Essays on Dynamics of Financial Markets

In this study, the effects of different macroeconomic news on stock markets and different stock market co-movements are investigated. Impacts of good and bad macroeconomic news announcement surprises on the mean and conditional volatility of U.S. daily equity and Treasury bond market returns during economic recessions and expansions are examined. By jointly modeling returns and volatilities using a generalized autoregressive conditional heteroskedasticity (GARCH) models, it is found that surprise in unemployment news has no impact on stock returns during business cycles. On the other hand, the results indicate a significantly positive relation between the short term (long term) bond prices and unemployment surprises during business cycles (expansions), indicating that U.S. government bonds is a complete hedge against unexpected unemployment. However, positive inflation surprises affect all considered market returns negatively during expansions. The price movements in stock markets can be explained by expected future interest rates when an inflation surprise is arrived. Hence, both news surprises have more impact on volatility during economic recessions than expansions. Another way to see the dynamics of stock markets is to search the effect of different country equity market effects on each other. The second essay investigates it by linear and nonlinear Granger causality tests for US, UK and Japan stock markets, implying an arbitrage opportunity between stock markets. The third study examines the dynamic relationship between the monthly inflation, inflation uncertainty and stock for G3 countries. Using a GARCH model to generate a measure of inflation uncertainty, the empirical evidence indicates that higher inflation rates lead to greater inflation uncertainty for all countries as predicted by Friedman (1997). However, in all countries, except Japan, inflation uncertainty does not significantly either rise or fall average inflation. In contrast to linear linkages, there is a strong bi-directional non-linear causal relationship between inflation and its uncertainty for all countries. The similar findings are found for the inflation uncertainty and stock returns. Inflation uncertainty does not linear Granger-cause stock returns, except Japan. However, there is a bi-directional nonlinear Granger causality for all countries

Non-linear Causality Between Stock Returns And Inflation Uncertainty: Evidence From The US And The UK

This study analyzes the dynamic relationships between inflation uncertainty and stock returns by employing the linear and non-linear Granger causality tests for the US and the UK. Using GARCH model to generate a measure of inflation uncertainty, it does not have a predictive power for stock returns, as predicted by Friedman, and it does not support the opportunistic central bank hypothesis suggested by Cukierman-Meltzer. However, the findings from non-linear Granger causality put forth that there is a bi-directional non-linear predictive power between these variables. Stock market is used as a hedge against inflation uncertainty

The Business Cycle And Impacts Of Economic News On Financial Markets

By jointly modeling returns and volatilities, we find that unemployment news has no significant impact on US stock market returns, but instead on stock market volatility. There is also a significantly positive relation between the long-term bond return and unemployment news during economic expansions, indicating that U.S. government bonds might be a hedge against unemployment news. Inflation news affects both stock and bond market returns negatively during expansions. Both unemployment and inflation news surprises also have more impact on volatility during economic recessions than during expansions

Sectoral Herding: Evidence from an Emerging Market

This study examines herding behavior in all industrial sectors of the Turkish stock market. Applying the methodology of Chang et al. (2000) to the Turkish sectoral daily stock prices from 2002 to 2014, we found strong evidence of herding. This evidence did not disappear even after we controlled for market regimes and firm fundamentals. Investor herding is asymmetric in all sectors; even though herding is prevalent in both rising and falling markets, it is more pronounced in rising markets. In the financial, services, and technology sectors herding is detected only in the highly volatile markets. In contrast, in low-volatility markets we confirm herding only in the services sector

Does U.S. Macroeconomic News Make Emerging Financial Markets Riskier?

