This study examines the day-of-the-week effect in the Indian stock market by analyzing daily returns of the S&P CNX NIFTY index from 1992 to 2004. It tests the hypotheses that average returns are equal across all days of the week and that Monday and Friday returns are equal. The study is significant because day-of-the-week effects challenge the efficient market theory. It also analyzes changes in the effects after India moved to a rolling settlement system in 1996.
The Indian stock market ended lower for the week, with the Sensex and Nifty declining by 1.4% and 1.5% respectively. The BSE mid-cap and small-cap indices also fell but outperformed their large-cap counterparts. The BSE Bankex index outperformed the Sensex, gaining 0.4% for the week. RBI raised repo and reverse repo rates by 25bp and 50bp respectively to 4.5% and 5.75%. SKS Microfinance offers exposure to India's large microfinance opportunity through a strong pan-India network and focus on risk management.
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
An empirical study of macroeconomic factors and stock market an indian persp...Saurabh Yadav
This document presents an empirical study analyzing the relationship between macroeconomic factors and the Indian stock market from 1990 to 2011. The study uses various econometric tools like unit root tests, cointegration tests, vector autoregression models, impulse response analysis, and Granger causality tests to analyze the impact of macroeconomic indicators like industrial production, money supply, inflation on the BSE Sensex index. It aims to contribute new insights on how regulatory changes in the Indian economy over this period impacted asset prices and whether domestic or global factors had a larger influence on the Indian stock market.
Macroeconomic effects on the stock marketWINGFEI CHAN
This document presents a group project investigating the effects of macroeconomic factors on stock market returns using the S&P 500 index. The project uses monthly data from 2007 to 2011 to test the model developed by Chen, Roll and Ross (1986) which identified seven economic variables that could impact stock prices. The paper reviews previous literature on the topic, describes the data collection and processing methodology, and outlines the ordinary least squares regression analysis and diagnostic tests to be performed. Key macroeconomic variables examined include industrial production, inflation, risk premium, term structure, oil prices and consumption expenditure. The results of the statistical analyses are presented and conclusions are drawn regarding the relationship between the macroeconomic factors and stock market returns.
Special report by epic research of 29 november 2017Epic Research
Epic Research prepares a special report on a daily basis which provides share market overview to the investors in brief. We aim to serve you best in class financial services at affordable prices.
Stochastic modeling of Rainfall Disaggregation using ANNShashank Singh
Rainfall Disaggregation modeling using stochastic model, Valencia-Schaake, Lane alongwith application of Artificial Neural Network to Disaggregate higher order scale time series to lower time scale series.
~Shashank Singh~
The document provides an overview of the S&P CNX Nifty index methodology. It is India's leading stock market index, comprising the 50 largest Indian companies listed on the National Stock Exchange based on market capitalization. The index covers 22 sectors of the Indian economy and aims to reflect overall market conditions. It is jointly owned and managed by India Index Services and Products and Standard & Poor's.
The Indian stock market ended lower for the week, with the Sensex and Nifty declining by 1.4% and 1.5% respectively. The BSE mid-cap and small-cap indices also fell but outperformed their large-cap counterparts. The BSE Bankex index outperformed the Sensex, gaining 0.4% for the week. RBI raised repo and reverse repo rates by 25bp and 50bp respectively to 4.5% and 5.75%. SKS Microfinance offers exposure to India's large microfinance opportunity through a strong pan-India network and focus on risk management.
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
An empirical study of macroeconomic factors and stock market an indian persp...Saurabh Yadav
This document presents an empirical study analyzing the relationship between macroeconomic factors and the Indian stock market from 1990 to 2011. The study uses various econometric tools like unit root tests, cointegration tests, vector autoregression models, impulse response analysis, and Granger causality tests to analyze the impact of macroeconomic indicators like industrial production, money supply, inflation on the BSE Sensex index. It aims to contribute new insights on how regulatory changes in the Indian economy over this period impacted asset prices and whether domestic or global factors had a larger influence on the Indian stock market.
Macroeconomic effects on the stock marketWINGFEI CHAN
This document presents a group project investigating the effects of macroeconomic factors on stock market returns using the S&P 500 index. The project uses monthly data from 2007 to 2011 to test the model developed by Chen, Roll and Ross (1986) which identified seven economic variables that could impact stock prices. The paper reviews previous literature on the topic, describes the data collection and processing methodology, and outlines the ordinary least squares regression analysis and diagnostic tests to be performed. Key macroeconomic variables examined include industrial production, inflation, risk premium, term structure, oil prices and consumption expenditure. The results of the statistical analyses are presented and conclusions are drawn regarding the relationship between the macroeconomic factors and stock market returns.
Special report by epic research of 29 november 2017Epic Research
Epic Research prepares a special report on a daily basis which provides share market overview to the investors in brief. We aim to serve you best in class financial services at affordable prices.
Stochastic modeling of Rainfall Disaggregation using ANNShashank Singh
Rainfall Disaggregation modeling using stochastic model, Valencia-Schaake, Lane alongwith application of Artificial Neural Network to Disaggregate higher order scale time series to lower time scale series.
~Shashank Singh~
The document provides an overview of the S&P CNX Nifty index methodology. It is India's leading stock market index, comprising the 50 largest Indian companies listed on the National Stock Exchange based on market capitalization. The index covers 22 sectors of the Indian economy and aims to reflect overall market conditions. It is jointly owned and managed by India Index Services and Products and Standard & Poor's.
The document discusses the NIFTY and SENSEX stock market indices of India. It provides details on:
1) How the SENSEX and NIFTY indices are calculated based on the free-floating market capitalization of their constituent stocks. The SENSEX includes 30 stocks and uses 1978-79 as the base year, while NIFTY includes 50 stocks and uses 1995 as the base year.
2) The major companies that make up the SENSEX (e.g. Reliance, TCS, HDFC Bank) and NIFTY (same top companies).
3) A brief history of the National Stock Exchange and the objectives and products it offers.
This document provides information about tutorials and datasets for using the STATA data analysis software. It explains that the tutorials use example datasets from an econometrics textbook and how to download the datasets and command files from www.STATA.org.uk. The website also contains step-by-step screenshot guides for using STATA and tutorials on topics like data management, statistical analysis, graphs, regressions, and other analyses.
STATA is data analysis software that can be used via menu options or typed commands. It has a wide range of econometric techniques and can open, examine, and run regressions on datasets. The tutorials on www.STATA.org.uk provide step-by-step guides for using STATA to perform tasks like data management, statistical analysis, importing data, summary statistics, graphs, regressions, and other analyses.
The document provides an overview of the Sensex and Nifty stock market indices in India. It discusses that the Sensex tracks the performance of the 30 largest companies listed on the Bombay Stock Exchange, while Nifty tracks the 50 largest companies listed on the National Stock Exchange. It provides details on how the indices are calculated and composed. It also discusses sectoral indices and provides examples of different sectoral indices that track specific industries.
The document provides information about key stock market indices in India, including the BSE Sensex and Nifty 50. It discusses what they are, how they are calculated, their objectives, and historical performance. Specifically, it notes that the Sensex is a market capitalization-weighted index of 30 large, well-established companies listed on the Bombay Stock Exchange. It aims to measure market movements, serve as a benchmark for fund performance, and facilitate index-based derivatives. The top sectors and companies in the Sensex by weight are also outlined.
This document outlines tutorials for using STATA software to perform time series analysis. It discusses how to manage time series data, perform Dickey-Fuller tests, estimate ARIMA, VAR, and ARCH/GARCH models, and provides challenges for forecasting with various models. Screenshot guides and sample datasets are available on the STATA website to help users learn how to apply these techniques in STATA. A variety of other statistical analysis topics also have tutorials on the site.
The document provides an overview of cluster analysis techniques. It discusses the need for segmentation to group large populations into meaningful subsets. Common clustering algorithms like k-means are introduced, which assign data points to clusters based on similarity. The document also covers calculating distances between observations, defining the distance between clusters, and interpreting the results of clustering analysis. Real-world applications of segmentation and clustering are mentioned such as market research, credit risk analysis, and operations management.
Index Effects on Stock Prices: Evidence from India,
Bid-Ask Spreads in Emerging Markets: Evidence from
The document discusses a study on the technical analysis of the S&P CNX Nifty Index in India. It introduces the Nifty Index and the importance of studying its price movements. It outlines the objectives to compare Nifty prices from 2003-2007 and analyze short and long term moving averages. The methodology involves using secondary data from the National Stock Exchange and statistical tools like trend analysis and moving averages. The study aims to help investors better understand market trends and determine when to buy and sell securities.
