Loss from the chasing of MAX stocks: Evidence from China

We evaluate the implications of the MAX effect in the Chinese financial market. First, the MAX effect prevails in China: A zero-cost MAX strategy, which goes long (short) stocks with the highest (lowest) maximum daily return in the prior month, generates significant losses over the full sample period. Second, further analysis on firm characteristics confirms that the MAX stocks exhibit lottery-like features, and the (negative) performance of the MAX strategy varies over time and is related to investor sentiment. Third, the MAX effect gets weaker after the introduction of short-selling in 2010. Finally, we document that there exists a reversed MAX effect among mutual funds, because a similarly implemented MAX strategy generates significant positive risk-adjusted returns among equity funds in China.     

Asymmetric causality in-mean and in-variance among equity markets indexes

The aim of this study is to research asymmetric causality in-mean and variance among financial markets. The methodology used has several advantages: the estimation is jointly and not by pairs of variables, it identifies whether the causality is asymmetric (different effects from positive and negative returns), and, in the case of bidirectional relationships, it allows us to test whether the effect is the same in both directions. This study provides evidence of causality in-mean and variance among the daily returns of stock markets indexes from January 1, 1997 to December 31, 2014. The indexes are grouped by geographical areas to avoid problems of asynchrony with partially overlapping markets. The main results show that the causalities in-mean and in-variance are asymmetric with a different effect from positive and negative returns. Notably, by geographical areas, the Indian index SENSEX (symmetric) and the Chinese Shanghai Stock Exchange (asymmetric) are causatives in-mean for Asia, The Italian MIB 30 (asymmetric) is causative in-variance for Europe, and the USA DOW JONES 100 (symmetric) and STANDARD&POORS 500 (asymmetric) indexes are causatives in-mean and in-variance for America. Also, the bidirectional relationships between the DOW JONES 100 and STANDARD&POORS 500 in-mean and in-variance have the same effect in both directions.     

Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?

We study the potential merits of using trading and non-trading period market volatilities to model and forecast the stock volatility over the next one to 22 days. We demonstrate the role of overnight volatility information by estimating heterogeneous autoregressive (HAR) model specifications with and without a trading period market risk factor using ten years of high-frequency data for the 431 constituents of the S&P 500 index. The stocks’ own overnight squared returns perform poorly across stocks and forecast horizons, as well as in the asset allocation exercise. In contrast, we find overwhelming evidence that the market-level volatility, proxied by S&P Mini futures, matters significantly for improving the model fit and volatility forecasting accuracy. The greatest model fit and forecast improvements are found for short-term forecast horizons of up to five trading days, and for the non-trading period market-level volatility. The documented increase in forecast accuracy is found to be associated with the stocks’ sensitivity to the market risk factor. Finally, we show that both the trading and non-trading period market realized volatilities are relevant in an asset allocation context, as they increase the average returns, Sharpe ratios and certainty equivalent returns of a mean–variance investor.     

Firm size,economic risks,and the cross-section of international stock returns

Recent empirical evidence from developed markets indicates a negative relation between value premium and firm size. We find that the value premium in small stocks is consistently priced in the cross-section of international returns, whereas the value premium in big stocks is not. Based on US data, we show that the small-stock value premium is associated with business cycle news and reflects changes in macroeconomic, especially credit market related risks. Our results hold true for regional and global equity markets and remain valid after controlling for firm characteristics and prominent profitability and investment factors.     

States of psychological anchors and price behavior of Japanese yen futures

This study explores whether the relationship between Japanese yen futures returns and the corresponding equity returns is affected by the states of psychological anchors of the currency and stock markets. This study employs the linear-regression-based tree model (a machine learning method) to account for the framing effect of the anchors. The empirical results of the linear-regression-based tree model show that the currency price behaviors of momentum and reversal, and prediction by equity markets, vary with the anchors. Empirical evidence also indicates that the linear-regression-based tree model outperforms the OLS model based on the estimation results and out-of-sample forecasting. The forecasting performance of the linear-regression-based tree model can be improved along with an increase in the forecasting period.     