This study analyzes the impacts of U.S. macroeconomic announcement surprises on the volatility of twelve emerging stock markets by employing asymmetric GJR-GARCH model. The model includes both positive and negative surprises about inflation and unemployment rate announcements in the U.S. We find that volatility shocks are persistent and asymmetric. Asymmetric volatility increases with bad news on U.S. inflation in five out of the twelve countries studied and it increases with a bad news on U.S. unemployment in four out of twelve countries. Asymmetric volatility decreases with good news about US employment situation in eight countries out of twelve countries. Such markets become less risky with an unexpected decrease in unemployment rate in the U.S. Our findings are important for demonstrating that the U.S. economic growth and employment situation has an impact on many emerging stock markets and that positive U.S. macroeconomic news, in fact, makes many emerging stock markets less volatile. Jel classification: G

Did Large Institutional Investors Flock Into the Technology Herd? An Empirical Investigation Using a Vector Markov-switching Model

This article investigates whether large non-bank institutional investors herded during the dot-com bubble of the 1990s. We use the vector Markov-switching model of Hamilton and Lin (1996) to analyse the technology stockholdings of 115 large institutional investors from 1980 to 2012. By imposing different restrictions on the elements of the transition probability matrix, we are able to test for various lead/lag scenarios that might have existed between the technology stockholding of each investor and that of the residual market. We find that only 17.4% of the investors in our sample herded during the dot-com bubble. Thus, during the dot-com bubble, herding among large institutional investors was not an especially widespread phenomenon. Among those investors that herded, 80% herded during the run-up, 10% during the collapse and 10% during both phases of the dot-com bubble. About 23% of all investors in our sample exited from the technology sector before the bubble collapsed. These results seem to support Abreu and Brunnermeier’s (2003) theory of bubbles and crashes

On the Relationship Between Exchange Rates and Stock Prices: Evidence from Emerging Markets

This study examines dynamic linkages between the exchange rates and stock prices for twelve emerging market countries for the period from May 1994 to April 2010 by using linear and non-linear Granger causality tests. Our empirical results show that stock prices and exchange rates have linear and non-linear bi-directional causality in most cases. The exceptional countries are Brazil, Poland and Taiwan, in that there is no evidence for a non-linear Granger causality from stock prices to exchange rates. The results support both the portfolio balance and the goods market theories for eight out of twelve countries. JEL Classifications Codes: F30, G15

The international REIT’s time-varying response to the U.S. monetary policy and macroeconomic surprises

International real estate markets and the ever increasing role of the U.S. economic and policy developments have played a central role both in international portfolio management as well as broader economic policy making. In this paper, we measure the extent of time-varying impact of the U.S. monetary policy and macroeconomic news on the international Real Estate Investment Trusts (REITs) stock returns. Results suggest that there has been significant variation both across time and across countries in the impact of U.S. news on the global REIT stocks. Further, the country’s stock market capitalization to GDP ratio has strong connections with the time-varying nature of the impact of the U.S. news on the global REIT stock returns

Oil Prices and Firm Returns in an Emerging Market

This study examines the oil price effect on Turkish stock market as an emerging country on firm level data. After controlling short term interest rate, nominal exchange rate and crude oil price, we find that firms behave differently to a change in oil prices. The findings include these: i) variations in oil prices do not significantly affect Turkish firm returns. Out of 153, only 38 firms are affected significantly by oil price after controlling exchange rate and interest rate; ii) oil prices influence stock returns of Turkish firms, suggesting that under reaction and gradual information diffusion hypotheses may hold. iii) small and middle-sized firms are more affected negatively from oil price changes, where large-sized firms affected more positively. The empirical findings of this study have potential implications and offer significant insights for both practitioners and policy makers

Climate Change and Its Impact on Wheat Production in Kansas

This paper studies the effect of climate change on wheat production in Kansas using annual time series data from 1949 to 2014. For the study, an error correction model is developed in which the price of wheat, the price of oats (substitute good), average annual temperature and average annual precipitation are used as explanatory variables with total output of wheat being the dependent variable. Time series properties of the data series are diagnosed using unit root and cointegration tests. The estimated results suggest that Kansas farmers are supply responsive to both wheat as well as its substitute (oat) prices in the short run as well as in the long run. Climate variables; temperature has a positive effect on wheat output in the short run but an insignificant effect in the long run. Precipitation has a positive effect in the short run but a negative effect in the long run