Chinese Lunar New Year effect in Asian stock markets, 1999–2012

This study investigates the Chinese Lunar New Year (CLNY) holiday effect in major Asian stock markets. These are China, Hong Kong, Japan, Malaysia, South Korea and Taiwan. For robustness test, India is also examined in this paper. Daily stock index returns for each market are analysed for the period of 01/09/1999 to 28/03/2012. Using an ARMA(1,1)-GARCH (1,1) model, we find that there is a significantly positive pre-CLNY holiday effect for all cases. The findings are robust for most cases with the exception of China. It is found that high pre-CLNY returns for China are rewards for high risk, whereas for the other markets, high returns are caused by unknown factors, other than the conditional risk.     

Evolving Market Efficiency with an Application to Some Bulgarian Shares

With new technically advanced methods and computers at our disposal, the efficient market hypothesis is once again being debated. At the same time, we are witnessing an unprecedented growth in both existing and new financial markets. These new markets are often in economies which have just recently embraced free market economics; we term these stock markets infant markets. Such stock markets are obviously not efficient in allocating the supply of savings to productive capital. We do not test whether or not these infant markets are informationally efficient, but instead examine whether and how they are becoming more efficient. We propose modelling the excess returns of individual securities using a multi-factor model with time-varying coefficients and generalised auto-regressive conditional heteroskedastic (GARCH) errors. If the markets are becoming more informationally efficient or the agents are learning, we would expect this to manifest itself as the time-varying coefficients becoming more stable as time increases. We test our model using data on four Bulgarian shares. First, we estimate an AR(2) model and a GARCH-M(1,1) model for the shares. Then, we estimated our AR(2) model with time varying coefficients and GARCH type errors. We find varying levels of efficiency and varying speeds of movement towards efficiency within our sample of four shares. This revised version was published online in July 2006 with corrections to the Cover Date.     

Adaptive market hypothesis: The story of the stock markets and COVID-19 pandemic

Since the level of markets’ information efficiency is key to profiteering by strategic players, Shocks; such as the COVID-19 pandemic, can play a role in the nature of markets’ information efficiency. The martingale difference and conditional heteroscedasticity tests are used to evaluate the Adaptive form of market efficiency for four (4) major stock market indexes in the top four affected economies during the COVID-19 pandemic (USA, Brazil, India, and Russia). Generally, based on the martingale difference spectral test, there is no evidence of a substantial change in the levels of market efficiency for the US and Brazilian stock markets in the short, medium, and long term. However, in the long term, the Indian stock markets became more information inefficient after the coronavirus outbreak while the Russian stock markets become more information efficient. Intuitively, these affect the forecastability and predictability of these markets’ prices and/or returns. Thereby, informing the strategic and trading actions of stock investors (including arbitrageurs) towards profit optimization, portfolio asset selection, portfolio asset adjustment, etc. Similar policy implications are further discussed.     

WHAT DO WE KNOW ABOUT THE PROFITABILITY OF TECHNICAL ANALYSIS?

Abstract.  The purpose of this paper is to review the evidence on the profitability of technical analysis. The empirical literature is categorized into two groups, 'early' and 'modern' studies, according to the characteristics of testing procedures. Early studies indicate that technical trading strategies are profitable in foreign exchange markets and futures markets, but not in stock markets. Modern studies indicate that technical trading strategies consistently generate economic profits in a variety of speculative markets at least until the early 1990s. Among a total of 95 modern studies, 56 studies find positive results regarding technical trading strategies, 20 studies obtain negative results, and 19 studies indicate mixed results. Despite the positive evidence on the profitability of technical trading strategies, most empirical studies are subject to various problems in their testing procedures, e.g. data snooping, ex post selection of trading rules or search technologies, and difficulties in estimation of risk and transaction costs. Future research must address these deficiencies in testing in order to provide conclusive evidence on the profitability of technical trading strategies.     

Predictability dynamics of Islamic and conventional equity markets

This study undertakes the challenging task of comparing the weak form efficiency of conventional and Islamic equity markets. Using 12 different Dow Jones indexes that cover 16 years of daily data, we compare the time-varying non-linear predictability patterns of conventional market indexes and their Islamic counterparts at country and continent level by using permutation entropy. Accordingly, we find that all indexes in our analysis have different degrees of time-varying predictability and all conventional markets are found to be more efficient compared to their Islamic counterparts. However, in some of the cases, this difference in efficiency is almost indistinguishable. Our findings reveal that compared to their conventional counterparts, Islamic markets do not necessarily need to carry a more deterministic or predictable structure since efficiency in these markets depends mostly on liquidity, market quality, institutional characteristics and the country/continent specific investment behavior.     

