Bank stock returns and economic growth

Previous research has established (i) that a country’s financial sector influence future economic growth and (ii) that stock market index returns affect future economic growth. We extend and tie together these two strands of the growth literature by analyzing the relationship between banking industry stock returns and future economic growth. Using dynamic panel techniques to analyze panel data from 18 developed and 18 emerging markets, we find a positive and significant relationship between bank stock returns and future GDP growth that is independent of the previously documented relationship between market index returns and economic growth. We also find that much of the informational content of bank stock returns is captured by country-specific and institutional characteristics, such as bank-accounting-disclosure standards, banking crises, enforcement of insider trading law and government ownership of banks.     

Structural Breaks and Predictive Regression Models of Aggregate U.S. Stock Returns

In this article we examine the structural stability of predictiveregression models of U.S. quarterly aggregate real stock returnsover the postwar era. We consider predictive regressions modelsof S&P 500 and CRSP equal-weighted real stock returns basedon eight financial variables that display predictive abilityin the extant literature. We test for structural stability usingthe popular Andrews SupF statistic and the Bai subsample procedurein conjunction with the Hansen heteroskedastic fixed-regressorbootstrap. We also test for structural stability using the recentlydeveloped methodologies of Elliott and Müller, and Baiand Perron. We find strong evidence of structural breaks infive of eight bivariate predictive regression models of S&P500 returns and some evidence of structural breaks in the threeother models. There is less evidence of structural instabilityin bivariate predictive regression models of CRSP equal-weightedreturns, with four of eight models displaying some evidenceof structural breaks. We also obtain evidence of structuralinstability in a multivariate predictive regression model ofS&P 500 returns. When we estimate the predictive regressionmodels over the different regimes defined by structural breaks,we find that the predictive ability of financial variables canvary markedly over time.     

Exchange rates,interventions, and the predictability of stock returns in Japan

Using monthly Japanese data for the period 1991–2005, we examined the link between exchange rate movements and stock returns. We found that exchange rate movements per se do not help to explain stock returns. There is, however, evidence of in-sample predictability if one accounts for the interventions of the Japanese monetary authorities in the foreign exchange market. This evidence does not indicate a violation of market efficiency insofar as investors cannot use information on interventions to systematically improve the performance of simple trading rules based on out-of-sample forecasts of stock returns.     

Technical Trading Rules in Emerging Markets and the 1997 Asian Currency Crises

The ability of simple technical trading rules to forecast future stock market movements is considered for seventeen emerging markets, sampled from January 1986 to September 2003. Some of the trading rules considered generated significant returns; this information could be exploited profitably on occasion. Market conditions and trading volume are found to be important to determining the usefulness of technical trading rules.     

Banking industry volatility and economic growth

Utilizing the recent dynamic panel GMM estimation techniques for 36 markets, this research investigates the relationship between banking industry volatility and future economic growth, and provides empirical evidence complementary to Cole et al. (2008) who examine the finance-growth nexus from a unique asset pricing theory perspective and document a positive relationship between bank stock returns and future economic growth that is significantly influenced by a series of country-specific and banking institutional characteristics. We find that the negative link between banking industry volatility and future economic growth is significantly affected by government ownership of banks, the enforcement of the insider trading law, systemic banking crises, and bank accounting disclosure standards, while the impact of financial development is ambiguous. The significant results are primarily driven by the data from emerging markets.     

With Economic Integration Comes Financial Contagion? Evidence from China

China's economy has maintained a rapid growth rate over the past two decades; however, its stock market has exhibited a very different level of performance during financial crises. In this paper, we try to explain this phenomenon and answer two important questions: Is there financial contagion in China? Can economic integration aggravate financial contagion? We construct a composite index of economic integration by reviewing the incremental reform and opening-up process in China's financial markets. We utilize a dynamic conditional correlation model to capture the correlations between stock returns of China and those of other important markets around the world. The empirical results provide positive evidence for the aforementioned two questions.     

Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.     

Do momentum-based strategies work in emerging currency markets?

