Testing Of Efficient Market Hypothesis: A Study On . - IOSR Journals
IOSR Journal of Business and Management (IOSR-JBM)e-ISSN: 2278-487X, p-ISSN: 2319-7668. Volume 16, Issue 8. Ver. III (Aug. 2014), PP 28-38www.iosrjournals.orgTesting of Efficient Market Hypothesis: a study on Indian StockMarketNeeraj Gupta, Ashwin Gedam(Lecturer, Amity Business School, Amity University, Gwalior, India)(Student, MBA, Amity Business School, Amity University, Gwalior, India)Abstract: Market efficiency refers to the accuracy and quickness with which prices reflect market relatedinformation. In the weak form of the market, current price reflect all the information found in past prices andtraded volumes. Further, prices cannot be predicted by analysis of past prices. Everyone has access to pastprices even though some people can get these more easily than others. Liquidity traders may sell their stockswithout considering the intrinsic value of the shares and cause price fluctuations. Buying and selling of theinformation traders lead the market price to align itself with the intrinsic value.The filter rule, runs test and serial correlation are adopted to find out market efficiency. In this paper runs testhas been used to find out market efficiency. The stock price of the selected companies has been taken from NSE(National Stock Exchange).Keywords: Market efficiency, weak form, runs test, serial correlation, and stock prices.I.IntroductionAn institution of considerable interest to the public and of importance to economists is the StockMarket. It is responsible for dealing with instruments that represents an assertion of right to the ownership ofindustrial, financial and service character. These claims are perceived by their owners as assets which areconvertible into money and which in turn are offered for their purchase. The worlds’ stock markets are theplaces which offer liquidity ability to the owners of the assets and contribute to the continuous and competitivedetermination of prices. Therefore, it is of great importance for stock markets to operate efficiently. In a generalsense, an Efficient Stock Market is a place in which firms can make production investment decisions andinvestors can choose among the various securities that represent ownership of firms activities. The stockmarkets efficiency is a major area of research in financial economics, particularly as it relates to stock marketsof developing economies. This is because of the significance of market efficiency to the functioning of thecapital market; especially as it is responsible for stimulation of investor’s interest in market activities. It isbelieved that the behavior of investor can be used to explain the behavior of stock market. Stock marketforecasting is checked more by its failure than by its successes, since stock prices reflect the judgments andexpectations of investors . Outstandingly, efforts have been made to apply econometric techniques of modelbuilding in the prediction of stock prices . Fama and French (1988) have argued that there are long-term patternin stock prices with several years of upswing followed by more sluggish periods. According to Fama (1965;1995), a stock market where successive price changes in individual securities are independent is by theirdefinition, a random walk market. Specifically, stock prices following a random walk imply that the pricechanges are as independent of one another as the gains and losses. The independence assumption relating to therandom walk hypothesis is valid as long as knowledge of the past behavior of the series of price changes cannotbe used to increase expected gains. Also, if successive price changes for a given security are independent, thenthere is no problem in timing purchases and sales of the security. A simple policy of buying and holding thesecurity will be as good as any more complicated mechanical procedure for timing purchase and sales. So, in allwe can say that stock market is increasingly becoming one of the most popular investments outlet in recenttimes due to its high returns and the market has gradually become an integral part of the global economy to theextent that any fluctuation in this market influences personal and corporate financial lives as well as theeconomic health of a country. Furthermore, the stock market is crucial to the nation’s economic developmentbecause it, along with other functions, performs the vital function of financial intermediation in the economy bytaking money from the surplus units in the economy and channeling same to the required units in the economy.However, the ability of the stock market to perform its role effectively and assure investors of fair returns iscontingent on the extent to which it can be said to be efficient. This underscores the