The use of technical and fundamental analysis in the stock market in emerging and developed economies

Table 4.72 Mann–Whitney U Test Risk Factors and Industry Specific Factors Ranks.. Table 4.73 Mann–Whitney U Test Risk Factors and Industry Specific Factors Test Statistics.. Table 4.74 M

The Use of Technical and Fundamental Analysis in the Stock Market in Emerging and Developed Economies

The Use of Technical and Fundamental Analysis

in the Stock Market in Emerging and Developed Economies

By

Naveen B Kumar

Indian School of Business, Hyderabad, India

Sanjay Mohapatra

Xavier Institute of Management, Bhubaneswar, India

United Kingdom – North America – Japan

    India – Malaysia – China

Emerald Group Publishing Limited

Howard House, Wagon Lane, Bingley BD16 1WA, UK

First edition 2015

Copyright © 2015 Emerald Group Publishing Limited

Reprints and permissions service

Contact: permissions@emeraldinsight.com

No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center Any opinions expressed in the chapters are those of the authors Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters’ suitability and application and disclaims any warranties, express or implied, to their use.

British Library Cataloguing in Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-1-78560-405-8

1.1 Securities Market in India: An Overview

1.1.1 Origin of Indian Stock Market

1.1.2 Assessment of Performance of Indian Securities Market (2000–2010)1.1.3 Market Segments

1.1.4 Market Participants

1.1.5 Secondary Market

1.1.6 Cash Market

1.1.7 India and International Comparison

1.2 Definitions of Technical Analysis and Fundamental Analysis

1.3 Importance and Need of the Study

1.4 Objectives of the Study

1.5 Hypotheses

1.6 Research Methodology

1.6.1 Sources of Data

1.6.2 Sampling Plan

1.6.3 Methods of Data Collection

1.6.4 Data Analysis Tools and Techniques

1.7 Scope and Limitations of the Study

1.8 Organisation of the Study

CHAPTER 2  Introduction to Various Approaches

2.1 Introduction

2.2 Fundamental Approach

2.2.1 Discounted Cash Flow Valuation

2.2.2 Dividend Discount Models

CHAPTER 3  Review of Literature

3.1 Review of Existing Literature

4.2.3 Relevant Work Experience

4.3 Objective 1 – Time Period Analysis

4.3.1 ANOVA One Way Using SPSS

4.3.2 Kruskal–Wallis H Test Using SPSS

4.4 Objective 2 – Importance Factors’ Analysis

4.4.1 ANOVA One Way Using SPSS

4.4.2 Kruskal–Wallis H Test Using SPSSS

4.5 Objective 3 – Complementarity Analysis

4.6 Objective 4 – Demographic and Technical and Fundamental Tools Association Analysis

4.6.1 Chi-Square Tests

4.6.2 Gender versus Analytical Techniques

4.6.3 Gender versus Computer Graphics and Services

4.6.4 Gender versus Chartist Publication

4.6.5 Gender versus Chart Company or Analyst

4.6.6 Gender versus Sentiment Indicators

4.6.7 Gender versus Earnings Multiple Method

4.6.8 Gender versus Discounted Cash Flows Methods

4.6.9 Gender versus Dividend Discount Models

4.6.10 Gender versus Value Added Concept

4.6.11 Age versus Analytical Techniques

4.6.12 Age versus Computer Graphics and Services

4.6.13 Age versus Chartist Publications

4.6.14 Age versus Chart Company or Analyst

4.6.15 Age versus Sentiment Indicators

4.6.16 Age versus Earnings Multiple Methods

4.6.17 Age versus Discounted Cash Flows Methods

4.6.18 Age versus Dividend Discount Models

4.6.19 Age versus Value Added Concepts

4.7 Crosstabs

4.7.1 Experience (EXP) versus Analytical Techniques

4.7.2 Experience (EXP) versus Computer Graphics and Services

4.7.3 Experience (EXP) versus Chartist Publications

4.7.4 Experience (EXP) versus Chart Company or Analyst

4.7.5 Experience (EXP) versus Sentiment Indicators

4.7.6 Experience (EXP) versus Earnings Multiple Methods

4.7.7 Experience (EXP) versus Discounted Cash Flows Methods

4.7.8 Experience (EXP) versus Dividend Discount Models

4.7.9 Experience (EXP) versus Value Added Concepts

CHAPTER 5  Conclusions and Recommendations

5.1 Objective 1 – Time Period

5.2 Objective 2 – Importance Factors

5.3 Objective 3 – Complementarity

5.4 Objective 4 – Demographic and Technical and Fundamental Tools Association5.5 Scope for Future Research

AppendicesBibliographyIndex

List of Tables

Chapter 1

Table 1.1 Key Performance Indicators of Securities Market (2000–2010).

Table 1.2 Secondary Market – Selected Indicators.

Table 1.3 International Comparison of Global Stock Markets.

Table 1.4 Research Methodology Framework.

Table 1.5 Determination of Sample Size.

Chapter 4

Table 4.1 Gender Composition in the Sample.

Table 4.2 Age Groups of the Respondents.

Table 4.3 Relevant Work Experience.

Table 4.4 Descriptives of Time Period.

Table 4.5 One Way ANOVA of Time Period.

Table 4.6 Robust Tests of Equality of Means-Time Period.

Table 4.7 Post Hoc Tests of Time Period.

Table 4.8 Technicality Degree.

Table 4.9 Overall Means of Time Period.

Table 4.10 Descriptive Statistics – Kruskal–Wallis Test-Time Period.

Table 4.11 Kruskal–Wallis Ranks – Time Period.

Table 4.12 Kruskal–Wallis Test Statistics-Time Period.

Table 4.13 Mann–Whitney U Test (Intraday and 1 Week) Ranks.

Table 4.14 Mann–Whitney U Test (Intraday and 1 Week) Statistics.

Table 4.15 Mann–Whitney U Test (Intraday and 1 Month) Ranks.

Table 4.16 Mann–Whitney U Test (Intraday and 1 Month) Test Statistics.

Table 4.17 Mann–Whitney U Test (Intraday and 3 Months) Ranks.

Table 4.18 Mann–Whitney U Test (Intraday and 3 Months) Test Statistics.

Table 4.19 Mann–Whitney U Test (Intraday and 6 Months) Ranks.

Table 4.20 Mann–Whitney U Test (Intraday and 6 Months) Test Statistics.

Table 4.21 Mann–Whitney U Test (Intraday and 1 Year) Ranks.

Table 4.22 Mann–Whitney U Test (Intraday and 1 Year) Test Statistics.

Table 4.23 Mann–Whitney U Test (Intraday and beyond Year) Ranks.

Table 4.24 Mann–Whitney U Test (Intraday and beyond Year) Test Statistics.

Table 4.25 Mann–Whitney U Test (1 Week and 1 Month) Ranks.

Table 4.26 Mann–Whitney U Test (1 Week and 1 Month) Test Statistics.

Table 4.27 Mann–Whitney U Test (1 Week and 3 Months) Ranks.

Table 4.28 Mann–Whitney U Test (1 Week and 3 Months) Test Statistics.

Table 4.29 Mann–Whitney U Test (1 Week and 6 Months) Ranks.

Table 4.30 Mann–Whitney U Test (1 Week and 6 Months) Test Statistics.

Table 4.31 Mann–Whitney U Test (1 Week and 1 Year) Ranks.

Table 4.32 Mann–Whitney U Test (1 Week and 1 Year) Test Statistics.

Table 4.33 Mann–Whitney U Test (1 Week and beyond 1 Year) Ranks.

