Horse race of weekly idiosyncratic momentum strategies with respect to various risk metrics: Evidence from the Chinese stock market

This paper focuses on the horse race of weekly idiosyncratic momentum (IMOM) with respect to various idiosyncratic risk metrics. Using the A-share individual stocks in the Chinese market from January 1997 to December 2017, we first evaluate the performance of the weekly momentum based on raw returns and idiosyncratic returns, respectively. After that the univariate portfolio analysis is conducted to investigate the return predictability with respect to various idiosyncratic risk metrics. Further, we perform a comparative study on the performance of the IMOM portfolios with respect to various risk metrics. At last, we explore the possible explanations to IMOM as well as risk-based IMOM portfolios. We find that 1) there are prevailing contrarian effect and IMOM effect for the whole sample; 2) the negative relations exist between most of the idiosyncratic risk metrics and the cross-sectional stock returns, and better performance is linked to idiosyncratic volatility (IVol) and maximum drawdowns (IMDs); 3) additionally, the IVol-based and IMD-based IMOM portfolios exhibit better explanatory power to the IMOM portfolios with respect to other risk metrics; 4) finally, higher profitability of IMOM as well as IVol-based and IMD-based IMOM portfolios is found to be related to upside market states, high levels of liquidity and high levels of investor sentiment.     

Value at risk and return in Chinese and the US stock markets: Double long memory and fractional cointegration

Given that the United States is an engine of global stock market while China is the largest emerging market with a cornucopia of anomalies in particular, it is vital to investigate the risk-return relationship in the two markets. This paper brings new insights not only into risk-return tradeoff, but also to the leverage effect, with the application of the fractionally co-integrated vector auto-regression (FCVAR) model capturing the fractional cointegrated relationship and long memory property. Results show that China stock markets own the property of double long memory but the US markets don’t. Most of all, in the US market, a positive risk-return tradeoff exists for the whole sample while after the crisis, even we find the negative relation, it’s not a volatility feedback effect but low risk and high returns. However, there is only a volatility feedback effect in China stock markets. Besides, there is a leverage effect in the US market, while Chinese market exhibits a reverse one, another anomaly, indicating significant difference in the two markets again.     

Lottery mindset,mispricing and idiosyncratic volatility puzzle: Evidence from the Chinese stock market

This study investigates the MAX effect regarding lottery mindset in the Chinese stock market. The MAX effect significantly affects stock returns through quintile portfolio and cross-sectional regression analyses. The most-overpriced stock groups, as categorized by mispricing index, show more support for the MAX effect. However, the idiosyncratic volatility (IVOL) effect continues regardless of consideration for the MAX effect, indicating that the MAX effect is not a source of the IVOL effect. Our results suggest that the MAX effect, which is highly relevant for overpriced stocks, might have information for determining stock price, and appears to be independent from information of the IVOL effect in the Chinese stock market.     

Idiosyncratic volatility puzzle exists at the country level

This paper reexamines the idiosyncratic volatility puzzle using 47 stock market indices from 1995 to 2016. We find that country-specific idiosyncratic volatility is significantly and negatively related to subsequent returns in the international markets, confirming the existence of the idiosyncratic volatility puzzle at the country level. Our results show that the positive relationship between idiosyncratic volatility and country-specific index returns documented by Bali and Cakici, 2010, Hueng and Yau, 2013 is not robust to sample selections and model misspecifications. We show that the country-level idiosyncratic volatility puzzle consistently exists after controlling for different model specifications and market segmentation in various subsamples.     

Dynamic time series momentum of cryptocurrencies

This paper examines the momentum effect for twenty cryptocurrencies compared to the US stock market. For this purpose, we implement a dynamic modeling approach to define and test momentum periods that follow a formation period for interday and various intraday price levels. We find evidence that large proportions of the asset classes’ formation periods are followed by momentum periods, strongly supporting the momentum effect. In particular cryptocurrencies have significantly larger and longer momentum periods in all frequencies which we attribute to the lower derivability of their intrinsic value leading to a higher degree of noise traders in the market. A momentum trading strategy based on the identical approach outperforms a buy-hold strategy for both asset classes, while only cryptocurrencies have higher risk-adjusted returns and lower downside risks than a passive investment. We also find critical price levels during structural elements of the momentum period where the volatility shortly but intensively increases and consequently initiates a price impulse in the direction of the momentum.     

Heterogeneous relationship between IPO return and risk across idiosyncratic variance characteristics

This paper analyzes the levels and changes in the post-IPO stock return volatility and provides insights into market responses to the presence of firm-specific risk. First, we document a negative relation between initial idiosyncratic volatility level and the post-IPO volatility change in that initially low volatility firms have more volatility increase and vice verse. This evidence suggests fundamental firm-specific changes after the IPO. Further, we find that underpricing and short-run post-IPO returns are positively related to the initial and corresponding idiosyncratic risk level. This finding suggests that underpricing compensates investors for acquiring costly information and firm-specific risk information is being incorporated into offer prices. Finally, we find that higher long-run post-IPO performance is related to both lower initial risk level and decreasing risk in the first year after the IPO.     

