Security Returns Research Articles

Governmental Announcements and Indian Stock Market: Evidence from Indian Manufacturing Sector

The Indian Manufacturing sector lags behind in contributing to economic devel- opment, as compared to its peer nations and therefore, to boost the sectorís contribution to the economy and to transform the economy into a cashless economy, the government of India had announced three major steps, Make in India, Demonetization and GST. In the present study using event study methodology, the immediate impact of the announcements on the stock of the companies from the Indian Manufacturing sector is examined and found that the announcement of the Make in India positively ináuenced the security returns. In contrast, negative impact on the security prices is witnessed on the announcement of Demonetization, whereas the GST implementation has no impact.

The dynamic interaction between investor attention and green security market: an empirical study based on Baidu index

PurposeThis paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.Design/methodology/approachThis study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window.FindingsThe empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance.Originality/valueThe conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.

Short- and long-term effects of responsible investment growth on equity returns

PurposeThe growth of socially responsible assets has been exponential over the last decade, they now account for almost a third of professional investments. As the growth persists, faith and conviction investors reshape the equity markets. To fully comprehend the impact of socially conscious participants on security returns, this paper attempts to provide insights on how responsible investment growth has impacted the returns of sustainable stocks. The examination is split by investment horizon to account for short and long effects.Design/methodology/approachUsing an exclusive dataset of non-financial ratings, provided by MSCI ESG research, the authors examine the cross-sectional returns of US and European sustainability-leading and lagging corporations between 2007 and 2019. Panel models robust to country, firm-year and industry effects were then employed to examine the impact of responsible investment growth on future stock returns.FindingsThe authors find evidence that the impact of responsible investment growth is dual contingent upon the timeframe considered. In the short run, sustainability-leading and lagging firms display similar stock returns. However, the spread in returns is negative over long horizons and increasing over time.Originality/valueThe examination performed in this study highlights the significant effect of responsible investment growth on future stock returns. Overall, the authors’ findings are consistent with the price pressure hypothesis in the short run and the cost of capital alteration over longer horizons.

Unparalleled Volatility in Sector-Wise Return in the Chittagong Stock Exchange: A Covid-19 Perspective

This study examined the effect of the Covid-19 health crisis on the volatility of sector-wise securities return listed in the Chittagong Stock Exchange (CSE) and compared this volatility with the pre-pandemic context. This study focused on the Chittagong Stock Exchange because this bourse offers a platform for negotiability and transferability of securities to investors in Chittagong and also plays a significant role in capital mobilization and the industrial development of Bangladesh. A sample of 90 securities under 19 sectors listed in the CSE were examined. The trend analysis indicated that Bank, Food, Footwear, Leasing, Life Insurance, Electrical and Engineering and Mutual Funds had same level of volatility between the Pre-Covid and Post-Covid time periods. Only four sectors, including Energy, Telecommunication, General Insurance and Miscellaneous sectors displayed a higher Post-Covid volatility relative to the Pre-Covid context. The result indicated that volatility of return was not the same for 19 sectors in the CSE over the selected time period. The researcher discovered that high and low periods of deaths had a significant impact on weekly volatility of return on 19 sectors of the CSE. However, the difference in volatility of return across all sectors between the Pre-Covid and Post-Covid time periods were not statistically significant from each other. Keywords: volatility of return, stock market, covid-19

Predictive Value of Estimated Beta

The Capital Asset Pricing Model (CAPM) is widely used in corporate finance to assess expected returns of securities and return on equity, and beta, a measure of systematic risk, is a component of the CAPM equation. Previous studies appear not to have addressed whether beta as a stand-alone metric allows individual investors to effectively assess returns relative to the market, and this study aims to address this. Exchange-traded funds (ETFs) reflecting a range of expected volatilities relative to the S&P 500 index were selected. Betas of XLK (Technology sector), XLE (Energy sector), XLU (Utilities sector), and XLY (Consumer Staples sector) were estimated by regressing their weekly returns over five years against those of the S&P 500 index. Three five-year periods were used (ending in 2005, 2010, and 2015). The betas largely conformed to anticipated values with the exception of that of XLY which was surprisingly greater than the market beta. Estimated and observed betas were compared using a two-tailed paired T-test and no difference was found, suggesting that estimated beta is statistically a good proxy for actual beta. In practical terms though, there were relatatively large variances in several instances between estimated and observed betas, and this could be a concern for investors. Returns using estimated beta and actual returns were also compared over one, two, three, four, and five years with regard to the three five-year periods. Significant variation was observed for expected minus observed returns both in sign and magnitude. A two-tailed paired T-test suggested there was a difference between returns using estimated beta and actual ones over the three five-year periods for all funds except XLE. The observations suggest betas are volatile and individual investors should incorporate additional metrics to forecast returns relative to the market.