Table 4.34 Mann–Whitney U Test (1 Week and beyond 1 Year) Test Statistics.

Table 4.35 Mann–Whitney U Test (1 Month and 3 Months) Ranks.

Table 4.36 Mann–Whitney U Test (1 Month and 3 Months) Test Statistics.

Table 4.37 Mann–Whitney U Test (1 Month and 6 Months) Ranks.

Table 4.38 Mann–Whitney U Test (1 Month and 6 Months) Test Statistics.

Table 4.39 Mann–Whitney U Test (1 Month and 1 Year) Ranks.

Table 4.40 Mann–Whitney U Test (1 Month and 1 Year) Test Statistics.

Table 4.41 Mann–Whitney U Test (1 Month and beyond Year) Ranks.

Table 4.42 Mann–Whitney U Test (1 Month and beyond Year) Test Statistics.

Table 4.43 Mann–Whitney U Test (3 Months and 6 Months) Ranks.

Table 4.44 Mann–Whitney U Test (3 Months and 6 Months) Test Statistics.

Table 4.45 Mann–Whitney U Test (3 Months and 1 Year) Ranks.

Table 4.46 Mann–Whitney U Test (3 Months and 1 Year) Test Statistics.

Table 4.47 Mann–Whitney U Test (3 Months and beyond Year) Ranks.

Table 4.48 Mann–Whitney U Test (3 Months and beyond Year) Test Statistics.

Table 4.49 Mann–Whitney U Test (6 Months and 1 Year) Ranks.

Table 4.50 Mann–Whitney U Test (6 Months and 1 Year) Test Statistics.

Table 4.51 Mann–Whitney U Test (6 Months and beyond 1 Year) Ranks.

Table 4.52 Mann–Whitney U Test (6 Months and beyond 1 Year) Test Statistics.

Table 4.53 Mann–Whitney U Test (1 Year and beyond 1 Year) Ranks.

Table 4.54 Mann–Whitney U Test (1 Year and beyond 1 Year) Test Statistics.

Table 4.55 Descriptives of Importance Factors.

Table 4.56 One Way ANOVA of Importance Factors.

Table 4.57 Robust Tests of Equality of Means-Importance Factors.

Table 4.58 Post Hoc Tests of Importance Factors.

Table 4.59 Means of Importance Factors.

Table 4.60 Homogeneous Subsets of Importance Factors.

Table 4.61 Kruskal–Wallis Descriptive Statistics-Importance Factors.

Table 4.62 Kruskal–Wallis Test Ranks-Importance Factors.

Table 4.63 Kruskal–Wallis Test Statistics-Importance Factors.

Table 4.64 Mann–Whitney U Test (Risk Factors and Liquidity Factors) Ranks.

Table 4.65 Mann–Whitney U Test (Risk Factors and Liquidity Factors) Test Statistics.

Table 4.66 Mann–Whitney U Test (Risk Factors and Financial Factors) Ranks.

Table 4.67 Mann–Whitney U Test (Risk Factors and Financial Factors) Test Statistics.

Table 4.68 Mann–Whitney U Test (Risk Factors and Technical Factors) Ranks.

Table 4.69 Mann–Whitney U Test (Risk Factors and Technical Factors) Test Statistics.

Table 4.70 Mann–Whitney U Test (Risk Factors and Economic Factors) Ranks.

Table 4.71 Mann–Whitney U Test (Risk Factors and Economic Factors) Test Statistics.

Table 4.72 Mann–Whitney U Test (Risk Factors and Industry Specific Factors) Ranks.

Table 4.73 Mann–Whitney U Test (Risk Factors and Industry Specific Factors) Test Statistics.

Table 4.74 Mann–Whitney U Test (Risk Factors and Company Specific Factors) Ranks.

Table 4.75 Mann–Whitney U Test (Risk Factors and Company Specific Factors) Test Statistics.

Table 4.76 Mann–Whitney U Test (Risk Factors and Others) Ranks.

Table 4.77 Mann–Whitney U Test (Risk Factors and Others) Test Statistics.

Table 4.78 Mann–Whitney U Test (Liquidity Factors and Financial Factors) Ranks.

Table 4.79 Mann–Whitney U Test (Liquidity Factors and Financial Factors) Test Statistics.

Table 4.80 Mann–Whitney U Test (Liquidity Factors and Technical Factors) Ranks.

Table 4.81 Mann–Whitney U Test (Liquidity Factors and Technical Factors) Test Statistics.

Table 4.82 Mann–Whitney U Test (Liquidity Factors and Economic Factors Ranks.

Table 4.83 Mann–Whitney U Test (Liquidity Factors and Economic Factors Test Statistics.

Table 4.84 Mann–Whitney U Test (Liquidity Factors and Industry Specific Factors) Ranks.

Table 4.85 Mann–Whitney U Test (Liquidity Factors and Industry Specific Factors) Test Statistics.

Table 4.86 Mann–Whitney U Test (Liquidity Factors and Company Specific Factors) Ranks.

Table 4.87 Mann–Whitney U Test (Liquidity Factors and Company Specific Factors) Test Statistics.

Table 4.88 Mann–Whitney U Test (Liquidity Factors and Others) Ranks.

Table 4.89 Mann–Whitney U Test (Liquidity Factors and Others) Test Statistics.

Table 4.90 Mann–Whitney U Test (Financial Factors and Technical Factors) Ranks.

Table 4.91 Mann–Whitney U Test (Financial Factors and Technical Factors) Test Statistics.

Table 4.92 Mann–Whitney U Test (Financial Factors and Economic Factors) Ranks.

Table 4.93 Mann–Whitney U Test (Financial Factors and Economic Factors) Test Statistics.

Table 4.94 Mann–Whitney U Test (Financial Factors and Industry Specific Factors) Ranks.

Table 4.95 Mann–Whitney U Test (Financial Factors and Industry Specific Factors) Test Statistics.

Table 4.96 Mann–Whitney U Test (Financial Factors and Company Specific Factors) Ranks.

Table 4.97 Mann–Whitney U Test (Financial Factors and Company Specific Factors) Test Statistics.

Table 4.98 Mann–Whitney U Test (Financial Factors and Others) Ranks.

Table 4.99 Mann–Whitney U Test (Financial Factors and Others) Test Statistics.

Table 4.100 Mann–Whitney U Test (Technical Factors and Economic Factors) Ranks.

Table 4.101 Mann–Whitney U Test (Technical Factors and Economic Factors) Test Statistics.

Table 4.102 Mann–Whitney U Test (Technical Factors and Industry Specific Factors) Ranks.

Table 4.103 Mann–Whitney U Test (Technical Factors and Industry Specific Factors) Test Statistics.

Table 4.104 Mann–Whitney U Test (Technical Factors and Company Specific Factors) Ranks.

Table 4.105 Mann–Whitney U Test (Technical Factors and Company Specific Factors) Test Statistics.

Table 4.106 Mann–Whitney U Test (Technical Factors and Others) Ranks.

Table 4.107 Mann–Whitney U Test (Technical Factors and Others) Test Statistics.

Table 4.108 Mann–Whitney U Test (Economic Factors and Industry Specific Factors) Ranks.

Table 4.109 Mann–Whitney U Test (Economic Factors and Industry Specific Factors) Test Statistics.

Table 4.110 Mann–Whitney U Test (Economic Factors and Company Specific Factors) Ranks.

Table 4.111 Mann–Whitney U Test (Economic Factors and Company Specific Factors) Test Statistics.

Table 4.112 Mann–Whitney U Test (Economic Factors and Others) Ranks.