RISE OF THE FIDUCIARY STATE: A SURVEY OF SOVEREIGN WEALTH FUND RESEARCH

We survey the literature documenting the rise of sovereign wealth funds (SWFs), which, with assets under management of over $5.4 trillion at year‐end 2014, are a major force in global finance. Research papers have analyzed the evolution of SWFs from stabilization funds to stand‐alone wealth management funds; we both survey this research and show that more than 25 countries have launched or proposed new SWFs since January 2008. The most salient and controversial feature of SWFs is that they are state‐owned; we survey the existing literature on state ownership and discuss what this predicts about the efficiency and beneficence of government control of SWF assets. We discuss the documented importance of SWF funding sources (oil sales revenues versus excess reserves from export earnings) and survey the normative literature describing how SWFs should allocate funds. We then summarize the empirical literature studying how SWFs actually do allocate funds—across asset classes, geographically, and across industries. We document that most SWF equity investments in publicly traded firms involve cross‐border purchases of sizeable minority stakes (median around 20%) in target firms, with a strong preference for investments in the financial sector. Next, we assess empirical studies examining the impact of SWF stock investments on target firm financial and operating performance, and find universal support for a positive announcement period stock price increase of 1–3%. This, however, is significantly lower than the 5% abnormal return documented for stock purchases by comparable privately owned financial investors in recent studies, indicating a “sovereign wealth fund discount.” We conclude by summarizing the lessons of SWF research and pointing out unresolved issues.     

Time–frequency quantile dependence between Bitcoin and global equity markets

In this paper, we examine return dependence between Bitcoin and stock market returns using a novel quantile cross-spectral dependence approach. The results suggest a right-tail (high return) dependence between Bitcoin and the stock markets in the long term and that said dependence decreases significantly from yearly to monthly investment horizons. Furthermore, right-tail dependence between Bitcoin and the US stock market is the strongest compared with other stock markets. We also extract information on the time-varying and time–frequency structure of co-movements between Bitcoin and the stock markets using wavelet-coherence analysis, the results of which suggest that the co-movement between Bitcoin and the US stock market is positive, whereas, for other stock markets, it is negative at certain frequencies and time periods. Overall, the findings highlight additional risk-management capabilities of Bitcoin according to different stock markets.     

有效市场假设和行为金融学——关于资本市场效率的理论

本文是对资本市场效率问题研究的一个简要回顾和介绍。资本市场效率决定了资本配置、使用的效率,因此是金融经济学的一个主要组成部分。芝加哥商学院教授法玛1970年正式提出有效市场假说(EMH),认为股票价格包含了所有相关信息因而是有效的。在此后很长一段时间内,EMH成为现代金融学的基石。但是近年来,越来越多的理论和实证的发现表明,市场是非有效的。这些理论和实证发现形成了对资本市场效率的新认识—行为金融学。     

Deregulation and liberalization of the Chinese stock market and the improvement of market efficiency

This study employs single and multiple variance ratio tests to reexamine the weak-form efficient market hypothesis (EMH) of A- and B-shares on the Shanghai and Shenzhen exchanges in Chinese stock market. The study also examines the influence of the release of investment restriction of B-share markets on market efficiency. For the whole sample period, the weak-form EMH is only supported for Shanghai A-shares, and is not supported for the remaining shares. For the sub-sample period, the Shenzhen A-share and B-shares of both exchanges being rejected for the weak-form EMH in the earlier sample period are supported following the regulatory change. Rolling multiple variance ratio test statistic values provide additional evidence of weak-form EMH. The improvement of market efficiency can be explained by the increased liquidity and maturity accompanying deregulation and liberalization.     

Time series properties of an artificial stock market

This paper presents results from an experimental computer simulated stock market. In this market artificial intelligence algorithms take on the role of traders. They make predictions about the future, and buy and sell stock as indicated by their expectations of future risk and return. Prices are set endogenously to clear the market. Time series from this market are analyzed from the standpoint of well-known empirical features in real markets. The simulated market is able to replicate several of these phenomenon, including fundamental and technical predictability, volatility persistence, and leptokurtosis. Moreover, agent behavior is shown to be consistent with these features, in that they condition on the variables that are found to be significant in the time series tests. Agents are also able to collectively learn a homogeneous rational expectations equilibrium for certain parameters giving both time series and individual forecast values consistent with the equilibrium parameter values.     

