scholarly journals Do Banking and Financial Services Sectors Show Herding Behaviour in Indian Stock Market Amid COVID-19 Pandemic? Insights from Quantile Regression Approach

2021 ◽  
pp. 097639962110323
Author(s):  
P. K. Mishra ◽  
S. K. Mishra
Keyword(s):  
Stock Market ◽  
Quantile Regression ◽  
Financial Services ◽  
Stock Exchange ◽  
Financial Assets ◽  
Supply Chain Disruptions ◽  
Market Participants ◽  
Market Instability ◽  
Indian Stock Market ◽  
Stock Market Investment

In India, the coronavirus (COVID-19) pandemic-induced country-wide regulatory lockdown and consequential supply-chain disruptions and market instability have all posed serious challenges before the regulators and policymakers. Amid the pandemic, the stock market showed return volatilities primarily due to the unexpected investors’ behaviour. One of the behavioural biases is herding, which has the power to wreck the market equilibrium and shatter the market efficiency. Given that the pandemic has generated unprecedented spirals of uncertainties across the globe, thereby creating interruptions in the pattern of stock market investment decisions, this study examined the herding behaviour of 54 stocks of banking and financial services sectors listed in the national stock exchange. In the quantile regression framework, the study provides evidence of the presence of herding for public sector banking and financial services under the bull market conditions during the pandemic in the 90th quantile of the return distribution. This finding has implications for the mispricing of financial assets in these sectors. So, the study suggests removing information asymmetry among the market participants and devising policy initiatives for ensuring market stability.

Risk-Managed Momentum: An Evidence from Indian Stock Market

2021 ◽  
pp. 231971452110230
Author(s):  
Simarjeet Singh ◽  
Nidhi Walia ◽  
Pradiptarathi Panda ◽  
Sanjay Gupta
Keyword(s):  
Stock Market ◽  
Asset Management ◽  
Stock Exchange ◽  
Sharpe Ratio ◽  
Relative Momentum ◽  
Extended Time ◽  
Momentum Strategies ◽  
Momentum Profits ◽  
Indian Stock Market ◽  
Time Frames

Relative momentum strategies yield large and substantial profits in the Indian Stock Market. Nevertheless, relative momentum profits are negatively skewed and prone to occasional severe losses. By taking into consideration 450 stocks listed on the Bombay Stock Exchange, the present study predicts the timing of these huge momentum losses and proposes a simple risk-managed momentum approach to avoid these losses. The proposed risk-managed momentum approach not only doubles the adjusted Sharpe ratio but also results in significant improvements in downside risks. In contrast to relative momentum payoffs, risk-managed momentum payoffs remain substantial even in extended time frames. The study’s findings are particularly relevant for asset management companies, fund houses and financial academicians working in the area of asset anomalies.

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.

Application of CAPM in the Indian Stock Market A Comprehensive Reassessment

2005 ◽  
Vol 1 (2) ◽  
pp. 1-12 ◽  
Author(s):  
Raj S. Dhankar ◽  
Rohini Singh
Keyword(s):  
Stock Market ◽  
Capital Market ◽  
Stock Exchange ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Conflicting Evidence ◽  
Empirical Tests ◽  
Indian Stock Market

There is conflicting evidence on the applicability of Capital Asset Pricing Model in the Indian stock market. Data for 158 stocks listed on the Bombay Stock Exchange was analyzed using a number of tests from 1991–2002, the period which roughly coincides with the period after liberalization and initiation of capital market reforms. Taken in aggregate the various empirical tests show that CAPM is not valid for the Indian stock market for the period studied.

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.

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.