Table 4.113 Mann–Whitney U Test (Economic Factors and Others) Test Statistics.

Table 4.114 Mann–Whitney U Test (Industry Specific Factors and Company Specific Factors) Ranks.

Table 4.115 Mann–Whitney U Test (Industry Specific and Company Specific Factors) Test Statistics.

Table 4.116 Mann–Whitney U Test (Industry Specific Factors and Others) Ranks.

Table 4.117 Mann–Whitney U Test (Industry Specific Factors and Others) Test Statistics.

Table 4.118 Mann–Whitney U Test (Company Specific Factors and Others) Ranks.

Table 4.119 Mann–Whitney U Test (Company Specific Factors and Others) Test Statistics.

Table 4.120 Descriptives of Gender versus Analytical Techniques.

Table 4.121 Chi-Square Test Results (Gender vs Analytical Techniques).

Table 4.122 Descriptives of Gender versus Computer Graphics and Services.

Table 4.123 Chi-Square Test Results (Gender vs Computer Graphics and Services).

Table 4.124 Descriptives of Gender versus Chartist Publication.

Table 4.125 Chi-Square Test Results (Gender vs Chartist Publications).

Table 4.126 Descriptives of Gender versus Chart Company or Analyst.

Table 4.127 Chi-Square Test Results (Gender vs Chart Company or Analyst).

Table 4.128 Descriptives of Gender versus Sentiment Indicators.

Table 4.129 Chi-Square Test Results (Gender vs Sentiment Indicators).

Table 4.130 Descriptives of Gender versus Earnings Multiple Method.

Table 4.131 Chi-Square Test Results (Gender vs Earnings Multiple Methods).

Table 4.132 Descriptives of Gender versus Discounted Cash Flows Methods.

Table 4.133 Chi-Square Test Results (Gender vs Discounted Cash Flows Methods).

Table 4.134 Descriptives of Gender versus Dividend Discount Models.

Table 4.135 Chi-Square Test Results (Gender vs Dividend Discount Models).

Table 4.136 Descriptives of Gender versus Value Added Concepts.

Table 4.137 Chi-Square Test Results (Gender vs Value Added Concepts).

Table 4.138 Descriptives of Age versus Analytical Techniques.

Table 4.139 Chi-Square Test Results (Age vs Analytical Techniques).

Table 4.140 Descriptives of Age versus Computer Graphics and Services.

Table 4.141 Chi-Square Test Results (Age vs Computer Graphics and Services).

Table 4.142 Descriptives of Age versus Chartist Publications.

Table 4.143 Chi-Square Test Results (Age vs Chartist Publications).

Table 4.144 Descriptives of Age versus Chart Company or Analyst.

Table 4.145 Chi-Square Test Results (Age vs Chart Company or Analyst).

Table 4.146 Descriptives of Age versus Sentiment Indicators.

Table 4.147 Chi-Square Test Results (Age vs Sentiment Indicators).

Table 4.148 Descriptives of Age versus Earnings Multiple Methods.

Table 4.149 Chi-Square Test Results (Age vs Earnings Multiple Methods).

Table 4.150 Descriptives of Age versus Discounted Cash Flows Methods.

Table 4.151 Chi-Square Test Results (Age vs Discounted Cash Flows Methods).

Table 4.152 Descriptives of Age versus Dividend Discount Models.

Table 4.153 Chi-Square Test Results (Age vs Dividend Discount Models).

Table 4.154 Descriptives of Age versus Value Added Concepts.

Table 4.155 Chi-Square Test Results (Age vs Value Added Concepts).

Table 4.156 Descriptives of Experience versus Analytical Techniques.

Table 4.157 Chi-Square Test Results (Experience vs Analytical Techniques).

Table 4.158 Descriptives of Experience versus Computer Graphics and Services.

Table 4.159 Chi-Square Test Results (Experience vs Computer Graphics and Services).

Table 4.160 Descriptives of Experience versus Chartist Publications.

Table 4.161 Chi-Square Test Results (Experience vs Chartist Publications).

Table 4.162 Descriptives of Experience versus Chart Company or Analyst.

Table 4.163 Chi-Square Test Results (Experience vs Chart Company or Analyst).

Table 4.164 Descriptives of Experience versus Sentiment Indicators.

Table 4.165 Chi-Square Test Results (Experience vs Sentiment Indicators).

Table 4.166 Descriptives of Experience versus Earnings Multiple Methods.

Table 4.167 Chi-Square Test results (Experience vs Earnings Multiple Methods).

Table 4.168 Descriptives of Experience versus Discounted Cash Flows Methods.

Table 4.169 Chi-Square Test Results (Experience vs Discounted Cash Flows Methods).

Table 4.170 Descriptives of Experience versus Dividend Discount Models.

Table 4.171 Chi-Square Test Results (Experience vs Dividend Discount Models).

Table 4.172 Descriptives of Experience versus Value Added Concepts.

Table 4.173 Chi-Square Test Results (Experience vs Value Added Concepts).

Table 4.174 Summary of Chi-Square (χ2 ) Test Results – Gender versus Chartist Methods and Services Table 4.175 Summary of Chi-Square (χ2 ) Test Results – Gender versus Valuation Techniques.

Table 4.176 Summary of Chi-Square (χ2 ) Test Results – Age Group versus Chartist Methods and Services.

Table 4.177 Summary of Chi-Square (χ2 ) Test Results-Age Group versus Valuation Techniques.

Table 4.178 Summary of Chi-Square (χ2) Test Results-Work Exp versus Chartist Methods and Services.

Table 4.179 Summary of Chi-Square (χ2 ) Test Results-Work Exp vs Valuation Techniques.

Chart 2.1 Dow Theory.

Chart 2.2 Line Chart.

Chart 2.3 Bar Chart.

Chart 2.4 Point and Figure Chart.

Chart 2.5 Candlesticks.

Chart 2.6 Candlesticks-DJ-30.

Chart 2.7 Trend Line.

Chart 2.8 Support Line.

Chart 2.9 Resistance Line.

Chart 2.10 Head and Shoulders Pattern.

Chart 2.11 Double Top (Reversal).

Chart 2.12 Double Bottom (Reversal).

Chart 2.13 Triangle Formation.

Chart 2.14 Rectangle Formation.

Chart 2.15 Rate of Change.

Chart 2.16 Stochastic Oscillator.

Chart 2.17 Relative Strength Index.

Chart 2.18 Moving Average Line.

Chart 2.19 Moving Average Convergence Divergence.

Chart 2.20 Breakaway Gap.

Chart 2.21 Runaway Gap.

Chart 2.22 Exhaustion Gap.

Chart 2.23 Composite Figure Depicting all Three Gaps.

Chapter 4

Chart 4.1 Gender Composition in the Sample.

Chart 4.2 Age Groups of the Respondents.

Chart 4.3 Relevant Work Experience.

Chart 4.4 Forecasting Styles.

Chart 4.5 Means Plot of Importance Factors.

Chart 4.6 Degree of Complementarity-I.

Chart 4.7 Degree of Complementarity-II.

Chart 4.8 Bar Chart Gender versus Analytical Techniques.

Chart 4.9 Bar Chart Gender versus Computer Graphics and Services.

Chart 4.10 Bar Chart Gender versus Chartist Publications.

Chart 4.11 Bar Chart Gender versus Chart Company or Analyst.

Chart 4.12 Bar Chart Gender versus Sentiment Indicators.

Chart 4.13 Bar Chart Gender versus Earnings Multiple Methods.

