Inflation and interest rate derivatives for FX risk management: Implications for exporting firms under real wealth

Firms that export goods face risks such as product price, cost, and exchange rate risks. Price and cost risks can substantially reduce the FX hedging performance in real wealth. We thus investigate hedging strategies that are intended to improve the performance of the FX hedge in real terms using inflation and interest rate derivatives. The impact of these additional instruments is not clear and has only been briefly analyzed in the hedging literature so far. For this purpose, we derive variance-minimizing hedge positions of an exporting firm. A cointegrated VAR and bootstrap methods are used to evaluate the efficiencies of several hedging strategies. While inflation derivatives work better in the short run, interest rate derivatives perform better over longer hedge horizons.     

Network analysis on Bitcoin arbitrage opportunities

Many studies have shown that investment in Bitcoin could serve to diversify the stock market. The existing literature offers insight into how arbitrage trading may diminish the risks associated with cryptocurrencies. Using arbitrage data and a novel methodology, this paper uncovers pertinent insights for investors interested in hedging against losses. Evidence points to the dsx, kraken, and bitstamp exchanges as the most attractive for buying Bitcoin and the cexio, bitmarketlt, and coindeal exchanges as the most attractive for selling Bitcoin. We employ network analysis to explore the interrelationships in thirteen cryptocurrency exchanges, providing evidence that kraken and bitstamp are leaders in market-forming trends, while coindeal and dsx serve as intermediary exchanges. Overall, these findings show that investors can mitigate their trading risks by knowing precisely where to buy and sell Bitcoin and which exchanges offer arbitrage opportunities. Using these results, investors can develop long-term and algorithmic trading strategies.     

Optimal Hedging Strategies and Interactions between Firms

This paper studies corporate risk management in a context of financial constraints and imperfect competition in the product market. The paper shows that interactions between firms affect their hedging strategies. As a general rule, firms’ hedging demands decrease with the correlation between their internal funds and investment opportunities. Moreover, when a firm’s hedging demand is high in the case where investments are strategic substitutes, its hedging demand is low in the case where investments are strategic complements and vice versa.     

A moments and strike matching binomial algorithm for pricing American Put options

This paper is dedicated to a new binomial lattice method called Moments and Strike Matching (MSM) consistent with the Black–Scholes model in the limit of an infinite step number and such that the Strike K is equal to one of the final nodes of the tree. The method is very easy to implement, since the parameters are explicitly given. Asymptotic expansions are obtained for the MSM European Put price and delta, which motivates the use of Richardson extrapolation. A numerical comparison with the best lattice based numerical methods known in literature, shows the efficiency of the proposed algorithm for pricing and hedging American Put options.      

On the choice between two delta-hedging strategies

This paper studies the choice between two popular hedging strategies by assuming that the hedge position (delta) follows a Markov chain with boundary conditions. We give the formula for long-run cost per unit time under two different cost structures: (I) a fixed transaction cost and (II) a non-fixed transaction cost. Then, we consider the case where the hedge position follows a random walk; we show that (i) re-balancing delta to the initial position is always more cost-efficient than re-balancing it to the edge for a fixed transaction cost; (ii) under certain conditions, re-balancing delta to the initial position is less cost-efficient than re-balancing it to the edge for a non-fixed transaction cost. In addition, we quantify the magnitude of the efficiency in both cases.     

Cross-hedging minimum return guarantees: Basis and liquidity risks

We reveal pitfalls in the hedging of insurance contracts with a minimum return guarantee on the underlying investment, e.g. an external mutual fund. We analyze basis risk entailed by hedging the guarantee with a dynamic portfolio of proxy assets for the funds. We also take account of liquidity risk which arises since the insurer may need to advance funds for performing the hedge. Based on a least-squares Monte Carlo simulation, we study the economic implications of basis and liquidity risks. We demonstrate that both risks may be surprisingly high and show how the design of the contract and the hedging strategy may help to alleviate them.     

Shortfall risk minimisation versus symmetric (quadratic) hedging

Abstract We consider the seller of a contingent claim who wants to hedge against the corresponding risk by means of a self-financing strategy, endowing less initial capital than the one required for (super)hedging. Two classical criteria used in this situation are shortfall risk minimisation and symmetric hedging (a natural generalisation of the quadratic hedging problem). We show that these two problems are equivalent if the market is complete. The case when the market is incomplete is also discussed. Mathematics Subject Classification (2000): 91B28, 91B70, 93E20 Journal of Economic Literature Classification: D81, G11     

K-matrix-class estimators and the full-information maximum-likelihood estimator as a special case

This article presents a unified treatment of simultaneous system estimation. A general class of full-information estimators is proposed, called K-matrix-class (KMC). It is shown that the K-matrix-class includes both full-information maximum-likelihood and three-stage least- squares estimators as special cases and that the k-class can be regarded as a subclass of the K-matrix-class. Conditions under which KMC estimators are consistent (similar to those of the k-class estimators) are given. Furthermore, as a full information-generalization of the double k-class estimators, the double K-matrix-class estimators (DKMC) are proposed.     

