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This study aims to analyse the effects of Economic Policy Uncertainty (EPU) on the return of growth/value and small/large-cap stocks during expansionary and recessionary periods across a conditional distribution.

The authors selected a sample covering the period between 01/1995–05/2021. Quantile regressions were applied to the EPU and Russell indices. Business cycles were established following the NBER.

The results show that EPU has a negative effect on stocks with the intensity of the effect depending on the stock's profile. Small-cap and growth stocks were found to be most sensitive to EPU, especially during recessions. The negative effect is moderated by the economic cycle but is progressively diluted at the lower tail of the stock return distribution.

The findings shed more light on investment strategies for growth/value investors that pursue opportunities arising from a changing economic cycle.

This study makes the following contributions: (1) explores the impact of EPU on the return of different stocks across a conditional distribution, and (2) provides evidence on how the economic cycle influences EPU impact on growth/value stocks and small/large stocks.

:本研究擬分析跨條件分佈、以及於擴張期和衰退期,經濟政策不確定性對成長型股票/價值股和小盤股/大型股的收益的影響。

我們選擇了涵蓋1995年1月與2021年5月期間的樣本進行研究。我們於經濟政策不確定性指數和羅素指數上採用分位數迴歸法進行研究; 並跟隨著美國國家經濟研究局,建立了多個經濟週期。

研究結果顯示,經濟政策不確定性對股票是有負面影響的,而影響的強度則視乎股票的投資組合而定。我們發現,小盤股和成長型股票對經濟政策不確定性是非常敏感的,尤其是在經濟衰退期間。這負面影響會被經濟週期緩和,唯這緩和作用卻會在股票收益的低尾處逐漸減輕。

研究結果使我們更容易理解為尋找因經濟週期改變而衍生的機會的增長/價值投資者所提供的投資策略。

本研究有以下的貢獻:(一) 、 探究了經濟政策不確定性對跨條件分佈、不同的股票收益的影響; (二) 、為經濟週期會如何左右經濟政策不確定性對成長型股票/價值股和小盤股/大型股的影響,提供了證據。

This study aims to analyse whether investment in green and sustainable stocks provide some cushion during current precarious time. To compare the impact of COVID-19 on the volatility of sustainable and market-capitalisation-based stocks, daily returns from Greenex, Carbonex, Large-Cap, Mid-Cap and Small-Cap index have been analysed over a period of six years from 2015 to 2021.

At the outset, logarithmic return of all selected indices has been tested for possible unit root and heteroscedastic. On confirmation of stationarity and heteroscedasticity of data, auto-regressive conditional heteroscedastic models have been applied. Thereafter, volatility is modelled through best suitable model as suggested by Akaike and Schwarz information criterions.

The findings indicate the positive impact of COVID-19 on the volatility of the indices. Asymmetric power ARCH model indicates highest significant impact of COVID-19 over the volatility of Large-Cap index, whereas exponential GARCH model detected highest significant impact of COVID-19 over the volatility of Mid-Cap Index.

To the best of the authors’ knowledge, the present study is original in the sense that it aimed at comparing the possible impact of COVID-19 over sustainable and market-capitalisation-based indices.

The purpose of this paper is to investigate whether sentiment and mood, which are distinct theoretical concepts, can also be distinguished empirically.

Using a sample of German small-cap stocks and linear techniques, the effect of sentiment and mood on short-term abnormal stock return following earnings announcements is tested separately.

Mood tends to be a positive factor in predicting short-term abnormal stock return, as its biologically based impact uniformly affects the risk aversion of all market participants. Notably, negative mood influences stock return significantly negatively. Sentiment is no factor, however, as its cognitively based impact affects only unsophisticated investors, namely, their cash-flow expectations.

As the sample is restricted to small-cap stocks from a single stock market and only two proxies of sentiment and mood, respectively, are used, the findings should be generalized with caution. Future research might investigate other markets and employ different proxies of sentiment and mood.

Market participants should be aware of the different effect of sentiment and mood on stock return and adjust investment strategies accordingly.

As sophisticated investors are likely to profit from the irrational behavior of unsophisticated investors, who are prone to sentiment, the financial literacy of retail investors should be enhanced.

This paper is unique in distinguishing between sentiment and mood, both theoretically and empirically. Such distinction was largely ignored by related past research.

The purpose of this paper is to obtain new empirical evidence about the connections between equity trading activity and five possible liquidity determinants: market capitalisation, dividend yield, earnings yield, company growth and the distinction between recently listed firms as opposed to more established ones.

The authors use a sample of 172 stocks from four European markets and estimate models using the entire sample data and different sub-samples to check the relative importance of the above determinants. The authors also conduct a factor analysis to re-classify the variables into a more succinct framework.

The evidence suggests that market capitalisation is the most important trading activity determinant, and the number of years listed ranks thereafter.