Existing studies on the profitability of trading rules in the currency market focus mainly on the currencies of developed countries. The profitability of technical trading rules on the currencies of emerging economies is surprisingly understudied. This paper evaluates the profitability of technical trading rules in emerging currency markets. Similar to Okunev and White [Okunev, J. and White, D., (2003) “Do Momentum-based Strategies Still Work in Foreign Currency Markets?” Journal of Financial and Quantitative Analysis 38, 425–447.], 354 long/short moving average rules for six currencies are investigated. It is found that investing in emerging currencies can generate a considerable annual return of over 20%, even after a 5% annual transaction cost is imposed. The trading-rule profits are relatively stable across the 20 year sample period. Furthermore, the impact of financial crises on the trading-rule returns is also examined. It is found that the profitability of the trading rules is improved after the crises.     

Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using Pacific Basin stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property, and that the asymmetric reverting property of stock returns is exploitable in generating profitable buy and sell signals for technical trading rules. We show that the positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric dynamics of stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical analysis.     

Investor attention,aggregate limit-hits,and stock returns

We develop a simple measure of investor attention by aggregating the number of days that a stock hits the upper or lower limit on a monthly basis. This attention proxy describes investor trading behavior and contains information of future stock returns. Using data from the Chinese equity market from 2002 to 2017, we provide extensive evidence that the investor attention captured by our measure negatively predicts cross-sectional stock returns, and the long–short trading strategy based on this attention measure produces significant economic value. We argue that the attention-motivated trading is the main cause behind the return predictability of aggregate limit-hits.     

Do Sovereign Re‐Ratings Destabilize Equity Markets during Financial Crises? New Evidence from Higher Return Moments

This study investigates the effects of S&P's sovereign re‐ratings on the higher moments of equity market returns over recent financial crises. Using a set of intraday stock market index prices and sovereign credit ratings for a sample of 36 countries that experienced sovereign rating changes over the period from 1996 to 2013, we find that the higher moments of stock market returns are significantly more responsive to sovereign re‐ratings during financial crises, but the effects on stock markets are not the same across different financial crises. The effects during crises are, however, magnified for large downgrades and those that are associated with a loss of investment grade status. We find that there are asymmetric effects during financial crises in that downgrades are consistently more significant than upgrades in increasing realized volatility and realized kurtosis. Both upgrades and downgrades affect realized skewness in times of crises in the expected direction.     

Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did by Brock, Lakonishok and LeBaron (1992) and later by Bessembinder and Chan (1998), this paper examines predictive power and profitability of simple trading rules by expanding their universe of 26 rules to 412 rules. In order to find out the relationship between market efficiency and excess return by applying trading rules, we examine excess return over periods in U.S. markets and also compare the excess returns between U.S. market and Chinese markets. Our results found that there is no evidence at all supporting technical forecast power by these trading rules in U.S. equity index after 1975. During the 1990s break-even costs turned to be negative, –0.06%, even failing to beat a buy-holding strategyin U.S. equity market. In comparison, our results provide support for the technical strategies even in the presence of trading cost in Chinese stock markets.     

Do corporations learn from mispricing? Evidence from takeovers and corporate performance

In this article we form the simple prediction that mispricing encourages traders to collect costly information that guides managerial decisions at corporate level. Our findings support this prediction based on evidence derived from both the US market for corporate control and the overall variation in aggregate corporate profits. The trading activity in response to the temporary mispricing of the merging companies provides useful information that leads to the design of high-synergy deals. Such synergies are reflected in an increase in the announcement period acquirer abnormal returns and are not reversed in the long-run. At the market-wide level, our results suggest that the growth in the overall stock trading volume in response to market mispricing is associated with high future corporate profit growth. Overall, after controlling for several economic and financial conditions, the temporary mispricing in a developed and generally efficient stock market stimulates informative trading, ultimately leading to value- and performance-enhancing corporate decisions.     

Generalized runs tests to detect randomness in hedge funds returns

The major contribution of this paper is to make use of generalized runs tests (Cho and White, 2011) to analyze the randomness, i.e. the lack of persistence, in both absolute and relative returns of hedge funds. We find that about 42% of the HFR universe exhibit iid absolute returns over the period spanning 2000 to 2012. These funds are mainly found in proportions within the Macro and Equity Hedge strategies. A similar result holds for relative returns. We also find that funds having non-iid returns often exhibit ARCH effects and structural breaks, with largest breaks located within financial crises. Also, only a small percentage displays persistence in their relative performance, 8.2% to 16.7% of the universe, mainly found in proportions within the Relative Value and Event-Driven strategies. The robustness of results is challenged by implementing the tests on a crisis-free period. We find similar results for absolute returns. For relative ones, differences appear across strategies and benchmarks, but still both ARCH and breaks are present. Our work contributes to the hedge fund literature in terms of methodology, portfolio allocation, and performance measurement.     