Acquiring firms' stock returns: Methods of payment,change in leverage,and management ownership

This study examines the effects of the method of payment, change in leverage, and management equity ownership on the acquiring firm's stock returns around the initial announcement date of the merger. Results indicate that stockholders of mergers financed with stocks suffer significant losses. These losses are larger when management ownership is low and smaller in mergers that resulted in acquiring firm leverage decreases. Stockholders of acquiring firms involved in cash mergers gain significant abnormal returns, provided that acquiring firms increase their leverage and that managerial ownership is high. When management equity ownership is low, leverage has no effect on stock returns. When management ownership is high, mergers which resulted in acquiring firm leverage increases have significant positive effects, and those which resulted in acquiring firm leverage decreases have negative but insignificant effects.     

The effect of interconnectivity on stock returns during the Global Financial Crisis

This paper examines the role of interconnectivity in global stock markets during the Global Financial Crisis (GFC) using a comprehensive dataset of 8,827 firms traded in developed and emerging markets. Our contribution includes two key findings. We first use a difference-in-differences approach to show that stocks in countries with higher trade openness ex-ante to the GFC experienced lower average and annual cumulative returns of 9.08 p.p. and 36.32 p.p., respectively, compared to stocks traded in less exposed countries, one year after the crisis outbreak. Second, we employ complex network theory to analyze the role of network interconnectedness in our baseline results. To construct the network of interdependence between stock returns, we utilize a regularized Vector Autoregression Model, which enables us to overcome the limitations of commonly used correlation networks. Our findings suggest that while a firm’s high connectivity before the crisis can alleviate adverse shock effects resulting from export dependence, this effect may be weakened if the firm’s performance is closely linked to central firms.     

Unconventional monetary policy and financialization of commodities

Our paper has two stages of analysis. First of all, we examine whether volatility spillover between US equity and commodity markets has significantly changed with the heavy influx of index traders in commodity derivatives markets, which is a phenomenon referred to as financialization. Given that previous findings show institutional traders enter into commodity markets at high liquidity episodes, in the second stage of our analysis, we investigate the particular impact of US quantitative easing policy on spillover between commodity and US stocks. Our results indicate that during financialization period, spillover from stocks to commodities have significantly increased for almost all commodities. More importantly, we show that quantitative easing is one of the underlying reasons for increasing volatility spillover between markets. Including interest rate, currency factors or default spread does not diminish the explicit role of quantitative easing on spillovers.     

Spillover effects on the sectoral returns for australian and New Zealand equity markets

In this paper, we examine the return and volatility spillovers, together with the trend spillovers on the sectoral equity returns for Australian and New Zealand markets. We find that the return spillovers of industrial, local and global shocks have a limited effect on Australian and New Zealand sector returns, whereas the volatility spillovers play a significant role on explaining the volatility of sector equity indices. Furthermore, we discover that the volatility spillover effects of the global and industrial shocks are greater in magnitude for explaining the volatility of the Australian sectors than those of New Zealand, particularly basic materials, oil and gas, technology and telecom sectors. By employing the trend spillover model, we find that the volatility spillover effects of global sector indices have been increasing over the volatility of the Australian sectoral returns until now. This finding proposes that Australian sector equity market is more integrated with the world than the New Zealand counterpart.     

The stochastic volatility in mean model and automation: Evidence from TSE

This paper investigates the behavior of volatility in Canadian equity markets before and after automation. We employ a stochastic volatility in mean (SVM) model that incorporates the unobserved volatility as an explanatory variable in the mean equation. The volatility persistent estimates all increase post-automation, with the scaling parameter increasing as well. The parameter estimates which measure both the ex ante relationship between returns and volatility and the volatility feedback effect are found to be negative for all series, and to increase post-automation. Our results fall in line with those of (French, K.R., Schwert, G.W., & Stanbaugh, R.F. (1987). Expected stock returns and volatility. Journal of Financial Economics, 19, 3–29) who find similar relationship between unexpected volatility dynamics and returns and confirm the hypothesis that rational risk-averse investors require higher expected returns when unanticipated increase in future volatility are highly persistent. Finally, our findings are consistent since higher values of persistence are combined with larger negative values for the in-mean parameter.     

