Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices

The correlation matrix of security returns is an important input component for mean–variance portfolio analysis. This study uses the average of sample correlations to estimate the correlation matrix and derives an expression of its estimation error in terms of sampling variance. This study then considers the impact of such estimation error on shrinkage estimation, where a weighted average is sought between the sample covariance matrix and an average correlation target, and between the sample correlation matrix and the target. An illustrative example using monthly returns of the current Dow Jones stocks is provided.     

Equilibrium asset pricing: with non-Gaussian factors and exponential utilities

We analyse the equilibrium asset pricing implications for an economy with single period return exposures to explicit non-Gaussian systematic factors, that may be both skewed and long-tailed, and Gaussian idiosyncratic components. Investors maximize expected exponential utility and equilibrium factor prices are shown to reflect exponentially tilted prices for non-Gaussian factor risk exposures. It is shown that these prices may be directly estimated from the univariate probability law of the factor exposure, given an estimate of average risk aversion in the economy. In addition, a residual form of the capital asset pricing model continues to hold and prices the idiosyncratic or Gaussian risks. The theory is illustrated on data for the US economy using independent components analysis to identify the factors and the variance gamma model to describe the probability law of the non-Gaussian factors. It is shown that the residual CAPM accounts for no more than 1% of the pricing of risky assets, while the exponentially tilted systematic factor risk exposures account for the bulk of risky asset pricing.     

Disagreement and Biases in Inflation Expectations

Disagreement in inflation expectations observed from survey data varies systematically over time in a way that reflects the level and variance of current inflation. This paper offers a simple explanation for these facts based on asymmetries in the forecasters' costs of over- and underpredicting inflation. Our model implies (i) biased forecasts, (ii) positive serial correlation in forecast errors, (iii) a cross-sectional dispersion that rises with the level and the variance of the inflation rate, and (iv) predictability of forecast errors at different horizons by means of the spread between the short- and long-term variance of inflation. We find empirically that these patterns are present in inflation forecasts from the Survey of Professional Forecasters. A constant bias component, not explained by asymmetric loss and rational expectations, is required to explain the shift in the sign of the bias observed for a substantial portion of forecasters around 1982.     

The impact of variance estimation in option valuation models

This paper examines some implications of using an estimate of the variance in option valuation models. This procedure produces biased option values. It is shown that the magnitude of this bias is not large. The dispersion induced in the option price is more significant particularly for parameter values of practical interest. The nature and extent of this dispersion is examined by numerical examples. The paper suggests how a Bayesian approach could be used to cope with the estimation error.     

Resolving the exposure puzzle: The many facets of exchange rate exposure

Theory predicts sizeable exchange rate (FX) exposure for many firms. However, empirical research has not documented such exposures. To examine this discrepancy, we extend prior theoretical results to model a global firm's FX exposure and show empirically that firms pass through part of currency changes to customers and utilize both operational and financial hedges. For a typical sample firm, pass-through and operational hedging each reduce exposure by 10–15%. Financial hedging with foreign debt, and to a lesser extent FX derivatives, decreases exposure by about 40%. The combination of these factors reduces FX exposures to observed levels.     

Private sector share of external debt and financial stability: Evidence from bank loans

In the last two decades, the private sector has contracted a substantially larger share in the total amount of foreign-currency international debt (private sector share of external debt), especially in developing countries. In this paper, I empirically examine the effect of this phenomenon on bank loan prices. I find that the private sector share of external debt negatively and significantly impacts the price of bank loans. This result supports the hypothesis that private sector debt contributes to international financial stability to a greater degree than sovereign debt. Nevertheless, this impact is canceled out in the presence of fixed exchange regimes that are unsuitable with respect to fundamentals. In such circumstances, the private sector may take advantage of capital market distortions that are maintained by official authorities and thus exposes the country to further financial instability. Additional results corroborate the observation that the gain in financial stability stems from more efficient use of funds and reduced monitoring costs.     

Foreign exchange exposure of “domestic” corporations

Unlike prior studies on foreign exchange risk that have focused on multinational companies, this paper documents that domestic companies face significant foreign exchange exposure. Indeed, we document that on average domestic company foreign exchange exposure is not significantly different from the exposures faced by multinational firms. As expected, the number of domestic firms with significant foreign exchange exposure increases with the exposure estimation horizon. More interestingly, the level of domestic firm exposure is significantly negatively related to firm size and asset turnover, and positively related to the market to book ratio and financial leverage. Our results have important implications for managers, policy makers, and accounting standards.     

The World Price of Covariance Risk

In a financially integrated global market, the conditionally expected return on a portfolio of securities from a particular country is determined by the country's world risk exposure. This paper measures the conditional risk of 17 countries. The reward per unit of risk is the world price of covariance risk. Although the tests provide evidence on the conditional mean variance efficiency of the benchmark portfolio, the results show that countries' risk exposures help explain differences in performance. Evidence is also presented which indicates that these risk exposures change through time and that the world price of covariance risk is not constant.     