New insights into the role of global factors in BRICS stock markets: A quantile cointegration approach

Because of the acceleration in marketization and globalization, stock markets in the BRICS (Brazil, Russia, India, China, and South Africa) countries are affected by various global factors, for example, oil prices, gold prices, global stock market volatility, global economic policy uncertainty, financial stress, and investor sentiment. This paper offers new insights into the short- and long-run linkages between global factors and BRICS stock markets by applying the quantile autoregressive distributed lags (QARDL) approach. This novel methodology enables us to test short- and long-run linkages accounting for distributional asymmetry. That is, the nonlinear dynamic relationship between the global factors and BRICS stock prices depends on market conditions. Our empirical results show that the effects of gold prices and global stock market volatility on BRICS stock prices are more significant in the long run than in the short run. A decrease in global stock market volatility is associated with higher stock prices, while gold prices demonstrate upward co-movement in dynamic correlations with stock markets. Irrational factors, such as economic policy uncertainty, financial stress, and investor sentiment, play a critical role in the short term, and negative interdependence is dominant. Finally, the rolling-window estimation technique is used to examine time-varying patterns between major global factors and BRICS stock markets.     

THE EFFECTS OF PENSION FUNDS ON MARKETS PERFORMANCE: A REVIEW

The worldwide reforming process of pension systems triggered by the demographic transition and globalization has led several countries to implement multi‐pillar pension systems and enhance pension funds. For this reason the studies on the effects that pension funds exert on markets performance have been flourishing in the last decades. In this paper, we provide an updated review of the empirical advances in this field of study, with particular focus on the effects that pension funds produce on labour markets, financial markets and economic growth.     

Country risk and stock market volatility,predictability, and diversification in the Middle East and Africa

With globalization, an understanding of country risk (political risk (PR), financial risk (FR), and economic risk (ER)) and its impact on stock market return volatility and predictability is important for evaluating direct investment and country selection decisions in globally and regionally diversified portfolios. This paper examines these issues in the context of the Middle East and Africa (MEAF) and analyzes 10 stock markets in the region over the period 1984–1999. After examining volatility and predictability, this paper explains how portfolios of stocks can be formed from these countries in order to achieve mean–variance efficient portfolios. This paper generally finds that country political, financial and economic risks significantly determine stock volatility and predictability. The diversification exercise shows that an international investor can still benefit by diversifying into the stock markets of Middle East and African countries.     

APPROACHES AND METHODS FOR THE ECONOMETRIC ANALYSIS OF MARKET POWER: A SURVEY AND EMPIRICAL COMPARISON

This study discusses two widely used approaches in the New Empirical Industrial Organization (NEIO) literature and examines the strengths and weaknesses of the Production-Theoretic Approach (PTA) and the General Identification Method (GIM) for the econometric analysis of market power in agricultural and food markets. We provide a framework that may help researchers to evaluate and improve structural models of market power. Starting with the specification of the approaches in question, we compare published empirical studies of market power with respect to the choice of the applied approach, functional forms, estimation methods and derived estimates of the degree of market power. Thereafter, we use our framework to evaluate several structural models based on PTA and GIM to measure oligopsony power in the Ukrainian dairy industry. The PTA-based results suggest that the estimated parameters of oligopsony power are significantly different from zero, while GIM-based results do not indicate any evidence of oligopsony market power in the Ukrainian dairy industry. Moreover, estimations results vary substantially due to the employed estimation procedure.     

Similarity of emerging market returns under changing market conditions: Markets in the ASEAN-4, Latin America,Middle East,and BRICs

We studied the risk-return distances of 18 emerging stock markets in the period from January 2000 to December 2013. Distances are linked to volatility and time-varying correlations estimated in standard and asymmetric DCC models. Our results revealed a positive relationship between risk-return distances and volatility, which means that during more volatile periods, the risk-return characteristics in emerging markets exhibit lower similarity to the characteristics found in developed markets. This result seems to be in sharp contrast to most empirical studies using correlations. Within the portfolio framework, our results suggest that diversification into emerging stock markets may still provide desirable benefits to international investors.     

Detecting predictable non-linear dynamics in Dow Jones Islamic Market and Dow Jones Industrial Average indices using nonparametric regressions

This study performs the challenging task of examining the forecastability behavior of the stock market returns for the Dow Jones Islamic Market (DJIM) and the Dow Jones Industrial Average (DJIA) indices, using non-parametric regressions. These indices represent different markets in terms of their institutional and balance sheet characteristics. The empirical results posit that stock market indices are generally difficult to predict accurately. However, our results reveal some point forecasting capacity for a 15-week horizon at the 95 per cent confidence level for the DJIA index, and for nine-week horizon at the 99 per cent confidence for the DJIM index, using the non-parametric regressions. On the other hand, the ratio of the correctly predicted signs (the success ratio) shows a percentage above 60 per cent for both indices which is evidence of predictability for those indices. This predictability is however statistically significant only four-weeks ahead for the DJIM case, and twelve weeks ahead for the DJIA as their respective success ratios differ significantly from the 50 percent, the expected percentage for an unpredictable time series. In sum, it seems that the forecastability of DJIM is slightly better than that of DJIA. This result on the forecastability of DJIM adds to its other findings in the literature that cast doubts on its suitability in hedging and asset allocation in portfolios that contain conventional stocks.     

