Narrow Results

Seeing the firm as a nexus of activities and projects, we propose a characterization of the firm where variations in the market price of risk should induce adjustments in the firm's portfolio of projects. In a setting where managers disagree with respect to what investment maximizes value, changing the portfolio of projects generates coordination costs. We then propose a new role for financial risk management based on the idea that the use of financial derivatives reduces coordination costs by moving the organization's expected cash flows and risks toward a point where coordination in favor of real changes is easier to achieve. We find empirical support for this new rationale for the use of financial derivatives, after controlling for the traditional variables explaining the need for financial risk management.

We study the exchange rate exposures of a sample of firms that undertake large acquisitions of foreign companies. Using data from Securities and Exchange Commission (SEC) filings on their foreign operations and derivatives usage, we examine how the exposures change from before to after the acquisition. We find that these deals generally lead to reduced currency exposure, which reflects the fact that most of the firms already have business in the target's country and the mergers serve as operational hedges. In contrast, we do not find a statistically significant effect for hedging with currency derivatives despite the fact that many of the firms in the sample use such instruments.

In this paper, we study how a competitive banking firm can use a variable deposit rate to insure against profit risk from risky assets and how the utility of the bank manager is affected by this kind of risk management policy. Furthermore, we study the advantage of a risk management policy which is based on financial hedging. Finally, we answer the question which of these risk management policies the bank manager prefers.

Credit risk is one of the most important forms of risk faced by national and international banks as financial intermediaries. Managing this kind of risk through selecting and monitoring corporate and sovereign borrowers and through creating a diversified loan portfolio has always been one of the predominant challenges in bank management. The aim of our study is to examine how a risky loan portfolio affects optimal bank behavior in the loan and deposit markets, when derivatives to hedge credit risk are available. In a stochastic continuous-time framework a hedging model is developed where the bank management can use derivatives to hedge credit risk. Optimal loan, deposit and hedging strategies are then studied. It is shown that the magnitude and the direction of hedging are determined by the bank manager's preferences, the corresponding risk premium and the variance of the loan rate and its hedging instrument respectively.

This paper aims to investigate the return and volatility spillover between world oil prices and the sectoral stock of Pakistan. We estimate a bivariate VAR(1)-AGARCH (1,1) model using weekly data sampled from January 1, 2001 to December 31, 2015. The model results are used to estimate the optimal portfolio weights and hedge ratios. The empirical findings suggest no short-run price transmission between world oil prices and stock sectors of Pakistan Stock Exchange. Only the past unexpected shocks in world oil prices has significant effect on the volatility of sectoral stock returns of Pakistan Stock Exchange, and no volatility spillover exist between world oil price and stock sectors. The optimal portfolio weights and hedge ratios for oil/stock holdings are sensitive to sectors considered. These findings are of great interest for policy makers, hedge fund managers, $i$ investors and market participants.

In this paper, we consider price weighted-volatility swap and price weighted-variance swap. The underlying asset considered in this paper is assumed to follow a general stochastic differential equation and exhibits stochastic volatility. We obtain analytical pricing formulas for the weighted-variance swap and approximate expression for the weighted-volatility swap. Nice bounds for the arbitrage-free variance swap price are also found. The proposed pricing formulas are easy to implement in real time and can be applied efficiently for practical applications. We consider the problem of hedging volatility swap with variance swap and obtain analytical formula for the hedge ratio. We also consider a problem of hedging an asset with variance swap and option. We determined the optimal amount of the underlying asset that has to be held for minimizing the hedging error by taking positions in options and weighted-variance swap. A numerical example is also provided.

This paper is the first to consider hedging under price, output and basis risks using a general framework. In doing so, it provides significant empirical results pertaining to the US.

In this study, we investigate how adding Bitcoin can influence the investment portfolios. For this purpose, we consider a portfolio including Bitcoin and the five major sector indices of the Tehran Stock Exchange (TSE). At first, the asset returns are predicted through an estimation model based on higher moments. In the second step, the properties of Bitcoin in the face of other assets in a portfolio are studied by the asymmetric dynamic conditional correlation (ADCC) model. Then, the optimal weights in the portfolios are estimated. Accordingly, we used four portfolio optimization models with different objective functions, including a hybrid function of the higher moments, predicted risk from the ADCC model, and maximizing Sharpe and Sortino ratios. The out-of-sample results showed the relative efficiency of the proposed model in predicting the asset returns in Tehran Stock Exchange. In addition, the results of the ADCC model showed that Bitcoin plays a risk-hedging role for the pharmaceutical and banking sectors in TSE. We also know Bitcoin as a safe haven for the banking, petrochemical, metals, automobile, and pharmaceutical sectors. The results of portfolio selection also prove the effectiveness of adding Bitcoin with a maximum weight of 10% in the investment portfolios.

Based on comparative analysis, we first discuss different kinds of Greek letters in terms of Black–Scholes option pricing model, then we show how these Greek letters can be applied to perform hedging and risk management. The relationship between delta, theta, and gamma is also explored in detail.

