Macroeconomic shocks and stock market returns: the case of Korea

This study examines the effects of macroeconomic shocks on key macro variables, including stock market returns in Korea, using the structural vector autoregression (SVAR) model. We suggest a three-variable SVAR model incorporating inflation, output growth and stock returns. We adopt a nonzero z-ratio restriction for the long-run identifying assumption to allow for economically meaningful relationships among variables. While our results support the negative (positive) relation of demand (supply) shocks to stock returns, we also find that demand shocks influence stock market variance more significantly than supply shocks do. The sub-period analysis finds that global market fluctuations during the global financial crisis have relatively little effect on Korean stock market performance. We also examine a generalized five-variable model that includes the foreign exchange rate and interest rate, confirming the results from the three-variable case.     

Industry-level determinants of the linkage between credit and stock markets

This paper examines the relationship between US credit default swaps (CDS) and stock returns on an industry-wide basis across a number of investment horizons, with particular focus on the major determinants of such a relationship. Wavelet analysis is first applied to extract the CDS–stock wavelet correlation for each US industry. Then, Bayesian Model Averaging is employed to identify the key driving factors of the industry CDS–stock wavelet correlations at short- and long-term horizons. The empirical results indicate that the wavelet correlations between the industry CDS and stock returns are primarily negative over time and across time scales. Moreover, the CDS–stock correlation at longer horizons exhibits a much more stable pattern than its counterpart at shorter time frames. The results also demonstrate that the volatility of US Treasury and stock markets, as measured by the MOVE and VIX indices, respectively, the volatility of volatility, as captured by the VVIX index, and US economic policy uncertainty, as measured by the EPU index, are the most robust determinants of the correlation between CDS and stock returns at shorter and longer horizons for most US industries. In contrast, the Fama–French systematic equity factors exhibit a practically negligible explanatory power on the CDS–stock link.     

Overflow effect of credit rating announcements on stock exchange based on event study

This study is aimed to identify the impact of credit rating announcements on the stock returns in stock markets and for this purpose, four different sectors of Pakistan stock exchange were selected and from each of these four sectors, different business organizations were selected, i.e. total 32 business organizations were selected. The credit rating announcement data were collected for these 32 business organizations belonging to four different sectors. Totally 101 credit rating announcements were selected and the time period for which the credit rating warnings were selected include last three years period, i.e. from 2014 to 2016. The collected data were analysed by calculating abnormal returns for each of the selected security and average abnormal returns, and cumulative average abnormal returns were calculated for four different sectors. Event study methodology was applied, and t-test and t-stats value were calculated and results were analysed on the basis of t-statistics. The results of analysis identified that credit rating announcements have a significant impact on stock prices and investors and other market participants are earning abnormal returns during two-day period after the announcements are made. In addition, these abnormal returns were either negative or positive, depending upon the nature of credit ratings announced. If the credit rating announced was upgraded, investors enjoyed positive abnormal returns while in case when credit rating announcements were downgraded, then investors bear negative abnormal returns. Finally, the findings of the study identified the applicability of random walk hypothesis on the Pakistan Stock Exchange and Pakistan Stock Exchange confirms the efficient market hypothesis with its semi-strong form of efficiency.     

Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data

Recent advancements in technology have led to wide availability of high-frequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models.

     

International Evidence for Return Predictability and the Implications for Long‐Run Covariation of the G7 Stock Markets

Abstract. Temporary fluctuations of the US consumption–wealth ratio do not only predict excess returns on the US but also international stock markets at the business cycle frequency. This finding is the reflection of a common, temporary component in national stock markets. Exposure to this common component explains up to 50% of the pairwise covariation among long‐horizon returns on the G7 stock markets for the time period from 1970 to 2008. This latter finding is less pronounced in the post‐1990s period.     

An analysis of commercial bank common stock returns: 1802–97

This study creates analyses for the first time a continous index of returns on commercial bank common stocks listed in a specific market. The index is constructed from a unique set of historical data and is calculated on both a weighted and unweighted basis, first including and then excluding dividends. A measure of volatility is calculated annually.

