实际股票收益率与通货膨胀率关系的实证研究

股票收益率与通货膨胀率之间的关系至今仍无定论.采用1991年1月到2011年8月的月度数据,运用VAR模型对我国的股票收益率与通货膨胀率之间的关系进行实证分析,结果发现不论是预期的通货膨胀还是非预期的通货膨胀与股票实际收益率都是负相关关系.表明费雪效应在我国不成立,股票并不是对冲通货膨胀风险的理想工具.     

Permanent and transitory components of GDP and stock prices: further analysis

Using the conventional VAR identification approach, Cochrane (Quarterly Journal of Economics 107: 241–65, 1994) finds that substantial amounts of variation in GDP growth and stock returns are due to transitory shocks. Following the common trend decomposition of King etal. (American Economic Review 81: 819–40, 1991), we show that Cochrane's results depend on the assumption of weak exogeneity of one of the variables with respect to the cointegration vector. When this assumption holds both approaches coincide. If not, the shocks Cochrane called transitory are not totally transitory. In this case, the conventional VAR approach with the assumption of the weak exogeneity may overstate the magnitude of transitory shocks and understate that of permanent shocks. We find that the permanent components of GDP and stock prices are much larger than those estimates of Cochrane, although substantial (but much smaller than in Cochrane 1994) variations in GDP growth and stock returns are attributed to transitory shocks.     

Investor Sentiment and Stock Returns: Evidence from Turkey

This paper investigates the relation between investor sentiment and stock returns on the Istanbul Stock Exchange, employing vector autoregressive (VAR) analysis and Granger causality tests. The sample period extends from July 1997 to June 2005. In the VAR models, stock portfolio returns and investor sentiment proxies are used as endogenous variables. Two dummy variables accounting for natural and economic crises are used as exogenous variables. The analysis results suggest that, excepting shares of equity issues in aggregate issues, stock portfolio returns seem to affect all investor sentiment proxies, namely closed-end fund discount, mutual fund flows, odd-lot sales-to-purchases ratio, and repo holdings of mutual funds. Investor sentiment does not appear to forecast future stock returns; only the turnover ratio of the stock market seems to have forecasting potential.     

What Drives Firm‐Level Stock Returns?

I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash-flow expectations (i.e., cash-flow news) and changes in discount rates (i.e., expected-return news). The VAR yields three main results. First, firm-level stock returns are mainly driven by cash-flow news. For a typical stock, the variance of cash-flow news is more than twice that of expected-return news. Second, shocks to expected returns and cash flows are positively correlated for a typical small stock. Third, expected-return-news series are highly correlated across firms, while cash-flow news can largely be diversified away in aggregate portfolios.     

Stock Market Returns and Economic Fundamentals in an Emerging Market: The Case of Korea

This paper investigates the feedback relationship between stock market returnsand economic fundamentals in an emerging market. Starting from an intertemporalconsumption-based CAPM (CCAPM), we obtain a restricted VAR model for stockreturns and macroeconomic variables. We then apply this model to Korea and findstatistically significant departures from the restrictions implied by CCAPM.Consequently, an unrestricted VAR model is used to analyze the variations of expectedand unexpected returns in the Korean stock market. It is shown that the expectedmarket returns vary with a set of macroeconomic variables, and that thepredictable component is substantial. Reflecting richer dynamics in the data,relative to the usual single equation modeling in the literature, the estimatedVAR model shows considerable predictive ability for both real economic activityand real returns. Using the model for a variance decomposition of unexpectedreturns, we find that, although we cannot directly observe the market's revisionof expected future dividend growth, we can estimate a large part of therevision with the news in the expected industry output growth from our VAR model.Finally, we also find that economic fundamentals can explain only a smallportion of the variation in unexpected returns in the Korean stock market.     

Causal Relations Among Stock Returns,Interest Rates,Real Activity,and Inflation

Using a multivariate vector-autoregression (VAR) approach, this paper investigates causal relations and dynamic interactions among asset returns, real activity, and inflation in the postwar United States. Major findings are (1) stock returns appear Granger-causally prior and help explain real activity, (2) with interest rates in the VAR, stock returns explain little variation in inflation, although interest rates explain a substantial fraction of the variation in inflation, and (3) inflation explains little variation in real activity. These findings seem more compatible with Fama (1981) than with Geske and Roll (1983) or with Ram and Spencer (1983) .     

