Knowledge that Transforms

Risk management methods based on Value-at-Risk estimate the lowest quantile of possible profits and losses over a fixed time horizon. To calculate this value there is a need to construct an approximation of the probabilistic distribution of P&L. One of the most popular techniques is based on an assumption that the portfolio value can be expressed as a deterministic function of some basic market parameters. Having a distribution of these parameters one can construct the distribution of the value function. The most popular method is delta approach. Here a first order expansion of the value function is used in order to approximate the distribution at the end of the period. Typically the time period is assumed short, in which case the changes in market parameters are distributed almost normally and under this linear approximation the value of the approximated portfolio is also normally distributed. Value-at-Risk methods based on a delta approximation can not take into account different forms of convexity. An appropriate solution to this problem is to consider a longer series expansion, for example the so-called delta-gamma approximation. However the delta-gamma approximation loses a very useful property of “delta only” approach ‐ linearity. This linearity property is very convenient computationally, since it guarantees that as soon as the market factors are distributed normally, the resulting changes in the portfolio value are also normally distributed. Denote by x a vector of n market parameters that can be easily measured and their historical distributions are known. For example stock prices, interest rates, exchange rates. Denoting the calendar time by t we can price a portfolio of assets V.t, x/. The Value-at-Risk measures the lowest 1% (sometimes 5%) quantile of the distribution of profits and losses of the fixed portfolio over a fixed time horizon (in banking for example 10 business days). The standard assumption of this measurement is that over a short time horizon the changes in the market factors 1x are normally distributed. If the value of the portfolio is linear in the market factors then the P&L distribution is normal as well and any quantile can be expressed analytically through its mean and standard deviation. However the assumption of linear dependence is often very restrictive, a higher order approximation is required to reflect convexity. Consider the value functionV.x,t/around the current market valuesx. As soon as the market changes are small and the function V smooth, we can use the Taylor expansion. However the variablex is stochastic. Thus instead of the standard series

Edwin J. Elton, Martin J. Gruber; Reflections on the Origins of the European Finance Association, European Finance Review, Volume 3, Issue 1, 1 January 199

Abstract This paper analyzes the relationship between a firm's capital structure and its information acquisition prior to capital budgeting decisions. It is found that low-growth industries can sustain a large number of levered firms. In these industries, leverage is negatively related to a firm's incentive to acquire information during the capital budgeting process. In contrast, high-growth industries only sustain a small number of levered firms. In these industries, levered firms acquire more information than all-equity financed firms. The model yields empirical predictions regarding the effects of leverage on the expected amount and the volatility of corporate investment.While leverage does not affect firm value, highly levered firms generate a more volatile cash flow than firms with low debt levels. JEL classification codes: G31, G32.

Abstract This article examines the contribution of hedging to firm value and the cost of hedging in a unified framework. Optimal hedging and firm value are explicitly linked to firm risk, the type of debt covenants and the relative priority of the hedging contract. It is shown that in some cases hedging is possible only if the counterparty to the forward contract also holds a significant portion of the debt. Also, the spread in the hedging contract reduces the optimal amount of hedging to less than the minimum-variance hedge ratio. Among other results this article elucidates why some firms hedge using forward contracts while other firms hedge in the futures markets, as well as why higher priority forward contracts are more efficient hedging vehicles. JEL Classification numbers: G13, G22 and G33.

Abstract This examines the predictability of short-horizon stock returns in the UK. We show that the subsequent return reversal of previous extreme performers is unlikely to be caused by either lead-lag effects or inventory imbalances, the most likely explanation being market overreaction. A market or trading based explanation is reinforced by the finding that these return reversals are asymmetric, being less significant after bad news. Further, we find that the lower transacting stocks exhibit the stronger return reversals, in direct contrast to both the existing US evidence and the implication that liquidity effects can explain the return reversals. JEL Classification: G10, G11, G12

Abstract This paper investigates the influence of Swiss firms' disclosure policy and of their financial analysts' coverage on stock price abnormal reactions to the publication of the annual reports. It first shows that, after controlling for the number of analysts, the absolute abnormal returns are significantly and positively affected by the rating measure used as a proxy of the informational quality of annual reports. It furthermore emphasises asymmetry in the relationship between stock price abnormal reactions and two informational variables, namely the quality of the firm's disclosure policy and its financial analysts' coverage. It appears that while positive abnormal returns are significantly and positively related to the rating variable, negative abnormal returns are only affected by the number of financial analysts. The inverse relationship between abnormal negative returns and the financial analysts' coverage supports the fact that competition among analysts reduces investors' adverse selection problem. Finally, the study evidences a non-linear relationship between rating and positive abnormal returns which is meaningful for the “good” and “very good type” firms and thus emphasises the signaling role played by a firm's financial disclosure policy.

This paper considers a problem of security design in the presence of monitoring done by a large investor to discipline the management of a firm. Since the large investor enjoys only part of the benefits generated by her monitoring activities but incurs all the associated costs, the design and amount of security need to be structured so as to motivate her to maintain an efficient level of monitoring, if no other mechanism exists to make her commit to specific levels of monitoring in advance. By assuming that the large investor takes account of the effect of the issued amount of security on the revenues received, we show that the optimal security is a debt-like security such as standard debt with a positive probability of default, or debt with call options. We also verify that the financial market equilibrium is constrained Pareto optimal.

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.

Abstract 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. JEL Classification: G13

Abstract 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.