Economic policy uncertainty,oil price volatility and stock market returns: Evidence from a nonlinear model

This paper investigates the nonlinear relationship between economic policy uncertainty, oil price volatility and stock market returns for 25 countries by applying the panel smooth transition regression model. We find that oil price volatility has a negative effect on stock returns, and this effect increases with economic policy uncertainty. Furthermore, there is pronounced heterogeneity in responses. First, oil-exporting countries whose economies depend more on oil prices respond more strongly to oil price volatility than oil-importing countries. Second, stock returns of developing countries are more susceptible to oil price volatility than that of developed countries. Third, crisis plays a crucial role in the relation between oil price volatility and stock returns.     

Tax aggressiveness and idiosyncratic volatility

This study finds that aggressive tax strategies adopted by a firm affect idiosyncratic stock return volatility. Aggressive tax strategies, which I measure as tax paid by a firm divided by pretax income (adjusted for special items), are associated with higher levels of idiosyncratic stock volatility. Uncertainty associated with tax strategies may result due to several factors, such as penalties, fines, and additional tax payments if particular tax strategies are disallowed by taxation authorities, or if there are changes in tax rules. Such uncertainty affects the future cash flows of a firm and is reflected in more volatile stock returns. Financial constraints, corporate governance mechanisms, and information environments surrounding a firm influence the relation between idiosyncratic volatility and effective tax rates.     

Evolution of price effects after one-day abnormal returns in the US stock market

This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market, using Dow Jones Index over the period 1890–2018. We utilise several statistical tests and econometric methods (the modified cumulative abnormal return approach, regression analysis with dummy variables, R/S analysis (Hurst, 1951), and the trading simulation approach). The results suggest that a strong momentum effect between 1940 and 1980 after a day of positive abnormal returns was present in the US stock market, and it was exploitable for profit. However, after the 1980s this has since disappeared. Overall, price effects after one-day abnormal returns during the analysed period tend to be unstable in terms of their strength and direction (momentum or contrarian effect). Nowadays, the evidence for the price effects after one-day abnormal returns in the US stock market is weak. Our results, therefore, are consistent with the Adaptive Market Hypothesis (Lo, 2004).     

Expected market returns: SVIX,realized volatility,and the role of dividends

This note provides a replication of Martin's (Quarterly Journal of Economics, 2017, 132(1), 367–433) finding that the implied volatility measure SVIX predicts US stock market returns up to 12‐month horizons. I find that this result holds for both S&P 500 and CRSP market returns, regardless of whether returns include or exclude dividends. The predictability largely disappears after the SVIX index is replaced by an exponentially weighted moving average measure of realized volatility, suggesting that SVIX holds incremental forward‐looking information compared to realized volatility, despite the high correlation between the two volatility measures.     

Positive IVOL-MAX effect: A study on the Singapore Stock Market

This paper demonstrates a positive and significant IVOL effect in the Singapore Stock Market meaning that the highly volatile stocks are showing better returns in the subsequent month. More explicitly, there is a strong positive relationship between stock’s idiosyncratic volatility (IVOL) and its subsequent month’s return in the Singapore equity market. This positive IVOL effect is stronger only for small market-statistic firms. But for the Large capital firms, the positive IVOL effect is insignificant. In addition, this paper shows that the relationship between maximum daily return over a month (MAX) and the subsequent month’s return is positive and significant in this market. However, IVOL is the true effect of this market rather than MAX.     

The VIX,the variance premium and stock market volatility

We decompose the squared VIX index, derived from US S&P500 options prices, into the conditional variance of stock returns and the equity variance premium. We evaluate a plethora of state-of-the-art volatility forecasting models to produce an accurate measure of the conditional variance. We then examine the predictive power of the VIX and its two components for stock market returns, economic activity and financial instability. The variance premium predicts stock returns while the conditional stock market variance predicts economic activity and has a relatively higher predictive power for financial instability than does the variance premium.     

Shifts in volatility driven by large stock market shocks

This paper presents an extension of the stochastic volatility model which allows for level shifts in volatility of stock market returns, known as structural breaks. These shifts are endogenously driven by large return shocks (innovations), reflecting large pieces of market news. These shocks are identified from the data as being bigger in absolute terms than the values of two threshold parameters of the model: one for the negative shocks and one for the positive shocks. The model can be employed to investigate different sources of stock market volatility shifts driven by market news, without relying on exogenous information. In addition to this, it has a number of interesting features which enable us to study the effects of large return shocks on future levels of market volatility. The above properties of the model are shown based on a study for the US stock market volatility.     