The women of Cairo: Equilibria in large anonymous games

In this article, I characterize Nash equilibria of large anonymous games by providing the following neccessary and sufficient condition for an equilibrium distribution: for no subset K of actions more players play actions in K than have a best response in K to the given distribution. While neccessity is trivial the proof for sufficiency relies on a theorem by [Math. Proc. Camb. Philos. Soc. 78 (1974) 323] which is an extension of Hall’s theorem or the marriage lemma well known from graph theory. The veiling problem for the women of Cairo serves as an illustrating heuristic example explaining the nature of the result.     

Is the nonlinear hedge of options more effective?—Evidence from the SSE 50 ETF options in China

The linear hedging of the options ignores the characteristic of the nonlinear change of option prices with the underlying asset. This paper establishes the nonlinear hedging strategy followed the study by Hull and White (2017) to investigate the effectiveness on the Shanghai Stock Exchange (SSE) 50 ETF options. The results show that the nonlinear hedge of the Chinese option market is less effective than the U.S option market because of the short history and the lower activity of the Chinese option market. The effect of nonlinear hedging strategy is better than the linear hedging strategy for calls in China. But for puts, the effect of the nonlinear hedging strategy is not as significant as it for calls. The difference in the trading volume between calls and puts and the high short-selling cost in the Chinese market are the main factors leading to the difference in hedge effectiveness. This paper suggests that the stock exchange could reduce margin standard of 50 ETF securities lending, promote a more flexible shorting mechanism, and accelerate the process of index options listed, so as to achieve hedging the risk of options more directly and efficiently.     

Contracting with Private Knowledge of Production Capacity

We analyze the design of procurement contracts when the supplier is privately informed about both his innate production capacity (K) and his innate unit cost of production. We identify conditions under which the supplier will strategically employ an inefficient production technology to expand output above K. We also show that when the buyer employs the simple fixed‐price cost‐reimbursement (FPCR) contracts in the setting examined by Rogerson (2003), the supplier has no incentive to exaggerate K. Furthermore, the buyer can secure with FPCR contracts at least 75% of the surplus she secures with fully optimal contracts.     

Quadratic hedging schemes for non-Gaussian GARCH models

We propose different schemes for option hedging when asset returns are modeled using a general class of GARCH models. More specifically, we implement local risk minimization and a minimum variance hedge approximation based on an extended Girsanov principle that generalizes Duan׳s (1995) delta hedge. Since the minimal martingale measure fails to produce a probability measure in this setting, we construct local risk minimization hedging strategies with respect to a pricing kernel. These approaches are investigated in the context of non-Gaussian driven models. Furthermore, we analyze these methods for non-Gaussian GARCH diffusion limit processes and link them to the corresponding discrete time counterparts. A detailed numerical analysis based on S&P 500 European call options is provided to assess the empirical performance of the proposed schemes. We also test the sensitivity of the hedging strategies with respect to the risk neutral measure used by recomputing some of our results with an exponential affine pricing kernel.     

New unit root asymptotics in the presence of deterministic trends

Recent work by Phillips (Econometrica 66 (1998) 1299) has shown that stochastic trends can be validly represented in empirical regressions in terms of deterministic functions of time. These representations offer an alternative mechanism for modelling stochastic trends. It is shown here that the alternate representations affect the asymptotics of all commonly used unit root tests in the presence of trends. In particular, the critical values of unit root tests diverge when the number of deterministic regressors K→∞ as the sample size n→∞. When they are appropriately recentered and standardized, unit root limit distributions are shown to be normal as K→∞.     

The Foreign Exchange Exposure Management Practices of Finnish Industrial Firms

This study employs questionnaire survey and financial accounting data to extend earlier empirical work on the foreign exchange (FX) exposure management practices of Finnish industrial firms. The paper concentrates on: (i) the form that FX corporate hedging policy takes; (ii) the control of FX procedures and trading; and, (iii) our respondents' perceptions about their ability to predict FX rate changes for hedging decisions. Our results indicate that the extent to which firms hedge FX exposure depends on the type of exposure and the form that FX hedging policy takes. Also, a significant number of the firms pursue FX hedging strategies on the expectation of attaining trading profits and this strategy appears to be accommodated within their FX policies. This feature is not explicitly demonstrated in previous studies. Finnish firms hedge a much higher proportion of both transaction and translation exposures compared to economic exposure. We partly attribute this emphasis to the requirements of the Finnish Accounting Act, which came into effect in 1993. The organisational, historical and financial settings of the firms also have significant impacts on exposure management practices. The overall implication of those results is that firms respond to changes in the financial, economic and regulatory environments in which they operate.     