Lessons from naïve diversification about the risk-reward trade-off

Studies of naïve diversification show that average total portfolio risk declines asymptotically as number of stocks increases. Recent work shows that a significant amount of idiosyncratic risk remains, even for portfolios with large numbers of stocks. The corresponding shocks are non-trivial. For example, more than half of all equal-weighted portfolios with 100 stocks have better than a 16 percent chance of an annual shock at least as large as about half of the annualized mean excess return on the U.S. total stock market index over July 1963–June 2018. I perform a simulation analysis of portfolio reward-to-risk as well as the components of total portfolio risk. On average, investors do not appear to be rewarded for exposure to non-systematic risk. The cross-sectional distribution of the true Sharpe ratio rises and its dispersion shrinks significantly as the number of stocks in the portfolio increases, whereas the cross-sectional distribution of the true non-systematic risk falls and its dispersion shrinks significantly as the number of stocks in the portfolio increases. This pattern appears regardless of the true asset pricing model for generating security returns, the portfolio weighting method, or specification of security alphas.

Empirical analysis of the illiquidity premia of German real estate securities

In this study, we analyze illiquidity premia and their effect on the expected returns of German real estate securities. To this end, we use a unique data set that includes real estate stocks, real estate investment trusts (REITs), and open- and closed-end real estate funds for 2003–2017. We follow Amihud’s (JFM 5:31–56, 2002) structural approach; specifically, we estimate Amihud’s illiquidity factors, investigate the relationships between expected returns and illiquidity, and analyze the effects of expected and unexpected market illiquidity on future returns. We show that illiquidity plays an important role in expected returns for real estate stocks and investment trusts (REITs); however, it has less clear effects on open- and closed-end funds. We find that the adjusted ILLIQ includes appropriate correction factors for securities with low trading activity and is a useful improvement. We also find evidence of structural breaks in the relationship between returns and illiquidity.

The Effect of U.S. Investor Sentiment on Cross-Listed Securities Returns: A High-Frequency Approach

This paper studies the impact of a high-frequency investor sentiment measure (New FEARS) on the returns of foreign securities listed in U.S. markets as American Depository Receipts (ADRs). We recreate a high-frequency investor sentiment measure by aggregating search volume indices (SVIs) for a set of negative economic search terms. We find that ADR aggregate market returns exhibit a negative reaction to increases in searches for negative economic terms such as “recession”, “crisis”, and “bankruptcy” by U.S. households. This is the first paper to measure the effects of high-frequency investor sentiment on cross-listed securities. Moreover, the results are consistent throughout our study regardless of the variation of sentiment and aggregate market return measure we use. We also explore ADR regional market indices and show that Latin American ADRs are more sensitive to this investor sentiment measure.

Effects of long-term no tillage and straw return on greenhouse gas emissions and crop yields from a rice-wheat system in central China