Chart 4.14 Bar Chart Gender versus Discounted Cash Flows Methods Chart 4.15 Bar Chart Gender versus Dividend Discount Models.

Chart 4.16 Bar Chart Gender versus Value Added Concepts.

Chart 4.17 Bar Chart Age versus Analytical Techniques.

Chart 4.18 Bar Chart Age versus Computer Graphics and Services Chart 4.19 Bar Chart Age versus Chartist Publications.

Chart 4.20 Bar Chart Age versus Chart Company or Analyst.

Chart 4.21 Bar Chart Age versus Sentiment Indicators.

Chart 4.22 Bar Chart Age versus Earnings Multiple Methods.

Chart 4.23 Bar Chart Age versus Discounted Cash Flows Methods Chart 4.24 Bar Chart Age versus Dividend Discount Models.

Chart 4.25 Bar Chart Age versus Value Added Concepts.

Chart 4.26 Bar Chart Experience versus Analytical Techniques.

Chart 4.27 Bar Chart Experience versus Computer Graphics and Services Chart 4.28 Bar Chart Experience versus Chartist Publications.

Chart 4.29 Bar Chart Experience versus Chart Company or Analyst Chart 4.30 Bar Chart Experience versus Sentiment Indicators.

Chart 4.31 Bar Chart Experience versus Earnings Multiple Methods Chart 4.32 Bar Chart Experience versus Discounted Cash Flows Methods Chart 4.33 Bar Chart Experience versus Dividend Discount Models Chart 4.34 Bar Chart Experience versus Value Added Concepts.

List of Abbreviations

ANOVA Analysis of Variance

APV Adjusted Present Value Method

BSE Bombay Stock Exchange

BV Book Value

DCF Discounted Cash Flow Analysis

DDM Dividend Discount Models

DMA Displaced Moving Average

EBIT DA Earnings before Interest, T ax, Depreciation and Amortization EMA Exponential Moving Average

EV Enterprise Value

EVA Economic Value Added

FT E Flow to Equity Method

GDP Gross Domestic Product

LCF Levered Cash Flow

MACD Moving Average Convergence Divergence

MV Moving Average

MVA Market Value Added

NOPAT Net Operating Profit after T axes

NPVF Net Present Value of Financing Side Effects

NSE National Stock Exchange of India Ltd.

P/BV Price to Book Value Ratio

P/E Price to Earnings Ratio

PSR Price to Sales Ratio

PV Present Value

ROC Rate of Change

RSI Relative Strength Index

S & P Standard and Poor

SEBI Securities and Exchange Board of India

SES Singapore Stock Exchange

SMA Simple Moving Average

ST II Singapore Straits T imes Industrial Index

UCF Unlevered Cash Flows

WACC Weighted Average Cost of Capital Method

Abstract

s in all financial markets, the primary question in the stock market is how market participantsand stock traders forecast future market prices The two general techniques for predictingstock market prices used by market professionals are ‘chartist’ or ‘technical’ analysis andfundamental or intrinsic value analysis This study aims at finding out the usage of technical andfundamental analysis in the Indian stock market (emerging market) by brokers and the perceivedimportance attached to them by brokers

Shiller (2000)

1.1 Securities Market in India: An Overview

The last decade (2000–2010) had been the most eventful period for the Indian securities marketduring which it took major strides to carve a niche for itself in the global securities markets Thissection discusses origin, structure and the developments of the Indian securities markets and broaderdevelopments in the securities markets during 2000–2010.1

1.1.1 ORIGIN OF INDIAN STOCK MARKET

The origin of the stock market in India goes back to the end of the eighteenth century when long-termnegotiable securities were first issued However, for all practical purposes, the real beginningoccurred in the middle of the nineteenth century after the enactment of the Companies Act in 1850,which introduced the features of limited liability and generated investor interest in corporatesecurities

An important early event in the development of the stock market in India was the formation of theNative Share and Stock Brokers’ Association at Bombay in 1875, the precursor of the present dayBombay Stock Exchange (BSE) This was followed by the formation of associations/exchanges inAhmadabad (1894), Calcutta (1908) and Madras (1937) In addition, a large number of ephemeralexchanges emerged mainly in buoyant periods to recede into oblivion during depressing timessubsequently

Stock exchanges are intricacy inter-woven in the fabric of a nation’s economic life Without astock exchange, the saving of the community – the sinews of economic progress and productive

efficiency – would remain underutilised The task of mobilisation and allocation of savings could beattempted in the older days by a much less specialised institution than the stock exchanges But asbusiness and industry expanded and the economy assumed more complex nature, the need for

‘permanent finance’ arose Entrepreneurs needed money for long term, whereas investors demandedliquidity – the facility to convert their investment into cash at any given time The answer was a readymarket for investments, and this was how the stock exchange came into being

The BSE and the National Stock Exchange of India Ltd (NSE) are the two primary exchanges inIndia In addition, there are 22 Regional Stock Exchanges However, the BSE and NSE haveestablished themselves as the two leading exchanges and account for about 90% of the equity volumetraded in India

1.1.2 ASSESSMENT OF PERFORMANCE OF INDIAN SECURITIES MARKET (2000–2010)

The last decade (2000–2010) has been the most eventful period for the Indian securities marketduring which it took major strides to carve a niche for itself in the global securities markets Themajor developments which hastened this incredible journey are because of improved marketmicrostructure, introduction of new products and progressive changes in the regulatory framework.The above initiatives have not only transformed the landscape of the securities market but alsocontributed to its growth This can be seen in the snapshot of the decadal performance of securitiesmarket shown in Chart 1.1 It can be seen that during the decade, there has been a significant rise inthe market capitalisation ratio, turnover ratio and traded value ratio The turnover in the cash markethas nearly doubled over the decade while the market capitalisation has become eight times the levelsthat existed in 2000 The turnover in the Indian derivatives market has increased from US$0.086trillion in 2000–2001 to US$3.92 trillion in 2009–2010 and has surpassed the cash market turnover inIndia The resource mobilisation in the primary market has increased dramatically, rising sixfoldbetween 2000 and 2010 Similarly, the resource mobilisation through euro issues has increasedsignificantly over the years Table 1.1 shows the performance in the capital market in terms of certainkey indicators

Chart 1.1: Snapshot of Performance of Indian Securities Market during 2000–2010 Source:

nseindia.com

Table 1.1: Key Performance Indicators of Securities Market (2000–2010).

Parameters Compound Annual Growth Rate (2000–2001 to 2009–2010) (%)

Resource mobilisation in primary markets 17.15

Resource mobilisation through Euro Issues 43.89

All-India market capitalisation 23.15

All-India equity market turnover a 19.94

All-India equity derivatives turnover 132.19

Assets under management of mutual funds 18.99

Net investments by foreign institutional investors 30.53

Net investments by mutual funds 54.07

Returns on Nifty 50 13.13

Source: nseindia.com

a CAGR calculated from 2001 – 2002 to 2009 – 2010.

The securities markets in India have made enormous progress in developing sophisticatedinstruments and modern market mechanisms The key strengths of the Indian capital market include afully automated trading system on all stock exchanges, a wide range of products, an integratedplatform for trading in both cash and derivatives, and a nationwide network of trading through

corporate brokers A significant feature of the Indian securities market is the quality of regulation.The market regulator, Securities and Exchange Board of India (SEBI), is an independent and effectiveregulator It has put in place sound regulations in respect of intermediaries, trading mechanism,settlement cycles, risk management, derivative trading and takeover of companies There is a well-designed disclosure-based regulatory system Information technology is extensively used in thesecurities market The stock exchanges in India have the most advanced and scientific riskmanagement systems The growing number of market participants, the growth in volume of securitiestransactions, the reduction in transaction costs, the significant improvements in efficiency,transparency and safety and the level of compliance with international standards have earned a newrespect in the world for the Indian securities market.

