36 research outputs found
Financial liberalization, foreign equity investment and volatility in emerging stock exchanges
Ankara : The Department of Management and the Institute of Economics and Social Sciences of Bilkent University, 2008.Thesis (Ph.D.) -- Bilkent University, 2008.Includes bibliographical references leaves 91-96.In this thesis, the effects of financial liberalization and foreign equity
investment on the return volatility of stocks in emerging stock exchanges are
investigated. At the aggregate level analyses, it is shown that the degree of
financial liberalization has an increasing impact on the aggregated total
volatility of stocks. The analysis of the components of the aggregated total
volatility indicates that that the degree of financial liberalization impacts the
aggregated total volatility through aggregated idiosyncratic and local volatility.
In the second part of the aggregate level analyses, the effect of foreign equity
investment on the return volatility of stocks is investigated by using foreign
equity flow data which is available for Ä°stanbul Stock Exchange. It is found
that foreign equity inflow and outflow have asymmetric effects on average
stock-return volatility. While an inflow has a decreasing impact on aggregated
stock return volatility, an outflow has an increasing impact. At the firm level
analysis, the time-series variation in return volatility of stocks that are crosslisted
on US exchanges is examined. Unlike previous studies in cross-listing
literature, return volatility is analyzed using conditional heteroscedasticity
models. It’s found that firms’ exposure to risks such as local and global market
betas remain unchanged after cross-listing. Moreover, no change in the
dynamics of the volatility of cross-listed stocks is detected. Furthermore, it’s
shown that the mean level of conditional variance is not affected by the
decision to cross-list. Thus, it is concluded that share holders of cross-listed
stocks are not subject to adverse volatility effects.Umutlu, MehmetPh.D
The Link between Financial System and Economics: Functions of the Financial System, Financial Crises, and Policy Implications
Financial system plays a key role in fostering economic growth by efficiently channelling the funds to investments. However, financial system is also considered as the source of instability especially during crisis periods. How to redesign financial system globally and nationally in order to achieve and maintain global financial stability without sacrificing the benefits of it is one of the priority issues for policy makers. This study surveys the benefits obtained from and damages caused by the financial system. This survey further overviews policy implications and suggestions about improving the financial system which help achieve long-term global financial stability
Financial Openness and Financial Development: Evidence from Emerging Countries
We investigate the potential relation between financial openness and financial development for 27 emerging countries for the period between 1996 and 2016. We focus on three dimensions of financial openness: capital account openness, trade openness, and stock-market openness. In this study, we propose alternative measures for capital account and trade openness. Moreover, we offer capital flow and valuation-based measures for stock-market openness as a potential determinant of financial development. Our findings indicate that capital account openness and trade openness are the key drivers of financial development. These results are not sensitive to the use of alternative financial openness and financial development measures, and are robust after being controlled for institutional quality and its components. Our results have implications for policymakers in emerging countries who try to increase the depth of their financial markets for an easier and cheaper access to funds
Idiosyncratic Volatility and Expected Returns at the Global Level
The author investigated the existence and significance of a global cross-sectional relation between idiosyncratic volatility and expected returns by introducing a global idiosyncratic volatility measure and globally diversified test assets. He found that portfolios with the highest and lowest global idiosyncratic volatility do not earn significantly different average returns, indicating no link between global idiosyncratic volatility and expected returns. His results show that global diversification is effective in stabilizing the returns of global test assets and that benefits from global diversification can be gained by diversifying across either countries or industries.In this study, I investigated the existence and significance of a cross-sectional relationship between global idiosyncratic volatility and expected return. This study extends the debate on whether idiosyncratic volatility matters for expected returns at the global level by taking the perspective of a global investor. I introduced a global idiosyncratic volatility measure that is defined as the residual volatility in which the residuals are obtained by regressing the returns of globally diversified test assets on the global systematic risk factors in an international asset pricing framework. I formed global test assets from characteristic-sorted local supersector, local stock market, and global sector indexes. The use of characteristic-sorted indexes facilitates diversification at the domestic, international, and industrial levels and thus leads to the formation of globally well-diversified test assets. I sorted the test assets on the basis of global idiosyncratic volatility and formed three portfolios. Portfolio 1 consisted of the test assets with the lowest global idiosyncratic volatility; Portfolio 3 contained the test assets with the highest global idiosyncratic volatility. I performed average return difference tests for Portfolios 3 and 1 to see whether a relationship exists between global idiosyncratic volatility and expected return. I consistently found no statistically significant return difference between the highest- and lowest-GIVOL portfolios and thus found no evidence of a relationship between global idiosyncratic volatility and expected return
Firm leverage and investment decisions in an emerging market
In this study, the effect of leverage on investment is analyzed by employing panel data methods for the Turkish non-financial firms that are quoted on İstanbul Stock Exchange. For one-way error component models, it is shown that there is a negative impact of leverage on investment for only firms with low Tobin’s Q. These results are in conformity with the previous literature and agency theories of corporate finance stating that leverage has a disciplining role for firms with low growth opportunities. However, when the model is extended to include the time effects in a two-way error component model, the relation between leverage and investment disappears
Does idiosyncratic volatility matter at the global level?