This paper presents arbitrage and risk arbitrage betting strategies for Team Jai Alai. This game is the setting for the analysis and most results generalize to other sports betting situations and some financial market applications. The arbitrage conditions are utility free while the risk arbitrage wagers are constructed according to the Kelly criterion/capital growth theory that maximizes asymptotically long-run wealth almost surely.

I consider the Black–Scholes–Merton option-pricing model from several angles, including personal, technical and, most importantly, from the perspective of a paradigm-shifting mathematical formula.

The objective of this paper is to estimate the hedge ratios of foreign-listed single stock futures (SSFs) and to compare the performance of risk reduction of different methods. The OLS method and a bivariate GJR-GARCH model are employed to estimate constant optimal hedge ratios and the dynamic hedging ratios, respectively. Data of the SSFs listed on the London International Financial Future and Options Exchange (LIFFE) are used in this research. We find that the data series have high estimated constant optimal hedge ratios and high constant correlation in the bivariate GJR-GARCH model, except for three SSFs with their underlying stocks traded in Italy. Our findings provide evidence that distance is a critical factor when explaining investor's trading behavior. Results also show that in general, of the three methods examined (i.e., naïve hedge, conventional OLS method and dynamic hedging) the dynamic hedging performs the best and that naïve hedge is the worst.

The objective of this paper is to estimate the hedge ratios of foreign-listed single stock futures (SSFs) and to compare the performance of risk reduction of different methods. The OLS method and a bivariate GJR-GARCH model are employed to estimate constant optimal hedge ratios and the dynamic hedging ratios, respectively. Data of the SSFs listed on the London International Financial Future and Options Exchange (LIFFE) are used in this research. We find that the data series have high estimated constant optimal hedge ratios and high constant correlation in the bivariate GJR-GARCH model, except for three SSFs with their underlying stocks traded in Italy. Our findings provide evidence that distance is a critical factor when explaining investor's trading behavior. Results also show that in general, of the three methods examined (i.e., naïve hedge, conventional OLS method and dynamic hedging) the dynamic hedging performs the best and that naïve hedge is the worst.

No abstract received.

The paper analyzes alternative mathematical techniques, which can be used to derive hedging strategies for credit derivatives in models with totally unexpected default. The stochastic calculus approach is used to establish abstract characterization results for hedgeable contingent claims in a fairly general set-up. In the Markovian framework, we use the PDE approach to show that the arbitrage price and the hedging strategy for an attainable contingent claim can be described in terms of solutions of a pair of coupled PDEs.

In this paper, we first present a review of statistical tools that can be used in asset management either to track financial indexes or to create synthetic ones. More precisely, we look at two important replication methods: the strong replication, where a portfolio of very liquid assets is created and the goal is to track an actual index with the portfolio, and weak replication, where a portfolio of very liquid assets is created and used to either replicate the statistical properties of an existing index, or to replicate the statistical properties of a custom asset. In addition, for weak replication, the target is not an index but a payoff, and the replication amounts to hedge the portfolio so it is as close as possible to the payoff at the end of each month. For strong replication, the main tools are predictive tools, so filtering techniques and regression play an important role. For weak replication, which is the main topic of this paper, in order to determine the target payoff, the investor has to find or choose the distribution function of the target index or custom index, as well as its dependence with other assets, and use a hedging technique. Therefore, the main tools for weak replication are modeling (estimation and goodness-of-fit) and optimal hedging. For example, an investor could wish to obtain Gaussian returns that are independent of some ETFs replicating the Nasdaq and S&P 500 indexes. In order to determine the dependence of the target and a given number of indexes, we introduce a new class of easily constructed models of conditional distributions called B-vines. We also propose to use a exible model to fit the distribution of the assets composing the portfolio and then hedge the portfolio in an optimal way. Examples are given to illustrate all the important steps required for the implementation of this new asset management methodology.

Energy-based assets are showing increased susceptibility to volatility arising out of geo-political, economic, climate and technological events. Given the economic importance of energy products, their market participants need to be able to access efficient strategies to effectively manage their exposures and reduce price risk. This chapter will outline the key futures-based hedging approaches that have been developed for managing energy price risk and evaluate their effectiveness. A key element of this analysis will be the breadth of assets considered. These include Crude and Refined Oil products, Natural Gas and wholesale Electricity markets. We find significant differences in the hedging effectiveness of the different energy markets. A key finding is that, Natural Gas and particularly Electricity futures are relatively ineffective as a risk management tool when compared with other energy assets.

We present arbitrage and risk arbitrage betting strategies for team jai alai. Most of the results generalize to other sports betting situations and some financial market applications. The arbitrage conditions are utility free. The risk arbitrage wagers use the Kelly expected log criterion.

Agricultural futures markets were the backbone of early futures trading and continue to play a vital role in today's global economy. For more than a century following the founding of the Chicago Board of Trade in 1848, the United States dominated the world's futures markets with agricultural commodities such as wheat, corn, oats, and soybeans. Today, the global agricultural futures markets include not only grains but also livestock such as cattle and hogs; dairy products such as milk, butter, and cheese; “soft” or tropical commodities such as cotton, coffee, sugar, and orange juice; and industrial products such as soybean oil, soybean meal, and lumber.