1.1.3 MARKET SEGMENTS

The securities market has two interdependent and inseparable segments, namely the new issues(primary) market and the stock (secondary) market The primary market provides the channel forcreation and sale of new securities, while the secondary market deals with securities previouslyissued Once the new securities are issued in the primary market they are traded in the stock(secondary) market

1.1.4 MARKET PARTICIPANTS

In every economic system, some units, individuals or institutions are surplus units which are calledsavers, while others are deficit units called spenders Households are surplus units and corporate andGovernment are deficit units Through the platform of securities markets, the savings units place theirsurplus funds in financial claims or securities at the disposal of the spending community and in turnget benefits like interest, dividend, capital appreciation, bonus etc These investors and issuers offinancial securities constitute two important elements of the securities markets The third criticalelement of markets is the intermediaries which act as conduits between the investors and issuers.Regulatory bodies, which regulate the functioning of the securities markets, constitute anothersignificant element of securities markets The process of mobilisation of resources is carried outunder the supervision and overview of the regulators The regulators develop fair market practicesand regulate the conduct of issuers of securities and the intermediaries They are also in charge ofprotecting the interests of the investors The regulator ensures a high service standard from theintermediaries and supply of quality securities and non-manipulated demand for them in the market.The four important elements of securities markets are the investors, the issuers, the intermediaries andregulators Chart 1.2 shows Indian household investment in different investment avenues since 1990–

1991 till 2008–2009 It can be observed that the household investments in government securities andmutual funds fell in the negative territory while investments in shares and debentures of privatecorporates, banking and PSU bonds were at 4.4% at par with investments last year

Chart 1.2: Saving of the Household Sector in Financial Assets Source: nseindia.com

1.1.5 SECONDARY MARKET

Exchanges in the country offer screen-based trading system There were 9,772 trading membersregistered with SEBI as by the end of March 2010 The market capitalisation has grown over theperiod indicating that more companies are using the trading platform of the stock exchange The All-India market capitalisation was around 61,704,205 million (US$1,366,952 million) by the end ofMarch 2010 The market capitalisation ratio is defined as market capitalisation of stocks divided byGross Domestic Product (GDP) It is used as a measure to denote the importance of equity marketsrelative to the GDP It is of economic significance since market is positively correlated with theability to mobilise capital and diversify risk The All-India market capitalisation ratio increased to94.20% in 2009–2010 from 55.40% in 2008–2009 (Table 1.2) By the end of March 2010, NSEmarket capitalisation ratio fell to 76.28% during 2009–2010, while BSE market capitalisation ratiowas 78.26%

Table 1.2: Secondary Market – Selected Indicators.

Source: CSO, SEBI, CMIE Prowess and NSE.

1.1.6 CASH MARKET

During 2009–2010, the trading volumes on the equity segment of exchanges increased significantly by43.26% y-o-y to ₹55,184,700 million (US$1,222,523 million) from ₹38,520,970 million(US$756,054 million) in 2008–2009 (Table 1.2) The turnover during April 2010–September 2010 inthe equity markets was ₹23,547,240 crore (US$522,807 million)

1.1.7 INDIA AND INTERNATIONAL COMPARISON

The securities markets in India and abroad witnessed recovery during 2009 This was reflected in therising market capitalisation of stock exchanges of emerging and developing countries The marketcapitalisation of the emerging markets increased to 28.3% of world total market capitalisation in

2009, up from 25.9% in 2008 The market value of emerging markets increased by 48.8% in 2009.The United States which accounted for 30.9% of the world total market capitalisation in 2009registered a rise of 28.4% in its market capitalisation However, neither the emerging countries northe developed economies were able to surpass the levels of growth witnessed in marketcapitalisation and turnover during the year 2007 This is clearly exhibited in Table 1.3 The stockmarkets worldwide have grown in size as well as depth over the years As can be observed from

Table 1.3, the market capitalisation of all listed companies in developed and emerging economiestaken together on all markets stood at US$48.71 trillion in 2009 up from US$34.88 trillion in 2008 Interms of market capitalisation, nearly all the countries showed an increase in the year 2009 ascompared with the year 2008 However, in terms of turnover, all the countries compared to the year

2009, the share of United States in worldwide market capitalisation remained at 30.9% at the end of

2009 as it was at the end of 2007 The stock market capitalisation for some developed and emergingcountries is shown in Chart 1.3

Table 1.3: International Comparison of Global Stock Markets.

Source: S&P Global Stock Market Factbook, 2009 and World Development Indicators, World Bank.

Note: Market capitalisation ratio is computed as a percentage of GDP.

Chart 1.3: Stock Market Capitalisation (% of GDP) Source: nseindia.com

1.2 Definitions of Technical Analysis and Fundamental

Cambridge Dictionaries Online defines Technical Analysis as, ‘a method used to calculate the futurevalue of shares by studying the patterns of their past behaviour rather than the fundamentals (= profits

of companies whose shares are traded, the real economy, etc.)’.2

Technical, or chartist, analysis of financial markets involves providing forecasts of asset prices

or buy/sell advice on the basis of visual observation and examination of the past history of pricemovements (Edwards et al., 1967), perhaps with the aid of certain quantitative techniques such asmomentum indicators and moving averages (Murphy, 1986), without considering any fundamentalfactors Oxford Dictionaries Online defines Technical analysis or (Chartism) as, ‘the use of charts offinancial data to predict future trends and to guide investment strategies’.3

The technical approach to investment is essentially a reflection of the idea that prices move intrends which are determined by the changing attitudes of investors toward a variety ofeconomic, monetary, political and psychological forces … Since the technical approach isbased on the theory that the price is a reflection of mass psychology (‘the crowd’) in action, itattempts to forecast future price movements on the assumption that crowd psychology movesbetween panic, fear, and pessimism on one hand and confidence, excessive optimism, andgreed on the other

Pring (1991)

Investopedia4 defines Technical Analysis as, ‘a method of evaluating securities by analysingstatistics generated by market activity, such as past prices and volume Technical analysts do notattempt to measure a security’s intrinsic value, but instead use charts and other tools to identifypatterns that can suggest future activity’

Another approach which is rather different from technical approach is fundamental analysis or theintrinsic value method The assumption of the fundamental analysis approach is that at any point intime an individual security has an intrinsic value which depends on the fundamentals of the security(earning potential of the security) The future earning potential of the security depends on factors likequality of management, outlook for the industry and the economy Through a careful study of thesefundamental factors the analyst should, be able to determine whether the actual market price of asecurity is above or below its intrinsic value (Fama, 1965)

Investopedia5 defines Fundamental Analysis as, ‘a method of evaluating a security that entailsattempting to measure its intrinsic value by examining related economic, financial and otherqualitative and quantitative factors’ Fundamental analysts attempt to study everything that can affectthe security’s value, including macroeconomic factors (like the overall economy and industryconditions) and company-specific factors (like financial condition and management) The end goal ofperforming fundamental analysis is to produce a value that an investor can compare with thesecurity’s current price, with the aim of figuring out what sort of position to take with that security

1.3 Importance and Need of the Study

Despite the increasing professional interest in non-fundamental factors, there is little empiricalevidence on the prevalence and importance of such techniques in the Indian stock market Goodman(1980) examines the performance of technical analysts, but does not provide evidence on theimportance which markets attaches to their advice Mitra (2009), Kakani et al (2006) and Pampana

et al (2005) analyses the profitability of different technical trading rules in the Indian stock marketbut has not directly compared the usefulness of technical and fundamental analysis in the Indian stockmarket