A Respecified Fama French Three‐Factor Model for the New European Union Member States

This study uses factor models to explain stock market returns in the Eastern European (EE) countries that joined the European Union (EU) in 2004. In line with other studies, we find that the market value of equity component in the Fama French (1993) three‐factor model performs poorly when applied to our emerging markets dataset. We propose a significant amendment to the standard three‐factor model by replacing the market value of equity factor with a term that proxies for accounting manipulation. We show that our three‐factor model is able to explain returns in the EE EU nations significantly better than the Fama French (1993) three‐factor model, hereby offering an alternative model for use in the numerous markets in which previous studies have found little correlation between market value of equity and equity returns.     

Individual stock sentiment beta and stock returns

Using the data in Chinese stock market, we measure the individual stock sentiment beta, which is defined as the sensitivity of individual stock returns to the individual stock sentiment changes. We demonstrate that stocks in the highest individual stock sentiment beta portfolio have significantly higher excess returns, CAPM alpha, Fama-French three-factor alpha and Fama-French five-factor alpha. Besides, we find that the high individual stock sentiment beta stocks are smaller, younger, more volatile stocks with higher price and higher market beta. After controlling for firm characteristic, the returns of High-Low individual stock sentiment beta portfolios are still significantly positive. Moreover, we show the effect of the individual stock sentiment beta on stock returns is positive and significant in different stock markets, in different sample periods, and in bull and bear market. Besides, the results of the Bayes-Stein individual stock sentiment beta are still stable.     

How can investors build a better portfolio in small open economies? Evidence from Asia’s Four Little Dragons

This study investigates the role of hedging and portfolio design among stocks, exchange rates, and gold in small open economies (SOEs) from 4 January 2000 to 31 March 2020. We adopt the trivariate dynamic conditional correlation-fractionally integrated asymmetric power ARCH model and unconditional quantile regression model, and our findings show that the hedging role of the U.S. dollar (USD) and gold against stocks differs under regular and extreme market conditions. The USD can act as a powerful hedge asset for stocks in regular market periods. Moreover, during the global financial crisis and COVID-19 outbreak, the safe-haven effect of gold becomes stronger for almost all stocks, whereas the USD can serve as a strong safe haven against stock markets of Korea, Taiwan, and Singapore when stock returns are extremely low. In terms of portfolio designing, we find that adding the USD and gold to portfolios improves their hedging effectiveness, and the optimally weighted stock-USD-gold portfolio is the best portfolio strategy, irrespective of referring to return or risk.     

Modelling Regime‐Specific Stock Price Volatility*

Single‐state generalized autoregressive conditional heteroscedasticity (GARCH) models identify only one mechanism governing the response of volatility to market shocks, and the conditional higher moments are constant, unless modelled explicitly. So they neither capture state‐dependent behaviour of volatility nor explain why the equity index skew persists into long‐dated options. Markov switching (MS) GARCH models specify several volatility states with endogenous conditional skewness and kurtosis; of these the simplest to estimate is normal mixture (NM) GARCH, which has constant state probabilities. We introduce a state‐dependent leverage effect to NM‐GARCH and thereby explain the observed characteristics of equity index returns and implied volatility skews, without resorting to time‐varying volatility risk premia. An empirical study on European equity indices identifies two‐state asymmetric NM‐GARCH as the best fit of the 15 models considered. During stable markets volatility behaviour is broadly similar across all indices, but the crash probability and the behaviour of returns and volatility during a crash depends on the index. The volatility mean‐reversion and leverage effects during crash markets are quite different from those in the stable regime.     

Equity market contagion during the global financial crisis: Evidence from the world's eight largest economies

The global financial crisis (2007–2009) saw sharp declines in stock markets around the world, affecting both advanced and emerging markets. In this paper we test for the existence of equity market contagion originating from the US to advanced and emerging markets during the crisis period. Using a latent factor model, we provide strong evidence of contagion effects in both advanced and emerging equity markets. In the aggregate equity market indices, contagion from the US explains a large portion of the variance in stock returns in both advanced and emerging markets. However, in the financial sector indices we find less evidence of contagion than in the aggregate indices, and this is particularly the case for the advanced markets. The results suggest that contagion effects are not strongly related to high levels of global integration.     