Co-movement of Asia-Pacific with European and US stock market returns: A cross-time-frequency analysis

We investigate the co-movement of 13 Asia-Pacific stock market returns with that of European and US stock market returns using the wavelet coherence method. Our results show consistent co-movement between most of the Asia-Pacific stock markets and that of Europe and the US in the long run. We also uncover evidence of a wide variation in co-movement across the time scale of the financial crises. The co-movement dynamics of the Asia-Pacific markets with that of Europe and the US are different during the two financial crises. The difference in the co-movement dynamics could be the result of the different natures of the financial crises or a change in regime.     

The predictability of security returns with simple technical trading rules

Technical traders base their analysis on the premise that the patterns in market prices are assumed to recur in the future, and thus, these patterns can be used for predictive purposes. This paper uses the daily Dow Jones Industrial Average Index from 1897 to 1988 to examine the linear and nonlinear predictability of stock market returns with simple technical trading rules. The nonlinear specification of returns are modelled by single layer feedforward networks. The results indicate strong evidence of nonlinear predictability in the stock market returns by using the past buy and sell signals of the moving average rules.     

A comprehensive investigation on the predictive power of economic policy uncertainty from non-U.S. countries for U.S. stock market returns

This study uses economic policy uncertainty (EPU) indices for ten developed countries, three diffusion models, and five combination methods to forecast excess returns in the U.S. stock market. It shows empirically that, over the period January 1997 to January 2022, non-U.S. EPU indices have better predictive power for U.S. equity market excess returns than the U.S. EPU index itself. This illustrates how economic information from international markets can affect the U.S. stock market. This finding challenges the extensively recognized view that the U.S. is where important market signals are initially transmitted to other markets, suggesting that this belief is incomplete. Our outcomes are robust to a battery of tests covering model selection, model specification, forecast horizons, and the pandemic period, and their economic values are assessed. The findings are essential for the financial field to confront future fierce situations and crises.     

Real‐Time Forecasting and Political Stock Market Anomalies: Evidence for the United States

Using monthly data from 1953 to 2003, we apply a real‐time modeling approach to investigate the implications of U.S. political stock market anomalies for forecasting excess stock returns in real‐time. Our empirical findings show that political variables, chosen on the basis of widely used model‐selection criteria, are often included in real‐time forecasting models. However, political variables do not contribute systematically to improving the performance of simple trading rules. For this reason, political stock market anomalies are not necessarily an indication of market inefficiency.     

Money and stock prices: Market efficiency and the lag in effect of monetary policy

This paper examines stock market efficiency with respect to money supply data by testing (1) regression models of stock returns on monetary variables and (2) trading rules based on money supply data. The evidence indicates no meaningful lag in the effect of monetary policy on the stock market and that no profitable security trading rules using past values of the money supply exist. Therefore this evidence is consistent with the efficient market model. Current security returns incorporate all information contained in past money supply data and, in addition, appear to anticipate future changes in the money supply. A number of previous studies have concluded that lags exist and can be used in profitable trading rules. Analysis of these studies demonstrates that for a variety of reasons the evidence in these past studies does not sustain such conclusions.     

Determinants of equity return correlations: a case study of the Amman Stock Exchange

This paper seeks to explain time-varying correlations among equity returns. The literature has shown that fundamental and economic factors can explain stock returns or the volatility of markets. Here, panel data analysis is employed to examine whether these factors can also explain the comovement of stock returns. Time-varying correlations among sectoral indexes are estimated using a restricted multivariate threshold GARCH model with dynamic conditional correlation controlling for the asymmetric effects of news and the influence of financial crises. The empirical results from this panel data analysis show that equity return correlations can be explained not only by macroeconomic variables but also by fundamentals within an industry.