International comovement of stock market returns: A wavelet analysis

The assessment of the comovement among international stock markets is of key interest, for example, for the international portfolio diversification literature. In this paper, we re-examine such comovement by resorting to a novel approach, wavelet analysis. Wavelet analysis allows one to measure the comovement in the time–frequency space. In this way, one can characterize how international stock returns relate in the time and frequency domains simultaneously, which allows one to provide a richer analysis of the comovement. We focus on Germany, Japan, UK and US and the analysis is done at both the aggregate and sectoral levels.     

The linkage between the US and Korean stock markets: the case of NASDAQ, KOSDAQ, and the semiconductor stocks

This paper examines the interrelationship between stock prices in the US and Korea by applying the vector autoregression (VAR) model to the daily stock prices at three different level of aggregation – the national aggregate index level, the high-tech industry level and the semiconductor firm level – for the period of July 1996 through February 2001. The major findings of this study are as follows. First, the US stock market plays a leading role over the Korean market at every level of aggregation. The reverse direction of influence, from Korea to the US, was found to be minimal. Second, the evidence also suggests that the speed of transmission of innovation from the US to Korea is swift and finished for the most part within a 24-h period, although it takes three or four days to complete the whole process. Third, the influence of the US stock prices on Korean stock prices, which is measured by the innovation transmission using the impulse–response function (IRF) analysis, seems to be somewhat stronger in the composite national stock price indices and the tech-laden indices than high-tech firms. Fourth, at the firm level, the influence of Micron Technology on the leading semiconductor manufacturers in Korea is shown to be strong and persistent by passing about 34 percent of its innovations to the Korean firms within the three-day period. The impact of IBM and Intel on the Korean chip makers seems to be relatively smaller. Finally, stock prices in Korea, national stock price indices and individual high-tech stocks alike, have become much more responsive to innovations in the US stock prices after the 1997 financial crisis. The implications of the main findings in this paper are also discussed.     

Auditor quality effects on the relationship between accruals,cash flows and equity returns: a variance decomposition analysis

In this paper, we examine the relative importance of the cash flow and accruals components of earnings in explaining the variation in UK company equity returns, together with the extent to which these relationships vary by auditor quality. We use a multivariate time-series approach that can be reconciled to a log-linear theoretical valuation model and, unlike the standard linear regression of returns on earnings components, accommodates time-varying discount rates. Based on a decomposition of the variance of equity returns, cash flows and accruals, our results indicate that both cash flow news and accruals news are important drivers of UK equity returns, although cash flows are more influential than accruals. We also find that variation in both earnings components has a more significant effect on returns for clients of large auditors. Finally, our results provide mixed evidence on the question of whether the impact of auditor quality is highest for the accruals component of earnings.     

An analysis of inflation and stock returns for the UK

Whether common stocks provide a hedge against inflation has been long debated. This paper focuses on this question by investigating the relationship between inflation and stock returns in the short term and medium term and under different inflationary regimes using the UK data. Empirical evidence suggests that the UK stock market fails to hedge against inflation in the short term. However, in the medium term there is mixed results. Results from different inflationary regimes show that the relationship between inflation and returns varies in different regimes.     

A multi-country test of the Fisher model for stock returns

This article provides a test of the Fisher model, linking expected stock returns and inflation, based on international data. Since the Fisher model is ‘universal’ and calls for a slope of 1 in any country, we improve the testing power by conducting a joint test over eight countries. The pooling of data for several countries seems to reduce the small-sample bias. We test the Fisher model, using an instrumental variable approach, for holding-period horizons ranging from 1–12 months. The Fisher model is not rejected at any horizon: however, the magnitude of the slope coefficient lends stronger support at long horizons. This study using multi-country panel data provides evidence corroborating the finding of Boudoukh and Richardson (1993) that the Fisher model holds at long horizons (5 years), using 180 years of US data.     

A nested factor model for non-linear dependencies in stock returns

The aim of our work is to propose a natural framework to account for all the empirically known properties of the multivariate distribution of stock returns. We define and study a ‘nested factor model’, where the linear factors part is standard, but where the log-volatility of the linear factors and of the residuals are themselves endowed with a factor structure and residuals. We propose a calibration procedure to estimate these log-vol factors and the residuals. We find that whereas the number of relevant linear factors is relatively large (10 or more), only two or three log-vol factors emerge in our analysis of the data. In fact, a minimal model where only one log-vol factor is considered is already very satisfactory, as it accurately reproduces the properties of bivariate copulas, in particular, the dependence of the medial point on the linear correlation coefficient, as reported in Chicheportiche and Bouchaud [Int. J. Theor. Appl. Finance, 2012, 15]. We have tested the ability of the model to predict out-of-sample the risk of non-linear portfolios, and found that it performs significantly better than other schemes.     

