scholarly journals The information content of US stock market factors

2020 ◽  
Vol 37 (2) ◽  
pp. 323-346
Author(s):  
Mohammed M. Elgammal ◽  
Fatma Ehab Ahmed ◽  
David G. McMillan
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Information Content ◽  
Predictive Power ◽  
Output Growth ◽  
Economic Conditions ◽  
Content Type ◽  
Economic Information ◽  
Market Factors ◽  
The Impact

Purpose The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth. Design/methodology/approach Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth. Findings The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime). Research limitations/implications The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior. Practical implications Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models. Originality/value This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.

A quantile regression approach to evaluate the relative impact of global and local factors on the MENA stock markets

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Slah Bahloul ◽  
Nawel Ben Amor
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Stock Returns ◽  
Stock Markets ◽  
Financial Integration ◽  
Ordinary Least Squares ◽  
Market Returns ◽  
Stock Market Returns ◽  
Content Type ◽  
The Impact

PurposeThis paper investigates the relative importance of local macroeconomic and global factors in the explanation of twelve MENA (Middle East and North Africa) stock market returns across the different quantiles in order to determine their degree of international financial integration.Design/methodology/approachThe authors use both ordinary least squares and quantile regressions from January 2007 to January 2018. Quantile regression permits to know how the effects of explanatory variables vary across the different states of the market.FindingsThe results of this paper indicate that the impact of local macroeconomic and global factors differs across the quantiles and markets. Generally, there are wide ranges in degree of international integration and most of MENA stock markets appear to be weakly integrated. This reveals that the portfolio diversification within the stock markets in this region is still beneficial.Originality/valueThis paper is original for two reasons. First, it emphasizes, over a fairly long period, the impact of a large number of macroeconomic and global variables on the MENA stock market returns. Second, it examines if the relative effects of these factors on MENA stock returns vary or not across the market states and MENA countries.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

Investor attention and market correction

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhongdong Chen
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Trading Behavior ◽  
Investor Attention ◽  
Information Effect ◽  
Content Type ◽  
Economic Significance ◽  
New Information ◽  
Positive Volume ◽  
The Impact

PurposeThis study disentangles the investor-base effect and the information effect of investor attention. The former leads to a larger investor base and higher stock returns, while the latter facilitates the dissemination of information among investors and impacts informational trading.Design/methodology/approachUsing positive volume shocks as a proxy for increased investor attention, this study evaluates the impacts of the investor-base effect and the information effect of investor attention on market correction following extreme daily returns in the US stock market from 1966 to 2018.FindingsThis study finds that the investor-base effect increases subsequent returns of both daily winner and daily loser stocks. The information effect leads to economically less significant return reversals for both the daily winner and daily loser stocks. These two effects tend to have economically more significant impacts on the daily loser stocks. The economic significance of these two effects is also related to firm size and the state of the stock market.Originality/valueThis study is the first to disentangle the investor-base effect and the information effect of increased investor attention. The evidence that the information effect facilitates the dissemination of new information and impacts stock returns contributes to the strand of studies on the impact of investor attention on market efficiency. This evidence also contributes to the strand of studies analyzing the impact of informational trading on stock returns. In addition, this study provides evidence for market overreaction and the subsequent correction. The results for up and down markets contribute to the literature on the investors' trading behavior.

Herding behavior in Islamic GCC stock market: a daily analysis

2018 ◽  
Vol 11 (2) ◽  
pp. 182-193 ◽  
Author(s):  
Mustapha Chaffai ◽  
Imed Medhioub
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Financial Markets ◽  
Stock Returns ◽  
Stock Markets ◽  
Content Type ◽  
Quantile Regression Analysis ◽  
Herd Behaviour ◽  
The Impact ◽  
Quantile Regression Method

Purpose This paper aims to examine the presence of herd behaviour in the Islamic Gulf Cooperation Council (GCC) stock markets following the methodology given by Chiang and Zheng (2010). Generalized auto regressive conditional heteroskedasticity (GARCH)-type models and quantile regression analysis are used and applied to daily data ranging from 3 January 2010 to 28 July 2016. Results show evidence of herd behaviour in the GCC stock markets. When the data are divided into down and up market periods, herd information is found to be statistically significant and negative during upward market periods only. These results are similar to those reported in some emerging markets such as China, Japan and Hong Kong, where stock returns perform more similarly during down market periods and differently during rising markets. Design/methodology/approach The authors present a brief literature on herd behaviour. Second, the authors provide some specificity of the GCC Islamic stock market, followed by the presentation of the methodology and the data, results and their interpretation. Findings The authors take into account the difference existing in market conditions and find evidence of herding behaviour during rising markets only for GCC markets. This result was confirmed after using the quantile regression method, as evidence of herding was observed only in highly extreme periods. Stock returns perform more similarly when market is down in Islamic GCC stock market. Research limitations/implications The research limitation consists in the fact that this work can be extended to compare the GCC stock markets with other markets in Asia such as Malaysia and Indonesia. Practical implications The principal implication consists in the fact that herding behaviour is limited in the GCC markets and Islamic finance can have an important contribution to moderate the behaviour in the financial markets. Social implications The work focusses on the role of ethics in the financial markets and their ability to reduce the impact of behavioural biases. Originality/value The paper studies the behaviour of investors in the Islamic financial markets and gives an idea about the importance of the behaviour in this particular market regarding its characteristics.

