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This paper analyzes two views on the issue of FDI and stock market development. The first view is that FDI is negatively correlated with the development of stock markets. The second view is that FDI is positively related to stock market development. After addressing the issues that might lead to these conclusions, the hypothesis is tested that the level of stock market development in a country is positively correlated to FDI. Data is collected from four Latin American countries and an empirical model is proposed to explain the observed relationship. Additional explanatory variables were included, and a model is developed.

This study presents evidence on the relations of stock market performance and industrial production growth for a group of 20 industrial markets. Evidence supports the notion that an increase in stock returns or a rise in the market value of stocks contributes positively to industrial production growth. Evidence suggests that stock market risk has a significantly negative effect on production growth for advanced markets. The Granger test finds a unidirectional causality running from stock returns or stock volatility to industrial growth. However, the United States shows a bilateral causality between stock volatility and industrial production growth.

This chapter studies the properties and characteristics of the Middle East and North African (MENA) stock markets, and the prospects and implications of enhanced financial liberalization in the region. It also explores whether these markets can offer international investors unique risk and returns characteristics to diversify international and regional portfolios. Johansen co-integration tests reveal that the Gulf Cooperation Council equity markets still offer international investors the portfolio diversification potentials mainly through mutual funds, while other emerging MENA stock markets like those of Turkey, Egypt, Morocco, and to a lesser extent Jordan have matured, and are now integrated with the world financial markets.

This paper explores the relationship between size, book-to-market, beta, and expected stock returns in the U.S. Information Technology sector over the July 1990–June 2001 period. Two models, the multivariate model and the three-factor model, are employed to test these relationships. The risk-return tests confirm the relationship between size, book-to-market, beta and stock returns in IT stocks is different from that in other non-financial stocks. However, the sub-period results (the periods before and after the technology crash in April 2000) show that the nature of the relationship between stock returns, size, book-to-market, and market factors, or the magnitude of the size, book-to-market, and market premiums, is on average unchanged for both sub-periods. This result suggests the technology stock crash in April 2000 was not a correction of stock prices.

The latest financial crisis marks a milestone in the development of financial markets. It was a period when it was possible to observe a booming development in the stock markets.

Faced with such a phenomenon, theorists have agreed on the need to resume the debate on the validity of the predictability of stock market returns, which is considered to be the cornerstone of all financial theories. The purpose of this article is to examine the predictability of the bearish stock market using a number of variables widely used in forecasting stock returns. In particular, we focus on variables related to imperfect credit markets.

We revisit the predictability of the bearish market using variables that measure the External Funding Premium (EFP), such as the Default Yield Spread.As the EFP is the key indicator of the extent of credit market imperfections, it should therefore be linked to stock market dynamics and provide useful predictive content.

This study develops an environment, social, and governance (ESG) momentum strategy by combining information about ESG scores and the momentum effect. This study, subsequently, applies the ESG momentum strategy to Taiwanese and Japanese stock markets and investigates the performance of the ESG momentum strategy in each market. Detailed comparisons of the ESG scores and ESG momentum performance between the two markets are conducted. The empirical results show that the ESG momentum strategy can obtain enhanced profits in the Taiwanese market, while the ESG momentum strategy cannot lead to substantial profits in the Japanese market. In addition, the ESG momentum effect in the Taiwanese market can last for three years after portfolio formation. In the Japanese market, the ESG contrarian strategy may deliver better profits than the ESG momentum strategy.

This study takes a broad approach to the relationship between political risk resolution through democracy and stock market development. Specifically, it examines the empirical relationship between the degree of democracy (ranging from non-democracies or autocracies to well-established “mature” democracies) and stock market size and liquidity. Using the random effects Generalized Least Squares methodology on a sample of 22 African countries and spanning the period 1985–2011, this study finds (i) the greater the degree of democracy, the greater the liquidity of the stock market but the impact on the size of the market is insignificant; (ii) the relationship between military leadership and stock market development is statistically insignificant; (iii) having constitutional limits on the number of years a chief executive is allowed to serve promotes stock market development; and (iv) a higher degree of political competitiveness has a significantly positive impact on both stock market size and liquidity.

The purpose of this chapter is to analyze the possible portfolio diversification opportunities between Asian Islamic market and other regions’ Islamic markets; namely USA, Europe, and BRIC. This study makes the initial attempt to fill in the gaps of previous studies by focusing on the proxies of global Islamic markets to identify the correlations among those selected markets by employing the recent econometric methodologies such as multivariate generalized autoregressive conditional heteroscedastic–dynamic conditional correlations (MGARCH–DCC), maximum overlap discrete wavelet transform (MODWT), and the continuous wavelet transform (CWT). By utilizing the MGARCH-DCC, this chapter tries to identify the strength of the time-varying correlation among the markets. However, to see the time-scale-dependent nature of these mentioned correlations, the authors utilized CWT. For robustness, the authors have applied MODWT methodology as well. The findings tend to indicate that the Asian investors have better portfolio diversification opportunities with the US markets, followed by the European markets. BRIC markets do not offer any portfolio diversification benefits, which may be explained partly by the fact that the Asian markets cover partially the same countries of BRIC markets, namely India and China. Considering the time horizon dimension, the results narrow down the portfolio diversification opportunities only to the short-term investment horizons. The very short-run investors (up to eight days only) can benefit through portfolio diversification, especially in the US and European markets. The above-mentioned results have policy implications for the Asian Islamic investors (e.g., Portfolio Management and Strategic Investment Management).

This chapter examines a multifactor model for stock returns in nine Asian markets (Japan, China, South Korea, Hong Kong, Taiwan, Singapore, Indonesia, Malaysia, and Thailand). The authors develop a model using the market risk premium, size, book-to-market, profitability, investment, momentum, price-to-earnings ratio, and dividend yield factors for each market. The empirical results suggest that this eight-factor model can better explain the variations of stock returns than the original Fama–French three-factor model. Factor-based models using local data outperform those using data from US markets. In addition, the evidence suggests that the eight-factor model can better explain stock returns when the market is under stress.