The Danish stock and bond markets: comovement,return predictability and variance decomposition

VAR models of the kind developed by Shiller and Beltratti [J. Monetary Econ. 30 (1992) 25] and Campbell and Ammer [J. Finance 48 (1993) 3] are used to analyze the Danish stock and bond markets and their comovement. In contrast to these papers, however, VAR parameter estimates are bias-adjusted and VAR generated statistics, including their standard errors and confidence intervals, are computed using bootstrap simulation. In addition, we modify the Campbell–Ammer variance decomposition such that it can handle returns from a long-term coupon bond. Some parts of the results for the Danish stock and bond markets are quite similar to the US results reported by Shiller and Beltratti and Campbell and Ammer, but other parts stand in sharp contrast to the results for the US. The most important differences between the US and Denmark are that in Denmark news about higher future inflation lead to an increase in expected future stock returns, and that excess stock return news and excess bond return news are negatively correlated.     

Macro variables and the components of stock returns

We conduct a decomposition for the stock market return by incorporating the information from 124 macro variables. Using factor analysis, we estimate six common factors and run a VAR containing these factors and financial variables such as the market dividend yield and the T-bill rate. Including the macro factors does not have a significant impact in the estimation of the components of aggregate (excess) stock returns—cash-flow, discount-rate, and interest-rate news. Using the macro factors in the computation of cash-flow and discount-rate news does not significantly improve the fit of a two-factor ICAPM for the cross-section of stock returns.     

A Reexamination of Real Stock Returns,Real Interest Rates,Real Activity,and Inflation: Evidence from a Large Data Set

Using the informational sufficiency procedure from Forni and Gambetti (2014) along with data from McCracken and Ng (2014), we update the results of Lee (1992) and find that his vector autoregression (VAR) is informationally deficient. To correct this problem, we estimate a factor augmented VAR (FAVAR) and analyze the differences once informational deficiency is corrected with an emphasis on the relationship between real stock returns and inflation. In particular, we examine Modigliani and Cohn's (1979) inflation illusion hypothesis, Fama's (1983) proxy hypothesis, and the “anticipated policy hypothesis.”     

Causal relations among stock returns and macroeconomic variables in a small,open economy

We investigate to what extent important results on relations among stock returns and macroeconomic factors from major markets are valid in a small, open economy by utilizing the multivariate vector autoregressive (VAR) approach on Norwegian data. Unlike many previous studies, which use a different methodology on other European markets, we establish several significant links. Consistent with US and Japanese findings, real interest rate changes affect both stock returns and inflation, and the stock market responds accurately to oil price changes. On the other hand, the stock market shows a delayed response to changes in domestic real activity.     

Correlations between stock returns and bond returns: income and substitution effects

We attempt to better understand the varying correlations between stock and bond returns across countries and over sample periods using international data. The observation is that there are two forces that affect the correlation between stock and bond returns. The force that drives a positive correlation is identified as the income effect. The force that drives a negative correlation is identified as the substitution effect. In combination, the two effects help determine the actual correlation between stock and bond returns. We contribute to the literature by proposing an empirical method, the structural vector autoregression (VAR) identification method, to identify the two—income and substitution—effects and to measure the relative importance of the two effects that determine the actual net relation between the two asset returns. We further provide some evidence that the income and substitution effects are related to, among other things, the size of the financial market, the growth and volatility (risk) of the economy, and the business cycle over time. In addition, the framework of the income and substitution effects helps us better understand the automatic stabilizing effects of the dynamic optimal asset allocation during business cycles.     

Dynamic Linkages among Budget Deficits,Interest Rates and the Stock Market*

This paper examines the dynamic linkages among the federal budget deficit, interest rates and the stock market for the United States from 1960 to 2006. The empirical strategy includes vector autoregression (VAR) and Granger causality analyses. The results suggest that budget deficits negatively impact upon stock returns, which implies a violation of the Ricardian Equivalence Proposition. Further analysis shows a higher sensitivity of stock returns to corporate taxes than to public spending. Finally, it is shown that although taxes are relevant for corporate profits in the short run, budget deficits are important for the stock market in the long run.     

Liquidity costs,idiosyncratic volatility and expected stock returns

This paper considers liquidity as an explanation for the positive association between expected idiosyncratic volatility (IV) and expected stock returns. Liquidity costs may affect the stock returns, through bid-ask bounce and other microstructure-induced noise, which will affect the estimation of IV. We use a novel method (developed by Weaver, 1991) to eliminate microstructure influences from stock closing price-based returns and then estimate IV. We show that there is a premium for IV in value-weighted portfolios, but this premium is less strong after correcting returns for microstructure bias. We further show that this premium is driven by liquidity in the prior month after correcting returns for microstructure noise. The pricing results from equally-weighted portfolios indicate that IV does not predict returns either before or after controlling for liquidity costs. These findings are robust after controlling for common risk factors as well as analysing double-sorted portfolios based on IV and liquidity.     

