HEDGING AND THE COMPETITIVE FIRM UNDER AMBIGUOUS PRICE AND BACKGROUND RISK

This paper examines the optimal production and hedging decisions of the competitive firm that possesses smooth ambiguity preferences and faces ambiguous price and background risk. The separation theorem holds in that the firm's optimal output level depends neither on the firm's attitude towards ambiguity nor on the incident to the underlying ambiguity. We derive necessary and sufficient conditions under which the full‐hedging theorem holds and thus options are not used. When these conditions are violated, we show that the firm optimally uses options for hedging purposes if ambiguity is introduced to the price and background risk by means of mean‐preserving spreads. We as such show that options play a role as a hedging instrument over and above that of futures.     

Export,Exchange Rate Risk and Hedging: The Duopoly Case

Abstract. This paper studies a Cournot duopoly in international trade with firms exposed to exchange rate risk. A hedging opportunity is introduced by a forward market on which one firm can trade the foreign currency. We investigate two settings: First, we assume that hedging and output decisions are taken simultaneously. It is shown that hedging is exclusively done for risk‐managing reasons as it is not possible to use hedging strategically. Second, the hedging decision is made before the output decisions. We show that hedging is not only used to manage the risk exposure but also as a strategic device.     

Operational and financial hedging for exporting firms

This paper examines the interaction between operational and financial hedging in the context of an internationally competitive but domestically monopolistic firm under exchange rate uncertainty. Operational hedging is modeled by letting the firm make its export decision after it has observed the true realization of the then prevailing spot exchange rate. Financial hedging, on the other hand, is modeled by allowing the firm to trade fairly priced exotic derivatives that are tailor-made for the firm's hedging need. We show that both operational and financial hedging unambiguously entice the firm into producing more. We further derive sufficient conditions under which operational hedging dominates (is dominated by) financial hedging in terms of promoting the firm's optimal output.     

股指期货套期保值理论及模型的演进与实证研究

将对股指期货套期保值策略进行比较全面的理论和实证研究。首先,概述了股指期货套期保值的相关理论,综述了套期保值的关键环节是最优套期保值比率的确定的相关的模型;其次,运用协整等分析方法,采用最小二乘回归模型（OLS）、向量自回归模型（VAR）、误差修正模型（ECM）、广义自回归条件异方差模型（GARCH）,分别对中国沪深300股指期货最优套期保值比率进行了实证研究,并对各模型的套期保值绩效做出了评价,得出ECM模型是最优的,是最适合中国沪深300股指期货的套期保值率估计模型。     

Belief elicitation in experiments: is there a hedging problem?

Belief-elicitation experiments usually reward accuracy of stated beliefs in addition to payments for other decisions. But this allows risk-averse subjects to hedge with their stated beliefs against adverse outcomes of the other decisions. So can we trust the existing belief-elicitation results? And can we avoid potential hedging confounds? We propose an experimental design that theoretically eliminates hedging opportunities. Using this design, we test for the empirical relevance of hedging effects in the lab. Our results suggest that hedging confounds are not a major problem unless hedging opportunities are very prominent. If hedging opportunities are transparent, and incentives to hedge are strong, many subjects do spot hedging opportunities and respond to them. The bias can go beyond players actually hedging themselves, because some expect others to hedge and best respond to this.     

Hedging exchange rate risk: The multiperiod case

We analyse production and hedging in a multiperiod framework for a risk-averse exporting firm facing a random exchange rate. We extend the separation theorem to this multiperiod model. Our study shows that unbiased currency forward markets in all periods do not imply standard full hedging. Under some conditions, the firm tends to overhedge compared to the one-period hedging models.     

Hedging and temporal permit issuances in cap-and-trade programs: The Market Stability Reserve under risk aversion

Cap-and-trade programs such as the European Union's Emissions Trading System (EU ETS) expose firms to considerable risks, to which the firms can respond with hedging. We develop an intertemporal stochastic equilibrium model to analyze the implications of hedging by risk-averse firms. We show that the resulting time-varying risk premium depends on the size of the permit bank. Applying the model to the EU ETS, we find that hedging can lead to a U-shaped price path, because prices initially fall due to negative risk premiums and then rise as the hedging demand declines. The Market Stability Reserve (MSR) reduces the permit bank and thus, increases the hedging value of the permits. This offers an explanation for the recent price hike, but also implies that prices may decline in the future due to more negative risk premiums. In addition, we find higher permit cancellations through the MSR than previous analyses, which do not account for hedging.     

Is hedging successful at reducing financial risk exposure?