I test the existence of a time-series relationship between the aggregate idiosyncratic volatility and the market index return at the global level by introducing various global measures of aggregate idiosyncratic volatility. I offer four definitions of aggregate global idiosyncratic volatility (GIVOL) based on factor models and two other definitions, which are free from factor models. Regardless of whether I use model-dependent or model-independent measures, I find no evidence of a robust and significant relation between the aggregate GIVOL and the global market return. This result is valid for four different sub-periods and four different subsamples reflecting the different states of the economy and the stock market. It is also robust to the inclusion of several control variables. As global idiosyncratic volatility is not a priced factor in the intertemporal asset pricing framework, the results indicate that international diversification is still effective in eliminating idiosyncratic volatility despite the globalization process
Size matters everywhere: Decomposing the small country and small industry premia
We explore the country and industry size effects by decomposing market value into four components: short-term return, representing momentum; long-run return, representing reversal; composite issuance; and lagged market value. We examine the implications of this decomposition for the country and industry size premia within a sample of 51 equity markets for the years 1973–2017. We confirm a significant size effect across countries and uncover an industry size effect: small industries markedly outperform large industries. While the cross-sectional dispersion in market value is determined almost exclusively by the lagged market value component, the country and industry size premia have two prmary drivers: lagged market value and long-run reversal. Our analysis also discovers an industry issuance effect and a remarkable January effect inboth country and industry returns. Finally we also shed some light on the vanishing small country effect in the last decade
The cross-section of industry equity returns and global tactical asset allocation across regions and industries
This study investigates which index characteristics predict returns in the cross-section of local industry indexes in six regions. The results show that geographical origin and market capitalization of indexes critically determine the predictive ability of characteristics. We find that industry indexes of any market capitalization with high earnings-to-price ratio yield higher expected returns in the US, Europe, and Asia-Pacific. Recent winner (loser) portfolios in Europe have a tendency to outperform (underperform) recent loser (winner) portfolios in the near future for all groups of market capitalization. Small portfolios with high idiosyncratic volatility in Asia-Pacific earn an idiosyncratic volatility premium. Dividend yield is positively related to future returns of small European portfolios. These results are robust to the inclusion of transaction costs and control variables and have implications for portfolio managers following a global tactical asset allocation policy
Economic Growth and Financial Development: Evidence from Panel Cointegration Tests in Emerging Countries
In This study analyzes the long-run relationship between economic growth (EG) and financial development (FD) in 27 emerging countries over the period 1980 to 2018 by employing the Johansen-Fisher panel cointegration method. The study also performs the vector error correction model (VECM) to determine the direction of a causal relationship among the variables. Two components of the index of financial development introduced by Svirydzenka (2016), financial markets and financial institutions indices, are employed to reveal through which channels EG has a long-term association with FD. Empirical findings show a significant long-run association between EG, the overall index of FD, and its lower-indices. Furthermore, the results from panel VECMs indicate a one-way unidirectional causality between EG and the FD index, while there is a two-way causality between EG and financial markets as well as between EG and financial institutions indices in the short run. We obtain similar results with Kao and Pedroni panel cointegration tests. We also show that financial institutions and financial markets indexes significantly affect economic growth in the long run. Thus, policy makers in emerging markets should take actions that facilitate the development of financial markets and institutions to increase GDP per capita
Return range and the cross-section of expected index returns in international stock markets
This study examines the cross-sectional relation between return range and future returns for the first time in literature. We show that the return range can serve as a very practical measure of total volatility instead of standard deviation due to the range's high correlation with standard deviation and strong predictive ability. Range, standard deviation, and idiosyncratic volatility are cross-sectionally linked to future returns on indexes of small size, while earnings-to-price ratio and net share issuance predict returns of mid-cap and large-cap indexes, respectively. Maximum and minimum return effects along with the momentum effect are prevalent in returns of indexes of any size but stronger for small-cap indexes