STRATEGIC ASSET ALLOCATION FOR LONG‐TERM INVESTORS: PARAMETER UNCERTAINTY AND PRIOR INFORMATION

We study the effect of parameter uncertainty on the long‐run risk for three asset classes: stocks, bills and bonds. Using a Bayesian vector autoregression with an uninformative prior we find that parameter uncertainty raises the annualized long‐run volatilities of all three asset classes proportionally with the same factor relative to volatilities that are conditional on maximum likelihood parameter estimates. As a result, the horizon effect in optimal asset allocations is much weaker compared to models in which only equity returns are subject to parameter uncertainty. Results are sensitive to alternative informative priors, but generally the term structure of risk for stocks and bonds is relatively flat for investment horizons up to 15 years. Copyright © 2013 John Wiley & Sons, Ltd.     

A spatial dominance approach to evaluate the performance of stocks and bonds: Does the investment horizon matter?

The common advice by practitioners is to allocate a greater proportion of stocks for long-term investors than for short-term investors. However, part of the academic literature disagrees with this advice. We use a spatial dominance test which is suited for comparing alternative investments for a given time horizon. Using daily data for the US from 1962 to 2012, we test for dominance of cumulative returns series for stocks versus bonds at different investment horizons from 1 to 15 years. We find evidence that bonds second order spatially dominate stocks for horizons from 1 to 4 years. In contrast, for horizons of 6 years and longer, we find evidence that stocks dominate bonds. The conclusion that bonds dominate stocks at short horizons, while stocks dominate bonds at long horizons is consistent across different periods and international markets. When different portfolios of stocks and bonds are compared, we find that for long investment horizons only those portfolios with a sufficiently high proportion of stocks are efficient in the sense of spatial dominance.     

欧洲股票市场的规模和动因:基于不同β系数的资本资产定价模型实证研究

我们选用在13个欧洲股市上市的证券,形成规模和动因组合。我们不仅发现规模溢价的证据,还发现8个样本市场存在重大动因收益率。这些收益率可能不构成异常现象,因为它们与不同β值的资本资产定价模型一致。我们还发现,系统风险与经济周期有关。此外,研究结果显示,虽然规模和动因收益率显著,但是难以在中、短期利用它们,因为在我们的样本中只有极少年份它们的数值为正且很大。     

Mutual excitation between OECD stock and oil markets: A conditional intensity extreme value approach

We analyze the degree of mutual excitation that exists between extreme events across the stock markets of OECD member nations and the Brent and WTI crude oil markets. For this analysis, marked point process models are proposed which are able to capture the dynamics of the intensity of occurrence and comovement during periods of crisis. The results show a significant, negative interdependence between most OECD markets, especially those of the USA, Japan and France. These major oil importing countries display links between equity market losses and positive returns in both oil markets. However, positive interdependence is not observed between any of the OECD countries except for South Korea. The great advantage of this methodology is that, apart from using the size distribution of extreme events, it also uses the occurrence times of extreme events as a source of information. With this information, these models are better able to capture the stylized facts of extreme events in financial markets such as clustering behavior and cross-excitation.     

The temporal dimension of risk

If returns are stationary, then the risk of an asset in any time frequency can be estimated from the risk of the asset in any other time frequency through a simple linear rescaling. This implies that short-term risk carries reliable information about long-term risk, and both data frequencies and investment horizons are irrelevant when evaluating an asset’s risk. However, most series of stock returns are nonstationary, which if ignored may lead investors to make significant mistakes. Using recent data from fourteen European securities markets, I show that investors that mistakenly assume stationarity are bound to underestimate the total and systematic risk (and overestimate the risk-adjusted returns) of European stocks. The underestimation of total risk ranges between .25% and 2.18% a month, and averages almost 1% a month.