This document summarizes a research study that tested for weak-form market efficiency in Saudi Arabia's stock market between 2006 and 2012. It used unit root tests, autocorrelation tests, and runs tests on daily closing prices for the overall market index and 11 sector indices. The tests confirmed weak-form efficiency for the overall market and all sector indices, indicating that past price movements could not be used to predict future prices. This adds to the limited existing literature on market efficiency in emerging Gulf markets like Saudi Arabia.
Study of volatility_and_its_factors_on_indian_stock_marketKarthik Juturu
The document discusses factors that contribute to volatility in the Indian stock market. It identifies several macroeconomic variables like geopolitical tensions, energy prices, inflation, interest rates, and government/RBI policies that create uncertainty and affect company valuations. It also notes that volatility has increased in recent years due to factors like increased financial leverage of companies. The main objective is to analyze the causes of stock market volatility in India and understand how the market reacts to different influences.
The document provides information about capital markets. It discusses the primary and secondary markets. The primary market deals with new security issues, while the secondary market allows for the buying and selling of previously issued securities through stock exchanges. It also outlines various types of capital market instruments like stocks and bonds, as well as risks associated with investing in both the stock and bond markets like price volatility and interest rate risk. Capital market reports like annual 10-K, quarterly 10-Q and Form 8-K provide information to investors. Individuals and institutions can invest in capital markets through both the stock and bond markets.
The document discusses commodity markets in India. It provides background on the history and development of commodity exchanges in India, including some of the earliest organized futures markets in cotton, oilseeds, and wheat dating back to the late 19th century. It then describes the major participants in commodity markets, including hedgers who use futures markets to manage price risk, speculators who trade based on price expectations, and arbitrageurs.
This document analyzes the relationship between stock market liquidity and stock returns in 27 emerging equity markets from January 1992 to December 1999. It finds that stock returns are positively correlated with measures of market liquidity, including turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses. This relationship holds even after controlling for other factors and contrasts with theories supported by studies of developed markets, where liquidity and returns are negatively correlated. The findings suggest emerging markets have a lower degree of integration with the global economy.
Summer training project report on fluctuation of indian stock marketshailehpalrecha
This document is a summer training project report submitted by Rahul Jajoo to the Rajasthan Technical University. The report studies the fluctuations of the Indian stock market over the past two years under the supervision of Prabath Financial Services Limited. The objective is to understand the factors affecting stock prices and market trends to help investors make informed decisions. The report includes research methodology, analysis of market fluctuations, and conclusions about how this impacts the Indian economy.
Measuring the volatility of foreign exchange market in indiaAlexander Decker
This document summarizes a research study measuring the volatility of foreign exchange rates in the Indian market. The study analyzes daily exchange rate data for the US dollar, euro, and Japanese yen against the Indian rupee over time. The objectives are to measure the volatility of these currencies, examine their co-movement, analyze the volatility distribution, and measure skewness and kurtosis. Hypotheses are tested regarding the normality of volatility distributions. The results could help manage foreign exchange risk more effectively in India's increasingly globalized economy.
11.[28 38]distribution of risk and return a statistical test of normality on ...Alexander Decker
This document summarizes a research study that examined the normal distribution of risk and return on the Dhaka Stock Exchange in Bangladesh. The study used statistical tests to analyze daily, weekly, and monthly returns calculated from three DSE indices from 2002 to 2010. The results found evidence of skewness and kurtosis in the returns, indicating they were not normally distributed and contradicting the assumption of random walk behavior required for an efficient market. Additionally, inconsistencies were found between daily and weekly risk and return, suggesting higher returns may be possible without higher risk. The study aims to contribute to evaluating market efficiency and the relationship between risk and return in the Bangladesh capital market.
Study of volatility_and_its_factors_on_indian_stock_marketKarthik Juturu
The document discusses factors that contribute to volatility in the Indian stock market. It identifies several macroeconomic variables like geopolitical tensions, energy prices, inflation, interest rates, and government/RBI policies that create uncertainty and affect company valuations. It also notes that volatility has increased in recent years due to factors like increased financial leverage of companies. The main objective is to analyze the causes of stock market volatility in India and understand how the market reacts to different influences.
The document provides information about capital markets. It discusses the primary and secondary markets. The primary market deals with new security issues, while the secondary market allows for the buying and selling of previously issued securities through stock exchanges. It also outlines various types of capital market instruments like stocks and bonds, as well as risks associated with investing in both the stock and bond markets like price volatility and interest rate risk. Capital market reports like annual 10-K, quarterly 10-Q and Form 8-K provide information to investors. Individuals and institutions can invest in capital markets through both the stock and bond markets.
The document discusses commodity markets in India. It provides background on the history and development of commodity exchanges in India, including some of the earliest organized futures markets in cotton, oilseeds, and wheat dating back to the late 19th century. It then describes the major participants in commodity markets, including hedgers who use futures markets to manage price risk, speculators who trade based on price expectations, and arbitrageurs.
This document analyzes the relationship between stock market liquidity and stock returns in 27 emerging equity markets from January 1992 to December 1999. It finds that stock returns are positively correlated with measures of market liquidity, including turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses. This relationship holds even after controlling for other factors and contrasts with theories supported by studies of developed markets, where liquidity and returns are negatively correlated. The findings suggest emerging markets have a lower degree of integration with the global economy.
Summer training project report on fluctuation of indian stock marketshailehpalrecha
This document is a summer training project report submitted by Rahul Jajoo to the Rajasthan Technical University. The report studies the fluctuations of the Indian stock market over the past two years under the supervision of Prabath Financial Services Limited. The objective is to understand the factors affecting stock prices and market trends to help investors make informed decisions. The report includes research methodology, analysis of market fluctuations, and conclusions about how this impacts the Indian economy.
Measuring the volatility of foreign exchange market in indiaAlexander Decker
This document summarizes a research study measuring the volatility of foreign exchange rates in the Indian market. The study analyzes daily exchange rate data for the US dollar, euro, and Japanese yen against the Indian rupee over time. The objectives are to measure the volatility of these currencies, examine their co-movement, analyze the volatility distribution, and measure skewness and kurtosis. Hypotheses are tested regarding the normality of volatility distributions. The results could help manage foreign exchange risk more effectively in India's increasingly globalized economy.
11.[28 38]distribution of risk and return a statistical test of normality on ...Alexander Decker
This document summarizes a research study that examined the normal distribution of risk and return on the Dhaka Stock Exchange in Bangladesh. The study used statistical tests to analyze daily, weekly, and monthly returns calculated from three DSE indices from 2002 to 2010. The results found evidence of skewness and kurtosis in the returns, indicating they were not normally distributed and contradicting the assumption of random walk behavior required for an efficient market. Additionally, inconsistencies were found between daily and weekly risk and return, suggesting higher returns may be possible without higher risk. The study aims to contribute to evaluating market efficiency and the relationship between risk and return in the Bangladesh capital market.