essence of studies that seekto test stock market efficiency. If a market is not efficient then, stocks that outperform the market will inspirepositive sentiments among investors while stocks that under-perform may induce panic. Consequently, stocksthat under-perform at any given point in time relative to the market are more sensitive to new information(Lulia, 2009). In other words, there is a negative relationship between the measure of price sensitivity to newsand the stock’s performance relative to the market. On the other hand, panic drives the price sensitivity to newwww.iosrjournals.org28 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Marketinformation than the thrill of investing in a high-return stock does, or simply yet, the downside hurts investorsmore than the upside helps them (Lulia, 2009).The Efficient Market Hypothesis (EMH) provides that the stocks always trade at their fair value onstock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks forinflated prices . As such, it should be impossible to outperform the overall market through expert stock selectionor market timing as the information is disseminated to all. The assets price is reflective of all the availableinformation available and anticipated risk. The only way an investor can possibly obtain higher returns is bypurchasing riskier investments. The Random Walk Model asserts that all price changes are serially independent,which implies that future price changes are independent of past price changes. Samuelson (1965) and Fama(1970) indicates that the EMH supposes that share price adjust rapidly to the appearance of new information,and thus, current prices fully reflect all available information and should follow a random walk process (Awadand Daraghma, 2009). The levels of market efficiency was provided by Fama (1971), who argued that marketscould be efficient at three levels, based upon what information was reflected in prices.In this context ,the present paper makes an earnest attempt to analyze the weak form market efficiencybased on the theory of Efficient Market Hypothesis (EMH) (Fama1965).,.In this the efficiencies of various topautomobile and IT companies of India is tested in this study. The closing stock prices of these companies aretaken from NSE (National Stock Exchange) and are then passed through necessary statistical tool to obtainwhether successive price change is independent or not. The whole research is being carried out keeping in mindto draw the efficiency of the Indian Stock Market at weak form with the help of movement of the closing stockprices over a period of time.II.Review Of LiteratureTo test the weak form efficiency of Indian stock market there are various kinds of studies that had beenconducted and some of them are given bySharma and Kennedy (1977) compared the behavior of stock indices of the Bombay, London and NewYork stock exchanges during 1963-73 using run test and spectral analysis. Both test confirmed the randommovement of stock indices for all the three stock exchanges. They concluded that stocks on the BSE (BombayStock Exchange) follow random walk and are weak- form efficient.Ramachandran (1986) tested for the weak - form of Efficient Market Hypothesis using weekend pricesof 60 scrips over the period 1976-81. He used filter rule tests in addition to runs test and serial correlation testsand found support for the weak - form of EMH.Yalawar (1988) conducted an intensive study on the efficiency of BSE (Bombay Stock Exchange). Hestudied the month end closing prices of 122 stocks listed on the BSE during the period 1963-82. He used onlythe non-parametric tests, Spearman’s rank correlation test and found the behaviour of stock prices to be random.Poshakwale (1996) focused on the accelerating trend of investment in the stock market. He analyzedthe weak form efficiency and day of the week effect on the Bombay Stock Exchange (BSE) using daily BSENational Index Data for the period 1987 to 1994. His study reveals that BSE supports the validity of day of theweek effect and the Indian stock market is weak - form inefficient.Seiler and Walter (1997) examined the degree of random walk. He analyzed the historical returns of allthe stocks listed on the New York Stock Exchange (NYSE) from February 1885 to July 1962. His studyconcludes that changes in historical prices are completely random and this conclusion is consistent with modernefficient market studies.Keasey and Mobarek (2000), in their paper investigated the weak-form efficiency of an emergingmarket by taking evidence from Dhaka Stock Market of Bangladesh over the period 1988 to 1997 by employingboth parametric and non parametric tests. The study reveals that Dhaka Stock Market of Bangladesh is weak form inefficient.Pandey (2003) analyzed the