Extensive attention has been attracted to no tillage and straw return due to its carbon sequestration and greenhouse gas (GHG) emissions alteration properties. However, the impacts of perceived long-term no tillage and straw return on GHG emissions and crop yields in the rice-wheat system remain unclear. A six-year field experiment was conducted to investigate the temporal impacts of no tillage and straw return on soil organic carbon (SOC), CH4 and N2O emissions, and crop yields. Significant effects of no tillage and straw return on SOC were observed after 5 years of the experiment. The influence of no tillage and straw return on N2O and CH4 emissions and crop yields presented temporal disparities. No tillage significantly increased N2O emission by 28.9%, but reduced CH4 emission by 18.3% during 6-year field experiment relative to conventional tillage. Moreover, no tillage had no significant effect on the annual crop yield. By contrast, straw return remarkably increased N2O emissions, CH4 emissions and annual crop yield by 41.2%, 47.5% and 4.1% over the 6-year field experiment relative to straw removal. Besides, no tillage significantly decreased net global warming potential (GWP) by 27.7%, and had no significant effect on net ecosystem economic budget (NEEB). Inversely, straw return markedly increased the net GWP by 46.2% and the NEEB by 3.4%. Together, these results showed that agricultural strategy of long-term no tillage with straw return is likely to result in low GHG emissions and high crop yields and economic profit in rice-wheat system, suggesting the potential benefit of no tillage with straw return for GHG mitigation and food security.

The Reaction Of The Indonesian Capital Market When Indonesia Experiences Recession In 2020

This study aims to explain whether or not there is evidence of differences in abnormal return, trading volume activity, and security return variability of companies listed in the LQ45 index on the IDX before and after the November 2020 recession announcement. This study uses quantitative research approach. The LQ45 index is the research population used in this study. Meanwhile, to determine the research sample in this study using purposive sampling technique. The Wilcoxon Signed Rank Test is a data analysis technique used. Based on the results of the research, the abnormal return indicator gives a change with sig. 0.012. Trading volume activity changes with sig. 0.000. Security return variability provides changes with the value of sig. 0.026. So it can be concluded that in the event of an announcement of a recession there is a capital market reaction to companies listed in the LQ45 index.

Indonesian Capital Market Reaction To The Announcement Of A Recession Due To The Pandemic Covid-19

On November 5, 2020, Indonesia was declared a recession after the Central Statistics Agency announced that the Indonesian economy experienced a decline in the third quarter of 2020. The Indonesian economy experienced a decline in the third quarter of 2020, which was minus 3.49 percent. In the second quarter of 2020, the Indonesian economy was already minus 5.32 percent. The announcement of the recession event gave rise to various perceptions for capital market participants. So the purpose of this study is to find out and compare the differences in the average Abnormal Return, Trading Volume Activity, and Security Return Variability of IDX 30 issuers before and after the announcement of the recession due to the COVID-19 pandemic.
 The research method used is quantitative research with an event study approach. The type of data in this study is secondary data with data collection techniques using the documentation method. The sample used is IDX30 stock issuers on the Indonesia Stock Exchange for the period August 2020 - January 2021. The data analysis technique in this study is descriptive statistical analysis, paired t-test and Wilcoxon signed rank test.
 The results of this study indicate that: (1) there is a significant difference in the average abnormal return of IDX 30 issuers before and after the announcement of the recession due to the covid-19 pandemic. (2) there is a significant difference in the average Trading Volume Activity of IDX 30 issuers before and after the announcement of the recession due to the covid-19 pandemic. (3) there is no significant difference in the average Security Return Variability of IDX 30 issuers before and after the announcement of the recession due to the covid-19 pandemic.

Portfolio optimization in real financial markets with both uncertainty and randomness

Financial market is a complex system full of unknown and indeterminacy. It is well known that uncertainty and randomness are two basic types of indeterminacy. Hence, the complexity of real financial markets may lead to various types of security returns. They are usually assumed as random variables when there are enough historical data. If there is a lack of available data, they can be considered as uncertain variables. However, uncertainty and randomness often exist simultaneously. In this paper, we consider a portfolio optimization problem in real financial markets with both uncertainty and randomness. First, the skewnesses for three kinds of uncertain random variables are derived. Then, in an uncertain random environment, considering different risk preferences, a mean-variance-skewness model for the portfolio optimization problem is proposed. In addition, we use the normalization method to eliminate the impact of investment returns and risks of different units. Finally, numerical simulations are carried out to show that the proposed model is realistic and applicable.

