Knowledge that Transforms

The paper by B. Chowdhry and J. Howe examines if production delocalization can play a useful role for corporate exchange rate risk management. Such “operational hedging” transfers the production costs into the foreign currency area and may thus reduce the operating exposure of a firm. The authors claim that operational hedging emerges only if a firm faces a combination of exchange rate and demand uncertainty. Exchange rate uncertainty alone cannot justify production delocalization because it can be hedged with foreign exchange instruments. Only the interaction of exchange rate risk with demand uncertainty can justify delocalization to the extend that market incompleteness prevents insurance of demand risk. The authors derive their conclusions from ad hoc assumptions which lack proper microfoundations. They concede this flaw in a short note on page 4 without fixing it. Two assumptions are in contradiction to microeconomic principles: First, the authors assume that local prices of a multinational firm are fixed in advance and do not change for any given exchange rate change. Second, they assume that the quantity sold in each market and the exchange rate are independent variables. Both assumptions present a dubious starting point and need to be rectified. The following section tries to clean up their model setting. Thereafter, I proceed to the central claim of the paper about the necessity of both demand and exchange rate uncertainty for delocalizations. It turns out this claim cannot be sustained if firm pricing behavior is properly modeled.

In this paper, we reexamine and extend the stochastic volatility model of Stein and Stein (S&S) (1991) where volatility follows a mean–reverting Ornstein–Uhlenbeck process. Using Fourier inversion techniques we are able to allow for correlation between instantaneous volatilities and the underlying stock returns. A closed-form pricing solution for European options is derived and some numerical examples are given. In addition, we discuss the boundary behaviour of the instantaneous volatility at v(t) = 0 and show that S&S do not work with an absolute value process of volatility.

This paper argues that in the fundamental subject of financial risk analysis, some valuable lessons may be drawn from insurance. The probability of ruin, defined as a first passage time, carries a dynamic element whose absence in Value at Risk is one liability, among others. Extreme value theory, which has been successfully applied to insurance shortly after it was introduced in probability, may offer a coherent framework for analyzing the extreme moves such as the ones observed in recent foreign exchange and financial crises. Lastly, we show that the genuine hazards generated by global capital markets and illustrated by the events of summer 1998, generate a market incompleteness that existing models of defaultable bonds do not fully address. In contrast, the long experience of risk premium analysis in the insurance and reinsurance industry, as well as the existence of historical data on natural disasters, render the valuation of catastrophe bonds less perilous than that of defaultable bonds.

Comment on ‘Valuation of Barrier Options in a Black–Scholes Setup with Jump Risk’ Hans-Peter Bermin Hans-Peter Bermin Search for other works by this author on: Oxford Academic Google Scholar Review of Finance, Volume 3, Issue 3, 1999, Pages 343–345, https://doi.org/10.1023/A:1009865221699 Published: 01 December 1999

The pricing of derivative securities in the presence of market frictions has always been a question of fundamental importance. The reason is twofold: market frictions are present in numerous practical applications and, in such settings, the classical valuation theories break down entirely. Examples of market frictions include among others, transaction costs, non-traded assets and portfolio constraints. Alternative valuation criteria have been proposed and a variety of methods have been developed in order to define coherent derivative prices and, ultimately, to specify the hedging strategies. Three main valuation methods have been developed up to date: the superreplication approach, the imperfect-replication method and the utility maximization theory. The super-replication approach looks for hedging strategies that super-replicate, instead of replicating exactly, the payoff of the derivative security. The motivation for such a pricing mechanism comes from the fact that exact replication might result in an infinite derivative price, like for example in the presence of transaction costs (Soner et al., 1995). The imperfect replication method allows

Many evaluation techniques typically measure performance as deviations of average returns on actively managed funds from those predicted by some asset pricing model. Empirical evidence, however, has so far suggested that all asset pricing models lack empirical support, implying that the models contain mis-specification errors to various degrees. Evaluating mutual fund performance relative to any of these models thus becomes problematic. In this paper, we propose an approach to performance measurement that emphasizes minimizing explicitly the pricing error associated with an asset pricing function which is employed to compute performance measures. This approach is henceforth called the minimum specification-error (MSE) method. We also discuss the statistical properties for implementing MSE performance measure. To demonstrate the significance of the pricing error confounded in evaluation measurement, we contrast our methodology with the Grinblatt and Titman (1989) period weighting approach and with the empirical implementation of Chen and Knez (1996). We find that the greater the pricing error of passive assets, the larger the performance measures. Given the average pricing error generated from a collection of 163 diverse passive portfolios used in this analysis the performance values assigned to a large number of the funds become statistically and economically insignificant.

We study a financial market containing an infinite number of assets, where each asset price is driven by an idiosyncratic random source as well as by a systematic noise term. Introducing ”asymptotic assets“ which correspond to certain infinitely well diversified portfolios we study absence of (asymptotic) arbitrage, and in this context we obtain continuous time extensions of atemporal APT results. We also study completeness and derivative pricing, showing that the possibility of forming infinitely well diversified portfolios has the property of completing the market. It also turns out that models where the all risk is of diffusion type are qualitatively quite different from models where one risk is of diffusion type and the other is of Poisson type. We also present a simple martingale based theory for absence of asymptotic arbitrage.

The model of Foster-Viswanathan (1990, FV) predicts that information heterogeneity among market participants generates patterns in volume, trading costs and volatility. In the Italian Treasury bond market, periodic information asymmetry is related to the arrival of block orders from international investors, which cluster soon after the opening of the market and, respectively, of the US market. Our evidence is that volume is lower and trading costs are higher after the two openings, consistent with FV. We find only weak evidence that volatility behaves as implied by the model.

This paper analyzes the effect of uncertainty about the mean return on the risky asset on the portfolio decisions of an investor who has a long investment horizon. Building on the earlier work of Detemple (1986), Dothan and Feldman (1986), and Gennotte (1986), it is shown that the possibility of future learning about the mean return on the risky asset induces the investor to take a larger or smaller position in the risky asset than she would if there were no learning, the direction of the effect depending on whether the investor is more or less risk tolerant than the logarithmic investor whose portfolio decisions are unaffected by the possibility of future learning. Numerical calculations show that uncertainty about the mean return on the market portfolio has a significant effect on the portfolio decision of an investor with a 20 year horizon if her assessment of the market risk premium is based solely on the Ibbotson and Sinquefield (1995) data.