Calendar anomaly: unique evidence from the Indian stock market

2018 ◽  
Vol 15 (1) ◽  
pp. 87-108
Author(s):  
Harshita Harshita ◽  
Shveta Singh ◽  
Surendra S. Yadav
Keyword(s):  
Stock Market ◽  
Autocorrelation Function ◽  
Abnormal Returns ◽  
Content Type ◽  
Volatility Clustering ◽  
Year Effect ◽  
Augmented Dickey Fuller ◽  
Short Term Investment ◽  
Investment Portfolios ◽  
Indian Stock Market

Purpose The purpose of this paper is to ascertain the monthly seasonality in the Indian stock market after taking into consideration the market features of leptokurtosis, volatility clustering and the leverage effect. Design/methodology/approach Augmented Dickey-Fuller, Phillips-Perron and Kwaitkowski-Phillips-Schmidt-Shin tests are deployed to check stationarity of the series. Autocorrelation function, partial autocorrelation function and Ljung-Box statistics are employed to check the applicability of volatility models. An exponential generalized auto regressive conditionally heteroskedastic model is deployed to test the seasonality, where the conditional mean equation is a switching model with dummy variables for each month of the year. Findings Though the financial year in India stretches from April to March, the stock market exhibits a November effect (returns in November are the highest). Cultural factors, misattribution bias and liquidity hypothesis seem to explain the phenomenon. Research limitations/implications The paper endeavors to provide a review of possible explanations behind month-of-the-year effect documented in literature in the past four decades. Further, the unique evidence from the Indian stock market supports the argument in the literature that monthly seasonality, by nature, may not be a consistent/robust phenomenon. Therefore, it needs to be examined from time to time. Originality/value As the seasonality in the stock market and resultant anomalies are dynamic phenomena, the paper reports the current seasonality/anomalies prevalent in the Indian market. This would aid investors in designing short-term investment portfolios (based on anomalies present) in order to earn abnormal returns.

Dynamic prediction of Indian stock market: an artificial neural network approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Himanshu Goel ◽  
Narinder Pal Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Stock Market ◽  
Institutional Investors ◽  
Time Series Data ◽  
Gradient Algorithm ◽  
Series Data ◽  
Content Type ◽  
Artificial Neural ◽  
Indian Stock Market

Purpose Artificial neural network (ANN) is a powerful technique to forecast the time series data such as the stock market. Therefore, this study aims to predict the Indian stock market closing price using ANNs. Design/methodology/approach The input variables identified from the literature are some macroeconomic variables and a global stock market factor. The study uses an ANN with Scaled Conjugate Gradient Algorithm (SCG) to forecast the Bombay Stock Exchange (BSE) Sensex. Findings The empirical findings reveal that the ANN model is able to achieve 93% accuracy in predicting the BSE Sensex closing prices. Moreover, the results indicate that the Morgan Stanley Capital International world index is the most important variable and the index of industrial production is the least important in predicting Sensex. Research limitations/implications The findings of the study have implications for the investors of all categories such as foreign institutional investors, domestic institutional investors and investment houses. Originality/value The novelty of this study lies in the fact that there are hardly any studies that use ANN to forecast the Indian stock market using macroeconomic indicators.

Artificial intelligence in financial services: a qualitative research to discover robo-advisory services

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankita Bhatia ◽  
Arti Chandani ◽  
Rizwana Atiq ◽  
Mita Mehta ◽  
Rajiv Divekar
Keyword(s):  
Artificial Intelligence ◽  
Stock Market ◽  
Financial Services ◽  
Future Research ◽  
Individual Investors ◽  
Content Type ◽  
Advisory Services ◽  
Wealth Management ◽  
Management Scenario ◽  
Indian Stock Market

Purpose The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms. Design/methodology/approach This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes. Findings Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors. Research limitations/implications Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market. Practical implications This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner. Social implications In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems. Originality/value This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