Liquidity and real estate asset pricing: a pan-European study

2014 ◽  
Vol 7 (1) ◽  
pp. 59-86 ◽  
Author(s):  
Alexander Scholz ◽  
Stephan Lang ◽  
Wolfgang Schaefers
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Asset Pricing ◽  
Real Estate ◽  
Stock Returns ◽  
Systematic Risk ◽  
Time Series Regression ◽  
Content Type ◽  
Market Factors ◽  
The Impact

Purpose – Understanding the pricing of real estate equities is a central objective of real estate research. This paper aims to investigate the impact of liquidity on European real estate equity returns, after accounting for well-documented systematic risk factors. Design/methodology/approach – Based on risk factors derived from general equity data, the authors extend the Fama-French time-series regression approach by a liquidity factor, using a pan-European sample of 272 real estate equities. Findings – The empirical results indicate that liquidity is a significant pricing factor in real estate stock returns, even after controlling for market, size and book-to-market factors. In addition, the authors detect that real estate stock returns load predominantly positively on the liquidity risk factor, suggesting that real estate equities tend to behave like illiquid common equities. These findings are underpinned by a series of robustness checks. Running a comparative analysis with alternative factor models, the authors further demonstrate that the liquidity-augmented asset-pricing model is most appropriate for explaining European real estate stock returns. Research limitations/implications – The inclusion of sentiment and downside risk factors could provide further insights into real estate asset pricing in European capital markets. Originality/value – This is the first study to examine the role of liquidity as a systematic risk factor in a pan-European setting.

scholarly journals IMPACT OF IMF LENDING ANNOUNCEMENTS ON THE PERFORMANCE OF STOCK MARKET: EMPIRICAL EVIDENCE FROM PAKISTAN

2021 ◽  
Vol 9 (3) ◽  
pp. 467-476
Author(s):  
Muhammad Azeem ◽  
Nisar Ahmad ◽  
Sarfraz Hussain ◽  
Muzammil Khurshid ◽  
Safyan Majid
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Empirical Evidence ◽  
Economic Performance ◽  
Economic Conditions ◽  
The Political ◽  
Time Varying ◽  
Negative Effect ◽  
Multiple Challenges ◽  
The Impact

Purpose of the study: Stock markets have demonstrated varying reactions to IMF lending announcements across various economies. Announcements offered by IMF often be perceived negatively by the participants of the stock market, because of stringent conditions accompanied with the loan that may oppose the political and economic agenda of a borrowing nation. Thus, this study intends to investigate the impact of IMF’s announcements about extending loans to Pakistan on the performance of the Stock market in the debt-ridden economy. Methodology: For regular returns from 1997 to 2017, the benchmarking indexes of KSE-100 and 30 were used. Meanwhile, IMF lending arrangements are categorized into three respective dummies (standby, extended credit facility, and extended fund facility). The Generalized Autoregressive Conditional Heteroscedastic (GARCH) model was used to investigate the effect of IMF’s lending news on the regular stock returns. Main findings: The results show a statistically significant effect of the IMF’s News about lending arrangements on the performance of the stock market in Pakistan. Surprisingly, the negative effect of IMF lending announcements on the performance of the stock market in Pakistan implies that the loans extended by IMF are not professed by speculators as good for the economic performance of the economy. Application of this study: The findings of this study imply that simply extending loans is not a panacea for politically unstable and financially ruined nations. Lending strategies of IMF need to be favourable for the political and economic conditions of a borrowing country. Originality/ Novelty: As for as the novelty is concerned, the study has highlighted the time-varying impact of IMF lending announcements on the performance of the stock market in a financially fragile country where a newborn government facing multiple challenges has made its best effort to avoid borrowing from IMF.