This document provides information on a project report about stock indices and factors affecting share prices. It includes a declaration by the author N.V.S Raghunath that the report was completed independently under the guidance of their professor Samanvi Bhograj. It also includes acknowledgements, a table of contents, and outlines the methodology, sources of data and limitations of the study. The study will analyze stock prices and indices of companies in the automobile sector from 2008-2011 to understand how economic, industry and company factors influence prices.
A STUDY OF CUSTOMER SATISFACTION OF NOKIA MOBILE USER IN DOMBIVALI WEST GANES...Sayali Mahajan
The document is a research project report on a study of customer satisfaction of Nokia mobile users in Dombivali West Ganesh Nagar area. It includes an introduction outlining the meaning of research methodology, objectives of the research, hypothesis, and limitations. The methodology section describes that primary and secondary data was collected through questionnaires and internal sources to analyze customer satisfaction with Nokia mobiles in the target area during October 2016.
This document is a study on the relationship between currency, equity, commodity, and their movements in the market. It includes chapters on the conceptual overview, research methodology, theoretical background, data analysis, interpretation and findings. The theoretical background chapter provides information on capital markets, equity shares, commodity markets including types of commodities traded, and foreign exchange markets. It analyzes secondary data from 2009-2014 on currency, equity, and commodities to examine their correlation and relationship. The findings suggest there is a relationship between the different market components and their movements impact each other.
This document is a research study submitted by Kiran M K to the M.P. Birla Institute of Management in partial fulfillment of an MBA degree. The study analyzes the return and beta of stocks that are components of the BSE Sensex index over an eight year period from 2001 to 2008. The objectives are to study the behavior of index stocks over time, understand their performance, and determine if there are any relationships between stock returns. The study reviews literature on beta, the capital asset pricing model, and factors that influence stock returns. It aims to test if index stocks follow a particular trend or format.
Stock return and volatility evidence from indian stock marketROHITH U J
The risk appetite of investors governs their investment in financial instruments. Persons who are minimum risk takers with return generally park their money in secure instruments but people with a higher risk appetite generally invest in a stock market financial instrument to achieve their financial goal. Investors with a higher risk appetite have to measure the market performance in the basis of risk and return so that they can alter their portfolio to keep pace with current market movement. In this research intended to study risk in terms of standard deviation and beta of all sectoral indices of NSE with respect to nifty and their performance in different time horizon and ranked them accordingly in terms of mean return and found out the best performing sector in a given time frame
A STUDY ON EQUITY & EQUITY DERIVATIVE - INDIAN SECURITIES MARKETYashmin Revawala
This document appears to be a student project report on equity and equity derivatives in the Indian securities market. It includes sections on an overview of the Indian securities market, identification of stocks from the CNX NIFTY index for investment purposes, comparing returns on investment in the CNX NIFTY index and selected stocks, using portfolio management techniques to further increase returns, an overview of the equity derivative market in India, and comparing the cash and derivative markets to analyze their impact on each other. The student also uses pivot points to predict future derivative prices and evaluates the accuracy of this prediction method.
This document describes an investigation into the relationship between market volatility and investor sentiment. It outlines the process of choosing indices to represent volatility and sentiment, and using regression analysis to select the best predictive indices. The Michigan Index of Consumer Sentiment was chosen as the sentiment indicator, and the VIX volatility index was selected. Regression results showed these two indices had p-values of 0.000, indicating they were the best predictors of S&P 500 price movements compared to alternative considered indices. The analysis of the relationship between these selected sentiment and volatility indicators will be conducted using time series methods.
The 3-page document includes:
1. Title page with the research title, student and supervisor names, and institution.
2. A brief certificate signed by the project supervisor certifying the work.
3. An acknowledgment section thanking those who assisted with the project.
4. A table of contents outlining the document structure.
A study on equity & equity derivative indian securities marketYashmin Revawala
*EQUITY:
1. Selection of Stocks using the 10 steps Process
2. Comparison of return on stocks and NIFTY BeES
3. Using Portfolio Management for increasing the return on investment
*EQUITY DERIVATIVE:
1. The impact of cash market segment on derivative market using settlement price and the value of underlying equity.
2. Predicting the cash market index (CNX NIFTY) & underlying index (FUTIDX NIFTY) using PIVOT POINT Method
This document summarizes a study examining the "day of the week effect" on stock returns in the Pakistani stock market between 2006-2010. The study finds evidence of a "Tuesday effect", with average returns on Tuesdays found to be significantly higher than other days of the week. Descriptive statistics show the mean Tuesday return was 164.88 compared to 100.25 on other days. Regression analysis also indicates returns were significantly higher on Tuesdays, violating the assumption of efficient market hypothesis that returns should be constant across all days. Therefore, the study concludes there is a day of the week effect in the Pakistani stock market with abnormal returns observed on Tuesdays.
The document discusses the NIFTY and SENSEX stock market indices of India. It provides details on:
1) How the SENSEX and NIFTY indices are calculated based on the free-floating market capitalization of their constituent stocks. The SENSEX includes 30 stocks and uses 1978-79 as the base year, while NIFTY includes 50 stocks and uses 1995 as the base year.
2) The major companies that make up the SENSEX (e.g. Reliance, TCS, HDFC Bank) and NIFTY (same top companies).
3) A brief history of the National Stock Exchange and the objectives and products it offers.
This document provides information about tutorials and datasets for using the STATA data analysis software. It explains that the tutorials use example datasets from an econometrics textbook and how to download the datasets and command files from www.STATA.org.uk. The website also contains step-by-step screenshot guides for using STATA and tutorials on topics like data management, statistical analysis, graphs, regressions, and other analyses.
STATA is data analysis software that can be used via menu options or typed commands. It has a wide range of econometric techniques and can open, examine, and run regressions on datasets. The tutorials on www.STATA.org.uk provide step-by-step guides for using STATA to perform tasks like data management, statistical analysis, importing data, summary statistics, graphs, regressions, and other analyses.
The document provides an overview of the Sensex and Nifty stock market indices in India. It discusses that the Sensex tracks the performance of the 30 largest companies listed on the Bombay Stock Exchange, while Nifty tracks the 50 largest companies listed on the National Stock Exchange. It provides details on how the indices are calculated and composed. It also discusses sectoral indices and provides examples of different sectoral indices that track specific industries.
The document provides information about key stock market indices in India, including the BSE Sensex and Nifty 50. It discusses what they are, how they are calculated, their objectives, and historical performance. Specifically, it notes that the Sensex is a market capitalization-weighted index of 30 large, well-established companies listed on the Bombay Stock Exchange. It aims to measure market movements, serve as a benchmark for fund performance, and facilitate index-based derivatives. The top sectors and companies in the Sensex by weight are also outlined.
This document outlines tutorials for using STATA software to perform time series analysis. It discusses how to manage time series data, perform Dickey-Fuller tests, estimate ARIMA, VAR, and ARCH/GARCH models, and provides challenges for forecasting with various models. Screenshot guides and sample datasets are available on the STATA website to help users learn how to apply these techniques in STATA. A variety of other statistical analysis topics also have tutorials on the site.
The document provides an overview of cluster analysis techniques. It discusses the need for segmentation to group large populations into meaningful subsets. Common clustering algorithms like k-means are introduced, which assign data points to clusters based on similarity. The document also covers calculating distances between observations, defining the distance between clusters, and interpreting the results of clustering analysis. Real-world applications of segmentation and clustering are mentioned such as market research, credit risk analysis, and operations management.
Index Effects on Stock Prices: Evidence from India,
Bid-Ask Spreads in Emerging Markets: Evidence from
The document discusses a study on the technical analysis of the S&P CNX Nifty Index in India. It introduces the Nifty Index and the importance of studying its price movements. It outlines the objectives to compare Nifty prices from 2003-2007 and analyze short and long term moving averages. The methodology involves using secondary data from the National Stock Exchange and statistical tools like trend analysis and moving averages. The study aims to help investors better understand market trends and determine when to buy and sell securities.
This document provides information on a project report about stock indices and factors affecting share prices. It includes a declaration by the author N.V.S Raghunath that the report was completed independently under the guidance of their professor Samanvi Bhograj. It also includes acknowledgements, a table of contents, and outlines the methodology, sources of data and limitations of the study. The study will analyze stock prices and indices of companies in the automobile sector from 2008-2011 to understand how economic, industry and company factors influence prices.