The positive relation between trading activity and market capitalisation is in line with prior literature, while the findings relating to the other determinants offer further empirical evidence which is a worthy addition in view of the contradictory results in prior research.

This study is of relevance to practitioners who would like to understand the cross-sectional variation in stock liquidity at a more detailed level.

The originality of the paper rests on two important grounds: the authors focus on trading turnover rather than on other liquidity proxies, since the former is accepted as an important determinant of the liquidity-generation process, and the authors adopt a rigorous approach towards checking the robustness of the results by considering various sub-sample configurations.

There have always been North Korea Risks in South Korea stock market since its opening. Some studies have concluded that it does not have a substantial impact on South Korea’s economy due to chronic geopolitical risks, while others have argued it has had an impact. However, in light of the Efficient Market Hypothesis (EMH) it can be argued that both opinions view that information about North Korea Risks affects stock markets and that stock prices react to it. This study analyzed the effects of North Korea Risks on South Korea’s stock market using event study methodology empirically, and it tested the semi-strong EMH-a market in which prices always fully reflect available information. The research results are following:

First of all, North Korea Risks have an impact on South Korea’s stock market and the data was statistically significant. In particular, stock market already reflected information about the forewarned events like nuclear test. However, market also responded to information about sudden events such as the impact of Kim Jung-il’s death on the South-North economic cooperation stock. Portfolio analysis demonstrated that small capital stocks were affected more than large caps. These results cannot reject the EMH.

Also, estimates of market model and that of Fama-French three-factor model did not show a statistically significant difference in different verification. There was no statistically significant difference between growth and value stock in large caps portfolio either. However, there was a statistically significant difference between defense stock and South-North economic cooperation stock, small caps and big caps, and weighted average and simple average.

The significance of this study lies in that it conducted the event study by variety estimation model with objective standards for selecting events when measuring the effect of North Korea Risks.

This paper aims to explore the influence of the COVID-19 outbreak and the Government's disease control measures on the stock returns and liquidity of Vietnam-listed companies in the financial services sector.

The authors have conducted a panel data regression analysis using data from 50 banking, insurance and finance companies listed in Vietnam's two biggest stock exchanges (HNX and HOSE) within the period from January 30th, 2020 to May 15th, 2021.

The regression results indicate that the daily growth in the total number of confirmed cases caused by COVID-19 has significant negative effects on the stock market returns and liquidity. Nevertheless, the Government's imposition of lockdown yields significant and positive outcomes on stock performance. In addition, the study reveals remarkable differences in returns of large-cap and small-cap stocks under the impact of the COVID-19 pandemic.

The study indicates government and regulators should act more actively to limit the outbreak of the virus, improve investor confidence as well to support the financial services industry and deal with the outbreak of the pandemic later.

This is the first study to explore the influence of the COVID-19 outbreak and the Government's disease control measures on the stock returns and liquidity of Vietnam-listed companies in the financial services industry.

We propose a risk factor for idiosyncratic entropy and explore the relationship between this factor and expected stock returns.

We estimate a cross-sectional model of expected entropy that uses several common risk factors to predict idiosyncratic entropy.

We find a negative relationship between expected idiosyncratic entropy and returns. Specifically, the Carhart alpha of a low expected entropy portfolio exceeds the alpha of a high expected entropy portfolio by −2.37% per month. We also find a negative and significant price of expected idiosyncratic entropy risk using the Fama-MacBeth cross-sectional regressions. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

We propose a risk factor of idiosyncratic entropy and explore the relationship between this factor and expected stock returns. Interestingly, expected entropy helps us explain the idiosyncratic volatility puzzle that stocks with high idiosyncratic volatility earn low expected returns.

The purpose of this paper is to empirically examine the return and dividend characteristics of two different types of Malaysian real estate investment trust (REIT) series, namely, conventional and Islamic, against macroeconomic variables over the period 2011-2017.

The required data are derived from Datastream database. Multiple regression analysis is used to determine the impact of macroeconomic variables on financial performance of 13 Malaysian REIT series.

Results show that the macroeconomic variables are able to predict future returns and dividends of Malaysian REITs. The analysis also suggests that Islamic REITs are seen to be less sensitive to macroeconomic variables and display better portfolio diversification benefits as compared to their conventional counterpart. The ongoing implications for large-cap and small-cap REITs are also highlighted.

The main limitation of the study is the small percentage of Islamic REITs sample due to limited period of observation available. However, the two Islamic REITs included are representative of Islamic REITs in Malaysia as both of them are listed in the Bursa Malaysia with asset size and market capitalization values more than RM1bn.

The results of this study may serve as a useful input for financial market players on making strategic business decisions especially with regards to differences between conventional and Islamic REITs characteristics.

The main contribution of this paper is to explore the relationship between REITs and macroeconomic factors on a unique capital market (Malaysia) that allows comparison between conventional and its Islamic counterpart.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.