Disposition effect at the market level: evidence from Indian stock market

2019 ◽  
Vol 12 (2) ◽  
pp. 69-82
Author(s):  
Sravani Bharandev ◽  
Sapar Narayan Rao
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Reference Points ◽  
Disposition Effect ◽  
Content Type ◽  
Ex Post ◽  
Abnormal Trading Volume ◽  
The Difference ◽  
Trading Volumes ◽  
Indian Stock Market

Purpose The purpose of this paper is to test the disposition effect at market level and propose an appropriate reference point for testing disposition at market level. Design/methodology/approach This is an empirical study conducted on 500 index stocks of NSE500 (National Stock Exchange). Winning and losing days for each stock are calculated using 52-week high and low prices as reference points. To test disposition effect, abnormal trading volumes of stocks are regressed on their percentage of winning (losing) days. Further using ANOVA, the difference between mean of percentage of winning (losing) days of high abnormal trading volume deciles and low abnormal trading volume deciles is tested. Findings Results show that a stock’s abnormal trading volume is positively influenced by the percentage of winning days whereas percentage of losing days show no such effect. Findings are consistent even after controlling for volatility and liquidity. ANOVA results show the presence of high percentage of winning days in higher deciles of abnormal trading volumes and no such pattern in case of losing days confirms the presence of disposition effect. Further an ex post analysis indicates that disposition prone investors accumulate losses. Originality/value This is the first study, which proposes the use of 52-week high and low prices as reference points to test the market-level disposition effect. Findings of this study enhance the limited literature available on disposition effect in emerging markets by providing evidence from Indian stock markets.

scholarly journals The Influence of Trading Volume, Market Trend, and Monetary Policy on Characteristics of the Chinese Stock Exchange: An Econophysics Perspective

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 985-998
Author(s):  
Meng Ran ◽  
Zhenpeng Tang ◽  
Weihong Chen
Keyword(s):  
Monetary Policy ◽  
Trading Volume ◽  
Stock Exchange ◽  
Composite Index ◽  
Policy Formulation ◽  
Time Intervals ◽  
Monetary Policies ◽  
Policy Cycles ◽  
Trading Volumes ◽  
Healthy Growth

Abstract The paper adopts the financial physics approach to investigate influence of trading volume, market trend, as well as monetary policy on characteristics of the Chinese Stock Exchange. Utilizing 1-minute high-frequency data at various time intervals, the study examines the probability distribution density, autocorrelation and multi-fractal of the Shanghai Composite Index. Our study finds that the scale of trading volume, stock market trends, and monetary policy cycles all exert significant influences on micro characteristics of Shanghai Composite Index. More specifically, under the conditions of large trading volumes, loose monetary policies, and downward stock trends, the market possesses better fitting on Levy’s distribution, the volatility self-correlation is stronger, and multifractal trait is more salient. We hope our study could provide better guidance for investment decisions, and form the basis for policy formulation aiming for a healthy growth of the financial market.

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.

Reporting human resources in annual reports

2015 ◽  
Vol 23 (3) ◽  
pp. 256-274 ◽  
Author(s):  
Monika Kansal ◽  
Mahesh Joshi
Keyword(s):  
Human Resources ◽  
Stock Exchange ◽  
Statistical Tests ◽  
Annual Reports ◽  
Public And Private ◽  
Content Type ◽  
Industrial Sectors ◽  
Significant Difference ◽  
The Difference ◽  
Training Programmes

Purpose – The purpose of this paper is to investigate the extent of corporate disclosure on human resources (HR) in the annual reports of top performing Indian companies. Design/methodology/approach – The paper explores the extent to which top 82 companies from India present information about HR in their annual reports. This study examines the annual reports of each of the top Indian firms listed on the Bombay stock exchange, using the “content analysis” method. Statistical tests have been performed to analyse the difference between the HR disclosure score across public and private sectors and disclosure variations among various industrial sectors. Findings – In-house training programmes has been noticed to be the favourite item of disclosure followed by safety awards/certifications and statements regarding cordial relations with the employees/unions. A majority of the Indian firms have ignored significant HR issues such as employee welfare fund, maternity/paternity leaves, holiday benefits, employee loans and adopting old age homes, etc. Overall, the study reflects low HR related disclosures. No statistically significant difference has been found between the mean HR disclosure from one industry to another and disclosure practices of the private and the public sector companies. Practical implications – The disclosure pattern of the Indian companies suggests that they only a few companies are concerned about employees’ welfare than the rest. This may motivate a change of the disclosure policy of the rest of the firms who may follow the reporting pattern of the most disclosing ones. Originality/value – This is first study on the disclosure of HR by the Indian corporate sector in the CSR domain with a disclosure analysis for a period of nine years . This research provides new directions for the literature in this area and may promote comparative studies on HR-based studies from different perspectives.

scholarly journals Trading Volume as a Predictor of Market Movement

2019 ◽  
Vol 8 (2) ◽  
pp. 57-69
Author(s):  
Edson Kambeu
Keyword(s):  
Logistic Regression ◽  
Stock Market ◽  
Regression Model ◽  
Trading Volume ◽  
Logistic Regression Model ◽  
Predictive Analytics ◽  
Stock Exchange ◽  
Stock Market Index ◽  
Trading Volumes ◽  
Popular Language