Herding Behavior in the Indian Stock Market : An Empirical Study

The herding behavior in financial markets indicates the process whereby the different participants of the market trade in a similar direction simultaneously. This kind of trading pattern seems like a consensus in the market. There are different reasons for herding to exist : to be part of a group, to avoid the feeling of being left out, reaction to some kind of new information, etc. In this paper, we tried to identify the existence of herding behavior in the Indian stock market. The markets were examined over a time frame of the last 15 years to determine the existence of herding behavior at various points of time. The three time periods selected for the study were 2003 – 2007 (pre - financial crisis), 2008 – 2012 (sub-prime crisis), and 2013 – 2017 (post) crisis. The study used security return dispersion as a substitute for herd behavior. In order to test the presence of herding behavior, linear regression model using dummy variables was used. The evidence supported the presence of herding in the Indian stock market during the financial crisis time period and the post-crisis period. In the pre - financial crisis period, there was no herding phenomenon observed.

Reaksi Pasar terhadap Peristiwa Politik 2019 di Indonesia

This study examines the information content in political events in 2019, namely the appointment of the president and vice president and the announcement of the Kabinet Indonesia Maju. Market reaction is measured by abnormal returns, security return variability, and trading volume activity. The observation period in this study was five days before and after the event, with a sample of 20 companies affiliated with the winner of the election and 25 companies at the announcement of the Indonesian Maju Cabinet. The results of hypothesis testing indicate that there is a difference in the average abnormal return in the event of the appointment of the elected president and vice president, but there is no difference in security return variability and trading volume activity. Furthermore, hypothesis testing shows that there is a significant difference in average trading volume activity before and after the announcement of the Kabinet Indonesia Maju, but there is no difference in abnormal return and security return variability.
 Keywords: Market Efficiency; Event Studies; Abnormal Returns; Security Return Variability; Trading Volume Activity.

REAKSI PASAR MODAL INDONESIA TERHADAP PERISTIWA PENGESAHAN UU CIPTA KERJA 2020 (STUDI KASUS PERUSAHAAN YANG TERDAFTAR PADA LQ45)

This study aims to analyze reaction of the Indonesian capital market about difference of average abnormal returns, trading volume activity, and security return variability between before and after the legalization of the Job Creation Act on October 5, 2020. This study used quantitative research with event study approach. The research sample is stocks registered in LQ45 with certain criteria determined used the purposing sampling method. Hypothesis testing used paired sample t-test and wilcoxon signed rank test. The results of the hypothesis testing show that: (1) There’s a significant difference in the average abnormal return between the period before and after the Job Creation Act legalization. (2) There’s no significant difference in the average trading volume activity between the periodsbefore and after the Job Creation Act legalization. (3) There’s a significant difference in the average security return variability between the period before and after the Job Creation Act legalization.Keywords: The Job Creation Act, Abnormal Return; Trading Volume Activity; SecurityReturn Variability

THE INFLUENCE OF GROUP AFFILIATION ON IPOS PERFORMANCE: AN EMPIRICAL ANALYSIS OF INDIAN IPOS

Securities and Exchange Board of India (SEBI) keeps on improving the securities market regulations to improve investors' protection. To revive the primary market, in 2009, SEBI ICDR (Issue of Capital and Disclosure Requirements) Regulations, 2009 was amended with revised guidelines. The advantage of group affiliation and reputation on IPO performance differs with time and varied business groups. Grouped IPOs evidenced mixed outcomes based on theories developed under tunnelling, propping, network and certification hypothesis. We examine how the business group affiliation impact the underpricing, liquidity and volatility performance of IPOs. Using database of 259 IPOs issued in Indian market from 2009 to 2019, we find less underpricing, liquidity and volatility for group affiliated IPOs. The present study supports certification, network and propping hypothesis. We find underpricing extent is reduced than earlier period, average security return 12 percent while underpricing 11.79 percent is evidenced. Liquidity and volatility reported a declining trend from listing day to 1-month post listing.