The international co-movements of Finish stocks

This paper provides new empirical evidence on the international co-movements of Finnish stocks. The vector autoregression (VAR) approach indicates that US and especially Swedish stock markets lead Finnish stock market returns by approximately one or two months. The results based on international market models indicate that the returns of individual Finnish stocks are significantly positively related to those of Sweden, while the relation between Finnish and US returns is significantly lower. The relation seems to vary clearly between industries, some industries being related to US markets as well. Significant time-series instability is reported in the results, however.     

The Comovement of US and UK Stock Markets

US and UK stock returns are highly positively correlated over the period 1918–99. Using VAR‐based variance decompositions, we investigate the nature of this comovement. Excess return innovations are decomposed into news about future dividends, real interest rates, and excess returns. We find that the latter news component is the most important in explaining stock return volatility in both the USA and the UK and that stock return news is highly correlated across countries. This is evidence against Beltratti and Shiller's (1993) finding that the comovement of US and UK stock markets can be explained in terms of a simple present value model. We interpret the comovement as indicating that equity premia in the two countries are hit by common real shocks.     

Linkages among European and world stock markets

Causal relations and dynamic interactions among equity returns in ten countries for the period 1983–1994 are analysed. An innovation accounting approach based on a multivariate vector autoregressive (VAR) model is used to estimate the proportion of each market return's forecast error attributable to innovations in foreign market returns. Three major results appear. The variance decompositions indicate a strong degree of economic interaction among stock markets. The US stock market has a considerable influence on stock market performance in almost every country, while there is no substantial inter-continental influence from the European stock markets on the world's two largest equity markets in New York and Tokyo. Finally, the pattern of the impulse-response functions illustrates a rapid international transmission of stock market events, supporting the hypothesis of international stock market efficiency.     

On the real estate market efficiency

This reseach reexamines the efficiency hypothesis of the real estate market using monthly data and the vector autoregressive (VAR) modelling technique. The tests focus on the causal linkage between real estate returns and a number of relevant financial and economic variables. An eight-by-eight VAR model is estimated using the FPE and the specific gravity criteria, in conjunction with an extensive series of specification tests. The empirical results distilled from system estimations suggest that the real estate market is efficient with respect to available information on the industrial production, the risk premia, the term structure of interest rates, and the monetary base. Movements in these variables are quickly and fully utilized by market agents, perhaps owing to the intensity with which their relationship with stock returns has been discussed in the literature and the popular media. However, the results also suggest the presence of a significant lagged relationship between real estate returns and fiscal policy moves, even when the paths through other potential determinants of these returns are taken into account. Of course, our finding that the fiscal policy measure is useful in predicting stock returns does not necessarily imply that the real estate market is inefficient. At a minimum, inefficiency is revealed only if a careful analysis of the budgetary process can help design a profitable (exploitable) trading strategy.     

UK Stock Returns and the Impact of Domestic Monetary Policy Shocks

Abstract:  We investigate the influence of changes in UK monetary policy on UK stock returns and the possible reasons behind such a response. Firstly, we conduct an event study to assess the impact of unexpected changes in monetary policy on aggregate and sectoral stock returns. The decomposition of unexpected changes in the policy rate is based on futures markets data. Secondly, using a variance decomposition in the spirit of Campbell (1991) we attempt to identity the channels behind the response of stock returns to monetary policy surprises. The variance decomposition results indicate that the monetary policy shock leads to a persistent negative response in terms of future excess returns for a number of sectors.     

The effects of oil price shocks on U.S. stock order flow imbalances and stock returns

This paper investigates for the first time the effects of oil demand shocks and oil supply shocks on stock order flow imbalances leading to changes in stock returns. Through the estimation of a structural VAR model, positive oil demand shocks are able to explain almost 36% of the observed variation in the daily average stock order flow imbalances measured by the buy/sell trades ratio; which consequently lead to a negative rather than positive stock returns reaction. In contrast, oil supply shocks exhibit a negative and marginally significant effect on stock order flow imbalances. Our aggregate analysis suggests that positive shocks on stock order flow imbalances are negatively related to stock returns. These effects are stronger for oil-related sectors when compared with the rest of the equities sectors.     

Stock Returns and Real Activity: A Century of Evidence

This paper analyzes the relation between real stock returns and real activity from 1889–1988. It replicates Fama's (1990) results for the 1953–1987 period using an additional 65 years of data. It also compares two measures of industrial production in the tests: (1) the series produced by Babson for 1889–1918, spliced with the Federal Reserve Board index of industrial production for 1919–1988, and (2) the new Miron and Romer (1989) index spliced with the Federal Reserve Board index in 1941. Fama's findings are robust for a much longer period—future production growth rates explain a large fraction of the variation in stock returns. The new Miron-Romer measure of industrial production is less closely related to stock price movements than the older Babson and Federal Reserve Board measures.