A STUDY OF CUSTOMER SATISFACTION OF NOKIA MOBILE USER IN DOMBIVALI WEST GANES...Sayali Mahajan
The document is a research project report on a study of customer satisfaction of Nokia mobile users in Dombivali West Ganesh Nagar area. It includes an introduction outlining the meaning of research methodology, objectives of the research, hypothesis, and limitations. The methodology section describes that primary and secondary data was collected through questionnaires and internal sources to analyze customer satisfaction with Nokia mobiles in the target area during October 2016.
This document is a study on the relationship between currency, equity, commodity, and their movements in the market. It includes chapters on the conceptual overview, research methodology, theoretical background, data analysis, interpretation and findings. The theoretical background chapter provides information on capital markets, equity shares, commodity markets including types of commodities traded, and foreign exchange markets. It analyzes secondary data from 2009-2014 on currency, equity, and commodities to examine their correlation and relationship. The findings suggest there is a relationship between the different market components and their movements impact each other.
This document is a research study submitted by Kiran M K to the M.P. Birla Institute of Management in partial fulfillment of an MBA degree. The study analyzes the return and beta of stocks that are components of the BSE Sensex index over an eight year period from 2001 to 2008. The objectives are to study the behavior of index stocks over time, understand their performance, and determine if there are any relationships between stock returns. The study reviews literature on beta, the capital asset pricing model, and factors that influence stock returns. It aims to test if index stocks follow a particular trend or format.
Stock return and volatility evidence from indian stock marketROHITH U J
The risk appetite of investors governs their investment in financial instruments. Persons who are minimum risk takers with return generally park their money in secure instruments but people with a higher risk appetite generally invest in a stock market financial instrument to achieve their financial goal. Investors with a higher risk appetite have to measure the market performance in the basis of risk and return so that they can alter their portfolio to keep pace with current market movement. In this research intended to study risk in terms of standard deviation and beta of all sectoral indices of NSE with respect to nifty and their performance in different time horizon and ranked them accordingly in terms of mean return and found out the best performing sector in a given time frame
A STUDY ON EQUITY & EQUITY DERIVATIVE - INDIAN SECURITIES MARKETYashmin Revawala
This document appears to be a student project report on equity and equity derivatives in the Indian securities market. It includes sections on an overview of the Indian securities market, identification of stocks from the CNX NIFTY index for investment purposes, comparing returns on investment in the CNX NIFTY index and selected stocks, using portfolio management techniques to further increase returns, an overview of the equity derivative market in India, and comparing the cash and derivative markets to analyze their impact on each other. The student also uses pivot points to predict future derivative prices and evaluates the accuracy of this prediction method.
This document describes an investigation into the relationship between market volatility and investor sentiment. It outlines the process of choosing indices to represent volatility and sentiment, and using regression analysis to select the best predictive indices. The Michigan Index of Consumer Sentiment was chosen as the sentiment indicator, and the VIX volatility index was selected. Regression results showed these two indices had p-values of 0.000, indicating they were the best predictors of S&P 500 price movements compared to alternative considered indices. The analysis of the relationship between these selected sentiment and volatility indicators will be conducted using time series methods.
The 3-page document includes:
1. Title page with the research title, student and supervisor names, and institution.
2. A brief certificate signed by the project supervisor certifying the work.
3. An acknowledgment section thanking those who assisted with the project.
4. A table of contents outlining the document structure.
A study on equity & equity derivative indian securities marketYashmin Revawala
*EQUITY:
1. Selection of Stocks using the 10 steps Process
2. Comparison of return on stocks and NIFTY BeES
3. Using Portfolio Management for increasing the return on investment
*EQUITY DERIVATIVE:
1. The impact of cash market segment on derivative market using settlement price and the value of underlying equity.
2. Predicting the cash market index (CNX NIFTY) & underlying index (FUTIDX NIFTY) using PIVOT POINT Method
This document summarizes a study examining the "day of the week effect" on stock returns in the Pakistani stock market between 2006-2010. The study finds evidence of a "Tuesday effect", with average returns on Tuesdays found to be significantly higher than other days of the week. Descriptive statistics show the mean Tuesday return was 164.88 compared to 100.25 on other days. Regression analysis also indicates returns were significantly higher on Tuesdays, violating the assumption of efficient market hypothesis that returns should be constant across all days. Therefore, the study concludes there is a day of the week effect in the Pakistani stock market with abnormal returns observed on Tuesdays.
This dissertation examines the barriers to effective market segmentation processes. It focuses on a case study of ABC Steel Company in India.
The author conducted a literature review on market segmentation and identified three main types of barriers: infrastructure barriers, processing issues, and implementation blockers. Qualitative research methods including interviews were used to collect empirical data from ABC Steel Company.
The findings revealed several key barriers in each of the three areas - infrastructure, processing, and implementation. The conclusion discusses overcoming these barriers and provides recommendations. The dissertation contributes to understanding the challenges of market segmentation in practice.
Alignment and Misalignment Examples of Scenario Elements I.docxSHIVA101531
Alignment and Misalignment Examples of Scenario Elements
In PSYC-8412 Research Foundations you build quantitative and qualitative research scenarios that include each of the
following key elements:
Social problem or phenomenon of interest
• Research problem
• Research purpose
• Research questions
• Theoretical or conceptual framework
• Research design
• Sampling strategy
o Sampling criteria (qualitative only)
o Data sources (qualitative only)
• Data collection method
• Variables (quantitative only)
• Analysis plan
• Trustworthiness (qualitative only)
All these key elements must logically align. Although the figure depicts
a linear flow, it is critical to understand that alignment is an iterative
process. For example, if after identifying a research problem and
research purpose additional research questions emerge, then the research
problem and purpose must be refined to align with the additional
research questions. Similarly, if variables of interest are identified that
are not represented in the research problem, purpose, or questions, and
that do not fit with the theoretical or conceptual framework, then those
elements will need to be refined to capture all of the variables of interest.
You will be piecing together your scenarios week-to-week, continually
adding new elements until a solid alignment of your research idea
emerges. Because of the iterative nature of alignment, you should not be
surprised that as a new element is added to your scenario that previous
elements may need to be modified to maintain alignment.
There are several ways for elements within a scenario to misalign, and it is not possible to provide examples of all
possible issues. In this document there are week-to-week example scenarios that demonstrate logically aligned elements
and some examples of the many ways elements become logically misaligned. Studying these will help you avoid some
common misalignment issues and understand how changing one element, sometimes even a single word, can affect
alignment. Below is one student’s reflection in Week 5 of the course:
I too struggled with the concept and terminology. For me, it is in fact the language that is used, and such
is definitely 'foreign' of sorts. As you go along though, it is all beginning to make sense. Initially the
feedback also was 'foreign' but now, going back and reviewing the question, answers, feedback are
beginning to all make sense. Even feedback that suggests that one simple word be changed makes sense
as what I submitted could possibly be misconstrued and cause the study to go in a different direction. I'm
beginning to understand how changing one simple word can make a difference. Research terminology
requires that things be concise and getting into the habit of relaying information properly makes all the
difference. I am beginning to speak 'research'. I believe it merely takes practice. One almost has to
develop a me.
Finance project on performance evaluation of indian mutual fundsProjects Kart
This document provides an executive summary of a report evaluating the performance of Indian mutual funds against the BSE Sensex stock market index over a 5-year period from 2004-2009. 21 open-ended equity growth mutual funds were selected for analysis. Statistical tools were used to calculate and compare the average returns, absolute returns, standard deviation, betas, and relative performance indexes of the funds versus the market. A Mann-Whitney U-test found that most funds' returns moved in sync with the market, except one fund that varied significantly. Cluster analysis grouped funds with similar performance metrics. The study concluded most funds provided returns similar to the market, with some variation during late 2005 to early 2006.
Performance evaluation of indian mutual fundsProjects Kart
This document is a report on the performance evaluation of Indian mutual funds submitted by students at SP Jain Center of Management in partial fulfillment of their GMBA program. It includes an introduction to the Indian mutual fund industry, an acknowledgement section, a declaration, and an index of the contents. The report will analyze data on 21 open-ended equity growth mutual funds over 5 years to evaluate their performance relative to the stock market and classify the funds based on statistical measures of returns, risk, and correlation with the market.
Performance Evaluation Of Indian Mutual Fundssagarbavishi
This document provides an analysis of the performance of Indian mutual funds. It begins with an acknowledgement and declaration section. It then provides an executive summary that analyzes the performance of 21 open-ended equity growth mutual funds against the BSE Sensex from 2004-2009. Various statistical tools are used to analyze average returns, absolute returns, standard deviation, betas, and relative performance indexes. A Mann-Whitney U-test finds that most funds performed similarly to the market except one fund. Cluster analysis also shows that most funds have similar properties and performance patterns. Overall, the study finds that most Indian mutual funds delivered returns in line with the stock market over the period examined.
