Knowledge that Transforms

We studied repeated acquirers in Federal Deposit Insurance Corporation (FDIC) assisted acquisitions. Using a sample of 128 FDIC assisted acquisitions and 387 non-assisted acquisitions, we found that FDIC assisted acquirers, on average, produced positive abnormal returns. This result was driven by repeated acquirers. First-time acquirers did not profit in these assisted acquisitions. In a logit analysis, we found that the FDIC repeated acquirer improved its profiting chances by reducing the winning bid and the number of bids. This evidence is consistent with the suggested experience/information effect based on theory and FDIC practices.

The US economy experienced major regulatory changes in the banking and finance industry with the passage of five major acts over the period 1980 to 1991. This has generated an extensive literature investigating the effects of these changes on the US banking industry. In particular, this body of research has examined the share market reaction to regulatory changes, as well as their impact on the risk, return, market value and profitability of banking industry stocks. Generally, it has been found that the regulatory changes have had a substantial impact, although the effect has not been uniform across all depository institutions. This paper extends this literature by analysing the stability of a sample of eighteen US banking industry stock betas across five periods: a pre-regulatory change period, a monetary experiment period, a deregulation period, a reregulation period and a post-regulatory change period. Based on an analysis of weekly returns, we find that the level of bank risk has increased. Further, we also find a tendency towards greater beta instability in both the monetary experiment and deregulation samples. The degree of beta instability is lowest in the pre-regulatory change and post-regulatory change samples. Overall the monetary experiment and regulatory change coincided with an increased tendency towards beta instability. We also compare our results to a randomly selected control sample of non-banks and find some more general effects of regulatory change on individual stock betas.

This paper explores the determinants of optimal bank interest margins based on a simple firm-theoretical model under multiple sources of uncertainty and risk aversion. The model demonstrates how cost, regulation, credit risk and interest rate risk conditions jointly determine the optimal bank interest margin decision. We find that the bank interest margin is positively related to the bank's market power, to the operating costs, to the degree of credit risk, and to the degree of interest rate risk. An increase in the bank's equity capital has a negative effect on the spread when the bank faces little interest rate risk. The effect of rising interbank market rate on the spread is ambiguous and depends on the net position of the bank in the interbank market. Our findings provide alternative explanations for the empirical evidence concerning bank spread behavior.

We test both the unconditional and conditional Mean Variance Efficiency of the UK stockmarket, paying particular attention to choosing a suitable set of instruments for the conditional version of the model. By considering more carefully than previous authors the pricing of economic risk within the mean-variance framework we show that certain instruments can enhance the basic model structure. Given the tendency for financial market data to display non-constancy in variance and non-normality we employ the GMM procedure described in Hansen (1982), which requires much weaker distributional assumptions than the more traditional OLS techniques. We discuss forming portfolios of stocks using both size and dividend yield as a criterion to achieve a suitable spread of risk and return, and find that our conclusions are sensitive both to the method of portfolio formation and to the choice of estimator. This is an important finding given the problem of thin trading associated with the size ordering of UK stocks. We find some support for both the unconditional and conditional version of the CAPM, though we are cautious about our conclusions given the instability of the parameter estimates.

Two classes of models for pricing interest rate contingent claims are compared. The first contains standard single factor models, while the second includes stochastic volatility variants of these. It is demonstrated that incorporating stochastic volatility significantly improves the ability of the models to fit movements in short term interest rates. The fundamental reason for this is that standard univariate models do not generate enough conditional heteroskedasticity. The models are also compared on the basis of bond option prices when each is constrained to fit a particular yield curve. The results suggest that stochastic volatility models will typically produce lower option values than corresponding single factor models, particularly for near-the-money to deep-out-of-the-money options. This is because estimated historical volatilities are significantly lower under stochastic volatility. When single factor models are constrained to the same level of volatility as implied by stochastic volatility models, in most cases the pricing differences become minor.

This is a critical evaluation of the state of the art in International Finance. Several points of reference are selected: The Mundell–Fleming–Branson (MFP) paradigm, the monetary model with purchasing power parity (PPP) as a long run anchor, the representative agent approach and the natural real exchange rate (NATREX) model. Their strengths and weaknesses are identified from both a theoretical and empirical point of view. We conclude with a suggestion of what is a fruitful explanation of medium to longer run movements in the real exchange rate and the current account.

In this paper, we examine the role that institutions may play in enabling banks to write contracts whereby sovereign debt is not forgiven ex post. Our model provides a rationale for the emergence of a centralized forum for debt renegotiation, such as the London Club, as well as for bank syndicates. These bank syndicates arise as part of a pre-commitment device rather than for risk sharing purposes. We propose a debt contract under which only involuntary default is forgiven ex post. Our main findings are that under this contract, debt forgiveness after voluntary (strategic) default is avoided. When voluntary default occurs, access to the credit market is denied only for a limited number of periods, rather than forever. In contrast to a voluntary default, involuntary default is forgiven immediately.

When should regulators close a financially ailing bank? FDIC practice in the US has moved in the direction of early closure. In contrast, banking regulators in Japan continue to follow a more patient approach. This paper analyses a series of models in which closure rules and bailout policies arise endogenously through the interaction of (i) regulators' attempts to minimize discounted, expected bankruptcy costs, and (ii) equity-holders' incentives to recapitalise banks. We characterize subsidy policies for distressed banks that implement socially optimal closure rules at minimum financial cost to regulators and which reduce moral hazard.

This article applies finite mixture distributions to the estimation of cost functions for financial firms through time. The mixture approach allows the estimation of multiple technologies when firms' technology choices are unobservable. Technology switching (‘diffusion’) and underlying technical change are simultaneously evaluated. An application to large samples of U.S. banks for the years 1982–1986 illustrates the approach. Results suggest banks switch to lower cost production technologies when unburdened by strict branching regulations.