This study investigates the impact of the introduction of index options on emerging market volatility in the context of Malaysia. Company specific daily closing prices for 29 listed companies were examined to determine the conditional volatility shifts before and after the introduction of index options. Multiple window periods are examined to avoid year-end effects.The exponential generalized autoregressive conditional heteroskedasticity (EGARCH) (1.1) model is used to determine the conditional volatility shift before and after the introduction of index options in Malaysia. The findings of this study suggest that the introduction of index options reduced market volatility in the Malaysia equity market at the 0.01 level of statistical significance. Further, this study contributed to extant literature because it uses company-specific daily equity price data and no such previous study exists on the impact of index options for this important emerging market. The study will be useful for academics, researchers, domestic and foreign investors and policy-makers, among others.
This document is a project report submitted as a requirement for an MBA degree. It analyzes selected commodities using fundamental and technical analysis. The objectives are to study the Indian commodity market, and analyze gold, silver, and copper. Fundamental analysis includes production, demand/supply, and volatility. Technical analysis uses charts and indicators. The scope is limited to metal indices on the commodity market. There are limitations due to the short time frame and that technical analysis is for the short-run while fundamental analysis is for long-run. The methodology includes collecting primary and secondary data, and presenting it using tables, charts and indicators to analyze the commodities.
This study examines how stock returns in the banking and textile industries in Pakistan vary with economic factors using a multifactor model. The results show that while market returns are the main driver of stock price changes, other macroeconomic and industry variables provide additional explanation of returns. Economic exposure is higher at the industry level than the firm level. Stock returns also respond differently to economic conditions depending on the individual firm.
Effect of equity derivatives trading on spot market volatility in indiaAlexander Decker
This document discusses a study examining the effect of equity derivatives trading on spot market volatility in India. It provides context on the growth of derivatives trading in India. The author reviews previous literature which has found mixed results on the impact of derivatives introduction on underlying volatility in other markets. Some studies found increased volatility, others found decreased volatility, and some found no significant impact. The present study aims to help resolve these inconsistent findings by analyzing the impact of equity derivatives introduction on spot market volatility in India, using statistical models to account for asymmetric responses to news.
This document is a research proposal that aims to investigate the efficiency of the Ghana Stock Exchange through various statistical tests and analyses of time series properties. Specifically, it will examine forms of efficiency, factors associated with efficiency, how efficiency evolves over time, and stochastic properties. The study is justified because understanding an emerging market's efficiency is important for attracting investment and facilitating economic growth. The proposal provides background on definitions of market efficiency and cites several references to situate the research in the relevant literature.
Stock return and volatility evidence from indian stock marketROHITH U J
The risk appetite of investors governs their investment in financial instruments. Persons who are minimum risk takers with return generally park their money in secure instruments but people with a higher risk appetite generally invest in a stock market financial instrument to achieve their financial goal. Investors with a higher risk appetite have to measure the market performance in the basis of risk and return so that they can alter their portfolio to keep pace with current market movement. In this research intended to study risk in terms of standard deviation and beta of all sectoral indices of NSE with respect to nifty and their performance in different time horizon and ranked them accordingly in terms of mean return and found out the best performing sector in a given time frame
Index Effects on Stock Prices: Evidence from India,
Bid-Ask Spreads in Emerging Markets: Evidence from
The document discusses a study on the technical analysis of the S&P CNX Nifty Index in India. It introduces the Nifty Index and the importance of studying its price movements. It outlines the objectives to compare Nifty prices from 2003-2007 and analyze short and long term moving averages. The methodology involves using secondary data from the National Stock Exchange and statistical tools like trend analysis and moving averages. The study aims to help investors better understand market trends and determine when to buy and sell securities.
The document discusses the relationship between stock markets and economic growth in India. It notes that developed stock markets can help promote economic growth by increasing savings and capital formation, improving capital allocation, and reducing the cost of capital. The document then provides background on India's stock markets, including the Bombay Stock Exchange and National Stock Exchange. It states that studies have examined the informational efficiency of stock markets by analyzing the causal relationships between stock prices and macroeconomic variables.
This project report summarizes a study on the currency futures market in India conducted by two MBA students, Milan Adodariya and Khima Goraniya, at Anagram Capital as part of their summer training. The report includes an introduction, literature review, research methodology, data collection and analysis sections. It also provides an overview of the foreign exchange market, history of currency futures in India, company and industry profiles, findings from surveys conducted, and conclusions.
Dynamics of currency futures trading and underlying exchange rate volatility ...Alexander Decker
This document summarizes a research paper that examines the impact of currency futures trading on exchange rate volatility of the euro in India after currency futures were introduced in 2010. The paper uses daily exchange rate data from 2008 to 2011 and unit root and ARCH LM tests to analyze time series properties. It then employs a GJR GARCH model to study the impact on underlying volatility. The results indicate that currency futures trading had no impact on spot exchange rate volatility in India's foreign exchange market. It also found that recent news has a greater impact on spot market volatility while the influence of older news has declined since futures trading began.
Factors affecting stock market prices in amman stock exchangeAlexander Decker
This document summarizes a study that examined factors affecting stock market prices on the Amman Stock Exchange. The study used surveys to collect data on how internal factors like dividend policy, firm size, management quality, and financial situation impact stock prices. It found that inflation had the most impact on prices, while the nature of the firm's business had the least. The study recommended that companies get more involved in drafting laws and regulations to strengthen their role in the stock market.
The document is a report submitted by Mayank Pandey to the Bank of Baroda as part of a summer training project on studying the Indian stock market. It includes sections on the research methodology used, an overview of key entities like SEBI and stock exchanges, current trends in the Indian economy and stock market, analysis of foreign exchange and commodity markets, and a conclusion with suggestions. The report provides information on the structure and functioning of the Indian capital markets for new investors.
The document discusses the influence of selected industries on the risk behavior of the Philippine Stock Exchange Composite Index (PSEi). It aims to identify industry sectors that affect the PSEi, evaluate the riskiness of the PSEi based on movements in industry indices using regression analysis, and assess the impact of political administrations on PSEi behavior. Regression results show that property, industrial, financial and oil industry sectors significantly influence the PSEi, except for mining. The model closely predicted PSEi behavior using sectoral index behavior. Political environment was also found to impact PSEi performance.
This document is Vishal Nabde's dissertation submitted to Mumbai University for his Masters in Management Studies degree. It examines the topic of technical analysis. The dissertation includes declarations, acknowledgements, a table of contents, and 10 chapters that will analyze technical analysis tools and indicators and apply them to study the stock of Power Grid. It aims to understand how technical analysis can be used to predict short-term stock price movements.
“Technical analysis” a study on selected stocksBozo All
The document discusses technical analysis and its use in analyzing stocks. It provides an overview of technical analysis, including that it uses historical price and volume data to identify trends and patterns in order to predict future price movements. It also notes that technical analysis assumes markets are primarily psychological rather than logical. The document then discusses various technical analysis tools and methods, such as candlestick techniques and Dow theory. It concludes by noting that economists have traditionally been skeptical of technical analysis due to theories of efficient markets.
Impact of MacroEconomic Variables on National Stock ExchangeWaquar Khan
- The document is a project guide that analyzes the impact of macroeconomic variables like inflation and exchange rates on India's National Stock Exchange.
- It outlines the profile and purpose of NSE, describes the CNX Nifty index, and explains the research methodology used involving regression analysis.
