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Abstract:
To analyze the intertemporal interaction between the stock and bond market returns, we allow the conditional covariance matrix to vary over time according to a multivariate GARCH model similar to Bollerslev, Engle and Wooldridge (1988). We extend the model such that it allows for asymmetric effects on conditional variances and covariances. Using weekly U.S. stock and bond market data, we find strong evidence of conditional heteroskedasticity in the covariance between stock and bond market returns. The results indicate that not only variances, but also covariances respond asymmetrically to return shocks. Regardless of the bond market shocks, bad news in the stock market is typically followed by a higher conditional covariance than good news. We find that volatility timing strategies for dynamic asset allocation significantly outperform passive strategies. Even when short-sale restrictions are present and transaction costs are high, the economic value of dynamic trading strategies is larger than that of a passive strategy. Moreover, the symmetric volatility timing strategy is outperformed by its asymmetric counterpart.

Multivariate GARCH, stock and bond market interaction, time-varying volatility, asymmetric effects, impact of news

Abstract:
In this paper, we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence that asymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond market are likely due to misspecification of the volatility model. Because firm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model. Moreover, by distinguishing FOMC (interest rate) announcements from PPI and EMP (labor market) announcements, we find that both types of announcements are important determinants in explaining the conditional mean and dynamics in volatility.

Multivariate GARCH, stock and bond market, time-varying volatility, asymmetric, macroeconomic announcements

Abstract:
In this paper we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence that asymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond markets are likely due to misspecification of the volatility model. Because firm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model. Moreover, by distinguishing FOMC (interest rate) announcements from PPI and EMP (labor market) announcements, we find that both types of announcements are important determinants in explaining the conditional mean and dynamics in volatility.

Multivariate GARCH, Stock and Bond Market, Time-Varying Volatility, Asymmetry, Macroeconomic Announcements

Abstract:
In this paper we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, for January 1982 - August 2001, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence that asymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond markets are likely due to misspecification of the volatility model. After including macroeconomic announcements into the model, the asymmetry disappears. Because firm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model.

Multivariate GARCH, Stock and Bond Market, Time-Varying Covariances, Asymmetry, Announcement Effects

Abstract:
In this paper we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, for January 1982 - August 2001, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence thatasymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond markets are likely due to misspecification of the volatility model. After including macroeconomic announcements into the model, the asymmetry disappears. Becausefirm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model.

Multivariate GARCH, Stock and Bond Market, Time-Varying Covariances, Asymmetry, Announcement Effects

Abstract:
We investigate small firms' capital structure, employing a proprietary database containing financial statements of Dutch small and medium-sized enterprises (SMEs) from 2003 to 2005. We find that the capital structure decision of Dutch SMEs is consistent with the pecking order theory: SMEs use profits to reduce their debt level, and growing firms increase their debt position since they need more funds. Furthermore, we document that profits reduce in particular short term debt, whereas growth increases long term debt. This implies that when internal funds are depleted, long term debt is next in the pecking order. We also find evidence for the maturity matching principle in SME capital structure: long term assets are financed with long term debt, while short term assets are financed with short tem debt. This implies that the maturity structure of debt is an instrument for lenders to deal with problems of asymmetric information. Finally, we find that SME capital structure varies across industries but firm characteristics are more important than industry characteristics.

Capital Structure, SMEs, pecking order theory, trade-off theory

Abstract:
This paper investigates market size effects for expected returns from a large set of developed and emerging markets over a time span of up to three decades. We find that expected returns decrease significantly in larger markets, an effect that is dominant in emerging rather than developed countries. Furthermore, we explore the relationship between size effects and the level of market segmentation in emerging countries. The size premium remains strong and persistent across periods over and above the segmentation premium documented in the literature with respect to the intensity of capital controls. This implies that as markets integrate and expand, expected returns fall due to the decrease of both size as well as segmentation premiums. The market size effect is independent of the segmentation premium and accounts for about 1% per year in terms of expected returns in emerging countries.