The results indicate that the dividend component of holding period returns is very important. Including dividends, average returns were 6.0% for the century; excluding dividends, average returns were 0.1%. Excess returns were calculated using two different measures of a riskless rate of return. Cumulative excess returns for the first half of the nineteenth century were negative. Real returns were calculated, and found to be generally positive over the century. The volatility of returns was quite high during certain periods.

Examining the effects of significant economic and political events on bank common stock returns, we find that the War of 1812, the Civil War, and the National Banking System had a significant impact on bank stock returns. Several economic panics, several depressions, the First and Second Banks of the United States, the Embargo of 1807, and the Suffolk Bank had no measureable impact.     

On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach

We combine the global Hurst exponent and Morlet wavelet multi-resolution analysis (MRA) to investigate the dynamic behaviour of six selected stock markets in the Mediterranean region. Specifically, we employ the resonance coefficients and their power spectra to identify potential extreme movements and long-term dependence in stock returns. Using weekly data for the period 2005 to 2010, our results reveal that the wavelet MRA is able to reconstruct the effects of major extreme shocks on stock returns of studied markets, such as the Asian financial crisis, the 9/11 terrorist attacks and the 2007–2009 financial crisis. Moreover, the wavelet-based global Hurst exponent indicates the presence of long-term dependencies in stock returns of all the considered markets, except for France where the anti-persistent behaviour is detected. Overall, our findings are useful to assess the stock market efficiency and provide new insights into stock market dynamics over different time scales.     

通货膨胀与农业股票收益多尺度分析

通货膨胀水平与股票收益率的关系是金融学研究的热点问题之一。文章介绍了小波方法的多尺度分析原理,采用农林指数月度收盘价的对数收益率和消费者价格指数分别代表农业股票收益率和通货膨胀率的水平,得到2007年9月到2012年12月农业股票收益率和通货膨胀率的统计特征。以小波方法分解已知的时间序列,得到不同尺度的数值,利用最小二乘法实证两者之间的关系,得到在中尺度和大尺度的分析周期上,两者具有统计意义上显著地正相关关系,支持了费雪效应假说。而在短尺度分析周期上,两者又具有统计意义上的负相关性,出现了费雪效应悖论。     

Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model

The predictability of stock return dynamics is a topic discussed most frequently in empirical studies; however, no unanimous conclusion has yet been reached due to the ignorance of structural changes in stock price dynamics. This study applies various regime switching GJR-GARCH models to analyze the effects of macroeconomic variables (interest rate, dividend yield, and default premium) on stock return movements (including conditional mean, conditional variance, and transition probabilities) in the U.S. stock market, so as to clearly compare the predictive validity of stable and volatile states, as well as compare the in-sample and out-of-sample portfolio performance of regime switching models. The empirical results show that macro factors can affect the stock return dynamics through two different channels, and that the magnitude of their influences on returns and volatility is not constant. The effects of the three economic variables on returns are not time-invariant, but are closely related to stock market fluctuations, and the strength of predictability in a volatile regime is far greater than that in a stable regime. It is found that interest rate and dividend yield seem to play an important role in predicting conditional variance, and out-of-sample performance is largely eroded when the effects of these two factors on volatility are ignored. In addition, the three macro factors do not play any role in predicting transition probabilities.     

STOCK‐BOND CO‐MOVEMENTS AND FLIGHT‐TO‐QUALITY IN G7 COUNTRIES: A TIME‐FREQUENCY ANALYSIS

This paper examines co‐movement between stock returns and changes in 10‐year government bond yields as well as flight‐to‐quality behaviour in G7 countries. We conduct the wavelet squared coherence analysis to explore the dynamics in both time and frequency domain. Our results provide evidence of positive co‐movements, which vary over time and across investment horizon. The higher co‐movement is found to be more concentrated in the lower frequency bands. We further analyse the dynamic nature of the scale‐dependent wavelet correlations and find that the correlations are highly volatile and significantly increase across different time scales during the episodes of equity market turbulence. The increase in correlations reflects flights from stocks to safer bond investments as a result of dramatic changes in investor sentiment and risk aversion at times of market stress.     