- The analysis finds that inflation has a negative influence on NSE returns while exchange rates have a positive influence, with R-squared being 43.8%. It concludes there is a significant relationship between macroeconomic factors and stock market performance.
The document provides a summary of initial public offerings (IPOs) on the Tokyo Stock Exchange in the first quarter of 2016. There were 24 IPOs in total raising $1.2 billion, making Tokyo Stock Exchange the third largest globally by IPO amount during this period. The majority (54%) of IPOs were on the Mothers market. Information technology companies represented the largest sector with 8 IPOs (35%).
The document provides an introduction to commodity futures markets. It defines key terms related to commodity trading such as futures contracts, arbitrage, contango, clearinghouses. It also summarizes the history and development of commodity markets in India, including the present regulatory structure with the Forward Markets Commission overseeing three national commodity exchanges.
Technical analysis a study on selected stocks conducted at religare securit...Projects Kart
Technical analysis is a method of evaluating securities such as stocks by analyzing statistics generated from market activity, like prices and trading volume. Technical analysts believe historical patterns in prices and volumes can help predict future price movements. The document discusses various technical analysis tools like charts, indicators, and patterns that analysts use to identify trends and make predictions. It also outlines some key assumptions of technical analysis, such as the idea that stock prices already reflect all publicly available information.
An empirical investigation on the financial integration between arab countrie...Alexander Decker
This document summarizes a study that examines the level of financial integration between the stock markets of European Union countries and Arab countries using the Johansen cointegration approach. The study analyzes monthly stock price index data from May 2005 to January 2011 for the two regions. The results show that when the Arab market index is the dependent variable, there is evidence of cointegration and long-run relationship between the EU and Arab markets. However, when the EU index is the dependent variable, the null hypothesis of no cointegration cannot be rejected, suggesting the markets are not integrated in that case. Therefore, the study finds the markets are moving together when Arab markets lead but not when EU markets lead.
Efficient Market Hypothesis (EMH) and Insider TradingPrashant Shrestha
The document discusses the Efficient Market Hypothesis (EMH) and different forms of market efficiency as it relates to insider trading. It provides an overview of the EMH, including its historical development and Fama's definitions of weak, semi-strong, and strong forms of market efficiency. Weak-form refers to efficiency based on past prices or returns. Semi-strong incorporates all public information. Strong-form suggests all private information is also reflected in prices. Evidence against full market efficiency is also presented.
This study investigates the impact of the introduction of index options on emerging market volatility in the context of Malaysia. Company specific daily closing prices for 29 listed companies were examined to determine the conditional volatility shifts before and after the introduction of index options. Multiple window periods are examined to avoid year-end effects.The exponential generalized autoregressive conditional heteroskedasticity (EGARCH) (1.1) model is used to determine the conditional volatility shift before and after the introduction of index options in Malaysia. The findings of this study suggest that the introduction of index options reduced market volatility in the Malaysia equity market at the 0.01 level of statistical significance. Further, this study contributed to extant literature because it uses company-specific daily equity price data and no such previous study exists on the impact of index options for this important emerging market. The study will be useful for academics, researchers, domestic and foreign investors and policy-makers, among others.
This document is a project report submitted as a requirement for an MBA degree. It analyzes selected commodities using fundamental and technical analysis. The objectives are to study the Indian commodity market, and analyze gold, silver, and copper. Fundamental analysis includes production, demand/supply, and volatility. Technical analysis uses charts and indicators. The scope is limited to metal indices on the commodity market. There are limitations due to the short time frame and that technical analysis is for the short-run while fundamental analysis is for long-run. The methodology includes collecting primary and secondary data, and presenting it using tables, charts and indicators to analyze the commodities.
This study examines how stock returns in the banking and textile industries in Pakistan vary with economic factors using a multifactor model. The results show that while market returns are the main driver of stock price changes, other macroeconomic and industry variables provide additional explanation of returns. Economic exposure is higher at the industry level than the firm level. Stock returns also respond differently to economic conditions depending on the individual firm.
Effect of equity derivatives trading on spot market volatility in indiaAlexander Decker
This document discusses a study examining the effect of equity derivatives trading on spot market volatility in India. It provides context on the growth of derivatives trading in India. The author reviews previous literature which has found mixed results on the impact of derivatives introduction on underlying volatility in other markets. Some studies found increased volatility, others found decreased volatility, and some found no significant impact. The present study aims to help resolve these inconsistent findings by analyzing the impact of equity derivatives introduction on spot market volatility in India, using statistical models to account for asymmetric responses to news.
This document is a research proposal that aims to investigate the efficiency of the Ghana Stock Exchange through various statistical tests and analyses of time series properties. Specifically, it will examine forms of efficiency, factors associated with efficiency, how efficiency evolves over time, and stochastic properties. The study is justified because understanding an emerging market's efficiency is important for attracting investment and facilitating economic growth. The proposal provides background on definitions of market efficiency and cites several references to situate the research in the relevant literature.
Stock return and volatility evidence from indian stock marketROHITH U J
The risk appetite of investors governs their investment in financial instruments. Persons who are minimum risk takers with return generally park their money in secure instruments but people with a higher risk appetite generally invest in a stock market financial instrument to achieve their financial goal. Investors with a higher risk appetite have to measure the market performance in the basis of risk and return so that they can alter their portfolio to keep pace with current market movement. In this research intended to study risk in terms of standard deviation and beta of all sectoral indices of NSE with respect to nifty and their performance in different time horizon and ranked them accordingly in terms of mean return and found out the best performing sector in a given time frame
Index Effects on Stock Prices: Evidence from India,
Bid-Ask Spreads in Emerging Markets: Evidence from
The document discusses a study on the technical analysis of the S&P CNX Nifty Index in India. It introduces the Nifty Index and the importance of studying its price movements. It outlines the objectives to compare Nifty prices from 2003-2007 and analyze short and long term moving averages. The methodology involves using secondary data from the National Stock Exchange and statistical tools like trend analysis and moving averages. The study aims to help investors better understand market trends and determine when to buy and sell securities.
The document discusses the relationship between stock markets and economic growth in India. It notes that developed stock markets can help promote economic growth by increasing savings and capital formation, improving capital allocation, and reducing the cost of capital. The document then provides background on India's stock markets, including the Bombay Stock Exchange and National Stock Exchange. It states that studies have examined the informational efficiency of stock markets by analyzing the causal relationships between stock prices and macroeconomic variables.
This project report summarizes a study on the currency futures market in India conducted by two MBA students, Milan Adodariya and Khima Goraniya, at Anagram Capital as part of their summer training. The report includes an introduction, literature review, research methodology, data collection and analysis sections. It also provides an overview of the foreign exchange market, history of currency futures in India, company and industry profiles, findings from surveys conducted, and conclusions.
Dynamics of currency futures trading and underlying exchange rate volatility ...Alexander Decker
This document summarizes a research paper that examines the impact of currency futures trading on exchange rate volatility of the euro in India after currency futures were introduced in 2010. The paper uses daily exchange rate data from 2008 to 2011 and unit root and ARCH LM tests to analyze time series properties. It then employs a GJR GARCH model to study the impact on underlying volatility. The results indicate that currency futures trading had no impact on spot exchange rate volatility in India's foreign exchange market. It also found that recent news has a greater impact on spot market volatility while the influence of older news has declined since futures trading began.