Islamic calendar and stock market behaviour in India

2018 ◽  
Vol 45 (11) ◽  
pp. 1550-1566
Author(s):  
Dharani Munusamy
Keyword(s):  
Stock Market ◽  
Least Square Method ◽  
Least Square ◽  
Stock Market Returns ◽  
Content Type ◽  
Ordinary Least Square ◽  
Average Return ◽  
Year Effect ◽  
The Common ◽  
The Impact

Purpose The purpose of this paper is to examine the behavior of the stock market returns in the different days of the week and different months of the year in accordance with the Islamic calendar. Further, the study estimates the risk-adjusted returns to test the performance of the indices during the Ramadan and non-Ramadan days. Finally, the study investigates the impact of Ramadan on the returns and the volatility of the stock market indices in India. Design/methodology/approach Initially, the study applies the Ordinary Least Square method to test the day-of-the-week and the month-of-the-year effect of the common and Shariah indices. Next, the study employs the risk-adjusted measurement to examine the underperformance and over-performance of the indices for both the periods. Finally, the study estimates the GARCH (1,1) and GJR-GARCH (1,1) models to observe the impact of Ramadan on the returns and the volatility of the Shariah indices in India. Findings The study finds that an average return of the indices during the Ramadan days are higher than non-Ramadan days. Further, the average returns of the Shariah indices are significantly higher on Wednesday than other days of the week. In addition, the highest and significant mean returns and mean risk-adjusted returns of the indices during the Ramadan days are observed. Finally, the study finds an evidence of the Ramadan effect on the returns and volatility of the indices in India. Originality/value The study observes evidence that the Ramadan effect influences the Shariah indices, but not the common indices in the stock market of the non-Muslim countries. It indicates that the Ramadan creates the positive mood and emotions in the investors buying and selling activities. The study suggests that investors can buy the shares before Ramadan period and sell them during the Ramadan days to get an abnormal return in the emerging markets.

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.

scholarly journals Random Walk Investigation in Indian Market with special reference to S&P Nifty – Fifty Stocks

2015 ◽  
Vol 4 (4) ◽  
pp. 52-61
Author(s):  
Tamilselvan Manickam ◽  
R Madhumitha
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Empirical Support ◽  
Weak Form ◽  
Indian Market ◽  
Price Series ◽  
Stock Market Efficiency ◽  
Indian Stock Market ◽  
Weak Form Efficiency

The competence of a financial system is entirely depending upon the stock market efficiency. The gradual growth of equity investor’s participation is inevitable to enrich the overall growth of emerging economies.Hence the necessity is felt to provide an empirical support to the investing community. For the purpose, this study attempts to examine the weak-form efficiency of Indian stock market – National Stock Exchange (NSE). The study has used the daily closing price of the Nifty fifty stocks from 3rdJanuary 2011 to 24thApril 2015. To test the weak form efficiency both parametric and non-parametric tests called Autocorrelation, Augmented Dicky Fuller test, and Runs Test were performed.  The study reveals that 39 stocks of NSE-Nifty Fifty are found to be weak form inefficient, so that the investors can formulate trading strategies to gain abnormal returns. The Index and 10 stocks are found to be weak form efficient during the study period since the price series found to be autocorrelation existence.

Thanks, neighbor! Stock market experience around significant European tax cuts

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huabing Wang ◽  
Anne Macy
Keyword(s):  
Stock Market ◽  
Spillover Effect ◽  
Abnormal Returns ◽  
The Other ◽  
Stock Index ◽  
Corporate Tax ◽  
Cross Sectional ◽  
Content Type ◽  
Study Approach ◽  
Tax Cuts