The effect of weather on the European stock market

2016 ◽  
Vol 43 (9) ◽  
pp. 943-958 ◽  
Author(s):  
Nikolaos Sariannidis ◽  
Grigoris Giannarakis ◽  
Xanthi Partalidou
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Negative Impact ◽  
Weather Variables ◽  
Socially Responsible ◽  
Content Type ◽  
Daily Data ◽  
Macroeconomic Indicators ◽  
Significant Negative Impact ◽  
The Impact

Purpose The purpose of this paper is to ascertain whether weather variables can explain the stock return reaction on the Dow Jones Sustainability Europe Index by employing a number of macroeconomic indicators as control variables. Design/methodology/approach The authors incorporate the generalized autogressive conditional heteroskeasticity model in methodology for the period August 26, 2009 to May 30, 2014 using daily data. Findings The empirical results indicate that not only do changes in humidity and wind levels seem to affect positively the European stock market but changes in returns oil and gold prices as well. However, the results show that the volatility of the US dollar/Yen exchange rate and ten-year bond value exerts significant negative impact on companies’ stock returns. Originality/value This study adds to the international literature by documenting the impact of weather variables on socially responsible companies.

The predictive ability of stock market factors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammed Mohammed Elgammal ◽  
Fatma Ehab Ahmed ◽  
David Gordon McMillan
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Five Factor Model ◽  
Trading Strategy ◽  
Expected Returns ◽  
Time Varying ◽  
Content Type ◽  
Varying Coefficients ◽  
One Step ◽  
Market Factors

Purpose This paper aims to ask whether a range of stock market factors contain information that is useful to investors by generating a trading rule based on one-step-ahead forecasts from rolling and recursive regressions. Design/methodology/approach Using USA data across 3,256 firms, the authors estimate stock returns on a range of factors using both fixed-effects panel and individual regressions. The authors use rolling and recursive approaches to generate time-varying coefficients. Subsequently, the authors generate one-step-ahead forecasts for expected returns, simulate a trading strategy and compare its performance with realised returns. Findings Results from the panel and individual firm regressions show that an extended Fama-French five-factor model that includes momentum, reversal and quality factors outperform other models. Moreover, rolling based regressions outperform recursive ones in forecasting returns. Research limitations/implications The results support notable time-variation in the coefficients on each factor, whilst suggesting that more distant observations, inherent in recursive regressions, do not improve predictive power over more recent observations. Results support the ability of market factors to improve forecast performance over a buy-and-hold strategy. Practical implications The results presented here will be of interest to both academics in understanding the dynamics of expected stock returns and investors who seek to improve portfolio performance through highlighting which factors determine stock return movement. Originality/value The authors investigate the ability of risk factors to provide accurate forecasts and thus have economic value to investors. The authors conducted a series of moving and expanding window regressions to trace the dynamic movements of the stock returns average response to explanatory factors. The authors use the time-varying parameters to generate one-step-ahead forecasts of expected returns and simulate a trading strategy.

scholarly journals Impact of gold and oil prices on the stock market in Pakistan

2020 ◽  
Vol 25 (50) ◽  
pp. 279-294
Author(s):  
Aiza Shabbir ◽  
Shazia Kousar ◽  
Syeda Azra Batool
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Structural Break ◽  
Oil Prices ◽  
Current Data ◽  
Small Sample ◽  
Data Set ◽  
Content Type ◽  
The Impact

Purpose The purpose of the study is to find out the impact of gold and oil prices on the stock market. Design/methodology/approach This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test. Findings The data analysis results showed that gold and oil prices have a significant impact on the stock market. Research limitations/implications Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set. Originality/value This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

Effects of MILA on their stock markets: an empirical analysis on market activity and dynamic correlations

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jorge Andrés Muñoz Mendoza ◽  
Sandra María Sepúlveda Yelpo ◽  
Carmen Lissette Velosos Ramos ◽  
Carlos Leandro Delgado Fuentealba
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Markets ◽  
Regime Switching ◽  
Series Data ◽  
Integration Process ◽  
Content Type ◽  
Market Activity ◽  
Dynamic Correlations ◽  
The Impact

PurposeThe purpose of this article is to analyze the effects of the integration process for the Integrated Market of Latin America (MILA) on its stock markets behavior as well as their degree of integration.Design/methodology/approachDaily time series data were used for stock returns, volatility, volume and the number of transactions and securities between August 16, 2007 and December 28, 2018. A DCC-MGARCH model was applied to analyze the impact of MILA on stock market behavior and predict dynamic correlations. A GARCH (1,1) model was used to determine the effect of MILA on co-movements between markets. Finally, a Markov regime switching model was used for robustness analysis.FindingsMILA increased stock market activity in terms of volume, transactions and securities traded. However, it reduced returns and volatility. MILA had significant effects on the dynamic correlations between regional stock markets. After the integration process, the dynamic correlations of returns and volatility were reduced, but those related to volume, transactions and securities traded increased. Mexico's subsequent entry into MILA further reduced market volatility, but it did not have relevant effects on markets' co-movements.Originality/valueThese results are relevant for investors and policymakers. MILA has benefited the markets by promoting stock market activity, reducing risk, creating a margin for diversification and limiting risk contagion between them. These results help to guide investment decisions due to the fact that MILA's benefits in terms of regional diversification would be greater in some markets.

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