A new fuzzy random multi-objective portfolio model with different entropy measures using fuzzy programming based on artificial bee colony algorithm

PurposeThis paper proposes a fuzzy random multi-objective portfolio model with different entropy measures and designs a hybrid algorithm to solve the proposed model.Design/methodology/approachBecause random uncertainty and fuzzy uncertainty are often combined in a real-world setting, the security returns are considered as fuzzy random numbers. In the model, the authors also consider the effects of different entropy measures, including Yager's entropy, Shannon's entropy and min-max entropy. During the process of solving the model, the authors use a ranking method to convert the expected return into a crisp number. To find the optimal solution efficiently, a fuzzy programming technique based on artificial bee colony (ABC) algorithm is also proposed.Findings(1) The return of optimal portfolio increases while the level of investor risk aversion increases. (2) The difference of the investment weights of the optimal portfolio obtained with Yager's entropy are much smaller than that of the min–max entropy. (3) The performance of the ABC algorithm on solving the proposed model is superior than other intelligent algorithms such as the genetic algorithm, differential evolution and particle swarm optimization.Originality/valueTo the best of the authors' knowledge, no effect has been made to consider a fuzzy random portfolio model with different entropy measures. Thus, the novelty of the research is constructing a fuzzy random multi-objective portfolio model with different entropy measures and designing a hybrid fuzzy programming-ABC algorithm to solve the proposed model.

The Cross Section of MBS Returns

ABSTRACTWe present a simple, linear asset pricing model of the cross section of Mortgage‐Backed Security (MBS) returns. MBS earn risk premia as compensation for their exposure to prepayment risk. We measure prepayment risk and estimate risk loadings using prepayment forecasts versus realizations. Estimated loadings on prepayment risk decrease monotonically in securities' coupons relative to the par coupon, consistent with the predicted effect of prepayment on bond value. Prepayment risk appears to be priced by specialized MBS investors. The price of prepayment risk changes sign over time with the sign of a representative MBS investor's exposure to prepayment shocks.

Multi-period uncertain portfolio optimization model with minimum transaction lots and dynamic risk preference

An accurate variable description of security returns is necessary to establish a valid portfolio optimization model. It is usually assumed to be a random variable when the historical data of security returns are sufficient. However, when historical data are too limited to estimate its probability distribution, uncertain variables are employed to characterize security returns to be effective. This paper focuses on a multi-period portfolio optimization problem in uncertain environment with the consideration of minimum transaction lots. Different from the previous multi-period work assuming the total available wealth in the end of the investment horizon is consistently in an exponential format, our study provides a simplified additive format of the total wealth, which may make the process of experimental calculation concise, since it is a linear function of decision variables. Besides, we consider the investor’s dynamic risk preference along the whole investment horizon. With these realistic constraints derived from the complex financial markets, we build a multi-period mean-VaR (value-at-risk) model with the objective of maximizing the terminal wealth under the risk control over the whole investment. Genetic algorithm is used to solve the proposed model, and two numerical examples are given to illustrate the effectiveness of the proposed approach.

SEMI-STRONG FORM EFFICIENCY OF GOLD MARKET: COLLECTIVE RATIONALISATION AND ISLAMIC CALENDAR ANOMALY

Purpose: The current study aimed to test the impact of two religious months on the return behaviour of the gold market in Pakistan under informational efficiency hypothesis i.e. to empirically test the semi-strong form of EMH in gold market for religious calendar anomaly.
 Methodology: Weekly gold prices in rupees per one gram that prevailed in Pakistan for the period January 2007 till December 2015 were selected, summing up to 468 observations. Data was taken from World Gold Council and the Bullion-rate database. Event methodology was employed for capturing and analyzing the pre and post event reactions by calculating abnormal returns. Furthermore, average security return variability was employed for robustness check. 
 Main Findings: Opposing results were achieved for both the lunar calendar occurrences where the gold market is inefficient for the month of Ramazan but is found efficient in Muharram's case concluding into mixed evidence and findings.
 Implications/Applications: The contribution of this study differs from previous gold studies in two aspects; first the research investigated the effect of Ramazan and Muharram as Islamic calendar events, and second is that gold market prices of Pakistan that had not been examined earlier. So this study is adding to the literature in the sense of examining the new relationship in Pakistan.
 Novelty/Originality of this study: Extensive literature can be found about the global gold market that tested the weak form efficiency, but empirical evidence related to the semi-strong form efficiency of the gold market in Pakistan is not available neither the calendar anomaly related to the gold market is available. The dynamics of this very highly valuable and volatile asset market require investigation of such type.