This article analyses whether firms use risk management instruments for hedging or speculative purposes. First, by analysing the relationship between the firm’s stock returns and financial risks in 567 Euronext firms, we measure the firm’s exposure to risk. Next, we investigate the effect of hedging in such exposures, addressing simultaneously the endogeneity of hedging decision through a treatment effect methodology. We have found that firms in our sample display higher percentages of exposure, when weighed against preceding studies, and confirmed that hedging reduces the level of the underlying financial exposure, concluding that firms use risk management instruments with hedging purposes.     

On the Effect of Skewness and Kurtosis Misspecification on the Hedging Error

Using a result in Angelini and Herzel (2009a) , we measure, in terms of variance, the cost of hedging a contingent claim when the hedging portfolio is re‐balanced at a discrete set of dates. We analyse the dependence of the variance of the hedging error on the skewness and kurtosis as modeled by a Normal Inverse Gaussian model. We consider two types of strategies, the standard Black–Scholes Delta strategy and the locally variance‐optimal strategy, and we perform some robustness tests. In particular, we investigate the effect of different types of model misspecification on the performance of the hedging, like that of hedging without taking skewness into account. Computations are performed using a Fast Fourier Transform approach.     

Optimal gasoline hedging strategies using futures contracts and exchange-traded funds

This article employs a variety of econometric models (including OLS, VEC/VAR, DCC GARCH and a class of copula-based GARCH models) to estimate optimal hedge ratios for gasoline spot prices using gasoline exchange-traded funds (ETFs) and gasoline futures contracts. We then compare their performance using four different measures from the perspective of both their hedging objectives and trading position using four different measures: variance reduction measure, utility-based measure and two tail-based measures (value at risk and expected shortfall). The impact of the 2008 financial market crisis on hedging performance is also investigated. Our findings indicate that, in terms of variance reduction, the static models (OLS and VEC/VAR) are found to be the best hedging strategies. However, more sophisticated time-varying hedging strategies could outperform the static hedging models when the other measures are used. In addition, ETF hedging is a more effective hedging strategy than futures hedging during the high-volatility (crisis) period, but this is not always the case during the normal time (post-crisis) period.     

Dynamic asset allocation with ambiguous return predictability

We study an investor's optimal consumption and portfolio choice problem when he is confronted with two possibly misspecified submodels of stock returns: one with IID returns and the other with predictability. We adopt a generalized recursive ambiguity model to accommodate the investor's aversion to model uncertainty. The investor deals with specification doubts by slanting his beliefs about submodels of returns pessimistically, causing his investment strategy to be more conservative than the Bayesian strategy. Unlike in the Bayesian framework, the hedging demand against model uncertainty may cause the investor's stock allocation to decrease sharply given a small doubt of return predictability, even though the expected return according to the VAR model is large. Over much of the parameter space, the robust strategy is very close to the Bayesian strategy with Epstein–Zin preferences and risk aversion chosen to match the same average portfolio holdings. This is true in particular when the IID model is unlikely and the dividend yield is low, as in recent years. However, differences in strategies can be substantial if the IID model is unlikely and the dividend yield is high.     

Adaptive Portfolio Allocation with Options

We conducted a laboratory experiment of repeated portfolio allocation choice between a bond, a stock, and a put option on the stock. The study involves two conditions: a full hedging possibility and a partial hedging possibility. Surprisingly, participants were able to converge to the mean-variance frontier in the environment with partial hedging possibilities, but were unable to do so in the full hedging condition. This suggests that subjects may not be cognizant of the mean-variance frontier. If subjects begin away from the frontier and have to adjust toward it, incentives off the frontier are critical. Simulations of adaptive dynamic models confirm this assertion. The study provides insight into the adaptive behavior of investors in the presence of hedging possibilities and implications for efficient investment strategies.     

The effect of family ownership on corporate hedging: the case of Thailand

We explore how corporate hedging decisions are affected by family ownership and control in Thailand. One crucial advantage of investigating this issue in Thailand is that hedging instruments became available only recently, long after families established their presence in the firm. Thus, endogeneity is much less likely. The evidence shows that family ownership by itself does not have a significant impact on the firm’s propensity to hedge. However, when family members have a presence on the board of directors, the firm is significantly more likely to engage in hedging activities. Furthermore, we find that the presence of institutional blockholders also increases the likelihood of hedging significantly. Our study is the first to examine the impact of family ownership and control on corporate hedging behaviour in an emerging market.     

