find that the estimated hedging performance is not improved. Their findings suggest that the effectiveness of the hedging performance of aluminum futures contracts in China is not affected by the magnitude or direction of return and volatility spillovers. Therefore, even when the magnitude and direction of volatility spillover from other markets can be correctly predicted, the hedging performance of a futures contract cannot be significantly improved. This paper uses precise measures of return spillovers and volatility spillovers based directly on the framework of vector autoregressive variance decompositions. The study also includes an analysis of both crisis and noncrisis episodes, with modeling on bursts in spillovers.     

价格异常与不对称相关结构下套期保值策略——来自亚洲股指期货市场的实证

在不对称相关结构下,尾部区域期货和现货价格联动模式异常复杂,传统套期保值策略在极端价格行为下将不可避免地出现系统性偏差。为此,恰当的连接函数被引入描述尾部区域的价格联动模式,依据MV框架构建局部套期保值策略,以解决极端价格行为下的套期保值问题。对亚洲市场日经指数和恒生指数期货套期保值的实证研究表明:(1)采用Rotated Gumbel连接函数,在传统MV策略(全局策略)下,虽然在降低套保组合方差方面没有明显优势,但日经指数和恒生指数期货的套期保值成本将显著下降,套保组合收益/组合方差的比率显著上升;(2)如果套期保值者能够对未来形成可靠预期,套期保值的成本将进一步下降,并且现货价格风险也得到有效控制。     

How fair-value accounting can influence firm hedging

The potential influence of accounting regulations on hedging strategies and the use of financial derivatives is a research topic that has attracted little attention in both the finance and the accounting literature. However, recent surveys suggest that company hedging can be substantially influenced by the accounting for financial instruments. In this study, we illustrate not only why but also how the accounting regulations may affect hedging behavior. We find that under mark-to-market accounting, most firms concerned with earnings smoothness adopt myopic hedging strategies relative to the benchmark, cash flow hedging. The specific influence of the accounting regulations depends on market and firm-specific characteristics, but, in general, the firms dramatically reduce the extent of hedging addressing price risk in future accounting periods. We illustrate that the change in hedging behavior significantly dampens the increase in earnings volatility stemming from fair value accounting of derivatives. However, the adjusted hedging strategies may substantially increase the firms’ cash flow volatility.     

A Markov regime switching approach for hedging energy commodities

This paper estimates constant and dynamic hedge ratios in the New York Mercantile Exchange oil futures markets and examines their hedging performance. We also introduce a Markov regime switching vector error correction model with GARCH error structure. This specification links the concept of disequilibrium with that of uncertainty (as measured by the conditional second moments) across high and low volatility regimes. Overall, in and out-of-sample tests indicate that state dependent hedge ratios are able to provide significant reduction in portfolio risk.     

Hedging efficiently under correlation

We show that when a derivative portfolio has different correlated underlyings, hedging using classical greeks (first-order derivatives) is not the best possible choice. We first show how to adjust greeks to take correlation into account and reduce P&L volatility. Then we embed correlation-adjusted greeks in a global hedging strategy that reduces cost of hedging without increasing P&L volatility, by optimization of hedge re-adjustments. The strategy is justified in terms of a balance between transaction costs and risk-aversion, but, unlike more complex proposals from previous literature, it is completely defined by observable parameters, geometrically intuitive, and easy to implement for an arbitrary number of risk factors. We test our findings on a CVA hedging example. We first consider daily re-hedging: in this test, correlation-adjusted greeks allow the reduction of P&L volatility by more than 30% compared to standard deltas. Then we apply our general strategy to a context where a CVA portfolio is exposed to both credit and interest rate risk. The strategy keeps P&L volatility in line with daily standard delta-hedging, but with massive cost-saving: only six rebalances of the illiquid credit hedge are performed, over a period of six months.     

Adapted hedging

Exponentials of squared returns in Gaussian densities, with their consequently thin tails, are replaced by the absolute return to form Laplacian and exponentially tilted Laplacian densities at unit time. Scaling provides densities at other maturities. Stochastic processes with these marginals are identified. In addition to a specific local volatility model the densities are consistent with the difference of compound exponential processes taken at log time and scaled by the square root of time. The underlying process has a single parameter, the constant variance rate of the process. Delta hedging using Laplacian and Asymmetric Laplacian implied volatilities are developed and compared with Black Merton Scholes implied volatility hedging.The hedging strategies are implemented for stylized businesses represented by dynamic volatility indexes. The Laplacian hedge is seen to be smoother for the skew trade. It also performs better through the financial crisis for the sale of strangles. The Laplacian and Gaussian models are then synthesized as special cases of a model allowing for other powers between unity and the square. Numerous hedging strategies may be run using different powers and biases in the probability of an up move. Adapted strategies that select the best performer on past quarterly data can dominate fixed strategies. Adapted hedging strategies can effectively reduce drawdowns in the marked to market value of businesses trading options.