efficiency of the Indian stock markets by using three Indian stock indicesto test the efficiency level in Indian stock market and the random walk nature of the stock market by using theruns test and the Auto Correlation Function ACF (K) for the period from January 1996 to June 2002. The studyfound that the series of stock indices in the Indian stock market biased the random time series and do notconfirm the Random Walk Theory.Sharma et al. (2009) examined the weak-form efficiency of eleven (11) securities listed on the BSEusing weekly data from July 2007 to October 2007 by employing runs test and auto-correlation tests. The studyconcludes that the BSE is weak-form efficient and the stock prices are having very scrimpy effect on futureprices which implies that an investor cannot reap out abnormal profits as the current share prices already reflectthe effect of past share prices.Pradhan et al. (2009) in their paper tried to examine the Efficient Market Hypothesis (EMH) in its weak- form by employing the unit root test on the sample of daily stock returns of National Stock Exchange (NSE)www.iosrjournals.org29 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Marketand Bombay Stock Exchange (BSE). The sample period lies between Jan. 2007 to Jul. 2009. The study revealsthat Indian Stock market is not weak - form efficient.Chigozie and Okpara (2009) examined the efficiency of Nigerian Stock Market over the period 1984 to2006 by employing an advance test viz; GARCH (Generalized Autoregressive Conditional Hetroscedasticity)Model. The study reveals that Nigerian Stock market is weak form efficient. The result agrees with the findingsof Samuels and Yacout (1981), Ayadi (1984), Olewe (1999) and Kukah (2007).III.Objectives Of Study To find out whether the past prices of the stock are reflected on the future priceTo find out whether the weak form of efficient market holds true or not Period of study is from 1st January 2014 to 31st March 2014The stock prices were taken from the NSE (National Stock Exchange)Four companies each from Automobile Industry and IT industry has been selectedThe sources of data for the research paper are mainly secondary which is collected from the websites,documents, which are in printed form like annual reports etc.IV.Research MethodlogyV.Research Plan5.1. Hypothesis testing:While studying the efficient market hypothesis, hypothesis testing has been taken into account. Thehypothesis which is tested under the assumption that it is true is called null hypothesis and is denoted by H0.The hypothesis which differs from a given null hypothesis, H0 and is accepted when H0 is rejected is called analternative hypothesis and is denoted by H1.Thus, in context of this research we have,H0: Past prices are not reflected on the present prices.H1: Past prices are reflected on the present prices.5.2. Data Analysis method:The study seeks to test the efficient market hypothesis, by employing Runs Test. Runs Test is a nonparametric test, which is used to test the randomness of the series which auto correlation fails to do. Runs Test isa traditional method used in the random walk model and ignores the properties of distribution. It has been usedto judge the randomness in the behaviour of Indian Stock market.In runs test we consider a series of price changes over a certain period of time and each price change iseither designated as a plus ( ) if it is an increase in price or a minus(-)if it is a decrease in price. A run existwhen two consecutive changes are the same (i.e., or--). When price changes in a different direction, such as -or- The run ends and a new run may begin .To test for independence, the number of runs for a given seriesof price changes are compared with the number of runs for a given series of price changes compared with thenumber in a table of expected values for the number of runs that should occur in a random series.To test the independence of the prices, we require:Total Number of Runs:Number of Positive Price Changes:Number of Negative Price Changes:(r)(n1)(n2)Once we have the data, the mean and the standard deviation of the mean are calculated by using the formulagiven below:Mean,µ(r) :(1)Standard deviation, σ(r) (2)5.3Level of significance:To test the weak form of efficiency of the stock market ,the Runs Test is applied at 5% significancelevel where z 1.96www.iosrjournals.org30 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Market5.4 Calculating lower limit and upper limit:Here,Lower limit :{ µ-1.96*(σ)}Upper limit :{ µ 1.96*(σ)}Where µ meanσ standard deviationVI.