This document is a report on the performance evaluation of Indian mutual funds submitted by three students in partial fulfillment of a Global MBA program. It includes an acknowledgment, declaration, index, and executive summary. The executive summary provides a high-level overview of the study, which evaluated the performance of 21 Indian equity mutual funds against the Indian stock market over 5 years. Various statistical analyses were conducted, including returns, standard deviation, betas, and clustering. Most funds performed similarly to the market, with some variation at times, though one fund showed significantly different returns.
PerformanceevaluationofindianmutualfundsProjects Kart
This document is a report on the performance evaluation of Indian mutual funds submitted by three students in partial fulfillment of a Global MBA program. It includes an introduction to the Indian mutual fund industry, an acknowledgement section, a declaration, and an index of topics to be covered in the report such as the executive summary, literature review, research methodology, data analysis and findings. The report evaluates the performance of 21 open-ended equity growth mutual funds in India from 2004-2009 by analyzing their returns, risks, and performance relative to the stock market over this period using statistical tools.
Ozone is a partnership supermarket business with the vision of becoming the number one retailer in the world. Its mission is to provide good customer service and fulfill customer needs. One of its objectives is to develop business across India. The structure of Ozone supermarket has multiple zones in its 5-floor building, including an electronics materials zone.
Engineering College Bikaner provides engineering education and seeks to strengthen students' technical skills. It offers undergraduate and postgraduate programs in engineering and management. The college has over 1000 students and 100 faculty members. It aims to increase enrollment in some programs and continues recruiting more faculty. The document provides details on the college's approvals, courses, faculty, library, computer center, campus facilities, and student development activities.
The Indian government is considering raising the fuel cess by Re 1 per liter to increase funding for highway development. Raising the cess by 50 paise per liter could generate an additional Rs. 5,000 crore annually for highway projects. The proposal to increase the fuel cess may be discussed prior to the upcoming budget. The roads ministry has suggested hiking the cess now to prepare for increased highway development funding needs once project implementation speeds up to meet the government's goal of building 20 km of highways per day.
Risk Identification is the process of determining risks that could affect a project. Participants include the project manager, team, risk management team, subject matter experts, customers, end users, and other stakeholders. Risks are identified through iterative processes as the project progresses. Inputs include the project scope statement, risk management plan, and project management plan. Tools used include documentation reviews, brainstorming, checklists, and diagrams. The output is a risk register listing identified risks, potential responses, and risk categories.
The document discusses the Industrial Training & Vocational Education Department of Haryana. Some key points:
1. There are 256 training institutes in Haryana with over 15,000 students in ITIs and 15,860 in VEIs.
2. Issues include that only 6% of Indian students enter vocational education compared to 60-70% in developed countries. There is a need to improve quality and increase this number.
3. Strategies discussed include certification of informal workers, setting up skill development missions, increasing ITI/Polytechnic capacity through new institutes, shifts, and PPP models.
1) The document is a curriculum vitae for Manjunath Reddy providing his personal and educational details.
2) It lists his educational qualifications including a B.Com from CSI College Dharwad in 2007-08 and PUC from RLS PU College Dharwad in 2004-05.
3) It also includes his computer skills, hobbies, and contact information and is signed by Manjunath Reddy on May 28, 2009 in Gulbarga.
The General Agreement on Tariffs and Trade (GATT) provided global trade rules and dispute resolution from 1948 to 1994, established after World War II to liberalize world trade by reducing tariffs. GATT's first round of negotiations impacted one fifth of world trade among 23 founding members. Its final eighth round in 1986-94 established the World Trade Organization and new trade agreements while also generating political conflicts between corporations seeking new markets and labor seeking to protect domestic jobs through trade restrictions.
India Cements is the largest cement producer in South India, with 7 plants across Andhra Pradesh and Tamil Nadu producing 9 million tons annually. It has a 28% market share in South India and plans to increase to 35%. Around 90% of its cement is sold in Tamil Nadu and Kerala. The company owns brands like Rassi Super Power and has subsidiaries in various industries. Its income and profits increased substantially from 2005-2006 to 2006-2007, and it plans to expand production capacity through a major investment.
The document shows annual inflation rates for the United States from 1999 to 2007. Inflation rates during this period ranged from a low of 3.63% in 2004 to a high of 6.16% in 2006, with most years seeing rates between 3 and 5 percent. Overall, the data demonstrates the changing rates of inflation in the American economy over a 9 year period.
1. A Study of
The-day-of-the-week effect in
S&P CNX NIFTY
A Dissertation submitted in partial fulfillment of the requirement
for the award of M.B.A Degree of Bangalore University
By
K.BALA SHANKAR
Reg.No. 04XQCM6040
Under the Guidance of
Dr.N.Malavalli
M.P.Birla Institute of Management
Associate Bharatiya Vidya Bhavan
#43, Race Course Road
Bangalore – 560001
1
2. DECLARATION
I hereby declare that this project work embodied in this
dissertation entitled “A Study of The-day-of-the-week effect in S&P
CNX NIFTY” has been carried out by me under the guidance and
supervision of Dr.N.Malavalli, M.P.B.I.M Bangalore.
I also declare that this Dissertation has not
been submitted to any University/Institution for the award of any
Degree/Diploma.
Place: Bangalore. (K. Bala Shankar)
Date:
2
3. CERTIFICATE
I hereby certify that the project work
embodied in this dissertation entitled “A Study of The-day-of-the-
week effect in S&P CNX NIFTY.” has been undertaken and
completed by Mr. K.Bala Shankar under my guidance and
supervision.
I also certify that she has fulfilled all the
requirements under the covenant governing the submission of
dissertation to the Bangalore University for the award of M.B.A
Degree.
Place: Bangalore (Dr.N.Malavalli)
Date: M.P.B.I.M
3
4. ACKNOWLEDGEMENT
I would like to thank my project guide and
our principle Dr.N.Malavalli,, whose contribution was
insightful and helped me, to get well acquainted to the project
intricacies.
4
5. Table of Contents
Chapter 1: Abstract
Abstract 2
Chapter 2: Introduction
Need & Significance of the study 4
Objectives of the study 6
Limitations of the study 7
Chapter 3: Literature Review
Literature Review 9
Overview of Indian stock Markets 12
NSE-Overview 18
Chapter 4: Methodology
Data 23
Hypothesis 23
Statistical tools 23
Calculations Involved 24
Chapter 5: Findings & Results
Findings & Results 27
5
8. ABSTRACT
Abstract:
The present study examines empirically the day of the week effect anomaly in
the Indian equity market for the period from 1992 to 2006using both high frequency and
end of day data for the benchmark Indian equity market index S&P CNX NIFTY. The
study mainly focuses on the returns on all the trading days are equal. In addition, there is
a perception in NSE that the returns on Monday are negative and the returns on Friday
are positive. The study is tested by ANOVA test and t-test. However, after the
introduction of the rolling settlement in 1996 the market returns are tested whether there
is any significant change. For this, the period is divided into 1992 to 1996 (before the
settlement period), 1997 to 2000, 2001 to 2004 and Jan 2005 to May 2006 (after the
settlement period).
8
10. 2. INTRODUCTION
Need and Significance of the study:
In recent years the testing for market anomalies in stock returns has become an
active field of research in empirical finance and has been receiving attention from not
only in academic journals but also in the financial press. Among the more well-known
anomalies are the size effect, the January effect and the day-of-the week effect. The
day of the week effect is a phenomenon that constitutes a form of anomaly of the
efficient capital markets theory. According to this phenomenon, the average daily return
of the market is not the same for all days of the week, as we would expect on the basis
of the efficient market theory.
January effect:
A general increase in stock prices during the month of January. This rally is
generally attributed to investors buying stocks that have dropped in price following a sell-
off at the end of December by investors seeking to create tax losses to offset any capital
gains.
The January effect is said to affect small-caps more than mid/large caps. This
historical trend, however, has been less pronounced in recent years because the
markets have adjusted for the effect. Another reason the January effect is now
considered less important is that more people are using tax-sheltered retirement plans
and therefore have no reason to sell at the end of the year for a tax loss.
Day-of-the-week effect:
The day of the week effect refers to the observation that equity returns are not
independent of the day of the week. This effect was first documented by Osborne(1962).
The last trading days of the week, particularly Friday, are characterized by positive and
substantially positive returns, while Monday, the first day of the week, and differs from
other days, even producing negative returns.