This is the first study concerned with how professional traders forecast stock rate movements inIndia Given that India is the second largest stock exchange market in terms of market capitalisation(Table 1.3) among emerging and developing countries and the fact that brokers’ views are animportant factor driving stock price movements, this study may enhance understanding of stock priceanalysis and forecasting

This study tries to extend the results of previous works done on the use of technical analysis andfundamental analysis among foreign exchange traders in London (Taylor et al., 1992) and work done

in Hong Kong (Lui et al., 1998) and work done in the European foreign exchange market(Oberlechner, 2001) to a new geographic location and to a new financial market

1.4 Objectives of the Study

The current research had been carried out to achieve the following objectives:

• To examine the importance that brokers’ personally give to fundamental and technical analysis overseven forecasting horizons: intraday, 1 week, 1 month, 3 months, 6 months, 1 year and beyond 1year

• To investigate the importance of risk factors, liquidity factors, financial factors, technical factors,economic factors, industry specific factors, company-specific factors and other factors on stockprice forecasting in long term

• To examine the importance of brokers’ views of the degree of complementarity of fundamental andtechnical analysis in stock price forecasting

• To understand the association between various demographic variables of brokers and the usage ofchartist methods and services and valuation techniques

1.5 Hypotheses

One of the objectives of the current research was to examine the importance that brokers personallygave to fundamental and technical analysis over seven forecasting horizons: intraday, 1 week, 1month, 3 months, 6 months, 1 year and beyond 1 year Hence it was decided to conduct means testusing one-way ANOVA (Oberlechner, 2001) For this purpose, basing on the literature available,following hypotheses were set up and further tested

Ho Mean importance ratings over seven forecasting horizons are equal, that is

= µ1 year =µ>1year

Ha Mean importance ratings over seven forecasting horizons are not equal, that is

µintraday ≠ µ1week ≠ µ1 month ≠ µ3 months ≠ µ6 months

≠ µ1 year ≠ µ>1 year

One of the objectives of the current research was to investigate the importance of risk factors,liquidity factors, financial factors, technical factors, economic factors, industry specific factors,company-specific factors and other factors on stock price forecasting in long term Hence it wasdecided to conduct means test using one-way ANOVA ( Oberlechner, 2001) For this purpose, basing

on the literature available, following hypotheses were set up and further tested

Ho Means of importance ratings of all factors are equal, that is

µRisk Factors = µLiquidity Factors = µFinancial Factors

= µTechnical Factors = µEconomic Factors

= µIndustry Specific Factors = µCompany Specific Factors = µOther Factors.

Ha Means of importance ratings of all factors are not equal, that is

µRisk Factors ≠ µLiquidity Factors ≠ µFinancial Factors

≠ µTechnical Factors ≠ µEconomic Factors

≠ µIndustry Specific Factors ≠ µCompany Specific Factors ≠ µOther Factors.

One of the objectives of the current research was to understand the association between,various demographic variables of brokers and the usage of chartist methods and servicesand valuation techniques Hence it was decided to conduct association tests using Chi-square analysis For this purpose, basing on the literature available, following hypotheseswere set up and further tested

Ho Usage of chartist methods and services: analytical techniques, computer graphics and

services, chartist publications, chart company or chart analyst and sentiment indicators areindependent of gender

Ha Usage of chartist methods and services: analytical techniques, computer graphics and

services, chartist publications, chart company or chart analyst and sentiment indicators are

dependent on gender.

Ho Usage of valuation techniques: earnings multiple methods, discounted cash flows

methods, dividend discount models and value added methods are independent of gender

Ha Usage of valuation techniques: earnings multiple methods, discounted cash flows

methods, dividend discount models and value added methods are dependent on gender

Ho Usage of chartist methods and services: analytical techniques, computer graphics and

services, chartist publications, chart company or chart analyst and sentiment indicators areindependent of age

Ha Usage of chartist methods and services: analytical techniques, computer graphics and

services, chartist publications, chart company or chart analyst and sentiment indicators aredependent on age

Ho Usage of valuation techniques: earnings multiple methods, discounted cash flows

methods, dividend discount models and value added methods are independent of age

Ha Usage of valuation techniques: earnings multiple methods, discounted cash flows

methods, dividend discount models and value added methods are dependent on age

Ho Usage of chartist methods and services: analytical techniques, computer graphics and

services, chartist publications, chart company or chart analyst and sentiment indicators areindependent of experience

Ha Usage of chartist methods and services: analytical techniques, computer graphics and

services, chartist publications, chart company or chart analyst and sentiment indicators aredependent on experience

Ho Usage of valuation techniques: earnings multiple methods, discounted cash flows

methods, dividend discount models and value added methods are independent of experience

Ha Usage of valuation techniques: earnings multiple methods, discounted cash flows

methods, dividend discount models and value added methods are dependent on experience

1.6 Research Methodology

After the selection and formulation of research problem, the next task of a researcher is to work out aresearch design Like an architect prepares a plan before construction, an army prepares a warstrategy before war operation; a researcher has to make a plan of study before starting the researchwork This plan of study of a researcher is called as research design It may also be considered as thespecification of methods and procedures for acquiring the information needed So research designcovers the following aspects (Table 1.4)

Table 1.4: Research Methodology Framework.

1.6.1 Sources of data Primary data

Secondary data 1.6.2 Sampling plan Sampling units

Sample size Sampling procedure Sampling contact method 1.6.3 Methods of data collection Design of questionnaire

T esting of questionnaire 1.6.4 Data analysis tools and techniques One-way ANOVA

t-test

Kruskal–Wallis H-test Mann–Whitney U-test

• Research works of various scholars

• Journals and magazines

• Websites of regulators like SEBI, RBI

• Databases like Science Direct

• Journals and magazines

• Websites of stock exchanges like NSE and BSE

• Books and other literature in the following related areas: corporate finance, technical analysis,valuation, research methodology etc

• Newspapers and articles

1.6.2 SAMPLING PLAN

The sampling plan for the current thesis constituted of sampling units, sample size, samplingprocedure and sampling contact method.

required From the regulator of stock market, SEBI website,6 the total corporate broker population

(N) in the BSE for the year ending 2009–2010 was identified as 826 Thus sample size is calculated

1.6.2.3 Sampling procedure (technique)

Probability random sampling technique was used for the purpose of collecting the sampling units.Sample units of 262 were, then selected using simple random sampling technique using randomnumber generation method and rand between function

1.6.2.4 Sampling contact method

The selected sampling units (corporate brokers in this case) were approached via online surveythrough their e-mail addresses Survey Monkey was used to conduct the online survey

1.6.3 METHODS OF DATA COLLECTION

1.6.3.1 Design of questionnaire

The current research required primary data For this purpose, questionnaire was used Questionnaireused in the present research for collecting primary data required for the study, the original wordingand question format was inferred from Taylor and Allen’s (1992)

i Specifying the information needed:

First of all information needed for research work was specified Required demographic dataincluded was age, gender, location of the office, e-mail address, relevant work experience.

ii Method of questioning:

For objective one, brokers were asked to indicate on 10-point Likert scale the relative

importance they attach to technical analysis versus fundamental analysis of stocks over sevenforecasting horizons: intraday, 1 week, 1 month, 3 months, 6 months, 1 year and beyond 1 year