PurposeThis paper analyzes the effect of corporate tax cuts on the competitiveness of the tax-cutting countries and neighbor countries.Design/methodology/approachThis study utilizes four significant corporate tax reforms among the OECD countries in Europe that offer a one-time tax cut of 6% or more. The short-term event study approach examines the stock index reactions for both the tax-cutting countries and the other countries. Multivariate fixed-effect regressions are employed to study the cross-sectional variations in the non-tax-cut countries.FindingsThis paper finds positive excess returns for Slovakia and Germany around the tax-cut passage. Multivariate analysis of stock market reactions of the non-tax-cutting countries reveals some evidence supporting both the positive spillover effect and the negative competitive loss effect. More advanced countries are more likely to experience higher abnormal returns, while higher tax countries are more likely to suffer lower abnormal returns. Other factors identified that might have influenced the effect of a foreign tax cut include the existing trade flows with the tax-cutting countries, whether the country has a common currency and the export orientation of the economy.Research limitations/implicationsThe findings are subject to sample-size issues. The lack of results for the other two countries is due to complicating events, as suggested by the further investigation of concurrent news events around the event days.Practical implicationsThe simultaneous analysis of the reform countries and the other countries in the region suggests that policymakers need to consider the relative positioning of their country vs the other countries in terms of economic development and current tax burdens when determining the optimal policy for their country or to respond to the tax policy changes in the other countries.Originality/valueThis study offers empirical evidence regarding the effect of corporate tax changes on competitiveness through the lens of stock markets' reactions, which depend on the net results of the spillover gain vs the competitive loss.

scholarly journals Does switching trading venues create value? Evidence from Hong Kong

2020 ◽  
Vol 27 (2) ◽  
pp. 209-222 ◽  
Author(s):  
Johnny K.H. Kwok
Keyword(s):  
Hong Kong ◽  
Stock Market ◽  
Stock Price ◽  
Abnormal Returns ◽  
Excess Returns ◽  
Trading Activity ◽  
Content Type ◽  
Growth Enterprise Market ◽  
Two Measures ◽  
Hong Kong Stock Market

PurposeThe purpose of this paper is to study whether switching trading venues create value in the Hong Kong stock market.Design/methodology/approachBy using an event study, the paper investigates the abnormal returns (AR) earned by firms in the Growth Enterprise Market (GEM) relating to switching to the Main Board (MB). Two measures, turnover of the stock and Amihud’s (2002) illiquidity ratio, are used to examine the liquidity effects.FindingsThe switch is accompanied by a long-term increase in stock price for low liquidity firms only. High liquidity firms underperform with persistent negative excess returns after switching, while the transient negative excess returns in low liquidity firms reverse gradually. The results further show a significant increase in trading activity for low liquidity firms following the switch, while there is a significant decline in both trading activity and liquidity in firms with high liquidity. The overall results suggest that moving from GEM to the MB is beneficial to low liquidity firms but detrimental to high liquidity firms.Originality/valueThis study is the first to investigate whether moving from GEM to the MB creates value in the Hong Kong stock market.

Stock market reaction to cash dividends: evidence from the Nigerian stock market

2019 ◽  
Vol 45 (3) ◽  
pp. 366-380
Author(s):  
Friday Kennedy Ozo ◽  
Thankom Gopinath Arun
Keyword(s):  
Stock Market ◽  
Event Study ◽  
Stock Price ◽  
Abnormal Returns ◽  
Cash Dividend ◽  
Content Type ◽  
Price Reaction ◽  
Stock Market Reaction ◽  
Dividend Announcements ◽  
Stock Price Reaction

PurposeVery little is known about the effect of dividend announcements on stock prices in Nigeria, despite the country’s unique institutional environment. The purpose of this paper is, therefore, to provide empirical evidence on this issue by investigating the stock price reaction to cash dividends by companies listed on the Nigerian Stock Exchange.Design/methodology/approachStandard event study methodology, using the market model, is employed to determine the abnormal returns surrounding the cash dividend announcement date. Abnormal returns are also calculated employing the market-adjusted return model as a robustness check and to test the sensitivity of the results toβestimation. The authors also examine the interaction between cash dividends and earnings by estimating a regression model where announcement abnormal returns are a function of both dividend changes and earnings changes relative to stock price.FindingsThe study find support for the signaling hypothesis: dividend increases are associated with positive stock price reaction, while dividend decreases are associated with negative stock price reaction. Companies that do not change their dividends experience insignificant positive abnormal returns. The results also suggest that both dividends and earnings are informative, but dividends contain information beyond that contained in earnings.Research limitations/implicationsThe sample for the study includes only cash dividend announcements occurring without other corporate events (such as interim dividends, stock splits, stock dividends, and mergers and acquisitions) during the event study period. The small firm-year observations may limit the validity of generalizations from these conclusions.Practical implicationsThe findings are useful to researchers, practitioners and investors interested in companies listed on the Nigerian stock market for their proper strategic decision making. In particular, the results can be used to encourage transparency and good governance practices in the Nigerian stock market.Originality/valueThis paper adds to the very limited research on the stock market reaction to cash dividend announcements in Nigeria; it is the first of its kind employing a unique cash dividends data.