10
11. Earlier studies have found the existence of the day of the week effect not only in
the USA and other developed markets but also in the emerging markets like Malaysia,
Hong Kong, Turkey. For most of the western economies, (U.S.A., U.K., Canada)
empirical results have shown that on Mondays the market has statistically significant
negative returns while on Fridays statistically significant positive returns. In other
markets such as Japan, Australia, Singapore, Turkey and France the highest negative
returns appear on Tuesdays.
The most satisfactory explanation that has been given for the negative returns on
Mondays is that usually the most unfavorable news appears during the weekends.
These unfavorable news influence the majority of the investors negatively, causing them
to sell on the following Monday. The most satisfactory explanation that has been given
for Tuesday’s negative returns are that the bad news of the weekend affecting the USA’s
market, influence negatively some markets lagged by one day.
The equity markets across many countries seem to exhibit the day-of-the-week
effect. Studies have also been conducted to identify the causes behind the patterns
observed. Institutional features of the national stock markets, such as settlement
procedures and in particular, delays between trading and settlement in the stocks,
pricing misquotes and measurement errors, specialists’ behaviour, or dividend patterns
have been put forward as the main reasons for such an effect. However none of these
reasons have been conclusively proved to be the cause of the effect. Explanations of the
day-of-the-week effect based on human nature have also been put forward to explain
the patterns observed (Jacobs and Levy, 1988). The human behaviors of disclosing
good news quickly on the weekdays and waiting for the weekend to disclose the bad
news so as to allow the market the weekend to absorb the shock, have been
explanations provided for the day-of-the-week effect.
11
12. Objectives of the Project
The objective of this project is to examine the day-of-the-week effect in the Indian
Stock Market. The paper in particular studies the day-of-the-week-effect with respect to
the settlement system followed. The daily closing price data on the S&P CNX NIFTY for
the period 1992-2004 has been used in the study. The first step was testing of the null
hypothesis that the mean returns on all trading days of the week are equal.
H0 = ReturnMonday = ReturnTuesday = ReturnWednesday =ReturnThursday = ReturnFriday
The null hypothesis that the means returns are equal across all trading days was
true at 5% significance level. The settlement system was changed to the weekly
settlement cycle on April 1996 in the NSE. The hypothesis was tested for the period
January 1992 to Dec 1996, for the period January 1997 to December 2000 and for the
period January 2001 to 2004 separately.
In the National Stock Exchange there is a predominant perception that the Friday
returns are lower and even negative when compared to the Monday returns. This is
because they believe that there is a selling pressure on Friday due to the weekend and
everybody is under pressure to square their positions. To test this perception the
following hypothesis was also tested. The hypothesis was tested for the period January
1992 to Dec 1996, for the period January 1997 to December 2000 and for the period
January 2001 to 2004 separately.
H0 = ReturnMonday = ReturnFriday
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13. Limitations of the study:
(i) Historical Data has been used for the project study. The daily closing price
data on the S&P CNX NIFTY for the period 1992-2006 has been used in the
study.
(ii) The appropriate statistical tools ANOVA (F-Test) & t-test has been used to
test the hypothesis.
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15. LITERATURE REVIEW
Literature Review:
In most developed markets such as the USA’s, the United Kingdom’s and
Canada’s, most studies, Cross (1973), Gibbons & Hess (1981), Keim & Stambaugh
(1984), Theobald and Price (1984), Jaffe & Westerfield (1985), Harris (1986), Simrlock &
Starts (1986), Board and Sutcliffe (1988), and Kohers and Kohers (1995), Tang and
Kwok (1997) for six indices [Dow Jones Industrial Average Index( US), Financial Times
Index (UK), Nikkei Average Index (Japan), Hang Seng Index (Hong Kong), FAZ General
Index (Germany) and All Ordinary Index (Australia)] and many others, have come to the
conclusion that Mondays’ average returns are negative and Fridays’ are positive. In
other words, the stock exchange market starts downwards and ends upwards. However,
in some other studies such as Condoyanni, O’Hanlon & Ward (1987), Solnik & Bousqet
(1990) in the French stock market; Athanassakos & Robinson (1994) in the Canadian
market, Jaffe & Westerfield (1985) in the stock markets of Australia and Japan, Kim
(1988) in the stock markets of Japan and Corea, Aggarwal & Rivoli (1989) in the stock
markets of Hong Kong, Singapore, Malaysia and Philippines, Ho (1990) in the stock
markets of Australia, Hong Kong, Japan, Korea, Malaysia, New Zealand, Philippines,
Singapore, Taiwan and Thailand, Wong, Hui and Chan (1992) in the markets of
Singapore, Malaysia, Hong Kong and Thailand, Dubois & Louvet (1996) in the stock
markets of Japan, Australia, Agrawal and Tandon (1994) for eighteen countries and
many others, the negative average returns are observed on Tuesdays. Also, for the
Istanbul stock exchange there were negative average returns on Tuesdays [Aydoðan
(1994), Balaban (1995), Bildik (1997) and Özmen (1997)].
On the other hand, studies on the Spanish stock market have revealed that there
is no day of the week effect, [Santemases (1986), Pena (1995) and Gardeazabal and
Regulez (2002)]. Solnik and Bousquet (1990) focused on the period 1978- 1987 and
examined the CAC Index of Paris Bourse. Their results showed strong and persistent
negative mean returns on Tuesdays. Solnik (1990) wondered whether the settlement
procedure could explain the pattern of daily returns observed in previous studies of the
Paris Bourse.
15
16. Dubois and Louvet (1996) re-examined the day of the week effect for the French
stock market along with other markets such as the US, UK, German, Japanese,
Australian and Swiss markets, during the period 1969-1992 using standard statistical
approaches and moving averages. They observed that Wednesdays presented the
highest return while the day with the lowest (negative) return was Monday for all the
above markets except the Japanese and the Australian. The null hypothesis of the
equality among the mean returns of all days of the week was rejected at the 1%
confidence level. The authors concluded that probably, the different settlement systems
could account for difficulties in comparing the results internationally, but could not
explain the possible reasons for this anomaly in the US and the European markets they
examined.
If an anomaly exists in the market, the investors can take advantage of the same
and adjust their buying and selling strategies accordingly to increase their returns with
timing the market.
The day of the week effect in Indian market was examined by many researchers
(Chaudhury (1991), Poshakwala (1996), Goswami and Anshuman (2000), Choudhry
(2000), Bhattacharya, Sarkar and Mukhopadhyay (2003)). All studies except Choudhry
(2000) and Bhattacharya et al (2003) have been based on data of mid-1980s and mid-
1990s and all these studies have used conventional methods like serial autocorrelation
tests and or fitting an OLS. Choudhry (2000) examined seasonality of returns and
volatility under a unified framework but the study has a misspecification issue with
regard to conditional mean. Bhattacharya et al (2003) used GARCH framework by
incorporating the lagged returns (BSE 1001) as explanatory variables in the conditional
mean. They have used reporting and non-reporting weeks2 to study the day of the week
effect. All these studies have used end of day data.
The availability of high frequency data from NSE has opened up many avenues
of research that helps us to look closer into the market activities. The present study aims
to find the day of the week effect on India equity market using high frequency data. This
study is different in two aspects: (1) it uses the high frequency data to study the day of
16
17. the week effect and for the same we have to calculate the 1-minute returns and then
aggregate the same for the day to get the daily returns. This is primarily done to
understand the market dynamic observed during the whole day and to conduct a micro
analysis. The closing value that is generally available is the average of last 30 minutes of
trade and may not suitably bring out the dynamics of the market and most of the
information that happens during the day is not absorbed in the last 30 minutes of trades;
(2) the study also does a comparative analysis using the closing values to understand if
any additional valuable information can be obtained from high frequency data.
Recently there are many studies had been done on the stock market anomalies.
The research study done by Hakan Berument and Halil Kiymaz on “The Day of the
Week Effect on Stock Market Volatility: Istanbul stock exchange “ proved that the day of
the week effect is present in both volatility and return equations. While the highest and
lowest returns are observed on Wednesday and Monday, the highest and the lowest
volatility are observed on Friday and Wednesday, respectively.
There are studies had been done on the Indian stock markets. In one of the
studies done by Golaka Nath on “ day of the week effect and market efficiency –
Evidence from indian equity market using high Frequency data of national stock
exchange” proved that the study finds that before introduction of rolling settlement in
January 2002, Monday and Friday were significant days. However after the introduction
of the rolling settlement, Friday has become significant. This also indicates that Fridays,
being the last days of the weeks have become significant after rolling settlement.
Mondays were found to have higher standard deviations followed by Fridays. The
existence of market inefficiency is clear. The market inefficiency still exists and market is
yet to price the risk appropriately.