R&D, patents and stock return volatility

Recent finance literature highlights the role of technological change in increasing firm specific (idiosyncratic) and aggregate stock return volatility, yet innovation data is not used in these analyses, leaving the direct relationship between innovation and stock return volatility untested. The paper investigates the relationship between volatility and innovation using firm level patent data. The analysis builds on the empirical work by Mazzucato (Rev Econ Dyn 5:318–345, 2002; J Evol Econ 13(5):491–512, 2003) where it is found that stock return volatility is highest during periods in the industry life-cycle when innovation is the most ‘radical’. In this paper we ask whether firms which invest more in innovation (more R&D and more patents) and/or which have more important innovations (patents with more citations) experience more volatility in their returns. Given that returns should in theory be higher, on average, for higher risk stocks, we also look at the effect of innovation on the level of returns. To take into account the competition between firms within industries, firm returns and volatility are measured relative to the industry average. We focus the analysis on firms in the pharmaceutical industry between 1974 and 1999. Results suggest that there is a positive and significant relationship between volatility, R&D intensity and the various patent related measures—especially when the innovation measures are filtered to distinguish the very innovative firms from the less innovate ones.     

New Evidence on Psychology and Stock Returns

This article provides econometric evidence on the importance of psychological considerations for aggregate stock price fluctuations. To this end, a novel measure of stock market sentiment, dubbed the Net Psychology Index (NPI), based on information contained in Bloomberg News's end-of-the-day stock market reports, is confronted with a battery of multivariate empirical analyses. Results suggest that NPI is statistically different from popular sentiment proxies within the literature. NPI exhibits predictive power, increasing stock returns in the short run with this impact dissipating in the medium term. NPI does not exhibit asymmetric effects on returns for size- and momentum-related portfolios. A trading strategy based on NPI generates a statistically significant positive monthly return. Recursive out-of-sample fit analyses report a lower standard deviation of forecasting errors for NPI-based returns models versus competing accounts.     

Cyclical Dynamics of the Turkish Economy and the Stock Market

Abstract

We analyze the cyclical dynamics of the Turkish economy and the stock market as well as their interactions. We use hidden Markov models that are robust to parameter instability arising from major shifts in economic policy, which have been typically observed in the Turkish economy. These models provide estimates of turning points for the growth, business, and stock market cycles. We identify three states of growth cycles and two states of business cycles in Turkey characterized by different mean estimates. We find that the economy went through five recessions since 1987. Crises are characterized by sharp drops in economic activity and are preceded by slowdowns. These crises are typically followed by strong recoveries during which the economy grows above its long-run average rate. We show that the Turkish stock market goes through three regimes having distinct risk-return dynamics. Bear markets associated with negative returns precede every recession with an average lead time of three quarters, suggesting that the stock market may be a useful forward-looking indicator of the Turkish economy.     

Asset prices and economic fluctuations: The implications of stochastic volatility

This paper investigates whether the multi-factor stochastic volatility of stock returns is related to economic fluctuations and affects asset prices. We address these issues in a dynamic Fama-French three-factor volatility model framework. Consistent with the ICAPM with stochastic volatility (Campbell et al., 2017), we find that the conditional volatility of the size and value factors is significantly related to economic uncertainty. These volatilities are also significant pricing factors. The out-of-sample forecasting analysis further reveals that the conditional volatility can predict stock returns and deliver economic gain in asset allocation. Our analysis sharpens the understanding on the link between the stock market and economic fundamentals.     

The dependence structure between the Canadian stock market and the USD/CAD exchange rate: a copula approach

Abstract This paper investigates the dependence structure between the real Canadian stock returns and the real USD/CAD exchange rate returns, using the Symmetrized Joe‐Clayton (SJC) copula function. We estimate the SJC copula with monthly data over the period 1995:1 to 2006:12. Our results show significant asymmetric static and dynamic tail dependence between the real stock returns and the real exchange rate returns, such that the two returns are more dependent in the left than in the right tail of their joint distribution. We explain this asymmetric dependence in terms of an asymmetric interest rate policy by Canadian monetary authorities in response to changes in the real exchange rate during sub‐periods of falling and rising commodity prices.     