A logistic regression model is has also become a popular model because of its ability to predict, classify and draw relationships between a dichotomous dependent variable and dependent variables. On the other hand, the R programming language has become a popular language for building and implementing predictive analytics models. In this paper, we apply a logistic regression model in the R environment in order to examine whether daily trading volume at the Botswana Stock Exchange influence daily stock market movement. Specifically, we use a logistic regression model to find the relationship between daily stock movement and the trading volumes experienced in the recent five previous trading days. Our results show that only the trading volume for the third previous day influence current stock market index movement. Overall, trading volumes of the past five days were found not have an impact on today’s stock market movement. The results can be used as a basis for building a predictive model that utilizes trading as a predictor of stock market movement.

Investors overconfidence behaviour at Bombay Stock Exchange

2018 ◽  
Vol 14 (5) ◽  
pp. 613-632 ◽  
Author(s):  
Venkata Narasimha Chary Mushinada ◽  
Venkata Subrahmanya Sarma Veluri
Keyword(s):  
Private Information ◽  
Trading Volume ◽  
Negative Impact ◽  
Stock Exchange ◽  
Public Information ◽  
Response Analysis ◽  
Content Type ◽  
Daily Data ◽  
Level Data ◽  
Attribution Bias

PurposeThe purpose of the paper is to empirically test the overconfidence hypothesis at Bombay Stock Exchange (BSE).Design/methodology/approachThe study applies bivariate vector autoregression to perform the impulse-response analysis and EGARCH models to understand whether there is self-attribution bias and overconfidence behavior among the investors.FindingsThe study shows the empirical evidence in support of overconfidence hypothesis. The results show that the overconfident investors overreact to private information and underreact to the public information. Based on EGARCH specifications, it is observed that self-attribution bias, conditioned by right forecasts, increases investors’ overconfidence and the trading volume. Finally, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a contribution to the observed excessive volatility.Research limitations/implicationsThe study focused on self-attribution and overconfidence biases using monthly data. Further studies can be encouraged to test the proposed hypotheses on daily data and also other behavioral biases.Practical implicationsInsights from the study suggest that the investors should perform a post-analysis of each investment so that they become aware of past behavioral mistakes and stop continuing the same. This might help investors to minimize the negative impact of self-attribution and overconfidence on their expected utility.Originality/valueTo the best of the authors’ knowledge, this is the first study to examine the investors’ overconfidence behavior at market-level data in BSE, India.

A new look at the meeting clustering effect

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ángel Pardo ◽  
Eddie Santandreu
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Relevant Information ◽  
Investor Attention ◽  
Content Type ◽  
Potential Link ◽  
Clustering Effect ◽  
Trading Volumes ◽  
The Relationship

PurposeThe study aims to test the existence of a meeting clustering effect in the Spanish Stock Exchange (SSE).Design/methodology/approachThis paper studies the relationship between the clustering of annual general meetings and stock returns in the SSE. A multivariate analysis is carried out in order to analyse the relationship between monthly returns and the clustering of general meetings in the SSE.FindingsThe authors show that meeting clustering exists and that some months exhibit significant and positive additional returns related to the holding of ordinary or extraordinary general meetings.Research limitations/implicationsThe authors have explored some possible explanations for the meeting clustering effect, such as a potential link with the “Halloween” effect or the presence of higher-than-normal levels of volatility, trading volumes or investor attention. However, none of these can explain the meeting clustering effect that emerges as a new anomaly in the SSE.Practical implicationsThe authors have documented significant and positive abnormal returns in some months that coincide with the holding of general meetings. Therefore, the holding of ordinary and/or extraordinary meetings in some months involves the release of relevant information for investors.Originality/valueThis study complements the financial literature because it is focused on the clustering of meetings and its effect on a stock market whose legal order is based on civil law. This fact allows us to shed new light on meeting clustering and its effect on other types of markets.

scholarly journals A Study of Black–Scholes Model’s Applicability in Indian Capital Markets

Paradigm ◽  
2020 ◽  
Vol 24 (1) ◽  
pp. 73-92
Author(s):  
Anubha Srivastava ◽  
Manjula Shastri
Keyword(s):  
Stock Market ◽  
Option Pricing ◽  
Trading Volume ◽  
Stock Exchange ◽  
Market Price ◽  
Significant Degree ◽  
Pricing Model ◽  
Fair Price ◽  
Black Scholes ◽  
Indian Stock Market

Derivative trading, started in mid-2000, has become an integral and significant part of Indian stock market. The tremendous increase in trading volume in Indian stock market has reflected into high volatility in the option prices. The pricing of options is very complex aspect of applied finance and has been subject of extensive research. Black–Scholes option model is a scientific pricing model which is applied for determining the fair price for option contracts. This article examines if Black–Scholes option pricing model (BSOPM) is a good indicator of option pricing in Indian context. The literature review highlights that various studies have been conducted on BSOPM in various stock exchange across the world with mixed outcome on its relevance and applicability. This article is an empirical study to test the relevance of BSOPM for which 10 most popular industry’s stock listed on National Stock Exchange have been taken. Then the BSOPM has been applied using volatility and risk-free rate. Furthermore, t-test has been used to test the hypothesis and determine the significant relationship between BS model values and actual model values. This study concludes that BSOPM involves significant degree of mispricing. Hence, this model alone cannot be adopted as an indicator for option pricing. The variation from market price is synchronised with respect to moneyness and time to maturity of the option.