In another study done on the Indian capital markets done by Kaushik
Bhattacharya & Nityananda Sarkar on Stability of the “Day of the Week Effect in Return
and in Volatility at the Indian Capital Market” proved that in favor of significant positive
returns on non-reporting Thursday and Friday, in sharp contrast to the finding of
significant positive returns only on non-reporting Monday by OLS procedure. Separate
subperiod analyses reveal that there have been changes in daily seasonality in both
returns and volatility since the mid-1990’s at the Indian capital market, manifested in the
opposite signs and changes in the level of significance of some similar coefficients
17
18. across periods. These findings on the day of the week effects along with its variation
within a fortnight suggest that stock exchange regulations and the nature of interaction
between the banking sector with the capital market could possibly throw valuable
insights on the origin of the day of the week/fortnight effect in returns, while inter-
exchange arbitrage opportunities due to differences in settlement period could lead to a
seasonality in volatility.
3. Overview of the Indian Stock Market
Evolution
Indian Stock Markets are one of the oldest in Asia. Its history dates back to
nearly 200 years ago. The earliest records of security dealings in India are meagre and
obscure. The East India Company was the dominant institution in those days and
business in its loan securities used to be transacted towards the close of the eighteenth
century.
By 1830's business on corporate stocks and shares in Bank and Cotton presses
took place in Bombay. Though the trading list was broader in 1839, there were only half
a dozen brokers recognized by banks and merchants during 1840 and 1850.
The 1850's witnessed a rapid development of commercial enterprise and
brokerage business attracted many men into the field and by 1860 the number of
brokers increased into 60.
In 1860-61 the American Civil War broke out and cotton supply from United
States of Europe was stopped; thus, the 'Share Mania' in India begun. The number of
brokers increased to about 200 to 250. However, at the end of the American Civil War, in
1865, a disastrous slump began (for example, Bank of Bombay Share which had
touched Rs 2850 could only be sold at Rs. 87).
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19. At the end of the American Civil War, the brokers who thrived out of Civil War in
1874, found a place in a street (now appropriately called as Dalal Street) where they
would conveniently assemble and transact business. In 1887, they formally established
in Bombay, the "Native Share and Stock Brokers' Association" (which is alternatively
known as " The Stock Exchange "). In 1895, the Stock Exchange acquired a premise in
the same street and it was inaugurated in 1899. Thus, the Stock Exchange at Bombay
was consolidated.
Other leading cities in stock market operations
Ahmedabad gained importance next to Bombay with respect to cotton textile
industry. After 1880, many mills originated from Ahmedabad and rapidly forged ahead.
As new mills were floated, the need for a Stock Exchange at Ahmedabad was realised
and in 1894 the brokers formed "The Ahmedabad Share and Stock Brokers'
Association".
What the cotton textile industry was to Bombay and Ahmedabad, the jute
industry was to Calcutta. Also tea and coal industries were the other major industrial
groups in Calcutta. After the Share Mania in 1861-65, in the 1870's there was a sharp
boom in jute shares, which was followed by a boom in tea shares in the 1880's and
1890's; and a coal boom between 1904 and 1908. On June 1908, some leading brokers
formed "The Calcutta Stock Exchange Association".
In the beginning of the twentieth century, the industrial revolution was on the way
in India with the Swadeshi Movement; and with the inauguration of the Tata Iron and
Steel Company Limited in 1907, an important stage in industrial advancement under
Indian enterprise was reached.
Indian cotton and jute textiles, steel, sugar, paper and flour mills and all
companies generally enjoyed phenomenal prosperity, due to the First World War.
19
20. In 1920, the then demure city of Madras had the maiden thrill of a stock
exchange functioning in its midst, under the name and style of "The Madras Stock
Exchange" with 100 members. However, when boom faded, the number of members
stood reduced from 100 to 3, by 1923, and so it went out of existence.
In 1935, the stock market activity improved, especially in South India where there was a
rapid increase in the number of textile mills and many plantation companies were
floated. In 1937, a stock exchange was once again organized in Madras - Madras Stock
Exchange Association (Pvt) Limited. (In 1957 the name was changed to Madras Stock
Exchange Limited).
Lahore Stock Exchange was formed in 1934 and it had a brief life. It was merged with
the Punjab Stock Exchange Limited, which was incorporated in 1936.
Indian Stock Exchanges - An Umbrella Growth
The Second World War broke out in 1939. It gave a sharp boom which was
followed by a slump. But, in 1943, the situation changed radically, when India was fully
mobilized as a supply base.
On account of the restrictive controls on cotton, bullion, seeds and other
commodities, those dealing in them found in the stock market as the only outlet for their
activities. They were anxious to join the trade and their number was swelled by
numerous others. Many new associations were constituted for the purpose and Stock
Exchanges in all parts of the country were floated.
The Uttar Pradesh Stock Exchange Limited (1940), Nagpur Stock Exchange
Limited (1940) and Hyderabad Stock Exchange Limited (1944) were incorporated.
In Delhi two stock exchanges - Delhi Stock and Share Brokers' Association Limited and
the Delhi Stocks and Shares Exchange Limited - were floated and later in June 1947,
amalgamated into the Delhi Stock Exchnage Association Limited.
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21. Post-independence Scenario
Most of the exchanges suffered almost a total eclipse during depression. Lahore
Exchange was closed during partition of the country and later migrated to Delhi and
merged with Delhi Stock Exchange.
Bangalore Stock Exchange Limited was registered in 1957 and recognized in 1963.
Most of the other exchanges languished till 1957 when they applied to the
Central Government for recognition under the Securities Contracts (Regulation) Act,
1956. Only Bombay, Calcutta, Madras, Ahmedabad, Delhi, Hyderabad and Indore, the
well established exchanges, were recognized under the Act. Some of the members of
the other Associations were required to be admitted by the recognized stock exchanges
on a concessional basis, but acting on the principle of unitary control, all these pseudo
stock exchanges were refused recognition by the Government of India and they
thereupon ceased to function.
Thus, during early sixties there were eight recognized stock exchanges in India
(mentioned above). The number virtually remained unchanged, for nearly two decades.
During eighties, however, many stock exchanges were established: Cochin Stock
Exchange (1980), Uttar Pradesh Stock Exchange Association Limited (at Kanpur, 1982),
and Pune Stock Exchange Limited (1982), Ludhiana Stock Exchange Association
Limited (1983), Gauhati Stock Exchange Limited (1984), Kanara Stock Exchange
Limited (at Mangalore, 1985), Magadh Stock Exchange Association (at Patna, 1986),
Jaipur Stock Exchange Limited (1989), Bhubaneswar Stock Exchange Association
Limited (1989), Saurashtra Kutch Stock Exchange Limited (at Rajkot, 1989), Vadodara
Stock Exchange Limited (at Baroda, 1990) and recently established exchanges -
Coimbatore and Meerut. Thus, at present, there are totally twenty one recognized stock
exchanges in India excluding the Over The Counter Exchange of India Limited (OTCEI)
and the National Stock Exchange of India Limited (NSEIL).
21
22. The Table given below portrays the overall growth pattern of Indian stock
markets since independence. It is quite evident from the Table that Indian stock markets
have not only grown just in number of exchanges, but also in number of listed
companies and in capital of listed companies. The remarkable growth after 1985 can be
clearly seen from the Table, and this was due to the favouring government policies
towards security market industry.
Source : Various issues of the Stock Exchange Official Directory, Vol.2 (9) (iii),
Bombay Stock Exchange, Bombay.
Trading Pattern of the Indian Stock Market
Trading in Indian stock exchanges are limited to listed securities of public limited
companies. They are broadly divided into two categories, namely, specified securities
(forward list) and non-specified securities (cash list). Equity shares of dividend paying,
growth-oriented companies with a paid-up capital of atleast Rs.50 million and a market
capitalization of atleast Rs.100 million and having more than 20,000 shareholders are,
normally, put in the specified group and the balance in non-specified group.
Two types of transactions can be carried out on the Indian stock exchanges: (a)
spot delivery transactions "for delivery and payment within the time or on the date
stipulated when entering into the contract which shall not be more than 14 days following
the date of the contract" : and (b) forward transactions "delivery and payment can be
extended by further period of 14 days each so that the overall period does not exceed 90
days from the date of the contract". The latter is permitted only in the case of specified
shares. The brokers who carry over the outstandings pay carry over charges (cantango
or backwardation) which are usually determined by the rates of interest prevailing.
A member broker in an Indian stock exchange can act as an agent, buy and sell
securities for his clients on a commission basis and also can act as a trader or dealer as
a principal, buy and sell securities on his own account and risk, in contrast with the
practice prevailing on New York and London Stock Exchanges, where a member can act
as a jobber or a broker only.