Market volatility and the dynamic hedging of multi-commodity price risk

Commodity cash and futures prices experienced a severe boom-and-bust cycle between 2006 and 2009. Increases in commodity price volatility have raised concerns about the usefulness of commodity futures and options as risk management tools. Dynamic hedging strategies have the potential to improve risk management when conditional (co)variances depart significantly from their unconditional, long-run counterparts and may be useful to decision-makers despite their greater complexity and higher transaction costs. We propose a Nonparametric Copula-based Generalized Autoregressive Conditional Heteroscedastic (NPC-GARCH) approach to estimate time-varying hedge ratios, and evaluate the benefits of dynamic hedging during four sub-periods between 2000 and 2011 using a stylized Texas cattle feedlot management problem. The NPC-GARCH approach allows for a flexible, nonlinear and asymmetric dependence structure between cash and futures prices for different commodities. We find that NPC-GARCH dynamic hedging performs better than either static, GARCH-Dynamic Conditional Correlation (DCC) or GARCH-Baba, Engle, Kraft and Kroner (BEKK) hedging in terms of lower tail risk (expected shortfall), but that there is no significant difference between hedging approaches in terms of portfolio variance reduction.     

Hedging the portfolio of raw materials and the commodity under the mark-to-market risk

This paper considers the hedging problem of a portfolio composed of raw materials and a commodity. A new theoretical model is presented to manage the risk exposure of the portfolio under the mark-to-market risk. Moreover, we employ the Lemke algorithm to obtain the optimal hedging strategy. We use a case of the soybean oil manufacturer from May 2008 to June 2011 to illustrate the proposed model and algorithm. The results show that the mark-to-market risk must be taken into account when devising the hedging strategies.     

Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops

This study elucidates plausible correlation between crude oil and agricultural commodities. We assess whether the conditional correlation of crude oil with energy crops (e.g., corn and soybeans) is different from that of food crops (e.g., oats and wheat). We find a stronger correlation of about 20 percent between returns of crude oil and energy crops. However, the correlation coefficient value for oil-oats and oil-wheat is as low as eight percent. We add to the literature by exploring correlation in a dynamic context using three different GARCH models and found that conditional correlation between crude oil and energy corps is relatively high. In order to reduce risk associated with crude oil price fluctuations, this study also examined hedging possibilities against crude oil by investment in agricultural commodities. Although hedging effectiveness is low with all underlying agricultural commodities, soybeans provide relatively better hedging possibilities compared to other agricultural crops.     

Can gold hedge and preserve value when the US dollar depreciates?

This paper examines gold's hedging and value-preserving properties against fluctuations in the US dollar. We propose a likelihood ratio test that draws a distinction between hedging and safe-haven characteristics on the basis of the conditional dependence structure under different market conditions. Our evidence, based on an analysis of data for US dollar exchange rates with a broad set of currencies, indicates that gold can serve as a hedge against US dollar depreciation but is a weak safe haven against extreme US dollar movements. These results have implications for risk management and hedging strategies.     

Market structure and multiperiod hedging

This paper develops a multiperiod hedging model for a competitive risk-averse international firm. We study the optimal sequential hedging strategy and analyze the impact of the structure of available risk sharing markets on the firm's export decision. As a main result, we find that the number of risk sharing markets critically affects the export level while the timing of these markets is inconsequential.     

Expected life-time utility and hedging demands in a partially observable economy

This paper analyzes the expected life-time utility and the hedging demands in an exchange only, representative agent general equilibrium under incomplete information. We derive an expression for the investor's expected life-time utility, and analyze his hedging demands for intertemporal changes in the stochastic unobservable growth of the endowment process and the changing quality of information regarding these changes. The hedging demands consist of two components, which could work in opposite directions so that a conservative consumer may end up having positive hedging demands. Our results are qualitatively different from those prevailing under constant growth (cf. [Brennan, M.J., 1998. The role of learning in dynamic portfolio decisions. European Finance Review, 1, 295-306; Ziegler, A., 2003. Incomplete Information and Heterogeneous Beliefs in Continuous-Time Finance. Springer, Berlin, Chapter 2].     

A comparison of pricing and hedging performances of equity derivatives models

This article investigates the pricing/hedging conundrum, i.e. the observation of a mismatch between derivatives models’ pricing and hedging performances, that has so far been under-emphasized as the literature tends to focus on increasingly complicated option pricing models, without adequately addressing hedging performance. Hence, we analyse the ability of the Black–Scholes, Practitioner Black–Scholes, Heston–Nandi and Heston models to Delta-hedge a set of call options on the S&P500 index and Apple stock. We extend earlier studies in that we consider the impact of asset dynamics, apply a stringent payoff replication strategy, look at the impact of moneyness at maturity and test for the robustness to the parameters’ calibration frequency and Delta-Vega hedging. The study shows that adding risk factors to a model, as stochastic volatility, should only be considered in light of the data dynamics. Even then, however, more complicated models generally fare poorly for hedging purposes. Hence, a better fit of a model to option prices is not a good indicator of its hedging performance, and so of its ability to describe the underlying dynamics. This can be understood for reasons of over-fitting. Those findings hint to a potentially appealing hedging-based calibration of models’ parameters, rather than the standard pricing-based one.