Do financial crises discipline future credit growth?

2017 ◽  
Vol 9 (3) ◽  
pp. 284-301
Author(s):  
Puspa Amri ◽  
Eric M.P. Chiu ◽  
Greg Richey ◽  
Thomas D. Willett
Keyword(s):  
Financial Crises ◽  
Statistical Tests ◽  
Empirical Support ◽  
Banking Regulation ◽  
Banking Crises ◽  
Credit Growth ◽  
Content Type ◽  
Ex Post ◽  
The Difference ◽  
Banking Regulation And Supervision

Purpose The purpose of this paper is to test whether financial crises themselves provide some degree of ex post discipline. In other words, is there learning from the mistakes associated with crises? The authors test this hypothesis on credit growth, a frequent contributor to banking crises. Design/methodology/approach The study uses statistical tests (comparison of means) on a sample of 72 banking crises, the onset of which occurred between 1980 and 2008. Tests for significance of the difference are conducted using Kolmogorov–Smirnov equality in distribution tests. Findings The results show that real credit growth fell substantially (relative to average) by about 8 per cent points from pre- to post-crisis periods, and that average banking regulation and supervision strengthens after a crisis. Originality/value This paper provides empirical support for the proposition that while financial markets may fail to give sufficient warning signals before a financial crisis, they may discipline governments to undertake reforms in the aftermath of a crisis.

scholarly journals The Market Reaction Around Ex-Dates of Stock Splits Before and After Decimalization

2005 ◽  
Vol 08 (02) ◽  
pp. 201-216 ◽  
Author(s):  
Robin K. Chou ◽  
Wan-Chen Lee ◽  
Sheng-Syan Chen
Keyword(s):  
New York ◽  
Stock Price ◽  
Trading Volume ◽  
Stock Exchange ◽  
New York Stock Exchange ◽  
Short Term ◽  
Tick Size ◽  
York Stock Exchange ◽  
Before And After ◽  
Abnormal Trading Volume

This paper examines the stock price behavior around the ex-split dates both before and after the decimalization on the New York Stock Exchange (NYSE). We find that the abnormal ex-split day returns decrease and the abnormal trading volume increases in the 1/16th and decimal pricing eras, relative to the 1/8th pricing era. These findings are consistent with the microstructure-based explanations for the ex-day price movements. Our study also supports the hypothesis that short-term traders perform arbitrage activities during the ex-split dates when transaction costs become lower after the tick size is reduced.

Determinants of house buyers’ expected holding periods in boom and bust markets in California

2017 ◽  
Vol 10 (2) ◽  
pp. 256-281 ◽  
Author(s):  
Ekaterina Chernobai ◽  
Tarique Hossain
Keyword(s):  
Rational Expectation ◽  
House Price ◽  
Housing Markets ◽  
Real Estate Market ◽  
Disposition Effect ◽  
Content Type ◽  
Ex Post ◽  
Novel Approach ◽  
Ex Ante ◽  
Financial Characteristics

Purpose This study aims to investigate the determinants of homeowners’ planned holding periods. Real estate market is known for displaying buying and selling behavior that does not conform to traditional economic theories such as rational expectation or expected utility. Mounting evidence of anomalous observations appear to be supported by other theories, such as prospect theory, which in particular helps explain the disposition effect – sellers are too quick to sell when prices are climbing and hold on to properties longer when prices are plummeting. While this evidence is widely documented in housing studies based on data on realized holding periods (i.e. ex post), this study explores factors that may motivate homeowners to alter their expected holding horizons (i.e. ex ante) to form new preferred holding periods that may be shorter or longer than those planned during house search. Design/methodology/approach The empirical study uses data collected from two cross-section surveys of recent homebuyers in rising and declining housing markets in Southern California in 2004-2005 and 2007-2008, respectively. Findings The empirical results demonstrate that in addition to the financial characteristics of the recent homebuyer, the characteristics of the buying experience – non-monetary, such as the realized search duration, and monetary, such as perception of negative or positive premium paid for the house relative to its market value – have a statistically significant effect on the holding horizon revision. The data strongly indicate that the perception of having overpaid increases the likelihood of upward revision of the original holding horizon. This effect is stronger in the declining than in the rising market – a crucial finding that mirrors the disposition effect. Originality/value This study sheds new light on what may contribute to the disposition effect in housing markets that has not yet been investigated in past literature. The novel approach here is to look at how different house price environments may affect homeowners’ holding periods ex ante when they begin, rather than ex post when already realized.

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