22
23. The nature of trading on Indian Stock Exchanges are that of age old conventional
style of face-to-face trading with bids and offers being made by open outcry. However,
there is a great amount of effort to modernize the Indian stock exchanges in the very
recent times.
Bombay Stock Exchange (BSE) and National Stock Exchange of India Ltd.
(NSE) are the two primary exchanges in India. In addition there are 22 Regional Stock
Exchanges. However BSE and NSE have established themselves as the two main
exchanges and account for about 80% of the volume traded in Indian equity markets.
Approximately NSE and BSE are equal in size in terms of daily volume traded. NSE has
about 1500 shares which are traded and has a total market capitalisation of around Rs.
9,21,500 Crores (Rs. 9215-bln). BSE has over 6000 stocks traded and has a total
market capitalisation of around Rs. 9,68,000 Crores (Rs.9680-bln). Most key stocks are
available on both exchanges and hence the investor could buy them on either exchange.
Both exchanges have a different settlement cycles. The primary index of BSE is BSE
Sensex, which comprises of 30 Stocks. NSE has its own S& P NSE 50 Index (Nifty)
which comprises of fifty stocks. Both these indexes are calculated on the basis of market
capitalisation and contain the most highly traded shares from the key sectors. Daily
volume on both exchanges is approximately Rs. 4500 Crores each. (Rs. 45-bln.) The
key regulator governing Stock Exchanges, Brokers, Depositories, Depository
participants, Mutual Funds, FIIs and other participants in Indian secondary and primary
market is Securities and Exchange Board of India (SEBI) Ltd.
23
24. National Stock Exchange (NSE)
With the liberalization of the Indian economy, it was found inevitable to lift the
Indian stock market trading system on par with the international standards. On the basis
of the recommendations of high powered Pherwani Committee, the National Stock
Exchange was incorporated in 1992 by Industrial Development Bank of India, Industrial
Credit and Investment Corporation of India, Industrial Finance Corporation of India, all
Insurance Corporations, selected commercial banks and others.
Trading at NSE can be classified under two broad categories:
(a) Wholesale debt market and
(b) Capital market.
Wholesale debt market operations are similar to money market operations - institutions
and corporate bodies enter into high value transactions in financial instruments such as
government securities, treasury bills, public sector unit bonds, commercial paper,
certificate of deposit, etc.
There are two kinds of players in NSE:
(a) trading members and
(b) participants.
Recognized members of NSE are called trading members who trade on behalf of
themselves and their clients. Participants include trading members and large players like
banks who take direct settlement responsibility.
Trading at NSE takes place through a fully automated screen-based trading mechanism
which adopts the principle of an order-driven market. Trading members can stay at their
offices and execute the trading, since they are linked through a communication network.
The prices at which the buyer and seller are willing to transact will appear on the screen.
24
25. When the prices match the transaction will be completed and a confirmation slip will be
printed at the office of the trading member.
NSE has several advantages over the traditional trading exchanges. They are as
follows:
NSE brings an integrated stock market trading network across the nation.
Investors can trade at the same price from anywhere in the country since inter-
market operations are streamlined coupled with the countrywide access to the
securities.
Delays in communication, late payments and the malpractice’s prevailing in the
traditional trading mechanism can be done away with greater operational
efficiency and informational transparency in the stock market operations, with the
support of total computerized network.
Unless stock markets provide professionalised service, small investors and foreign
investors will not be interested in capital market operations. And capital market being
one of the major source of long-term finance for industrial projects, India cannot afford to
damage the capital market path. In this regard NSE gains vital importance in the Indian
capital market system.
Settlement Cycle
Settlement refers to the process whereby payment is made by all those who
have made purchases and shares are delivered by all those who have made sales. The
exchange ensures that buyers, who have paid for the shares purchased, receive the
shares. Similarly sellers who have given delivery of shares to the exchange receive
payment for the same. The entire process of settlement of shares and money is
managed by stock exchanges (SEs) through Clearing House (CH) which are entities
formed specifically to ensure that the process of settlement takes place smoothly.
25
26. Settlement Cycle refers to a calendar according to which all purchase and sale
transactions done within the dates of the settlement cycle are settled on a net basis.
NSE and BSE currently follow their own weekly settlement cycles. SEBI has introduced
a rolling settlement cycle from Jan 12, 2000. Currently 43 stocks are traded in rolling
settlement cycles. All other stocks are traded in the weekly settlement cycles of SEs.
SEBI plans to add more and more stocks to rolling settlement cycle by moving them out
of the weekly settlement cycle. A brief description of various settlement cycles is given
below:
NSE Settlement Cycle
Before the settlement period introduced the BSE and the NSE followed two
different settlement weeks. While the BSE followed a Monday to Friday cycle, for the
NSE, it is from Wednesday to next Tuesday.
This has provided market players, mainly speculators, an opportunity to shift their
position from one exchange to another depending on the end of settlement week. This
has also afforded an arbitrage opportunity for the big operators. All this would become
passed with the introduction of the uniform settlement in the two exchanges, which have
virtually decimated the smaller regional exchanges after trading went online.
The NSE has stated that SEBI has listed 414 securities, which are included in the
ALBM/BLESS/MCFS and BSE 200 list, for trading only in the compulsory rolling
settlement. But in the NSE this covered only 301 securities as the rest of them were
either not listed or not traded on the NSE.
In the compulsory rolling settlement, traders/buyers cannot carry forward their
position to the next day. They will have to either square off their position within that day
or take delivery of scrips/receive payment on the due date.
The remaining listed and permitted securities would be available in both the
rolling and account period settlement
26
27. Rolling Settlement Cycle:
The Exchange has commenced trading in the Dematerialised (Demat) segment
with effect from December 29, 1997 where there is no physical delivery of securities as
in the physical segment. Trading in the Demat segment is on a Rolling Settlement basis
(T+5) where T stands for Trade Day. The pay-in and pay-out for the transactions in this
segment are both conducted on a single day. The Pay-in & Pay-out for transactions
executed on Monday is conducted on the following Monday, i.e., corresponding day in
the following week. Auction session for shortages in demat segment is conducted on
BOLT on the day after pay-in/pay-out. The pay-in / pay-out (money part) takes place
through computerised posting of debits and credits in the members’ bank accounts as in
the case of physical segment
Hence unlike a BSE or NSE weekly settlement cycle where one buys or sells
shares on the beginning of the settlement cycle and can decide till the end of the
settlement cycle whether to give delivery or make payment or square of the transaction
by covering. In a rolling settlement cycle, decision has to be made by end of trading on
the same day. Rolling settlement cycles have been recently introduced on both
exchanges form January 12, 2000. To start with only 43 shares will be traded on the
Rolling Settlement Cycle.
27
29. METHODOLOGY:
Data:
The daily closing price data on the S&P CNX NIFTY for the period 1992-2004 has
been used in the study. S&P CNX Nifty is a well diversified 50 stock index accounting for
25 sectors of the economy. It is used for a variety of purposes such as benchmarking
fund portfolios, index based derivatives and index funds.
Hypothesis:
To the day-of-the-week present in the NSE, the first step was testing of the null
hypothesis that the mean returns on all trading days of the week are equal.
H0 = ReturnMonday = ReturnTuesday = ReturnWednesday =ReturnThursday = ReturnFriday
To test the predominant perception that the Friday returns are lower and even
negative when compared to the Monday returns, the following Hypothesis is taken.
H0 = ReturnMonday = ReturnFriday
Statistical tests used:
To the chosen hypothesis, stastical tools have been used.
ANOVA ( F-Test)
t-test
Both the tests are performed to see whether there are any significant deviations
from the means. The ANOVA test is used when there is 23 or more groups are involved
and the t-test is used to test the significant deviation in two means.
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30. ANOVA ( F-Test):
Analysis of Variance (ANOVA) is statistical method used to compare two or more
means. It may seem odd that the technique is called "Analysis of Variance" rather than
"Analysis of Means”. ANOVA is used to test general rather than specific differences
among means.
Analysis of Variance (ANOVA) allows us to extend this to more than two
populations or measurements (treatments). That is, we can test the following:
Are all the means from more than two populations equal?
Are all the means from more than two treatments on one population equal?
T-test:
A t-test is an inferential test that determines if there is a significant difference
between the means of two data sets. In other words, a t-test decides if the two data sets
come from the same population or from different populations).