Market Size, Emerging Markets, Market Integration, Capital Controls

Abstract:
To analyze the intertemporal interaction between the stock and bond market returns, we allow the conditional covariance matrix to vary over time according to a multivariate GARCH model similar to Bollerslev, Engle and Wooldridge (1988). We extend the model such that it allows for asymmetric effects on conditional variances and covariances. Using weekly U.S. stock and bond market data, we find strong evidence of conditional heteroskedasticity in the covariance between stock and bond market returns. The results indicate that not only variances, but also covariances respond asymmetrically to return shocks. Regardless of the bond market shocks, bad news in the stock market is typically followed by a higher conditional covariance than good news. We find that volatility timing strategies for dynamic asset allocation significantly outperform passive strategies. Even when short-sale restrictions are present and transaction costs are high, the economic value of dynamic trading strategies is larger than that of a passive strategy. Moreover, the symmetric volatility timing strategy is outperformed by its asymmetric counterpart.

multivariate GARCH, stock and bond market interaction, time-varying volatility, asymmetric effects, impact of news

Abstract:
Including surprises on a set of 25 regularly scheduled macroeconomic announcements in a factor model, we quantify the relation between news on the real economy and expected returns. Our results show that macroeconomic news constitutes priced risks that are not captured by the market, size, value, and momentum factors. In particular, news on fundamentals describing sentiment towards future business conditions, as well as news on Industrial Production and the Producer Price Index, are priced. Prices for news on macroeconomic fundamentals are substantial, with estimates ranging from -0.758% per day for Business Inventories to 1.622% per day for the Index of Leading Indicators.

Economic risk premia, macroeconomic announcements, factor pricing

Abstract:
To analyze the intertemporal interaction between the stock and bond market returns, we allow the conditional covariance matrix to vary over time according to a multivariate GARCH model similar to Bollerslev, Engle and Wooldridge (1988). We extend the model such that it allows for asymmetric effects on conditional variances and covariances. Using weekly U.S. stock and bond market data, we find strong evidence of conditional heteroskedasticity in the covariance between stock and bond market returns. The results indicate that not only variances, but also covariances respond asymmetrically to return shocks. Regardless of the bond market shocks, bad news in the stock market is typically followed by a higher conditional covariance than good news. We find that volatility timing strategies for dynamic asset allocation significantly outperform passive strategies. Even when short-sale restrictions are present and transaction costs are high, the economic value of dynamic trading strategies is larger than that of a passive strategy. Moreover, the symmetric volatility timing strategy is outperformed by its asymmetric counterpart.

multivariate GARCH, stock and bond market interaction, time-varying volatility, asymmetric effects, impact of news

Abstract:
Using a large and unique real-life dataset we investigate gender differences in the recommendation issuing process of financial analysts. We document gender heterogeneity in the probability to issue a particular type of recommendation that is related to gender differences in risk attitudes. Interestingly, these gender differences disappear when competition increases, implying that gender differences in preferences for performing in a competition is related to gender differences in risk attitude. In addition, we document that the differences are most pronounced when the dispersion in existing recommendations is low; male analyst have a larger probability to issue extreme positive recommendations and to deviate from the consensus recommendation, exactly at the time the market could interpret this behavior as being skilled.

Analyst Recommendations, Gender Differences, Professional Labor Markets

Abstract:
We present a two-stage model for the decision making process of financial analysts when issuing earnings forecasts. In the first stage, financial analysts perform a fundamental earnings analysis in which they are, potentially, subject to a behavioral bias. In the second stage analysts can adjust their earnings forecast in line with their strategic incentives. The paper analyzes this decision process throughout the forecasting period and explains the underlying drivers. Using quarterly earnings forecasts, we document that throughout the entire forecasting period financial analysts overweight their private information. At the same time, financial analysts behave strategically. They issue initial optimistic forecasts by strategically inflating their forecast. In their last revision, they become pessimistic and strategically deflate their earnings forecast, which creates the possibility of a positive earnings surprise. This analysis of the dynamics of the decision process provides empirical evidence on the coexistence of overconfidence and strategic incentives.

Financial analysts, Earnings Forecasts, Overconfidence, Conflicts

Abstract:
In this paper we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, for January 1982 - August 2001, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence that asymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond markets are likely due to misspecification of the volatility model. After including macroeconomic announcements into the model, the asymmetry disappears. Because firm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model.

Multivariate GARCH, Stock and Bond Market, Time-Varying Covariances, Asymmetry, Announcement Effects

Abstract:
We present a two-stage model for the decision making process of financial analysts when issuing earnings forecasts. In the first stage, financial analysts perform a fundamental earnings analysis in which they are, potentially, subject to a behavioral bias. In the second stage analysts can adjust their earnings forecast in line with their strategic incentives. The paper analyzes this decision process throughout the forecasting period and explains the underlying drivers. Using quarterly earnings forecasts, we document that throughout the entire forecasting period financial analysts overweight their private information. At the same time, financial analysts behave strategically. They issue initial optimistic forecasts by strategically inflating their forecast. In their last revision, they become pessimistic and strategically deflate their earnings forecast, which creates the possibility of a positive earnings surprise. This analysis of the dynamics of the decision process provides empirical evidence on the coexistence of overconfidence and strategic incentives.

financial analysts, earnings forecasts, overconfidence, conflicts of interest