(3)(4)Data AnalysisTable 1 showing the Result of Hypothesis testing:Company’sNameEICHER MOTORSASHOK INDRA andMAHINDRATATA 1.703.8639.2624.1334VII.Hypothesistesting at a givenlevel ofsignificanceH0 acceptedH0acceptedH0acceptedRuns Test AnalysisTable 2 showing the monthly closing stock value and applied runs test of EICHER MOTORSDate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb2014Closing 04899.904901.80Price change Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421th mar201422st mar201424nd mar201425th mar201426th mar201427th mar201428th mar201431st mar2014www.iosrjournals.orgClosing 155832.055961.50Price change 31 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Market21 st feb201424 th feb201425 th feb20144884.004820.204916.15 Evaluation of EICHER MOTORS:Total runs (r) 30Number of positive changes (n1) 29Number of negative changes (n2) 33Mean (µ) 31.87Standard deviation (σ) 3.80Upper limit 39.31Lower limit 24.42Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance ( H0 is accepted.Thus, the market is weakly efficient.Table 3 showing the monthly closing stock value and applied runs test of ASHOK LEYLANDDate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425 th feb2014Closing 015.50Price change -Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar 201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421th mar201422st mar201424nd mar201425th mar201426th mar201427th mar201428th mar201431st mar2014Closing 22.6022.1022.8523.65Price change Evaluation of ASHOK LEYLAND:Total runs (r) 30Number of positive changes (n1) 29Number of negative changes (n2) 30Total mean (µ) 30.49www.iosrjournals.org32 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock MarketStandard deviation (σ) 3.80Upper limit 37.93Lower limit 23.04Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance (H0 is accepted).Thus, the market is weakly efficientTable 4 showing the monthly closing stock value and applied runs test of MAHINDRA AND MAHINDRADate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425th feb2014Closing .40928.10935.15943.20929.95930.00944.10943.90Price change -Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201422th mar201422nd mar201424nd mar201425th mar201426th mar201427th mar201428th mar201431st mar2014Closing ce change Evaluation of MAHINDRA AND MAHINDRA:Total run (r) 34Number of positive price changes (n1) 33Number of negative price changes (n2) 29Mean (µ) 31.87Standard deviation (σ) 3.88Upper limit 39.47Lower limit 24.26Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance (H0 is accepted).Thus, the market is weakly efficient.www.iosrjournals.org33 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock MarketTable 1.5 showing the monthly closing stock value and applied runs test analysis of TATA MOTORSDate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425 th feb2014Closing .15194.50195.80195.00194.05196.05196.40194.70Price change -Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421st mar201422nd mar201424th mar201425th mar201426th mar201427th mar201428th mar201431st mar2014Closing 0190.70190.25190.35194.50194.20196.30202.40Price change Evaluation of TATA MOTORS:Total runs(r) 36Number of positive price changes (n1) 34Number of negative price changes (n2) 28Mean (µ) 31.70Standard deviation (σ) 3.86Upper limit 39.26Lower limit 24.13Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance (H0 is accepted).Thus, the market is weakly efficient.Table 6 showing the monthly closing stock value and applied runs test analysis of Tata Consultancy ServicesDate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan2014Closing 1.952280.90Price change Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar2014www.iosrjournals.orgClosing 8.502142.65Price change -34 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Market13 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425 th .952189.352205.702177.902188.9011th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421st mar201422nd mar201424th mar201425th mar201426th mar201427th mar201428th mar201431st mar2014 33.15 Evaluation of TCS:Total runs(r) 30Number of positive runs (n1) 30Number of negative runs (n2) 31Mean (µ) 31.5Standard deviation (σ) 3.87Upper limit 39.08Lower limit 23.91Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance (H0 is accepted).Thus, the market is weakly efficient.Table 7 showing the monthly closing stock value and applied runs test analysis of TECH MAHINDRADate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan2014Closing .701828.651842.151830.651793.55Price change -Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421st mar201422nd mar201424th mar2014www.iosrjournals.orgClosing .501822.151808.951819.651844.30Price change 35 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Market27 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425 th 1.451839.60 25th mar201426th mar201427th mar201428th mar201431st mar20141828.801815.351833.451836.751795.35 -Evaluation of TECH MAHINDRA:Total