On the estimation of stock-market reaction to corporate layoff announcements

This study investigates the stock-market reaction to layoff announcements where more than 1000 workers are affected. We employ a dummy variable regression (DVR) version of the market model and compare the results obtained using ordinary least squares (OLS) versus exponential GARCH (EGARCH), and value-weighted (VW) versus equally weighted (EW) market index. We find that the stock market responds negatively to layoffs attributed to low demand. We also find that contrary to prior research, the market reacts positively to restructuring-related layoffs on the announcement date. This pattern of market reaction is observed regardless of the market index used or the parameter estimation methods employed, although the empirical results indicate that using EGARCH/VW market index tends to generate fewer statistically significant test results and smaller (in the absolute size of the cumulative) abnormal returns (ARs). Taken together, our study provides additional support for the claim that studies of stock-market reaction to corporate events must account for the time variation in return volatility. Ignoring these could result in erroneous inferences.     

Multifactor risk loadings and abnormal returns under uncertainty and learning

We explore the time variation of factor loadings and abnormal returns in the context of a four-factor model. Our methodology, based on an application of the Kalman filter and on endogenous uncertainty, overcomes several limitations of competing approaches used in the literature. Besides taking learning into account, it does not rely on any conditioning information, and it only imposes minimal assumptions on the time variation of the parameters. Our estimates capture both short- and long-term fluctuations of risk loadings and abnormal returns, also showing marked variation across US industry portfolios. The results from mean-variance spanning tests indicate that our baseline model yields accurate predictions and can therefore improve pricing and performance measurement.     

Beta and firm age

We document a robust pattern of beta declining over the age of a firm. We find that changes in systematic risk via firm characteristics and life-cycle stages are insufficient to explain this pattern. Moreover, standard proxies for the quantity and quality of information also explain this pattern only partially. To fully explain this pattern we rely on the increasingly important role of familiarity in financial decision making: familiarity is a determinant of beta and firm age is a proxy for the degree of familiarity that investors feel toward individual stocks. To illustrate the implication of our findings, we document that when we control for firm age there is support for the CAPM and its use as an input for the cost of equity capital calculation.     

A new approach to measuring riskiness in the equity market: Implications for the risk premium

We introduce a new approach to measuring riskiness in the equity market. We propose option implied and physical measures of riskiness and investigate their performance in predicting future market returns. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P 500 index option implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic variables. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.     

Oil commodity returns and macroeconomic factors: A time-varying approach

This paper analyses the dynamic influence of macroeconomic factors on oil commodity returns (crude oil and heating oil) shown in monthly data over the period of 1990–2013. Using a time-varying parameter model via the Kalman filter, we find that macroeconomic factors are relevant for explaining oil commodity returns. We find that multilateral exchange rates have a negative effect on commodity returns. We confirm the existence of a strong linkage between energy and non-energy commodities. More importantly, we find shifts in global demand and SP500 effects that are not identified through the constant parameter model. These variables have had a progressively positive effect on oil commodity returns, especially since 2008.     

Currency unions and trade: A post-EMU reassessment

In our European Economic Review (2002) paper, we used pre-1998 data on countries participating in and leaving currency unions to estimate the effect of currency unions on trade using (then-) conventional gravity models. In this paper, we use a variety of empirical gravity models to estimate the currency union effect on trade and exports, using recent data which includes the European Economic and Monetary Union (EMU). We have three findings. First, our assumption of symmetry between the effects of entering and leaving a currency union seems reasonable in the data. Second, our preferred methodology indicates that EMU has boosted exports by around 50%. While other estimation techniques yield different results, a panel approach with both time-varying country and dyadic fixed effects on a large span of data (across both countries and time) seems to deliver insensitive and reliable results. Third, different currency unions have different trade effects.     

A stochastic cost efficiency analysis of international tourist hotels in Taiwan

The one-stage stochastic frontier approach (SFA) is used in this study to simultaneously estimate cost efficiency scores and factors of cost inefficiency for 66 international tourist hotels in Taiwan during 1997–2006. An SFA model with three outputs and three inputs is defined. The three outputs are room revenue, food and beverage revenue, and other operation revenue while the three inputs are price of labor, price of other operation, and price of food and beverage. This model also takes into account five environmental variables, including dummy variable of the hotels located in non-metropolitan area, dummy variable of chain hotels, the number of tourist guides, the minimum distance from each hotel to Taoyuan international airport and the minimum distance from each hotel to Kaohsiung international airport. Empirical results show that international tourist hotels in Taiwan are on average operating at 91.15% cost efficiency. All nominal variables are transformed into real variables in 1997 prices by GDP deflators. Chain systems, tourist guides, and international transportation can significantly improve the cost efficiency of international tourist hotels in Taiwan.     

The expected real return to equity

The expected return to equity – typically measured as a historical average – is a key variable in the decision making of investors. A recent literature uses analysts' forecasts, investor surveys or present-value relationships and finds estimates of expected returns that are sometimes much lower than historical averages. This study extends the present-value approach to a dynamic optimizing framework. Given a model that captures this relationship, one can use data on dividends, earnings and valuations to infer the model-implied expected return. Using this method, the estimated expected real return to equity ranges from 4.9% to 5.6% . Furthermore, the analysis indicates that expected returns have declined by about 3 percentage points over the past 40 years. These results indicate that future returns to equity may be lower than past realized returns.     

The estimation and determinants of emerging market country risk and the dynamic conditional correlation GARCH model

Country risk assessment is central to the international investment, which recently has increasingly focused on emerging markets (EM). In this paper we proxy for country risk in EM by using time-varying beta. We extend existing literature by applying a dynamic conditional correlation GARCH model. After confirming beta is time varying in twenty EM over the period January 1995 to December 2008 we investigate the GARCH (1,1) model and find the t-distribution generates the lowest forecast errors compared to the normal error distribution and a generalised error distribution. In a comparison of previous modelling techniques the results of our modified Diebold-Mariano test statistics suggest that the Kalman Filter model outperforms the GARCH model and the Schwert and Seguin (1990) model. Using a DCC-GARCH model our evidence suggests that considering dynamic betas can improve beta out-of-sample predicting ability and therefore offers potential gains for investors. Finally, we find dynamic betas across EM are strongly associated with each nation's interest rates, US interest rates and the Consumer Price Index (CPI) and to a lesser extent the exchange rates. Our results have some similarities to those in previous studies of developed markets in the economic determinants of time-varying beta but differences exist in the results on best model to forecast time-varying beta. These findings have implications for estimating country risk for investment and risk management purposes in EM.