A long memory property of stock market returns and a new model

A ‘long memory’ property of stock market returns is investigated in this paper. It is found that not only there is substantially more correlation between absolute returns than returns themselves, but the power transformation of the absolute return ¦r_t¦^d also has quite high autocorrelation for long lags. It is possible to characterize ¦r_t¦^d to be ‘long memory’ and this property is strongest when d is around 1. This result appears to argue against ARCH type specifications based upon squared returns. But our Monte-Carlo study shows that both ARCH type models based on squared returns and those based on absolute return can produce this property. A new general class of models is proposed which allows the power δ of the heteroskedasticity equation to be estimated from the data.     

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.     

International competition and exchange rate shocks: a cross-country industry analysis of stock returns

This article systematically examines the importance of exchangerate movements and industry competition for stock returns. Commonshocks to industries across countries are more important thancompetitive shocks due to changes in exchange rates. Weeklyexchange rate shocks explain almost nothing of the relativeperformance of industries. Using returns measured over longerhorizons, the importance of exchange rate shocks increases slightlyand the importance of industry common shocks increases moresubstantially. Both industry and exchange rate shocks are moreimportant for industries that produce internationally tradedgoods, but the importance of these shocks is economically smallfor these industries as well.     

Detecting log-periodicity in a regime-switching model of stock returns

Log-periodic precursors have been identified before most and perhaps all financial crashes of the Twentieth Century, but efforts to statistically validate the leading model of log-periodicity, the Johansen–Ledoit–Sornette (JLS) model, have generally failed. The main feature of this model is that log-harmonic fluctuations in financial prices are driven by similar fluctuations in expected daily returns. Here we search more broadly for evidence of any log-periodic variation in expected daily returns by estimating a regime-switching model of stock returns in which the mean return fluctuates between a high and a low value. We find such evidence prior to the two largest drawdowns in the S&P 500 since 1950. However, if we estimate a log-harmonic specification for the stock index for the same time periods, fixing the frequency and critical time according to the results of the regime-switching model, the parameters do not satisfy restrictions imposed by the JLS model.     

Speculative trading and stock returns: A stochastic dominance analysis of the Chinese A-share market

The pricing of A-shares in China has long puzzled financial economists. This paper applies recent tests of stochastic dominance (SD) to examine whether differences in the return distributions of A- and B-shares in China are consistent with market efficiency. As SD is nonparametric, market efficiency can be examined without the joint test problem arising from misspecifications in the asset pricing benchmark. Our results show A-shares have second-order dominated B-shares from 1996 to 2005. This dominance was most significant during the market segmentation period, but has continued, albeit to a lesser extent even after the B-share market was opened to local investors in 2001. Our results are robust to using residual returns from an international asset pricing model instead of raw returns. We conclude that the superior performance of A-shares cannot be attributed to risk. The results are more likely due to a return bias caused by intense speculation among retail individuals under limited arbitrage.     

A model for stock market returns: non-Gaussian fluctuations and financial factors

While there are various theories to account for the large variations in stock prices, some observed statistical aspects require further analysis. A model is proposed for aggregate stock prices, based on observed data, rather than any efficient market hypothesis, and considering jumps in statistical parameters between phases of generally increasing, or generally decreasing, aggregate stock prices. The model relates a critical parameter for short-term behaviour directly to financial factors, especially interest rates, to explain large short-term variations which follow a non-Gaussian distribution. Economic fundamentals may affect changes over longer periods.      

The role of future economic conditions in the cross-section of stock returns: Evidence from the US and UK

Our study investigates the explanatory power of future economic conditions on individual stock returns in the US and UK equity markets. We analyse a new trading strategy that is based on rational forecasts of future real activity. In addition, we specifically examine the performance of this trading strategy applied to two different classifications of stocks – procyclical stocks and countercyclical stocks. Our findings indicate a strong persistence in the relationship between returns on pro-cyclical stocks and the business cycle. However, such persistence is not present when moving to counter-cyclical stocks in the US and the UK. From this we suggest that US and UK equity investors who predict future real activity accurately can improve their investment profitability by longing pro-cyclical stocks when they expect future economic conditions to be above the long-run trend and shorting those stocks when future activity is anticipated to be below the steady state.     