Friday the 13th effect on Indian stock market

2020 ◽  
Vol 07 (02) ◽  
pp. 2050010
Author(s):  
Tarika Singh Sikarwar ◽  
Karuna Shrivastava ◽  
Pratibha Jadon
Keyword(s):  
Stock Market ◽  
Design Methodology ◽  
Stock Exchange ◽  
Emerging Market ◽  
Indian Market ◽  
Study Results ◽  
Developed Nations ◽  
Indian Stock Market ◽  
Work Done ◽  
Practical Implications

Purpose: This paper attempts to investigate the presence of Friday the 13th Effect in the Indian stock market. Design/methodology/approach: This paper tests the presence of the Friday the 13th Effect using different sets of hypotheses for 7 days, 15 days and normal versus Friday the 13th by using statistical methods. Findings: The findings of the study do not support the presence of Friday the 13th Effect for all cases. There are few months for certain specific years where the effect was seen. Research limitations/implications: The Friday the 13th effect has been examined for two major indices of the Indian market, i.e., the Bombay Stock Exchange Index SENSEX and the National Stock Exchange Nifty Fifty Index. However, there are other major and sectoral indices as well where in the effect may be checked. Practical implications: The study results indicate that Indian stock market shows phased anomaly. The effect of Friday the 13th is seen only in some cases during certain years only. Originality/value: Friday the 13th effect has been mostly checked for developed nations and again there has been less work done with respect to this particular market anomaly. The present research is an original work done for emerging market naming India.

The Settlement Infrastructure of Ukrainian Stock Market: State and Directions for Reform

2020 ◽  
Vol 10 (2) ◽  
pp. 565
Author(s):  
Oleksandra V. KOLOHOIDA ◽  
Iryna V. LUKACH ◽  
Valeriia V. POIEDYNOK ◽  
Volodymyr I. BOBRYK
Keyword(s):  
Stock Market ◽  
Legal Status ◽  
Stock Exchange ◽  
Financial Instruments ◽  
Legal Personality ◽  
Market Participants ◽  
Clearing Functions ◽  
Market State ◽  
Exchange Markets ◽  
Banking Institution

The research defines the concepts of clearing and clearing activity. It explores the models of the clearing institutions’ organizational structure in EU countries. It also outlines the directions for the settlement and clearing infrastructure reform based on the diversification of the settlement and clearing functions. It should ensure the integrity of the stock market, the reduction of risks, the creation of an efficient and transparent system for the execution of transactions with securities; reduction of expenses of market participants; acceleration of payment terms for operations with securities and process of registration of property rights; differentiation of responsibility at different stages of performance of transactions. The author has defined the legal status of the Financial Settlements Center as a banking institution with a special legal personality of the conducting monetary settlements under transactions concerning securities and other financial instruments, made on the stock exchange and outside the stock exchange, if payments are made according to the principle of ‘supply against payment’. The study shows the need for the universal model of settlements to serve all the exchange markets. We offer to demonopolize the market of clearing services and to provide access for international clearing institutions. We also suggest transferring the settlement function to the Central Depositary and the clearing function – to clearing institutions.  

scholarly journals The performance of the Indian stock market during COVID-19

2020 ◽  
Vol 17 (3) ◽  
pp. 133-147
Author(s):  
Rashmi Chaudhary ◽  
Priti Bakhshi ◽  
Hemendra Gupta
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Stock Exchange ◽  
Health Care Information ◽  
Crisis Period ◽  
Daily Data ◽  
Composite Indices ◽  
Health Care Information Technology ◽  
Indian Stock Market ◽  
The Impact

The current empirical study attempts to analyze the impact of COVID-19 on the performance of the Indian stock market concerning two composite indices (BSE 500 and BSE Sensex) and eight sectoral indices of Bombay Stock Exchange (BSE) (Auto, Bankex, Consumer Durables, Capital Goods, Fast Moving Consumer Goods, Health Care, Information Technology, and Realty) of India, and compare the composite indices of India with three global indexes S&P 500, Nikkei 225, and FTSE 100. The daily data from January 2019 to May 2020 have been considered in this study. GLS regression has been applied to assess the impact of COVID-19 on the multiple measures of volatility, namely standard deviation, skewness, and kurtosis of all indices. All indices’ key findings show lower mean daily return than specific, negative returns in the crisis period compared to the pre-crisis period. The standard deviation of all the indices has gone up, the skewness has become negative, and the kurtosis values are exceptionally large. The relation between indices has increased during the crisis period. The Indian stock market depicts roughly the same standard deviation as the global markets but has higher negative skewness and higher positive kurtosis of returns, making the market seem more volatile.

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