Factors affecting stock market prices in amman stock exchangeAlexander Decker
This document summarizes a study that examined factors affecting stock market prices on the Amman Stock Exchange. The study used surveys to collect data on how internal factors like dividend policy, firm size, management quality, and financial situation impact stock prices. It found that inflation had the most impact on prices, while the nature of the firm's business had the least. The study recommended that companies get more involved in drafting laws and regulations to strengthen their role in the stock market.
The document is a report submitted by Mayank Pandey to the Bank of Baroda as part of a summer training project on studying the Indian stock market. It includes sections on the research methodology used, an overview of key entities like SEBI and stock exchanges, current trends in the Indian economy and stock market, analysis of foreign exchange and commodity markets, and a conclusion with suggestions. The report provides information on the structure and functioning of the Indian capital markets for new investors.
The document discusses the influence of selected industries on the risk behavior of the Philippine Stock Exchange Composite Index (PSEi). It aims to identify industry sectors that affect the PSEi, evaluate the riskiness of the PSEi based on movements in industry indices using regression analysis, and assess the impact of political administrations on PSEi behavior. Regression results show that property, industrial, financial and oil industry sectors significantly influence the PSEi, except for mining. The model closely predicted PSEi behavior using sectoral index behavior. Political environment was also found to impact PSEi performance.
This document is Vishal Nabde's dissertation submitted to Mumbai University for his Masters in Management Studies degree. It examines the topic of technical analysis. The dissertation includes declarations, acknowledgements, a table of contents, and 10 chapters that will analyze technical analysis tools and indicators and apply them to study the stock of Power Grid. It aims to understand how technical analysis can be used to predict short-term stock price movements.
“Technical analysis” a study on selected stocksBozo All
The document discusses technical analysis and its use in analyzing stocks. It provides an overview of technical analysis, including that it uses historical price and volume data to identify trends and patterns in order to predict future price movements. It also notes that technical analysis assumes markets are primarily psychological rather than logical. The document then discusses various technical analysis tools and methods, such as candlestick techniques and Dow theory. It concludes by noting that economists have traditionally been skeptical of technical analysis due to theories of efficient markets.
Impact of MacroEconomic Variables on National Stock ExchangeWaquar Khan
- The document is a project guide that analyzes the impact of macroeconomic variables like inflation and exchange rates on India's National Stock Exchange.
- It outlines the profile and purpose of NSE, describes the CNX Nifty index, and explains the research methodology used involving regression analysis.
- The analysis finds that inflation has a negative influence on NSE returns while exchange rates have a positive influence, with R-squared being 43.8%. It concludes there is a significant relationship between macroeconomic factors and stock market performance.
The document provides a summary of initial public offerings (IPOs) on the Tokyo Stock Exchange in the first quarter of 2016. There were 24 IPOs in total raising $1.2 billion, making Tokyo Stock Exchange the third largest globally by IPO amount during this period. The majority (54%) of IPOs were on the Mothers market. Information technology companies represented the largest sector with 8 IPOs (35%).
The document provides an introduction to commodity futures markets. It defines key terms related to commodity trading such as futures contracts, arbitrage, contango, clearinghouses. It also summarizes the history and development of commodity markets in India, including the present regulatory structure with the Forward Markets Commission overseeing three national commodity exchanges.
Technical analysis a study on selected stocks conducted at religare securit...Projects Kart
Technical analysis is a method of evaluating securities such as stocks by analyzing statistics generated from market activity, like prices and trading volume. Technical analysts believe historical patterns in prices and volumes can help predict future price movements. The document discusses various technical analysis tools like charts, indicators, and patterns that analysts use to identify trends and make predictions. It also outlines some key assumptions of technical analysis, such as the idea that stock prices already reflect all publicly available information.
An empirical investigation on the financial integration between arab countrie...Alexander Decker
This document summarizes a study that examines the level of financial integration between the stock markets of European Union countries and Arab countries using the Johansen cointegration approach. The study analyzes monthly stock price index data from May 2005 to January 2011 for the two regions. The results show that when the Arab market index is the dependent variable, there is evidence of cointegration and long-run relationship between the EU and Arab markets. However, when the EU index is the dependent variable, the null hypothesis of no cointegration cannot be rejected, suggesting the markets are not integrated in that case. Therefore, the study finds the markets are moving together when Arab markets lead but not when EU markets lead.
Efficient Market Hypothesis (EMH) and Insider TradingPrashant Shrestha
The document discusses the Efficient Market Hypothesis (EMH) and different forms of market efficiency as it relates to insider trading. It provides an overview of the EMH, including its historical development and Fama's definitions of weak, semi-strong, and strong forms of market efficiency. Weak-form refers to efficiency based on past prices or returns. Semi-strong incorporates all public information. Strong-form suggests all private information is also reflected in prices. Evidence against full market efficiency is also presented.
Traditional methods to measure volatility case study of selective developed ...Alexander Decker
This document analyzes stock market volatility across developed and emerging markets from 1997-2009 using traditional measures like standard deviation. Key findings include:
- Returns for all markets showed non-normality, with emerging markets exhibiting more non-normality and higher kurtosis, indicating more peaked return distributions.
- Volatility, as measured by standard deviation, was highest for Turkey, Brazil, and China - all emerging markets. However, some developed markets were found to be more volatile than some emerging markets, suggesting volatility is not unique to emerging markets.
- The analysis concludes volatility should be measured using other methods like extreme value analysis due to the heavy-tailed distributions found in emerging market returns. This could provide better guidance for
1) The document examines the relationship between stock market liquidity and stock returns in 27 emerging markets from 1992 to 1999.
2) It finds that stock returns are positively correlated with measures of market liquidity such as turnover ratio, trading value, and turnover-volatility multiple, in both cross-sectional and time-series analyses.
3) This positive correlation between returns and liquidity in emerging markets differs from theories and findings in developed markets, and may be due to emerging markets having a lower degree of integration with the global economy.
This document presents an empirical test of the informational efficiency hypothesis on the Moroccan stock market. It begins with a literature review on the efficient market hypothesis and the three forms of market efficiency: weak, semi-strong, and strong. The authors then test for weak-form efficiency on the Moroccan stock market using daily MASI index data from 2002-2022. They employ runs tests, autocorrelation tests, unit root tests, and variance ratio tests. The results of all four tests show that the MASI index does not follow a random walk and reject the hypothesis of weak-form efficiency on the Moroccan stock market. The authors conclude that the Moroccan stock market is informationally inefficient in
This document summarizes the history and development of the concept of market efficiency. It discusses early works in the 1900s that anticipated the idea, and key studies in the 1950s-60s that developed the random walk model and market efficiency theory. Major topics covered include event studies in the late 1960s that provided empirical evidence; analysis in the 1960s-70s of mutual funds and managers that supported efficient markets; and anomalies identified starting in the 1970s that challenged aspects of efficiency. The document concludes by noting the ongoing debate between the efficient market framework and behavioral theories to explain anomalies.