Labor-Market Search and International Business Cycles

The objective of this paper is to explain the observed international fluctuations by modifying the traditional modelling of the labor market in the two-country real business cycles model. Our intuition is that labor-market search can be useful to understand the propagation of international fluctuations. Changes in the expected returns to search induce responses in search and recruiting activities, the effects of which are propagated through time via changes in the stock of employment. Given that the technology shock spills over to the other country, domestic and foreign firms start searching at the same time in anticipation. Employment then increases simultaneously and displays a hump-shaped profile in the two countries. This partially curtails the capital outflow from the country which does not benefit from the shock. Introducing in a search framework a non-separability between consumption and leisure in the utility function allows both to solve the consumption puzzle and to complete the explanation of the international comovement puzzle. Journal of Economic Literature Classification Numbers: E32, F41, J40.     

Are fundamentals still relevant for European economies in the post-Euro period?

A structural VAR model, with stock prices, real economic activity, a short-term interest rate and inflation, was applied to four European countries to investigate whether economic fundamentals play an important role in their national stock markets. The analysis considers the pre- and post-Euro introduction periods. In general, the results suggest a breakdown in the relationship between real economic activity and real stock returns during the post-Euro period. Second, impulse response analyses reveal that (shocks by) fundamental variables still influence somewhat real stock returns for some countries but the extent and nature of their impact differ among countries in the post-Euro period. Finally, an examination of equity risk premiums corroborates the above findings and, overall, they may be interpreted as the equity markets having a mind of their own, disconnected from the fundamentals and that they are significantly affected by foreign rather than country-specific forces.     

石化权证在GARCH模型下的实证检验

股票价格的波动率特征是股票衍生品价格的决定性因素。Black&Scholes假设股票价格服从几何布朗运动,其重要的假设条件是波动率为一个常数。但是,越来越多的实证研究结果表明,股票收益率存在显著的尖峰厚尾现象,其波动率存在明显的时变性特征。因此,放宽波动率恒定条件,并且研究股票波动率的变动特征,对认购权证的正确定价具有重要意义。     

Sign and phase asymmetry: News, economic activity and the stock market

In this paper, we present a general model of the joint data generating process underlying economic activity and stock market returns allowing for complex nonlinear feedbacks and interdependencies between the conditional means and conditional volatilities of the variables. We propose statistics that capture the long and short run responses of the system to the arrival of news, conditioning on the sign and time of arrival of the news. The model is applied to US data. We find that there are significant differences between the short and long run responses of economic activity and stock returns to the arrival of news. Moreover, for certain classifications of news, the respective responses of economic activity and stock returns vary according to the nature of the news and the phase of the business cycle at which the news arrives.     

A Study of Longterm Memory in Stock Market Prices Using Rescaled Range Analysis

Most of the studies on the behaviourof the Indian stock market using the autocorrelation function have revealed that the stock market is weakly efficient and the time series of stock prices and stock indices are random walks. The autocorrelation function assumes Gaussian or near-Gaussian properties in the underlying distribution. The distribution function is assumed to have the normal bellshaped curve. Mandelbrot [1972] has proved that the autocorrelation function works well in determining short-term dependence only. But it tends to underestimate long-run correlation for non-Gaussian series. Alternatively the Rescaled Range Analysis is used to study the long-term dépendance in the time series. The Rescaled Range Analysis (R/S Analysis) is a nonparametric methodology developed by H. E. Hurst, a British hydrologist in 1951. Originally this methodology was applied to study the long-term storage capacity of reservoirs and later it was extended to study many natural systems. This statistical methodology is used for distinguishing random time series from biased random time series (Fractal time series) and to study the persistence of trends and also the presence of periodic and nonperiodic cycles in a time series. In this paper a study of the Indian stock market is carried out using the method of Rescaled Range Analysis and Hurst Coefficient. We conclude that the series of stock prices have persistent behaviour. Nearly 18% of the stock prices are influenced by the past. This ‘memory effect’ in the case of stock indices is found to be 23%. The stock market has shown persistent trends and that the series of prices and indices are biased random walks. The present prices are influenced by the past prices and this influence goes across time scales, one period influencing all the subsequent periods.