Calculations Involved:
From the collected data, the returns are calculated as given below
Return = ln ( Vt/Vt-1)
Where
Vt =the closing value of the index on day t
Vt-1 = the closing value of the index on the previous day
The hypothesis was tested using the F test at 0.05 level of significance. The
hypothesis was tested on different periods of data to check whether the day-of-the-week
effect varies with time. The periods were chosen such that they reflected periods where
different settlement systems were followed. The settlement system was changed to the
30
31. weekly settlement cycle on April 1996 in the NSE. The hypothesis was tested for the
period January 1992 to Dec 1996, January 1997 to Dec 2000and for the period January
2001 to Dec 2004 separately. The idea was to check if the change in the settlement
system induced any change in the mean returns.
31
33. Results and Findings:
(i) Hypothesis Tested: Mean returns are equal across all trading days of the
week
H0=ReturnMonday = ReturnTuesday = ReturnWednesday =ReturnThursday = ReturnFriday
Findings:
Hypothesis
period Fcal Ftable Probability
Result
Null hypothesis
Jan 1992 to Dec 2005 1.725 2.37 14%
can’t be rejected
Null hypothesis
Jan 1992 to Dec 1996 1.589 2.39 18%
can’t be rejected
Null hypothesis
Jan 1997 to Dec 2000 1.446 2.39 22%
can’t be rejected
Null hypothesis
Jan 2001 to Dec 2004 0.1262 2.22 25%
can’t be rejected
Null hypothesis
Jan 2005 to May 2005 0.3728 2.40 83%
can’t be rejected
Means for the various periods:
Jan 1992 Jan 1992 Jan 1997 Jan 2001 Jan 2005
Days to Dec to Dec to Dec to Dec to May
2004 1996 2000 2004 2006
Monday .00256 0.00186 0.0042 0.002 0.006
Tuesday 0.00161 0.003 0.001 0.0013 0.005
Wednesday 0.00106 0.0031 0.001 0.0014 0.004
Thursday 0.00161 0.00.31 0.0037 0.001 0.0067
Friday 0.001 0.0019 0.001 0.001 0.0072
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34. Results:
Results of the hypothesis that the mean returns on all trading days of the week
are equal. The null hypothesis that the means returns are equal across all trading days
is accepted at 5% significance level.
The null hypothesis as can be seen from above Table was accepted in all the
four cases shown. The weekly settlement system came into being in April 1996, and the
very fact that the hypothesis is proven for all periods show that the settlement system did
not produce any day-of-the-week effect in the Indian stock market. More important and
startling is the conclusion that Indian stock markets are indeed efficient as far as the
day-of-the-week effect is concerned.
For the period chosen from 1992 to 2006, the returns from all the trading days are
equal from the data taken and proved from the test. Therefore, in the Indian stock market
context the day-of-the-week effect is not present.All the results for the four cases are
shown in the following Exhibits.
Exhibits 1: Jan 1992 to May 2006
Source Of Degrees of
Sum of Square Mean Square
Variation Freedom
Between (column) 0.002354 4 0.00059
Within(Error) 0.6361 1866 0.00034
Total 0.6384 1870
34
35. Exhibits 2: Jan 1992 to Dec 1996
Source Of Degrees of
Sum of Square Mean Square
Variation Freedom
Between (column) 0.0029 4 0.00072
Within(Error) 0.2962 650 0.00046
Total 0.2991 654
Exhibits 3: Jan 1997 to Dec 2000
Source Of Degrees of
Sum of Square Mean Square
Variation Freedom
Between (column) 0.00178 4 0.00044
Within(Error) 0.1715 557 0.00031
Total 0.1733 561
Exhibits 4: Jan 2001 to Dec 2004
Source Of Degrees of
Sum of Square Mean Square
Variation Freedom
Between
0.00014 5 0.00035
(column)
Within(Error) 0.1563 570 0.00027
Total 0.1565 574
35
36. Exhibits 4: Jan 2001 to May 2006
Source Of Degrees of
Sum of Square Mean Square
Variation Freedom
Between
2.1010E-03 4 5.2526E-04
(column)
Within(Error) 0.4767 342 1.3939E-04
Total 0.4788 346
36
37. (ii) Hypothesis is tested:
H0 = ReturnMonday = ReturnFriday
The above hypothesis is tested to evaluate the returns on Monday & Friday is equal.
period p á Hypothesis Result
Null hypothesis
Jan 1992 to May 2006 0.5 0.1
can’t be rejected
Null hypothesis
Jan 1992 to Dec 1996 0.124 0.1
can’t be rejected
Null hypothesis
Jan 1997 to Dec 2000 0.989 0.1
can’t be rejected
Null hypothesis
Jan 2001 to Dec 2004 0.69 0.1
can’t be rejected
Null hypothesis
Jan 2005 to may 2006 0.81 0.1
can’t be rejected
The above table shows Results of the hypothesis that the mean returns are equal
across Friday and Monday. The results show that the null hypothesis is true for the
complete period from January 1992 to May 2006 hypothesis is tested at .05%
significance.
As the per the t-test, in all the cases p > á , the null hypothesis cannot be rejected.
For the period chosen from 1992 to 2006, the returns on the Mondays and the
Fridays are equal from the data taken and proved from the test. Therefore, in the Indian
stock market context the day-of-the-week effect is not present.
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38. Results from Jan 1992 to Dec 1996:
Mean of X 0.001858
Mean of Y -0.001945
Standard Deviation of X 0.025830
Standard Deviation of Y 0.022389
Large Sample Standard Deviation 0.003285
t-statistic 1.157599
degrees-of-freedom 163.958525
p-value 0.124356
Results from Jan 1997 to Dec 2000:
Mean of X -0.001087
Mean of Y 0.004294
Standard Deviation of X 0.015947
Standard Deviation of Y 0.018368
Large Sample Standard Deviation 0.002323
t-statistic -2.316816
degrees-of-freedom 208.770327
p-value 0.989258
Results from Jan 2000 to Dec 2004:
Mean of X 0.000744
Mean of Y 0.001507
Standard Deviation of X 0.014555
Standard Deviation of Y 0.014840
Large Sample Standard Deviation 0.001938
38
39. t-statistic -0.393531
degrees-of-freedom 227.913936
p-value 0.694295
Results from Jan 1992 to Dec 2004:
Mean of X 0.002560
Mean of Y -0.000878
Standard Deviation of X 0.019685
Standard Deviation of Y 0.018423
Large Sample Standard Deviation 0.001462
t-statistic 2.350966
degrees-of-freedom 641.521269
Results from Jan 1992 p-value 0.009513 to May 2006:
Mean of X 0.005898
Mean of Y 0.007158
Standard Deviation of X 0.030550
Standard Deviation of Y 0.031872
Large Sample Standard Deviation 0.005364
t-statistic -0.234964
degrees-of-freedom 131.732143
p-value 0.814601
39
41. Analysis:
The study focuses on the returns on all the trading days are equal or not. In
addition, to test the perception of NSE that the returns on Mondays are positive and
Fridays are negative.
The null hypothesis as can be seen from above Table was accepted in all the
four cases shown. The weekly settlement system came into being in April 1996, and the
very fact that the hypothesis is proven for all periods show that the settlement system did
not produce any day-of-the-week effect in the Indian stock market. More important and
startling is the conclusion that Indian stock markets are indeed efficient as far as the
day-of-the-week effect is concerned.
For the period chosen from 1992 to 2004, the returns from all the trading days
are equal from the data taken and proved from the test. Therefore, in the Indian stock
market context the day-of-the-week effect is not present The results also showed that
the perception of the NSE of non-significant from the data collected.
Results of the hypothesis that the mean returns are equal across Friday and
Monday. The results show that the null hypothesis is true for the complete period from
January 1992 to Dec2004. This hypothesis was tested at the significance of 5%.
For the period chosen from 1992 to 2004, the returns on the Mondays and the
Fridays are equal from the data taken and proved from the test. Therefore, in the Indian
stock market context the day-of-the-week effect is not present.
41
42. Conclusion:
The study has proved that there is day-of-the-week effect is not present in the of
market index from 1992-2004. Nevertheless, the data is only represents certain period
from 1992 to 2004 and only that S&P CNX NIFTY of market index. In addition to that
there are different periods are chosen to test during that particular period is there any
day-of-the-week effect persent.this is because to test, roll settlement system that started
in 1996 has any effect on the returns.
The study had proved that day- of- the- week effect is not present during the
January 1992 and December 2004 periods by using S&P CNX NIFTY. After the
introduction of the rolling settlement in 1996 the market returns for 1992 to 1996 (before
the settlement period), 1997 to 2000 and 2001 to 2004 (after the introduction of the
settlement periods) are same.
So the research study showed that there is no day-of-the-week effect present in
the S&P CNX NIFTY of market index.
42