Testing the Weak–Form Market Efficiency on the Borsa Istanbul (BIST) Sustaina...inventionjournals
An efficient market is a concept discussed and maintained in the financial literature. This concept expressed as the instant reflection of all the information concerning the stocks defends that there shouldn’t be any stocks that are low or overvalued on the market. The purpose in this study is the weak-form efficiency of stock market in Turkey to be analyzed with the help of Runs Test. In the research, daily session closing prices of the stocks being currently traded in the Borsa Istanbul (Istanbul Stock Exchange) Sustainability Index within a 12–month period between the dates 01.12.2015 and 30.11.2016 have been employed and tested whether or not the consecutive price changes in said range of time were independent from each other. The fact that consecutive price changes were independent from each other has revealed that the Random Walk Hypothesis was not applicable in terms of the index examined. The outcome acquired contains findings that BIST stock market is not a weak–form efficient market.
Testing the Weak–Form Market Efficiency on the Borsa Istanbul (BIST) Sustaina...inventionjournals
An efficient market is a concept discussed and maintained in the financial literature. This concept expressed as the instant reflection of all the information concerning the stocks defends that there shouldn’t be any stocks that are low or overvalued on the market. The purpose in this study is the weak-form efficiency of stock market in Turkey to be analyzed with the help of Runs Test. In the research, daily session closing prices of the stocks being currently traded in the Borsa Istanbul (Istanbul Stock Exchange) Sustainability Index within a 12–month period between the dates 01.12.2015 and 30.11.2016 have been employed and tested whether or not the consecutive price changes in said range of time were independent from each other. The fact that consecutive price changes were independent from each other has revealed that the Random Walk Hypothesis was not applicable in terms of the index examined. The outcome acquired contains findings that BIST stock market is not a weak–form efficient market.
A Critical Review Of The Market Efficiency ConceptAaron Anyaakuu
This document provides a critical review of the concept of market efficiency through 3 key points:
1) It defines the different forms of market efficiency proposed by Malkiel and Fama (1970) - weak, semi-strong, and strong - and how each reflects stock prices based on certain information.
2) It highlights several empirical tests that have been conducted to examine market efficiency in its different forms, such as tests of the weak form in Pakistan and India, and a test of the semi-strong form in Australia. The results were mixed, with some supporting efficiency and others not.
3) It discusses differing views on market efficiency, with some arguing markets efficiently reflect information, while others point to anomalies and
REVIEW OF COMMODITY FUTURES MARKET EFFICIENCY AND RELATED ISSUES Karthika Nathan
The study of market efficiency in commodity futures markets is important to both the government and the producers/marketers in India. In this paper, we review
the available literature on commodity futures market efficiency and related issues viz. the effect of seasonality on commodity futures market efficiency, the
inflationary impact of commodity futures trading and the impact of commodity futures trading on spot market volatility. The review shows that the results
produced in available literature are often conflicting: the efficiency hypothesis is supported only for certain markets and only over some periods. Also there are
very few studies on microstructure and macroeconomic issues in commodity futures market, and integration with other international markets. This forms further
scope of research in this area.
The aim of this study is to assess the impact of stock market characteristics on African economic
growth. We perform a panel smooth threshold regression (PSTR) analysis developed by Gonzalez et al. (2005)
using two panels of African countries from 1990 to 2020 for the first panel and 2006 to 2020 for the second
panel. The findings indicate that there is a specific threshold above which the stock market has an impact on
economic growth, namely market size and asset turnover, both of which positively affect growth. Market
liquidity, on the other hand, has a negative impact on growth. Our main recommendations are to share market
liquidity between private investors and the government on the one hand, and to increase market liquidity on the
other
11.the theoretical considerations of financial markets integration the case o...Alexander Decker
The document discusses the theoretical considerations of financial market integration in Arab countries. It begins by defining financial market integration and reviewing different approaches to measuring integration. It then examines factors that have hindered integration among Arab markets, including their limited economic size and the dominance of oil exports. Efforts by Arab countries toward integration are also reviewed, such as the Arab League and plans for projects like the Arab Gas Pipeline. The results indicate that integration among Arab financial markets remains low due to challenges like differing levels of economic development and a history of agreements not being fully implemented. More work is still needed to achieve real integration.
Impact of macroeconomic variables on stock returnsMuhammad Mansoor
The document discusses the impact of macroeconomic factors on stock returns. It provides background information on financial markets, primary and secondary markets, and stock market returns. It then summarizes several empirical studies that have examined the relationship between macroeconomic variables like interest rates, inflation, GDP, exchange rates, and stock market returns in countries like Pakistan, Japan, Nigeria, and others. The studies found both positive and negative relationships between different macroeconomic factors and stock returns in various markets. The document aims to contribute to this area of research by examining the impact of macroeconomic variables on stock returns in the Pakistani stock market.
Stock market efficiency of pakistan stock exchange a review of literature fro...Fiaz Ahmad
This document contains the literature review on Stock market efficiency of Pakistan stock exchange from 1995 2018. This will be helpful for the Investors and the researchers as well
Co movements of u.s. eu and indian equity markets-portfolio diversification ...Alexander Decker
This document discusses research on the co-movements of equity markets in the US, EU, and India and the implications for international portfolio diversification. It provides an extensive literature review on previous research examining correlations and co-integration between developed and emerging stock markets. The literature review covers studies investigating the degree of integration between markets over time and how globalization has impacted opportunities for diversification. The present study aims to focus on the co-integration relationship between the American, European, and Indian equity markets.
Co movements of u.s. eu and indian equity markets-portfolio diversification ...Alexander Decker
This document discusses research on the co-movements of equity markets in the US, EU, and India and the implications for international portfolio diversification. It provides an extensive literature review on previous research examining the integration and correlations between developed and emerging stock markets over time. The literature review covers studies investigating the co-movement and integration patterns between markets in North America, Europe, Asia, and other regions. The present study aims to focus on the co-integration relationship between the American, European and Indian equity markets.
The research studies the impact of the exchange rate fluctuations of the local currency on the share dividends exchanged in the stock market, and stating whether there is a trace of the fluctuations occurring in the exchange rate on the fluctuations reflected on the stock returns in the stock market – during the political and economic crisis in Syria. The descriptive analytical approach was adopted to indicate whether there is any direct or indirect impact of fluctuations in the exchange rate of the pound (Lira) against the dollar on the exchange value of the Damascus Securities Exchange Index. The study community consists of all stock companies listed in Damascus Securities Exchange. It covers the total of 23 listed companies. It relied on the period from 1/7/2011 through 12/31/2013 to study the impact of exchange rate fluctuations on stock returns, where the crisis began on 18/03/2011, but reflections on economic life began to appear in mid-2011 when the severe fluctuations in the exchange rate and returns began as a result of lack of stability and economic siege Syria has been witnessing and the study stretched until the year 2013. The data is a sort of daily observations of each of the dependent and independent variable sending with 381 observations. The study reached the many results some of which include that there is an inverse weak between the Syrian pound exchange rate and Damascus Securities Exchange Index returns. The inefficiency of Damascus Securities Exchange Index on the weak level, where, as we have seen, this index is not subject to normal distribution and it is auto-correlated of the third degree and does not settle at the first level; instead, it settles at the first change.