A note on portfolio choice for sovereign wealth funds

The current vast account surpluses of commodity-rich nations, combined with record account deficits in developed markets (the United States, Britain) have created a new type of investor. Sovereign wealth funds (SWF) are instrumental in deciding how these surpluses will be invested. We need to better understand the investment problem for an SWF in order to project future investment flows. Extending Gintschel and Scherer (J. Asset Manag. 9(3):215–238, 2008), we apply the portfolio choice problem for a sovereign wealth fund in a Campbell and Viceira (Strategic Asset Allocation, 2002) strategic asset allocation framework. Changing the analysis from a one to a multi-period framework allows us to establish a three-fund separation. We split the optimal portfolio for an SWF into speculative demand as well as hedge demand against oil price shocks and shocks to the short-term risk-free rate. In addition, all terms now depend on the investor’s time horizon. We show that oil-rich countries should hold bonds and that the optimal investment policy for an SWF as a long-term investor is determined by long-run covariance matrices that differ from the correlation inputs that one-period (myopic) investors use.

Impact of idiosyncratic volatility on stock returns: A cross-sectional study

This paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMM-type estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual US stock return data over the course of 2000–2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect.     

A 10-year retrospective on the determinants of Russian stock returns

We study factors influencing returns at the Russian stock market from 1995 to 2004, putting emphasis on how these evolved over time. We find that the relationship is highly unstable and this instability is not confined to financial crises alone. Most computed statistics exhibit constant ups and downs, but there has been recently a sharp rise in explainability of stock returns. Domestic factors have been playing a gradually diminishing role, while the importance of international factors has been increasing. In recent years, the effect of oil prices and foreign exchange rates has diminished, the impact of US stock prices and international and domestic interest rates has increased, while the influence of monetary aggregates such as gold reserves and credit balances has fallen to practically zero.     

A macroeconomic hedge portfolio and the cross section of stock returns

We use a stock's returns on days when important macroeconomic news is released to form a hedge portfolio, which is long (short) in stocks which have a sensitive (insensitive) reaction to the surprise component of the macroeconomic news. This macroeconomic hedge portfolio (MHP) earns a risk premium of about 5% p.a. over time and a similar premium when used as a risk factor in an asset pricing model. This premium can be interpreted as a cost of an insurance against unexpected changes in an investor's marginal utility. We show that risk premiums associated with the MHP are estimated with a higher precision than traditional macroeconomic tracking portfolios. Furthermore, when the MHP is present in a common factor model, risk factors like high minus low lose much of their ability to explain the cross section of stock returns.     

A careful re-examination of seasonality in international stock markets: Comment on sentiment and stock returns

In questioning Kamstra, Kramer, and Levi’s (2003) finding of an economically and statistically significant seasonal affective disorder (SAD) effect, Kelly and Meschke (2010) make errors of commission and omission. They misrepresent their empirical results, claiming that the SAD effect arises due to a “mechanically induced” effect that is non-existent, labeling the SAD effect a “turn-of-year” effect (when in fact their models and ours separately control for turn-of-year effects), and ignoring coefficient-estimate patterns that strongly support the SAD effect. Our analysis of their data shows, even using their low-power statistical tests, there is significant international evidence supporting the SAD effect. Employing modern, panel/time-series statistical methods strengthens the case dramatically. Additionally, Kelly and Meschke represent the finance, psychology, and medical literatures in misleading ways, describing some findings as opposite to those reported by the researchers themselves, and choosing selective quotes that could easily lead readers to a distorted understanding of these findings.     

Cross-sectional analysis of Swedish stock returns with time-varying beta: the Swedish stock market 1983–96

This paper analyses the ability of beta and other factors, like firm size and book-to-market, to explain cross‐sectional variation in average stock returns on the Swedish stock market for the period 1983–96. We use a bivariate GARCH(1,1) process to estimate time-varying betas for asset returns. The estimated variances of these betas, derived from a Taylor series approximation, are used for correcting errors in variables. An extreme bound analysis is utilized for testing the sensitivity of the estimated coefficients to changes in the set of included explanatory variables.
Our results show that the estimated conditional beta is a more accurate measure of the true market beta than the beta estimated by OLS. The coefficient for beta is not significantly different from zero, while the variables book-to-market and leverage have significant coefficients, and the latter coefficients are also robust to model specification. Excluding the down turn 1990–92 from the sample shows that the significance of the risk premium for leverage might be considered as an industry effect during this extreme period. Finally, we find a close dependence between the risk premium for beta and that for size and book-to-market. The omission of each of these variables may cause statistical bias in the estimated coefficient for beta.