Stock market predictability

2014 ◽  
Vol 31 (4) ◽  
pp. 354-370 ◽  
Author(s):  
Silvio John Camilleri ◽  
Christopher J. Green
Keyword(s):  
Stock Market ◽  
High Frequency ◽  
Serial Correlation ◽  
Design Methodology ◽  
High Frequency Data ◽  
Frequency Data ◽  
Content Type ◽  
Lag Effects ◽  
Daily Data ◽  
Indian Stock Market

Purpose – The main objective of this study is to obtain new empirical evidence on non-synchronous trading effects through modelling the predictability of market indices. Design/methodology/approach – The authors test for lead-lag effects between the Indian Nifty and Nifty Junior indices using Pesaran–Timmermann tests and Granger-Causality. Then, a simple test on overnight returns is proposed to infer whether the observed predictability is mainly attributable to non-synchronous trading or some form of inefficiency. Findings – The evidence suggests that non-synchronous trading is a better explanation for the observed predictability in the Indian Stock Market. Research limitations/implications – The indication that non-synchronous trading effects become more pronounced in high-frequency data suggests that prior studies using daily data may underestimate the impacts of non-synchronicity. Originality/value – The originality of the paper rests on various important contributions: overnight returns is looked at to infer whether predictability is more attributable to non-synchronous trading or to some form of inefficiency; the impacts of non-synchronicity are investigated in terms of lead-lag effects rather than serial correlation; and high-frequency data is used which gauges the impacts of non-synchronicity during less active parts of the trading day.

Stock market reactions to layoff announcements – analysis of the renewable energy sector

2017 ◽  
Vol 11 (2) ◽  
pp. 311-328 ◽  
Author(s):  
Stephan Kunert ◽  
Dirk Schiereck ◽  
Christopher Welkoborsky
Keyword(s):  
Renewable Energy ◽  
Stock Market ◽  
Capital Market ◽  
Abnormal Returns ◽  
Shareholder Wealth ◽  
Energy Sector ◽  
Market Reactions ◽  
Content Type ◽  
The Public ◽  
Stock Market Reactions

Purpose This study aims to analyze stock market reactions to layoff announcements in the renewable energy sector. The global renewable energy sector and most of the producers of wind and solar energy equipment are struggling. While changes in the regulation and in the promotion of energy production from renewable sources reduced the attractiveness of these technologies, many involved companies had to downsized their workforce to increase performance. The public often perceives these announcements as a way of increasing shareholder wealth at the cost of the employees. Support for this claim is often given in the form of isolated case study considerations. However, the case may be different for the renewable energy sector as changes in the overall institutional environment have sustainably deteriorated the prospects of this industry. Design/methodology/approach This study analyses stock market reactions of 65 layoff announcements made by companies in the renewable energy industry in the years from 2005 to 2014. The reactions are measured by cumulative abnormal returns, which are obtained by using the event study methodology. Findings It shows a significantly negative market reaction to the announcement of a layoff plan on the event day. The findings are generally in line with our expectations and underline the negative perspectives of the sector from a capital market point of view and the declining importance of the sector with respect to employment numbers. Originality/value The results of this study are important for investors when estimating the capital market reactions to layoff announcements and when they form their own expectations regarding possible future layoff announcements. For the public, the results are of interest as the prejudice, that layoff plans are used to increase shareholder wealth, can be dismantled. The opposite is shown.

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