Forecasting stock prices with commodity prices: New evidence from Feasible Quasi Generalized Least Squares (FQGLS) with non-linearities

The complexities in modern stock markets make it imperative to unravel the possible predictors of their future values. This paper thus provides insights into the predictability of stock prices of the BRICS countries with large dependence on commodities either for foreign exchange earnings or industrial while accounting for the role of asymmetries. Essentially, empirical evidence abound for the high volatility in world commodity markets, thus making us to determine if positive and negative changes in commodity prices predict stock prices differently. In addition, unlike the traditional forecast models, our choice of forecast models additionally addresses certain statistical features, including conditional heteroskedasticity, serial dependence, persistence and endogeneity, inherent in the predictors, which have the potential of causing estimation bias. In all, we find evidence in favour of the ability of commodity prices to predict stock prices of Brazil, Russia and South Africa. Also, both the in-sample and out-of-sample forecast performances of the predicted models support asymmetries in a number of commodity prices in each of these three countries. Our results are robust to different data samples and forecast horizons.     

Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?

This paper investigates risk spillovers and hedge strategies between global crude oil markets and stock markets. In the paper, we propose a multivariate long memory and asymmetry GARCH framework that integrates state-dependent regime switching in the mean process with multivariate long memory and asymmetry GARCH in the variance process. Our results first show that there are linear risk spillovers running from the US stock markets to the WTI oil market in the short term. However, the linear risk spillover effect running from the oil market to the US stock market can only exist in the long term. In addition, there is a bidirectional linear risk spillover effect between the European stock markets and the Brent oil market in the short and long terms. Furthermore, there is no linear risk spillover effect between the Dubai oil market and the Chinese stock market. Second, the nonlinear risk spillovers running from the WTI oil market to the US stock market can be found in the tranquil regime. Moreover, there is also a nonlinear risk spillover effect running from the European stock markets to the Brent oil market in the tranquil regime. In addition, the nonlinear risk spillover effect running from the Brent oil markets to the European stock market can be found in the crisis regime. Furthermore, there is bidirectional nonlinear Granger causality between the Dubai crude oil market and the Chinese stock market in the tranquil regime. Finally, dynamic hedge effectiveness shows that the regime switching process combined with long memory and asymmetry behavior seems to be a plausible and feasible way to conduct hedge strategies between the global crude oil markets and stock markets.     

Sovereign rating changes—Do they provide new information for stock markets?

The purpose of this paper is to examine the impact of sovereign rating changes on international financial markets using a comprehensive database of 42 countries, covering the major regions in the world over the period 1995–2003. In general, we find that rating agencies provide stock and foreign exchange markets with new tradable information. Specifically, rating upgrades (downgrades) significantly increased (decreased) USD denominated stock market returns and decreased (increased) volatility. Whereas the mean response is contributed evenly by the local currency stock returns and exchange rate changes that make up the USD returns, only the foreign exchange volatility was behind the USD denominated return volatility. In addition, we find significant asymmetric effects of rating announcements. The market responses – both return and volatility – are more pronounced in the cases of downgrades, foreign currency debt, emerging market debt, and during crisis periods. This study has important policy implications for international investors’ asset allocation plans and for regulatory bodies such as the Basel Committee who increasingly rely upon Moody's, Standard and Poor's and Fitch's ratings for their regulatory regimes.     

Corporate bond market interdependence: Credit spread correlation between and within U.S. and Canadian corporate bond markets

This study investigates the correlation and interdependence between and within the U.S. and Canadian corporate bond markets. The empirical framework adopted allows credit spreads to depend on common systematic risk factors derived from structural models and incorporates dynamic conditional correlations (DCC) between spreads. Results show that there is a surprisingly weak correlation between the two markets in normal times. However, during crises, there is a sudden and strong increase in the correlation between U.S. and Canadian credit spreads. The analysis of credit spread correlation within each market also shows an unusual increase in credit spread correlations between sectors and between risk classes in the U.S. during the 2007–2009 global financial crisis. This increase persists over the post-crisis period. By contrast, in Canada, credit spread correlations between sectors remain remarkably stable over time, suggesting an interdependence of credit spreads within the Canadian market.