runs(r) 41Number of positive price changes (n1) 31Number of negative price changes (n2) 31Mean (µ) 32Standard deviation (σ) 3.90Upper limit 39.64Lower limit 24.35Inference:Since the Observed number of runs doesn’t falls within the upper and the lower limit, we can concludethat that the prices are not independent at 5% level of significance ( H1 is accepted)Thus, the market is weakly inefficient.Table 8 showing the monthly closing stock value and applied runs test analysis of INFOSYSDate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb2014Closing 53573.803596.25Price change Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421st mar201422nd mar201424th mar201425th mar201426th mar201427th mar201428th mar201431st mar2014www.iosrjournals.orgClosing 053262.603282.80Price change 36 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock Market12 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425 th 711.253750.703749.903782.90 Evaluation of INFOSYS:Total runs(r) 25Number of positive price changes (n1) 36Number of negative price changes (n2) 26Mean (µ) 31.19Standard deviation (σ) 3.80Upper limit 38.63Lower limit 23.74Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance (H0 is accepted).Thus, the market is weakly efficient.Table 9 showing the monthly closing stock value and applied runs test analysis of Persistent TechnologiesDate1st jan20142 nd jan20143 rdjan20146 th jan20147 th jan20148 th jan20149th jan 201410 th jan201413 th jan201414 th jan201415 th jan201416 th jan201417 th jan201420 th jan201421 st jan201422 nd jan201423 th jan201424 th jan201427 th jan201428 th jan201429 th jan201430th jan201431st jan20143rd feb20144 th feb20145 th feb20146 th feb20147 th feb201410 th feb201411 th feb201412 th feb201413 th feb201414 th feb201417 th feb201418 th feb201419 th feb201420 th feb201421 st feb201424 th feb201425 th feb2014Closing 124.601151.30Price change Date26 th feb201428th feb20143rd mar20144th mar20145th mar20146th mar20147th mar201410th mar201411th mar201412th mar201413th mar201414th mar201418th mar201419th mar201420th mar201421st mar201422nd mar201424nd mar201425th mar201426th mar201427th mar201428th mar201431st mar2014www.iosrjournals.orgClosing 501041.701049.45Price change 37 Page
Testing of Efficient Market Hypothesis: a study on Indian Stock MarketEvaluation of PERSISTENT TECHNOLOGIES:Total runs(r) 34Number of positive changes (n1) 34Number of negative changes (n2) 28Mean (µ) 31.7Standard deviation (σ) 3.86Upper limit 39.26Lower limit 24.13Inference:Since the Observed number of runs falls within the upper and the lower limit, we can conclude that thatthe prices are independent at 5% level of significance (H0 is accepted).Thus, the market is weakly efficient. VIII.LimitationsThe findings are on the basis of run test hence findings are subject to the limitation of non parametric testFindings are applicable in the situations
that Indian Stock market is not weak - form efficient. Chigozie and Okpara (2009) examined the efficiency of Nigerian Stock Market over the period 1984 to 2006 by employing an advance test viz; GARCH (Generalized Autoregressive Conditional Hetroscedasticity) Model. The study reveals that Nigerian Stock market is weak form efficient.
Detection and Hypothesis testing Rejecting a hypothesis aka detection H 0: The \null" hypothesis i.e., the hypothesis that the data might allow you to reject H 1: The alternate hypothesis Example: H 0: Average IQ of Group1 subjects Group2 subjects H 1: Average IQ of Group1 subjects Group2 subjects Given data we wish to probabilistically test out the hypotheses
The Efficient Market Hypothesis CHAPTER 8 8.1 RANDOM WALKS AND THE EFFICIENT MARKET HYPOTHESIS Efficient Market Hypothesis (EMH) Do security prices reflect information Why look at market efficiency –Implications for business and corporate finance –Implications for investm
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inclusion in the sample. Johan A. Elkink hypothesis testing. Statistical inference Point estimation . Johan A. Elkink hypothesis testing. Statistical inference Point estimation Confidence intervals Hypothesis tests Bayesian inference Terminology Aparameteris a characteric of the population distribution (e.g. . large. Johan A. Elkink .
7. Know that your hypothesis may change over time as your research progresses. You must obtain the professor's approval of your hypothesis, as well as any modifications to your hypothesis, before proceeding with any work on the topic. Your will be expressing your hypothesis in 3 ways
Cover photo: Yasgur farm, Woodstock, New York revision date 15 JULY 2009 HYPOTHESIS TESTING COMPARED TO JURY TRIALS 3 COMPARISONS BETWEEN HYPOTHESIS TESTS AND JURY DECISION-MAKING General Specific Example Criminal Trial Null Hypothesis H0