Supply Chain Finance: A supply chain-oriented perspective to mitigate commodity risk and pricing volatility

This study addresses the Supply Chain Finance challenge of Commodity Price Volatility (CPV) by adopting a supply chain-oriented perspective. In particular, the effectiveness of two Supply Chain Risk Management (SCRM) strategies in mitigating CPV, namely, Switching suppliers and Substituting Commodities, and the main factors that may affect their value, are investigated with a simulation analysis. A Real Option Valuation (ROV) model was developed and tested on real cases of CPV mitigation, as experienced by a large multinational company (Fortune 100) leader in the Fast Moving Consumer Goods (FMCG) industry. The results show the effectiveness of Switching suppliers and Substituting Commodities in mitigating CPV, highlighting that the convenience of adopting such strategies is strongly influenced by some specific conditions, like the relative values of the long-term prices of the commodities, the purchasing volume, and the sunk cost needed to build flexibility.     

存在交易成本的权证避险策略实证研究

权证发行人在存在交易成本时对冲风险,若按照B—S理论进行动态连续避险操作,将造成巨大的交易成本,致使B-S动态连续避险不可行。因此存在交易成本时,对避险的操作都采用间断性避险。本文在统一均值方差框架下,系统全面的比较了存在交易成本的五种避险策略。在比例交易成本情形下,Whalley—Wilmott避险策略优于其他所有策略,当避险误差的标准差相同时该策略的交易成本最小;其次分别是delta固定避险带避险策略,基于标的资产价格变化的避险策略,Leland避险模型和间断的B—S避险策略。随着波动率σ上升,无风险利率γ下降,基于变动的避险策略相对于基于时间的策略优势更大。     

Hedging to market-wide shocks and competitive selection

This paper examines hedging against a large market-wide shock in a model with heterogeneous firms and sunk costs of entry. If hedging is voluntary only the most efficient firms hedge against this shock, a finding in line with empirical evidence but at odds with standard motivations for risk management. Hedging affects the critical level of the marginal cost needed to operate in the market. A setting with mandatory hedging is associated with stronger competition than when hedging is voluntary which, in turn, is associated with stronger competition than when hedging is unavailable.     

“Small things matter most”: The spillover effects in the cryptocurrency market and gold as a silver bullet

The cryptocurrencies with small market capitalization are often overlooked despite they can potentially be the source of shocks to other cryptocurrencies in the market. To address this caveat, this paper attempts to investigate the spillover effects among 14 cryptocurrencies by employing transfer entropy. Our results suggest that among different types of cryptos, Bitcoin is still the most appropriate instrument for hedging, while Tether (USDT) which have a strong anchor with the US dollar is significantly volatile. Interestingly, we document that the small coins are more likely to be shock creators in the cryptocurrency market. Using the same approach, we further explored the link between gold prices and cryptocurrency prices. The results show that gold could be a good hedging instrument for cryptocurrencies due to its independence. In light of empirical results, it is advisable to carefully consider the coins with small capitalization. Further, investors should conduct portfolio rebalancing by including gold to hedge against the unexpected movement in the cryptocurrency market. Our paper not only contributes in terms of the application of advanced empirical methodology but also provides evidence on idiosyncratic features of the cryptocurrency market.     

Revisiting the effect of household size on consumption over the life-cycle

Although the link between household size and consumption has strong empirical support, there is no consistent way in which demographics are dealt with in standard life-cycle models. We study the relationship between the predictions of the Single Agent model (the standard in the literature) versus a simple model extension (the Demographics model) where deterministic changes in household size and composition affect optimal consumption decisions. We show theoretically that the Demographics model is conceptually preferable to the Single Agent model as it captures economic mechanisms ignored by the latter. However, our quantitative analysis demonstrates that differences in predictions for consumption are negligible across models, when using standard calibration strategies. This suggests that it is largely irrelevant which model specification is used.     

Weak convergence of tree methods,to price options on defaultable assets

Abstract We discuss a practical method to price and hedge European contingent claims on assets with price processes which follow a jump-diffusion. The method consists of a sequence of trinomial models for the asset price and option price processes which are shown to converge weakly to the corresponding continuous time jump-diffusion processes. The main difference with many existing methods is that our approach ensures that the intermediate discrete time approximations generate models which are themselves complete, just as in the Black-Scholes binomial approximations. This is only possible by dropping the assumption that the approximations of increments of the Wiener and Poisson processes on our trinomial tree are independent, but we show that the dependence between these processes disappears in the weak limit. The approximations thus define an easy and flexible method for pricing and hedging in jump-diffusion models using explicit trees for hedging and pricing. Mathematics Subject Classification (2000): 60B10, 60H35 Journal of Economic Literature Classification: G13