The document discusses testing the weak form efficient market hypothesis for four stock market indexes: DFM, MSM 30, S&P/ASX 200, and Euro Stoxx 50. Statistical tests including descriptive statistics, run tests of randomness, and least squares regression were used.
The results showed that DFM and MSM 30 indexes failed the run test, indicating they do not follow random walks and are not weak form efficient. Meanwhile, the S&P/ASX 200 and Euro Stoxx 50 indexes passed the run test, showing they are weak form efficient. Additional least squares regression was used to confirm the run test results.
A study of the Ghana stock market performance before and after general electionsGabriel Abbam
This document summarizes a dissertation that studied the performance of Ghana's stock market before and after the country's last five general elections in 1992, 1996, 2000, 2004, and 2008. The study analyzed the Ghana Stock Exchange monthly indices from 1991 to 2009 using statistical tests to compare market performance in the years before and after elections. The study found a significant difference in market performance between pre- and post-election periods. However, comparing control years that did not include elections still showed significant differences, making it difficult to conclude that elections alone caused the changes in market performance. The dissertation provided background on Ghana's political system and history of general elections as well as the establishment and structure of the Ghana Stock Exchange.
Similar to Is the Saudi Stock Market Efficient? A case of Weak-form Efficiency (20)
Solution Manual For Financial Accounting, 8th Canadian Edition 2024, by Libby...Donc Test
Solution Manual For Financial Accounting, 8th Canadian Edition 2024, by Libby, Hodge, Verified Chapters 1 - 13, Complete Newest Version Solution Manual For Financial Accounting, 8th Canadian Edition by Libby, Hodge, Verified Chapters 1 - 13, Complete Newest Version Solution Manual For Financial Accounting 8th Canadian Edition Pdf Chapters Download Stuvia Solution Manual For Financial Accounting 8th Canadian Edition Ebook Download Stuvia Solution Manual For Financial Accounting 8th Canadian Edition Pdf Solution Manual For Financial Accounting 8th Canadian Edition Pdf Download Stuvia Financial Accounting 8th Canadian Edition Pdf Chapters Download Stuvia Financial Accounting 8th Canadian Edition Ebook Download Stuvia Financial Accounting 8th Canadian Edition Pdf Financial Accounting 8th Canadian Edition Pdf Download Stuvia
Economic Risk Factor Update: June 2024 [SlideShare]Commonwealth
May’s reports showed signs of continued economic growth, said Sam Millette, director, fixed income, in his latest Economic Risk Factor Update.
For more market updates, subscribe to The Independent Market Observer at https://blog.commonwealth.com/independent-market-observer.
In a tight labour market, job-seekers gain bargaining power and leverage it into greater job quality—at least, that’s the conventional wisdom.
Michael, LMIC Economist, presented findings that reveal a weakened relationship between labour market tightness and job quality indicators following the pandemic. Labour market tightness coincided with growth in real wages for only a portion of workers: those in low-wage jobs requiring little education. Several factors—including labour market composition, worker and employer behaviour, and labour market practices—have contributed to the absence of worker benefits. These will be investigated further in future work.
Seminar: Gender Board Diversity through Ownership NetworksGRAPE
Seminar on gender diversity spillovers through ownership networks at FAME|GRAPE. Presenting novel research. Studies in economics and management using econometrics methods.
Lecture slide titled Fraud Risk Mitigation, Webinar Lecture Delivered at the Society for West African Internal Audit Practitioners (SWAIAP) on Wednesday, November 8, 2023.
2. Elemental Economics - Mineral demand.pdfNeal Brewster
After this second you should be able to: Explain the main determinants of demand for any mineral product, and their relative importance; recognise and explain how demand for any product is likely to change with economic activity; recognise and explain the roles of technology and relative prices in influencing demand; be able to explain the differences between the rates of growth of demand for different products.
Understanding how timely GST payments influence a lender's decision to approve loans, this topic explores the correlation between GST compliance and creditworthiness. It highlights how consistent GST payments can enhance a business's financial credibility, potentially leading to higher chances of loan approval.
5 Tips for Creating Standard Financial ReportsEasyReports
Well-crafted financial reports serve as vital tools for decision-making and transparency within an organization. By following the undermentioned tips, you can create standardized financial reports that effectively communicate your company's financial health and performance to stakeholders.
BONKMILLON Unleashes Its Bonkers Potential on Solana.pdfcoingabbar
Introducing BONKMILLON - The Most Bonkers Meme Coin Yet
Let's be real for a second – the world of meme coins can feel like a bit of a circus at times. Every other day, there's a new token promising to take you "to the moon" or offering some groundbreaking utility that'll change the game forever. But how many of them actually deliver on that hype?
How Does CRISIL Evaluate Lenders in India for Credit RatingsShaheen Kumar
CRISIL evaluates lenders in India by analyzing financial performance, loan portfolio quality, risk management practices, capital adequacy, market position, and adherence to regulatory requirements. This comprehensive assessment ensures a thorough evaluation of creditworthiness and financial strength. Each criterion is meticulously examined to provide credible and reliable ratings.
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
Is the Saudi Stock Market Efficient? A case of Weak-form Efficiency
1. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
35
Is the Saudi Stock Market Efficient?
A case of weak-form efficiency
Batool Asiri1*
Hamad Alzeera2
1. Department of Economics and Finance, University of Bahrain, P O Box 32038, Bahrain
2. Superintendent, Banking Supervision, Central Bank of Bahrain, Bahrain
* E-mail of the corresponding author: batoolasiri@gmail.com
Abstract
The purpose of the paper is to test the weak-form market efficiency in Saudi Arabia's stock market, Tadawul
which is expected to follow a random walk. All share index and sectoral indices for daily closing prices in
Tadawul between October 15, 2006 and November 15, 2012 are collected. Unit root Dickey-Fuller test, Pearson
Correlation test, Durbin-Watson test and Wald-Wolfowitz runs-test are used as basic stochastic tests for a non-
stationarity of the daily prices for all the listed companies in the market, both overall and sector-wise. The four
tests confirmed the weak-form market efficiency in the Saudi stock market for All share prices and 11 individual
sectors. The findings are necessary for all investors in Saudi Arabia and the member states of the Gulf
Cooperation Council (GCC). Listed firms could also benefit from the findings by seeing the true picture of their
stock price. The finding is used as a basis for testing the market efficiency in the semi-strong form, which has
not yet been tested by any researcher. Accordingly, investors in the Saudi market are not expected to generate
abnormal returns simply by depending on past information and technical analysis. This paper will add value to
the literature of market efficiency in the emerging market and the GCC since it covers all the listed companies,
tests sector-wise, and covers an extended period of time. To confirm the weak-form efficiency in Saudi, the
study uses four tests and covers a long period of time during and after the financial crisis.
Keywords: Weak-form market efficiency, random walk hypothesis, unit root test, auto correlation, run test,
Kingdom of Saudi Arabia.