A score of zero would indicate the use of pure chartist (technical) analysis alone at that

horizon and a score of 10 would indicate the use of pure fundamental analysis and an

intermediate score would indicate a weighted mix of technical analysis and fundamental

analysis

 For objective two, brokers were asked to rate on five-point Likert scale the importance ofthe different factors that they take into consideration while making investment in the stockmarket in the long term Scale indicating very important at one end to very un-important at theother end was used

 For objective three, brokers were asked to indicate on 10-point Likert scale the degree towhich they view technical analysis and fundamental analysis to be complementary tools ofanalysis in stock exchange trading A score of 10 implied a view that the two approaches aremutually exclusive, a score of zero implied a view that they are strongly complementary and

an intermediate score an intermediate degree of complementarity

 For objective four, we asked them about the usage of chartist methods and services andvaluation techniques using dichotomous questions and tried to understand their associationwith demographic variables

iii Approaching the respondents:

We sent respondents the link to the questionnaire through e-mail, thereby conducting onlineweb-based survey for collecting primary data

1.6.3.2 Testing of questionnaire

It was decided to test the validity and reliability of the questionnaire For this purpose, firstly theresearcher has identified different approaches available There are various methods of testing aquestionnaire like test/retest approach, test of face validity, conducting pilot study etc (Malhotra,

2007) To test the questionnaire used for ANOVA analysis and Kruskal–Wallis H-test, it was

decided to conduct pilot study (details of the pilot study are presented in the annexure part of thereport)

1.6.4 DATA ANALYSIS TOOLS AND TECHNIQUES

In order to extract meaningful information from the raw data collected, the data analysis was carriedout by the researcher The data were first edited, coded and tabulated for the purpose of analysingthem The analysis was conducted by using simple statistical tools like percentages, averages andmeasures of dispersion Diagrams, graphs, charts and pictures were used

One-way ANOVA, t-tests, Kruskal–Wallis H-test, Mann–Whitney U-test and Chi-square analysis

were used for the purpose of testing the hypotheses Data analysis software SPSS (version 19)

package was used to conduct, one-way ANOVA, t-tests, Kruskal–Wallis H-test, Mann–Whitney

U-test and Chi-square U-tests

1.7 Scope and Limitations of the Study

The first objective was to examine the importance that brokers’ personally gave to fundamental andtechnical analysis over seven forecasting horizons: intraday, 1 week, 1 month, 3 months, 6 months, 1year and beyond 1 year For this purpose researcher has conducted online questionnaire surveyamong corporate stock brokers registered with BSE in India only Online survey was conducted forthis purpose as the brokers were geographically distributed all over India and the cost and timeinvolved in reaching them personally was huge Attempt was made to understand the relativeimportance brokers attach to chartist/technical analysis versus fundamental analysis of stocks overseven forecasting horizons

The second objective was to investigate the importance of risk factors, liquidity factors, financialfactors, technical factors, economic factors, industry specific factors, company-specific factors andother factors on stock price forecasting in long term An attempt was made to understand theimportance of the above factors that brokers take into consideration, while making investment in thestock market in long term

The third objective was to examine the importance of brokers’ views of the degree ofcomplementarity of fundamental and technical analysis in stock price forecasting For this purposeresearcher had conducted online questionnaire survey among corporate stock brokers registered withBSE in India only An attempt was made to understand degree to which brokers viewchartist/technical analysis and fundamental analysis to be complementary tools of analysis in stockexchange trading

An attempt was made to understand the association between various demographic variables ofbrokers and the usage of chartist methods and services and valuation techniques

The study was limited to only select approaches, namely technical approach and fundamentalapproach Another limitation of the study was economic conditions which might have varied overtime as the survey was taken quite some time to complete

1.8 Organisation of the Study

The thesis is divided into five chapters In the first chapter an overview of securities market in India,introduction to the topic technical analysis and fundamental analysis have been presented Theimportance and need for the study in the current capital markets was discussed This chapter alsocovered the objectives, research methodology, scope and limitations of the study

The second chapter deals with the theoretical background of technical analysis and fundamentalanalysis and various tools and techniques of technical analysis and fundamental analysis have alsobeen discussed

The third chapter comprises a review of literature The available literature that has been

reviewed was presented The research gap was also included in this chapter.

The fourth chapter presents the analysis and interpretation of data The data which was analysedhas been presented using tables, graphs, charts and figures The various statistical tests that were used

to test the hypothesis set up have also been presented in this chapter

The fifth and final chapter presents the conclusions and recommendations that have been madebased on the study

References

Edwards, R D., & Magee, J (1967) Technical analysis of stock trends Boston, MA: John Magee.

Fama, F E (1965) Random walks in stock market prices Financial Analysts Journal, 10, 35–61.

Goodman, S H (1980) Who’s better than the toss of a coin? Euromoney, 12, 80–84.

Kakani, S., & Sundhar, M (2006) Profiting from technical analysis in Indian equity markets: Using moving averages XLRI

Jamshedpur School of Business, 06-02.

Kothari, C R (2004) Research methodology (pp 179–180) New Delhi: New Age International Publishers.

Lui, Y H., & Mole, D (1998) The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence.

Journal of International Money and Finance, 17, 535–545.

Malhotra, N K., & Dash, S (2007) New Delhi: Marketing research Pearson.

Mitra, S K (2009) How rewarding is technical analysis in the Indian stock market? Quantitative Finance, 11(2), 287.

Murphy, J J (1986) Technical analysis of the futures markets New York, NY: New York Institute of Finance.

Oberlechner, T (2001) Importance of technical and fundamental analysis in the European foreign exchange market International

Journal of Finance and Economics, 6, 81–93.

Pampana, C., & Sahu, R (2005) Application of technical trading strategies in Indian stock market Retrieved from

http://www.Centerforpbbefr.Rutgers.Edu 037.

Pring, M J (1991) Technical analysis explained (pp 2–3) New York, NY: McGraw-Hill.

Shiller, J R (2000) Irrational exuberance New York, NY: Broadway Books.

Taylor, M P., & Allen, H (1992) The use of technical analysis in the foreign exchange market Journal of International Money and

Finance, 11, 304–314.

Websites

Cambridge dictionary online, technical analysis Retrieved from www.dictionary.cambridge.org Accessed on February 4, 2010.

Definitions, technical analysis Retrieved from www.investopedia.com Accessed on February 4, 2010.

Definitions, fundamental analysis Retrieved from www.investopedia.com Accessed on February 4, 2010.

Handbook of statistics on the Indian securities market Retrieved from www.sebi.gov.in

Oxford dictionary online, technical analysis Retrieved from www.oxforddictonaries.com/ Accessed on February 4, 2010.

Securities market in India: An overview Retrieved from www.nseindia.com Accessed on April 5, 2010.

1Securities Market in India: An Overview, www.nseindia.com, April 5, 2010.