Modeling time variation and asymmetry in foreign exchange exposure

Many recent studies suggest that exchange rate exposure is unstable over time and exhibits asymmetric behavior during currency appreciations and depreciations. This paper proposes a dynamic framework for the study of such questions and our empirical findings show that exchange rate exposure of U.S. stocks is time varying. Using decile and sector portfolios, we find asymmetric exposure to be pervasive across the decile portfolios as well as the financial and industrial sectors. Moreover, the response of return variance to past innovations is asymmetric for the majority of cases. The dynamic exchange rate exposure parameters are found to be mean-reverting with low persistence, generally ranging from 1 to less than 2 days. The average time-varying exposure is statistically significant for the size-based and sector-based portfolios. Lastly, the variability in the time-varying exposure is smaller (larger) for the largest (smallest) firms and for industrial (technology) firms.     

Shadow banking,insurance and financial sector stability

Motivated by the recent financial crisis and the near collapse of the insurance giant American International Group (AIG), we empirically study the link between the insurance sector, the size of the shadow system and financial stability across countries. Using the Z-score as a measure of financial stability and the ratio of insurance assets to GDP for 26 countries during the period 1998–2011, this paper shows that: (i) the insurance sector is negatively and significantly related to financial stability, and that (ii) using the shadow banking system as a channel, the insurance sector is detrimental to financial stability for countries with a high level of shadow banking assets.     

Testing the expectations hypothesis of the term structure with permanent-transitory component models

This study proposes a new application of Permanent-Transitory Component Models (PTCMs) to test the Expectation Hypothesis of the Term Structure (EHTS). Unlike previous approaches, tests based on PTCMs can simultaneously detect departures from rational expectations and time varying term premia. We set out analytically and empirically the links across previous tests and PTCMs. We also show that PTCMs identify an additional restriction for rational expectations, on top of the one-to-one relationship between forward and spot rates, that must be imposed in estimations of term premia. Data for the short-end of the US term structure suggest that both factors contribute to the rejection of the EHTS. Moreover, the empirical estimates of term premia are persistent and exhibit sign fluctuations. Their stochastic properties depend crucially on whether the additional restriction for rational expectations is imposed in estimation.     

Home Bias in Emerging Bond and Stock Markets

In this paper, we empirically examine sizes and sources of home bias in both bond and equity markets for twenty emerging countries and twenty-two developed countries over the 2001-11 sample period. The average size of home bias in both bond and stock markets is found to be much larger in emerging countries than in developed countries. Using the explanatory variables in two categories of economic development and market performance, we employ dynamic panel data regression models to analyze major sources of home bias. The main results are the following: First, market performance factors generally affect home bias more strongly than do economic development factors. Second, market factors including market return, volatility, and liquidity support various hypotheses under informational asymmetries, such as return chasing, risk aversion, and flight to quality. Third, among macroeconomic factors, it is shown that real gross domestic product growth has negative effects and country leverage has positive effects on a specific home bias, backing up the size-bias and the flight-to-quality hypotheses, respectively. Finally, and perhaps most important in this paper, the effect of bond market performance on equity home bias is found to be significantly stronger than the effect of equity market performance on bond home bias from the market interaction model estimation, suggesting that a policy design needs to begin with increasing bond market efficiency to reduce equity market home bias.     

Measuring systemic importance of financial institutions: An extreme value theory approach

This paper proposes a set of market-based measures on the systemic importance of a financial institution or a group of financial institutions, each designed to capture different aspects of systemic importance of financial institutions. Multivariate extreme value theory approach is used to estimate these measures. Using six big Canadian banks as the proxy for Canadian banking sector, we apply these measures to identify systemically important banks in Canadian banking sector and major risk contributors from international financial institutions to Canadian banking sector. The empirical evidence reveals that (i) the top three banks, RBC Financial Group, TD Bank Financial Group, and Scotiabank, are more systemically important than other banks, while we also find that the size of a financial institution should not be considered as a proxy of systemic importance; (ii) compared to the European and Asian banks, the crashes of the U.S. banks, on average, are the most damaging to Canadian banking sector, while the risk contribution to the Canadian banking sector from Asian banks is quite lower than that from banks in the U.S. and euro area; (iii) the risk contribution to Canadian banking sector exhibits “home bias”, that is, cross-country risk contribution tends to be smaller than domestic risk contribution.     

An Empirical Analysis of Financial and Non-financial Managers' Remuneration in Small and Medium-sized UK Enterprises

This paper examines empirically the influences on managerial remuneration in a sample of 97 UK small and medium-sized enterprises (SMEs). The empirical analysis, based on data obtained from interviews with middle (i.e. non-director level) managers and the published financial records of their employing firms lodged at Companies House, examines the relative explanatory power of a number of human capital, job/firm specific and external labour market variables. In addition, the sample was partitioned into two groups, one comprising 29 financial managers and the other comprising 68 non-financial managers. Separate wage equations were estimated for the two groups to determine whether the factors that influence remuneration differ between the two groups of managers. For the overall sample, the results indicate that the managers' ages, qualifications and previous careers and the size, growth, industry and location of their employing firms are able to explain a large proportion of the variance in remuneration. For the sub-sample analyses, firm profitability, (several aspects of) size, and the managers' career histories are of relatively greater importance in respect of financial managers' remuneration, whilst asset growth, industrial sector and location seem to be of more importance for the non-financial managers. These results are viewed as being broadly consistent with the expectations derived from the extant theoretical and empirical literatures on managerial remuneration.     