Oil price uncertainty and movements in the US government bond risk premia

In this paper, we analyze the predictability of the movements of bond premia of US Treasury due to oil price uncertainty over the monthly period 1953:06 to 2016:12. For our purpose, we use a higher order nonparametric causality-in-quantiles framework, which in turn, allows us to test for predictability over the entire conditional distribution of not only bond returns, but also its volatility, by controlling for misspecification due to uncaptured nonlinearity and structural breaks, which we show to exist in our data. We find that oil uncertainty not only predicts (increases) US bond returns, but also its volatility, with the effect on the latter being stronger. In addition, oil uncertainty tends to have a stronger impact on the shortest and longest maturities (2- and 5-year), and relatively weaker impact on bonds with medium-term (3- and 4-year) maturities. Our results are robust to alternative measures of oil market uncertainty and bond market volatility.     

Volatility analysis of precious metals returns and oil returns: An ICSS approach

This study examines volatility persistence on precious metals returns taking into account oil returns and the three world major stock equity indices (Dow Jones Industrial, FTSE 100, and Nikkei 225) using daily data over the sample period January 1995 to May 2008; the aim is to analyze market relationships before the global financial crisis. We first determine when large changes in the volatility of each market returns occur by identifying major global events that would increase fluctuations in these markets. The Iterated Cumulative Sums of Squares (ICSS) algorithm was used to identify the existence of structural breaks or sudden changes in the variance of returns. In each market the standardized residuals were obtained through the GARCH(1,1) mean equation. Our main results identify a clear relationship between precious metals returns and oil returns, while the interaction between precious metals and stock returns seems to be an independent one in the case of gold with mixed results for silver and platinum. In relation to volatility persistence, the results show clear evidence of high volatility persistence between these markets, especially during times when markets were affected by excessive volatility due to economic and financial shocks.     

The political uncertainty and stock market behavior in emerging democracy: the case of Taiwan

This paper examines the congressional effect between the pre- and post-democratization on the stock market by the asymmetric Generalized Autoregressive Conditional Heterosce desticity (GARCH) model in the period 1984–2004. The results found that the congressional effect is negative effect on stock returns but volatility is not significant. However, the democratic effect on stock returns is negative and increased of volatility. Moreover, the congressional effect on stock market returns following democratization significantly exceeds that before democratization, but have no significant effect for the volatility in the same circumstances. These results provide evidences consistent with the contention of liberalization (Hayek, Am. Econ. Rev. 35, 519–530, Individualism and Economic order, The university of Chicago press, Chicago, London, 1945, 1948; Popper, The open society and its Enemies, Princeton university, NJ, 1950).     

Stock returns and carry trades

This paper studies the role the stock market plays in determining the carry trade return. Evidence shows stock market returns significantly affect the carry trade returns in Australia, Mexico, Japan, the UK, Sweden, and the Eurozone. This paper further examines three channels through which stock returns affect the carry trade returns: the Balassa-Samuelson, risk-premium, and flight-to-quality effects. Our model shows that the stock market impact on the carry trade return depends on stock market volatility, and the flight-to-quality effect prevails globally. Furthermore, the introduction of the stock return significantly improves the out-of-sample forecast of the carry trade return when the domestic market is volatile.     

The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods

Based on the new perspective of high-dimensional and time-varying methods, this paper analyzes the contagion effects of US financial market volatility on China’s nine financial sub-markets. The results show evidence of non-linear Granger causality from the US financial volatility (VIX) to the China’s financial markets. Increased US financial volatility has a negative next-day impact on the stock, bond, fund, interest rate, foreign exchange, industrial product and agricultural product markets, and a positive next-day impact on the gold and real estate markets. US financial volatility has the greatest impact on industrial product market, following by stock, agricultural product, fund, real estate, bond, gold, foreign exchange, and interest rates. Major risk events such as the global financial crisis can cause an enhanced contagion effect of US financial volatility to China's financial markets. This paper supports the achievements of China's actions to prevent and resolve major financial risks in the period of the COVID-19 epidemic.     

Stock market return and volatility: day-of-the-week effect

This paper examines the stock market returns and volatility relationship using US daily returns from May 26, 1952 to September 29, 2006. The empirical evidence reported here does not support the proposition that the return-volatility relationship is present and the same for each day of the week.     

Oil prices,stock returns,and exchange rates: Empirical evidence from China and the United States

Employing the diagonal BEKK model as well as the dynamic impulse response functions, this study investigates the time-varying trilateral relationships among real oil prices, exchange rate changes, and stock market returns in China and the U.S. from February 1991 to December 2015. We highlight several key observations: (i) oil prices respond positively and significantly to aggregate demand shocks; (ii) positive oil supply shocks adversely and significantly affect the Chinese stock market; (iii) oil price shocks persistently and significantly impact the trade-weighted US dollar index negatively; (iv) the US and China stock markets correlate positively just as the dollar index and the exchange rate does; (v) a significant parallel inverse relation exists between the US stock market and the dollar and between the China stock market and the exchange rate; and (vi) the Chinese stock market is more volatile and responsive to aggregate demand and oil price shocks than the US stock market in recent years.