2 Cambridge Dictionary Online “Technical Analysis,” www.dictionary.cambridge.org February 4, 2010.

3 Oxford Dictionary Online “Technical Analysis,” www.oxforddictonaries.com, February 4, 2010.

4 Definitions “Technical Analysis,” www.investopedia.com, February 4, 2010.

5 Definitions “Fundamental Analysis,” www.investopedia.com, February 4, 2010.

6Handbook of Statistics on the Indian Securities Market, www.sebi.gov.in

2.2 Fundamental Approach

Fundamental analysis is a method of evaluating a stock by attempting to measure its intrinsic value.Fundamental analysts study everything from the overall economy and industry conditions, to thefinancial condition and management of companies In other words, fundamental analysis is aboutusing real data to evaluate a stock’s value The method uses revenues, earnings, future growth, return

on equity, profit margins and other data to determine a company’s underlying value and potential forfuture growth

The above analysis involves making careful estimates of the expected stream of benefits and therequired rate of return for a common stock The intrinsic value can then be obtained through any of thefollowing approaches

1 Discounted cash flow (DCF) Valuation

2 Dividend discount models (DDM)

3 Relative valuation

4 Value-added methods

2.2.1 DISCOUNTED CASH FLOW VALUATION

DCF valuation is used as foundation for most of other valuations In order to do relative valuation anddividend discount valuation you need to know the fundamentals of DCF valuation This approach hasits foundation in the present value (PV) rule, where the value of any asset is the PV of expected futurecash flows that the asset generates (Aswath, 2006).

where, n = life of the asset; CF t = cash flow in period t; r = discount rate reflecting the riskiness of

the estimated cash flows The cash flows can change from asset to asset – dividends for stocks,interest payments and the face value for bonds and after-tax cash flows for a project The discountrate will be a function of the riskiness of the estimated cash flows, with higher rates for riskier assetsand lower rates for safer projects

Commonly used DCF methods are adjusted present value method (APV), weighted average cost

of capital method (WACC) and flow to equity method (FTE)

a APV is to value the firm in pieces, beginning with its operations and adding the effects on value

of debt and other non-equity claims The value of the firm can also be obtained by valuing eachclaim on the firm separately In this approach, which is called APV, we begin by valuing equity

in the firm, assuming that it was financed only with equity We then consider the value added (ortaken away) by debt by considering the present value of the tax benefits that flow from debt andthe expected bankruptcy costs Value of firm = Value of all-equity financed firm + Present Value(PV) of tax benefits − Expected bankruptcy costs (Aswath, 2006)

  The value of a project to a levered firm (APV) is equal to the value of the project to anunlevered (all equity) firm (net present value (NPV)) plus the net present value of financing side

effects (NPVF) Discount rate used in arriving NPV is R O, all-equity cost of capital Among sideeffects like tax subsidy, financial distress costs, floatation costs and interest subsidies the

important ones are tax subsidy to debt and the costs of financial distress

1 Tax subsidy of debt: For perpetual debt the value of tax subsidy is given by t C B, where t C

represents the corporate tax rate and B is the value of debt.

2 Financial distress: The possibility of financial distress and bankruptcy arises with debt

financing Financial distress certainly imposes costs leading to lowering of firm value

3 The costs of issuing new securities: There will be some floatation costs for issuing new

securities that lowers the value of the project Unlevered cash flows (UCF) are after tax cashflows assuming all-equity financing

For perpetual cash flows the NPV calculation is

For Non-perpetual cash flows the NPV calculation is

 APV = NPV +  t C *B (Ross, Westerfield, & Jaffe, 2008).

b WACC is to value the entire firm, which includes, besides equity, the other claimholders in the

firm (bondholders, preferred stockholders etc.) The value of the firm is obtained by discountingexpected cash flows to the firm, that is the residual cash flows after meeting all operating

expenses, reinvestment needs and taxes, but prior to any payments to either debt or equity

holders, at the WACC, which is the cost of the different components of financing used by thefirm, weighted by their market value proportions (Aswath, 2006) This approach is of the insightthat projects are financed with both debt and equity The cost of capital is a weighted average of

the cost of debt and the cost of equity The cost of equity is R S , cost of debt is R B , t C is tax rate,

B = total value of debt, S is the total value of equity and after tax cost of debt is (1 − t C )R B

The weight for equity, (S/S + B), and the weight for debt, (B/S + B), are target ratios Target ratios are generally expressed in terms of market values, not book values RWACC is lower than thecost of equity capital for an all-equity firm; this is because debt financing provides a tax subsidythat lowers the average cost of capital This technique calculates the project’s after-tax cashflows assuming all-equity financing, (unlevered cash flows (UCF)) The tax advantage of debt isreflected in the denominator because cost of debt capital is determined net of corporate tax The

numerator does not reflect debt at all UCF of the project are then discounted with RWACC

For perpetual cash flows

(Ross et al., 2008)

c FTE is to value just the equity stake in the business The value of equity is obtained by

discounting expected cash flows to equity, that is the residual cash flows after meeting all

expenses, reinvestment needs, tax obligations and net debt payments (interest, principal

payments and new debt issuance), at the cost of equity, that is the rate of return required by

equity investors in the firm (Aswath, 2006) Here we discount the cash flows from the project to

the equity holders of the levered firm at the cost of equity capital, R S If the cash flows are

perpetual then the formula becomes cash flows from project to equity holders of the levered firm

divided by R S

Steps

1 First you need to calculate the Levered Cash Flow (LCF), that is cash flows after consideringinterest charges, preference dividends and tax

2 Calculating the discount rate R S.

R S = cost of equity capital of levered firm

R O = cost of capital for a project of an all equity firm

B = total debt

S = total equity

t C = tax rate

R B = cost of debt

Valuation of the project is done by discounting the LCF by R S

For perpetual flows it is given as

For non-perpetual cash flows (Ross et al., 2008)

2.2.2 DIVIDEND DISCOUNT MODELS

The DDM is a specialised case of equity valuation, where the value of the equity is the PV ofexpected future dividends According to the DDM, the value of an equity share is equal to the PV ofdividends expected from its ownership plus the PV of the sale price expected when the equity share issold Securities that represent the ultimate ownership and risk position in a corporation (Chandra,

2008) Commonly used DDMs are given below

Assumptions

1 Dividends are paid annually

2 The first dividend is received 1 year after the equity share is bought

2.2.2.1 Single-Period Valuation Model

This model is for equity wherein an investor holds it for 1 year

P O = current price of the equity share; P1 is the expected price of the equity share at the end of the

year; K e is the investors required rate of return on the equity share; D1 = expected dividend on equityshare at the end of the year.

2.2.2.2 Multi-Period Valuation Model

Value of a share of a common stock can be viewed as the discounted value of all expected cashdividends provided by the issuing firm until the end of time Cash dividends are all that stockholders,

as a whole, receive from the issuing company Consequently, the foundation for the valuation ofcommon stock must be dividends

D t is the expected cash dividend at the end of time period t; K e is the investor’s required rate of return

on equity share; P2 is the expected sale price at the end of year 2; P O is the price of the equity sharetoday

Assumptions about the Patterns of Dividend Growth

The dividend per share remains constant forever, implying that the growth rate is zero The dividendper share grows at a constant rate per year perpetually The dividend per share grows at a constanthigher rate for a finite period, followed by a constant normal rate of growth forever thereafter Thedividend per share, currently grows at an above normal rate, experiences a gradually declining rate ofgrowth for a while Thereafter, it grows at a constant normal rate

2.2.2.3 Constant Dividend (Zero Growth) Model

If the dividend paid remains constant year after year perpetually Then multi-period dividendvaluation model becomes

2.2.2.5 Two-Stage Growth Model

Two-stage growth models assumes that extraordinary growth will be there for first few years andthereafter normal growth rate would be there perpetually

where P O = current price of the equity share; D1 = dividend expected a year hence; g1 = extraordinary

growth rate applicable for n years; P n = price of the equity share at the end of year n; g2 = growth rate

in the second period; K e is the investors required rate of return on the equity share

RHS: In first term K e  > g1 or K e < g1 but, K e not equal to g1

In second term K e  > g2

First term represents the PV of the dividend stream during initial period and second term represents

PV of the share at the end of the initial period (Chandra, 2008)