1. Introduction
Many studies have tested market efficiency in the developed markets. In the last two decades, studies in the
emerging markets started to follow suit. Most of these studies have tried to answer a simple question: Are share
prices moving randomly? However, empirical testing came up with mixed findings and different conclusions in
both developed and emerging markets. One view in support of the random walk hypothesis (RWH) is that stock
returns are following a random walk process and thus, it is not possible to predict their future movements based
on past information. The second view, in contrast, states that there is indeed a trend path in the stock returns and
that it is possible to predict the future price movements based on the history of prices. The dissimilar results
could depend on: (1) the tests that are used; (2) the markets under examination; (3) the type of sector and
industry examined, and (4) the time-frame for the study. The RWH which has been tested heavily on the weak-
form efficiency has obviously failed to prove the performance of equity markets worldwide. However,
developed markets have shown a higher degree of informational efficiency than emerging markets.
The market is said to be efficient when prices of securities reflect all relevant information (Fama, 1991).
Investors are freely obtaining new information which makes them, due to competition, immediately discount this
information into the price. In other words, there is no chance for an arbitrage opportunity that can be used to
make excess abnormal profits (Fama 1965). Efficient market hypothesis (EMH) was earlier developed by Fama
(1970) and Fama and French (1989) and later revised to identify three levels of efficiency, which differ in terms
of the type of information set reflected in the market. The weak form efficiency, which is the first level of EMH,
assumes the absence of predictability of time-series of security prices. This leads to the random walk theory
which claims that the prices are independent of each other and past movements or trends cannot be used to
predict future movements. Therefore, serial independence (i.e. no autocorrelation) for the set of share price
changes is a fundamental requirement for the market to follow a random walk. As Fama (1970) stated that all
types of "new" news, by definition, have to be "new and unpredictable", resulting in the unpredictability of
future stock prices. Both Samuelson (1965) and Fama (1970) indicated that the EMH supposes that the share
price adjusts instantaneously to new information. Hence, current prices should fully discount and reflect all
available information and ought to follow a random walk process, meaning that the successive returns are
independently and identically distributed. The second level is the semi-strong form efficiency where prices
reflect all past prices and the public information. The third level is the strong form efficiency where the share
price reflects all past, public and insider information.
2. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
36
EMH deals with the question of whether stock prices fully reflect the entire historical price. The simplest
random walk model, as shown in the following equation, states that the actual price equals the previous price
plus the realization of a random variable:
Pit = Pit-1 E(R) it εit
where:
Pit = Current stock price for firm i
Pit-1 = Last closing price to current time t-1
E(R)it = Expected return (price change) at time t, also called drift
εit = Random Error
Furthermore, according to the above equation, the expected return on a security is based on the available
information set at time t (φt), as argued by (Solnik, 1996): E (Rit | φt). The paper investigates informational
efficiency in the Saudi stock market for the period January 1, 2007 until October 30, 2012 at the general market
and sector levels. Its main purpose is to test the weak-form market efficiency through the random walk model.
Accordingly, if the question is answered, it can be decided whether the usage of technical analysis to forecast
and predict future price changes is of material benefit. The rationale for this study is that little research has
targeted countries from the Middle East and the stock exchanges in the GCC.1
The knowledge of how efficient a
stock market is and how it discounts and reflects the set of information into the market prices of the securities is
of central importance to users of the capital markets. Taking into account the economic growth, trade
liberalization, introduction of electronic trading, globalization and emergence of global markets; once the
behavior of the prices is determined, the easier it is to understand the market and the economy. Another
contribution of this study to the literature is the sectoral analysis of the Saudi Arabia, which has been limited to
only a few papers.
2. The Saudi Arabia Stock Exchange (TADAWUL)
The Saudi Stock Exchange (Tadawul) is the only stock exchange in the Kingdom of Saudi Arabia. Its trading
hours are 11:00AM to 3:30PM, Saturday to Wednesday and it is supervised by the Capital Market Authority
(CMA). Saudi joint stock companies had their beginnings in the mid-1930s, when the Arab Automobile was
established as the country's first joint stock company. The Saudi Stock Exchange emerged in the late 1970s
where the number of joint stock companies was increasing as a result of nationalization of foreign companies,
including banks. By 1975 there were about 14 public companies. The rapid economic expansion, beside the
nationalization of part of the foreign banks capital in the 1970s led to the establishment of a number of large
corporations and joint stock banks. The market remained informal until the early 1980s when the Saudi
government created a national stock market. In 1984, a Ministerial Committee composed of the Ministry of
Finance and National Economy, Ministry of Commerce and Saudi Arabian Monetary Agency (SAMA) was
formed to regulate and develop the market. SAMA was the government body charged with regulating and
monitoring market activities until the CMA was established in July 2003 under the Capital Market Law (CML)
by Royal Decree No. (M/30). The CMA is the sole regulator and supervisor of the capital market, it issues the
required rules and regulations to protect investors and ensure fairness and efficiency in the market. The Council
of Ministers approved on March 19, 2007, the formation of the Saudi Stock Exchange (Tadawul) Company. This
was in accordance with Article 20 of the Capital Market Law establishing Tadawul as a joint stock company.
Tadawul is organized into 15 sectors, each consisting of companies that have a common business line and
operate in the same industry. The market capitalization on October 4, 2011 was $315,521 million. In addition,
Tadawul All Share Index consists of all listed companies, as shown in table 1.
3. Previous Studies
Bachelier (1900) was the first to point out that security prices and prices of other speculative commodities follow
a random walk; this was later confirmed by Pearson (1905) and Working (1934). Kendall (1953) was the first
researcher to use the term "random walk" in the finance literature. Until the early 1950s, it was accepted that
technical analysis, could be used to examine the behavior of past prices and beat the market. Malkiel (1992)
McQueen et al (1996), Fama and French (1989), Al-Loughani and Chappell (1997), Seiler and Rom (1997), and
Abrosimova et al (2002) supported the assumption that price changes are random and past prices were not useful
in predicting future price.
Alexander (1964) and Fama and Blume (1966) used a filter rule, which gives a rule for buying and selling stocks
1
The Gulf Cooperation Council countries are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the Uunited
Arab Emerats.
3. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
37
depending on past price movements but found that such rule could not generate trading profits. Jensen (1968)
performed risk-adjusted measures and found that mutual funds do not outperform the market from 1945–1964.
Conrad and Kaul (1988) and Lo and MacKinlay (1988) examined the weekly returns of the NYSE stock and
both studies found that a positive serial correlation over short horizons, but one that is negligible and
insignificant. Lo and MacKinlay (1988) provide evidence that random walk model was strongly rejected in
NYSE-AMEX between 1962 and1985. However, Huber (1995) studied the Vienna Stock Market and rejected
the RWH. Kvedaras and Basdevant (2004) concluded that the Estonian, Latvian and Lithuanian Stock Exchange
Market, with some turbulence, approaching the weak form of efficiency.
Keim and Stambaugh (1986) found significant predictability in stock prices using forecasts based on certain
predetermined variables. Fama and French (1988) show that long holding-period returns are significantly
negatively serially correlated, implying that 25-40% of the variation of longer-horizon returns is predictable from
past returns. Balaban (1995) rejected the random walk on Istanbul Securities Exchange. Kompa and
Matuszewska-Janica (2009) examined the Warsaw Stock Exchange from 2000 to 2006 for the log daily returns.
The weak-form efficiency was found in the main market indexes as well as companies in the following sectors:
telecommunication, gas and oil, and metals. Medium-size company index was found to achieve abnormal returns.