Discriminating between wealth and information effects in event studies in accounting and finance research

This article examines the power of tests of given size to detect and distinguish between wealth (i.e., mean) and information (i.e., variance) effects in event studies. We find that an Estimated Generalized Least Squares (EGLS) mean-effects test is consistently more powerful than the test based upon the average standardized residual and is as powerful as a nonparametric rank test. Unlike the test based upon the average standardized residual and the rank test, the EGLS test is well specified even when the event affects the variances of the prediction errors. We also find that conventional parametric tests to detect changes in the variance of the event-day average abnormal return are misspecified when the null of no change is true. We analyze the reasons this occurs and suggest a rank procedure that produces tests of the correct size under the null. Our evidence suggests that the critical factors allowing researchers to distinguish between wealth and information effects are an estimation procedure incorporating the heteroskedasticity inherent in market model prediction errors and an explicit test for event-day variance changes.     

Factor decomposition and diversification in European corporate bond markets

In this paper we present an analysis of diversification strategies on portfolios of European corporate bonds. From the perspective of a US-based investor we study whether mean–variance diversification strategies change as a result of the introduction of the European Economic and Monetary Union (EMU). Using a comprehensive and unique data set of European corporate bonds we show that country factors are more important than industry factors to describe the cross-section of European corporate bonds. In particular we find that in the Post-EMU period country factors remain important.     

Does sovereign risk matter? New evidence from eurozone corporate bond ratings and zero-volatility spreads

In this paper, we empirically examine if sovereign risk matters for corporate bonds in developed economies. Using a unique panel data sample of 897 corporate bonds from eleven countries within the Economic and Monetary Union (EMU), we investigate sovereign and corporate ratings as well as zero-volatility spreads (z-spreads). In the time period from March 2006 to June 2012, we find sovereign risk to be a significant driver of corporate risk. The effect is stronger for companies with domestic revenue structure, for companies that are (partly) owned by the government, and companies active in the utility and transportation sector. Interestingly, the impact of sovereign risk on corporate risk during the acute European sovereign debt crisis period decreases if ratings are examined, but increases if z-spreads are utilized. Rating agencies seem to take a more differentiated view on individual company risk during the sovereign debt crisis, while institutional investors might want to reduce their exposure to a country in financial distress as a whole, regardless of whether sovereign or corporate bonds are held.     

Oil Risk Exposure: The Case of the U.S. Oil and Gas Sector

We estimate oil price risk exposures of the U.S. oil and gas sector using the Fama‐French‐Carhart's four‐factor asset pricing model augmented with oil price and interest rate factors. Results show that the market, book‐to‐market, and size factors, as well as momentum characteristics of stocks and changes in oil prices are significant determinants of returns for the sector. Oil price risk exposures of U.S. oil and gas companies in the oil and gas sector are generally positive and significant. Our study also finds that oil price risk exposures vary considerably over time, and across firms and industry subsectors.     

Mandatory CSR disclosure and analyst forecast properties: Evidence from a quasi-natural experiment in China

Based on a quasi-natural experiment that mandates a subset of listed firms to issue standalone corporate social responsibility (CSR) reports, we examine whether mandatory CSR disclosure improves analysts’ information environment. We focus on two properties of analysts’ earnings forecasts: forecast error and forecast dispersion. We find that the mandatory issuance of standalone CSR reports is related to less forecast error and less dispersed forecasts, and the effect varies with the firm-level information environment and province-level marketization. Additional tests show that the improvement in forecast properties is mainly driven by CSR reports that i) are of high quality and ii) contain more long-term-oriented information than other CSR reports. Our findings provide evidence that mandatory CSR disclosure plays an important informational role for financial analysts.     

Do we need higher-order comoments to enhance mean-variance portfolios? Evidence from a simplified jump process

We consider a joint distribution that decomposes asset returns into two independent components: an elliptical innovation (Gaussian) and a systematic non-elliptical latent process. The paper provides a tractable approach to estimate the underlying parameters and, hence, the assets’ exposures to the latent non-elliptical factor. Additionally, the framework incorporates higher-order moments, such as skewness and kurtosis, for portfolio selection. Taking into account estimation risk, we investigate the economic contribution of the non-elliptical term. Overall, we find weak empirical evidence to support the inclusion of the non-elliptical term and, hence, the higher-order comoments. Nonetheless, our findings support the mean–variance (MV) decision rule that incorporates the elliptical term alone. Excluding the non-elliptical term results in more robust mean–variance estimates and, thus, enhanced out-of-sample performance. This evidence is significant among stocks that exhibit a strong deviation from the Gaussian property. Moreover, it is most pronounced during market turmoils, when exposures to the latent factor are highest.