Knowledge that Transforms

The objective of this paper is to estimate the cost components of the bid–ask spread on the London Stock Exchange using intraday data. The findings are unambiguous in isolating the three cost components of quoted spreads. They are, therefore, consistent with the earlier work of Stoll based on the quote driven Nasdaq market (Stoll, H., 1989. Journal of Finance 44, 753–776). Additionally, the three spread components vary with the liquidity of the stocks measured by the minimum number of shares market makers are obliged to trade.

This paper derives the optimal size of the financial sector using a general equilibrium framework that is an extension of the paper of Holmstrom and Tirole (1997) [Quarterly Journal of Economics 112, 663–691]. We show that the financial sector has a unique optimal size relative to the size of the economy as a whole. Creating and maintaining this sector requires diversion of some physical capital from production of output to monitoring that production. However, the efficiency gain in output production brought about by monitoring warrants the diversion. It is also found that the optimal size of the financial sector is independent of the state of the economy and does not vary over the business cycle.

This paper proposes an unobserved fundamental component of volatility as a measure of risk. This concept of fundamental volatility may be more meaningful than the usual measures of volatility for market regulators. Fundamental volatility can be obtained using a stochastic volatility model, which allows us to `filter’ out the signal in the volatility information. We decompose four FTSE100 stock index related volatilities into transitory noise and unobserved fundamental volatility. Our analysis is applied to the question as to whether derivative markets destabilise asset markets. We find that introducing European options reduces fundamental volatility, while transitory noise in the underlying and futures markets does not show significant changes. We conclude that, for the FTSE100 index, introducing a new options market has stabilised both the underlying market and existing derivative markets.

Internal credit risk rating systems are becoming an increasingly important element of large commercial banks’ measurement and management of the credit risk of both individual exposures and portfolios. This article describes the internal rating systems presently in use at the 50 largest US banking organizations. We use the diversity of current practice to illuminate the relationships between uses of ratings, different options for rating system design, and the effectiveness of internal rating systems. Growing stresses on rating systems make an understanding of such relationships important for both banks and regulators.

We find empirical evidence that inflation, nominal, and real interest rates in the US are trend-stationary with a structural break in both the unconditional mean and the drift rate of a deterministic trend, which occurs shortly after the change in operating procedures of the Fed in September 1979. This finding casts some doubts on cointegration tests of the long-run Fisher effect conducted in recent studies, since the results of these tests can be affected by the existence of common structural breaks in the series. We propose an alternative test of the Fisher effect, based on a VAR representation in appropriately detrended variables. We find strong support for the Fisher effect both in the medium term and in the long term.

The distribution of ratings changes plays a crucial role in many credit risk models. As is well-known, these distributions vary across time and different issuer types. Ignoring such dependencies may lead to inaccurate assessments of credit risk. In this paper, we quantify the dependence of rating transition probabilities on the industry and domicile of the obligor, and on the stage of the business cycle. Employing ordered probit models, we identify the incremental impact of these factors. Our approach gives a clearer picture of which conditioning factors are important than comparing transition matrices estimated from different sub-samples.

Motivated by recent regulatory changes, this study investigates the degree of integration in retail lending in six core European Union (EU) countries using co-integration methodology which allows to investigate the presence and effects of structural breaks. While in the pre-break period we could detect integration to a limited degree, the evidence for integration weakened in the post-1992 period. This could however reflect a convergence process, particularly with respect to spreads. This result is clearly a regional, not a global phenomenon. As European lending rates are not yet fully integrated, the still segmented financial markets pose a challenge for a unified monetary policy.

In implementing a variance-minimizing cross or delta hedge, the regression coefficient is often estimated using data from the past, but one could also use estimators that are suggested by the random-walk or unbiased-expectations models and require just a single price. We compare the performances of various hedge ratios for three-month currency exposures, and find that the price-based hedge ratios generally perform better than the regression-based ones. Specifically, all our regressions do systematically worse in the case of a delta hedge, and seem to beat the price-based hedge ratios only in the case of cross- or cross-and-delta problems where the two currencies are so distantly related – like, e.g., hedging ITL/USD using JPY/USD – that no risk manager would even consider them as hedges of each other. The poor performance of the regressions is all the more surprising as we correct the futures prices for errors-in-variables (synchronization noise, bid–ask bounce, and changing time to maturity). The results are robust to observation frequency in the regressions, sample period, percentage vs dollar returns, and OLS versus IV. One reason why price-based methods do better is that they provide immediate adjustment to breaks in the data (like EMS realignments, which get incorporated into rolling regression coefficients only very slowly, as time elapses) or other events that change the relationship between the regressor and regressand. For cross or cross-and-delta hedges between European currencies, regressions also have difficulties in capturing cross-correlations between exchange rates.

Within the past two years, important advances have been made in modeling credit risk at the portfolio level. Practitioners and policy makers have invested in implementing and exploring a variety of new models individually. Less progress has been made, however, with comparative analyses. Direct comparison often is not straightforward, because the different models may be presented within rather different mathematical frameworks. This paper offers a comparative anatomy of two especially influential benchmarks for credit risk models, the RiskMetrics Group's CreditMetrics and Credit Suisse Financial Product's CreditRisk+. We show that, despite differences on the surface, the underlying mathematical structures are similar. The structural parallels provide intuition for the relationship between the two models and allow us to describe quite precisely where the models differ in functional form, distributional assumptions, and reliance on approximation formulae. We then design simulation exercises which evaluate the effect of each of these differences individually.

We examine the investment behavior of market participants within different international markets (i.e., US, Hong Kong, Japan, South Korea, and Taiwan), specifically with regard to their tendency to exhibit herd behavior. We find no evidence of herding on the part of market participants in the US and Hong Kong and partial evidence of herding in Japan. However, for South Korea and Taiwan, the two emerging markets in our sample, we document significant evidence of herding. The results are robust across various size-based portfolios and over time. Furthermore, macroeconomic information rather than firm-specific information tends to have a more significant impact on investor behavior in markets which exhibit herding. In all five markets, the rate of increase in security return dispersion as a function of the aggregate market return is higher in up market, relative to down market days. This is consistent with the directional asymmetry documented by McQueen et al. (1996) (McQueen, G., Pinegar, M.A., Thorley, S., 1996. Journal of Finance 51, 889–919).