Reviewing the Arab markets and the GCC, most of the studies used run test and serial correlation to examine the
RWH. Gandhi et al (1980) used monthly data for the period 1975-1978 for the Kuwait Stock Exchange and
found that RWH for the All Share and Industrial indices was rejected. Testing United Arab Emirates (UAE)
market, Ebid (1990) found that it is considered to be weak-form efficient. Butler and Malaikah (1992) analyzed
the behavior of the Kuwait and Saudi Arabia stock markets between 1985 and 1989 and they provided evidence
of weak-form inefficiency in both of the markets. However, they could not conclude if the Saudi market is
informationally inefficient. Civelek (1991) and El-Erian and Kumar (1995) studied the Amman Financial Market
and both got relatively frequent positive dependence. Al-Loughani (1995) used the weekly data for the Kuwait
Stock Exchange for 1986-1990 and found that autocorrelation and runs test were consistent with the RWH.
Khababa (1998) concluded that Saudi market is not weak-form efficient. Dahel and Laabas (1999) examined the
behavior of the daily stock prices over the period 1994-1998 in the Gulf markets: Bahrain, Kuwait, Saudi Arabia
and Oman. They concluded that Kuwait Stock Market is the only efficient market and is strongly in support of
the concepts of the RWH. Abraham et al (2002) used weekly data for All Share indices of Saudi Arabia, Kuwait
and Bahrain for 1992-1998. Variance ratio tests rejected the RWH for all three stock markets. By applying the
Beveridge and Nelson (1981) decomposition of index returns and after removing the effects of infrequent trading,
a RWH was not rejected for the Saudi and Bahraini markets. Taking into considerations market imperfections
such as thinly and infrequent trading, Hassan et al (2003) examined Kuwait Stock Exchange over the period
1995-2000 by using EGARCH and GARCH-M and found that the market is weak-form inefficient.
Rao and Shankaraiah (2003) studied the weak form efficiency of the Bahrain Stock Market over the period
1996–2000 and confirmed the weak-form efficiency. Smith (2007) studied the RWH in the Middle Eastern stock
markets and found that Israeli, Jordanian, and Lebanese markets were weak-form efficient while the Kuwait and
Oman markets were not. For the Tel-Aviv, Amman and Beirut stock market and non-Kuwaiti companies that
traded on the Kuwait stock market, stock price indices follow a random walk. Moustafa (2004) examined the
behavior of the prices in the UAE stock market and concluded that most firms are weak-form efficient and prices
follow a random walk. Babaker (2004) investigated the market efficiency of all Arab Stock Exchanges and the
results showed that emerging markets are less efficient than developed markets. In addition, at different time
periods, stock markets vary in efficiency. Asiri (2000, 2004, 2007) examined Kuwait's stock market for the daily
stock prices for 1999-2001, 1991-2002 and 2000-2002. Using unit root test, ARIMA (AR1); exponential
smoothing and autocorrelation tests confirmed the weak-form efficiency. Sector analysis also gives robust
support to the findings. The results confirmed the randomness for all share prices and each sector. Studying all
companies listed on the Bahrain Stock Exchange, Asiri (2008) confirmed that all daily prices and each sector
follow a random walk with no drift and trend and supporting the weak-form market efficiency. Using daily
sectoral indices between 2000 and 2005, Squalli (2006) explored the efficiency in the different sectors of the
Dubai Financial Market (DFM) and Abu Dhabi Securities Market (ADSM). Variance ratio tests rejected the
randomness in all of the sectors in UAE except in the banking sector in DFM. In comparison, using runs test,
the insurance sector of the ADSM gave evidence of weak-form efficiency in the UAE. Al-Khazali et al (2007)
re-examined the empirical validity of the weak-form in emerging markets of the MENA region: Bahrain, Egypt,
Jordan, Kuwait, Morocco, Oman, Saudi Arabia and Tunisia. In their study, they utilized the Lo and MacKinlay
(1988, 1989), Wright’s (2000) rank and sign VR and the runs tests. Once the returns from the indices were
adjusted to reconcile distortions from thinly and infrequently traded stocks, the study found random walk and
weak-form efficiency in all of the markets examined.
4. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
38
Using multiple variance tests on different sectors, Benjelloun and Squalli (2008) tested the markets of Jordan,
Qatar, Saudi Arabia and the UAE and found that there is no consistency in their results among the different
sectors and the different markets. Randomness was rejected in Jordan, Abu Dhabi and Dubai when using the
general index. However, if the sectoral indexes were used, they failed to reject the randomness in some sectors.
Using the runs test, randomness was rejected in all of the stock market if general indexes were used, with the
exception to Dubai. However, using the sectoral indexes, they have failed to reject the weak-form efficiency in
some sectors.
Elango and Hussein (2008) examined the market efficiency across seven stock markets in the GCC countries2
for
the daily indices over the period 2001-2006. Kolmogorov-Smirnov test shows that all of the seven markets
reject the RWH and using the runs test for randomness, they found that the successive price changes were not
random. Marashdeh and Shrestha (2008) investigated if the stock price index in the UAE follows random by
using unit root, Augmented Dickey Fuller and Philip-Perron tests along with Perron’s Innovational Outliner and
Additive Outliner models. The results show that the data has a unit root and follows a random walk. Awad and
Daraghma (2009) examined the efficiency of the Palestine Security Exchange for 35 stocks listed in the market
using the daily indices and concluded that daily returns are inefficient in the weak-form. AlKhazali (2011) has
conducted a study examining the market efficiency in the Gulf countries and concluded that the RWH is not
rejected in all the GCC markets. Al-Jafari (2011) and Al-Jafari and Altaee (2011) found that both Bahrain and
Kuwait stock markets are informationally inefficient at the weak-form level. Salameh et al (2011) explored the
weak form market efficiency for Saudi Arabia, Amman, Kuwait, Dubai, Abu Dhabi, Egypt, Morocco, Tunisia,
Qatar, Oman, Bahrain and Palestine markets. In general, Saudi Market was the only market that behaved
randomly under both the serial autocorrelation tests and the runs test. However, under both the Augmented
Dickey-Fuller and Phillips-Perron unit root tests, it was found that all of the markets do not behave randomly.
Testing the daily closing prices for the eleven high-volume trading banks listed on the Karachi Stock Exchange,
Bashir et al (2011-a) rejected the weak-form efficiency in the banking sector and (2011-b) rejected in the textile
sector in Pakistan.
4. Data and Methodology
The Data. All Share Index and sectoral indices for daily closing prices in Tadawul over the period October 30,
2006 through November 15, 2012 are collected. The data set consists of the daily closing values of 16 indices,
the All-Share Index (TASI), and 15 other sectoral indices. The data collected is for two periods: during and after
the financial crisis. Random walk is tested for the whole market and then for each sector and each period. The
actual returns on the market are calculated as follows:
Rit = [(Iit – Iit-1) / Iit-1] x 100
where:
Rit = the daily return on day t for sector i
Iit = stock index closing value for sector i
Iit-1 = stock index closing value for sector i on day t-1
The daily return is computed either as a percentage or logarithmic price change. Osborne (1959) suggested that
the lognormal probability distribution of price change is better explained in random walk. Jaradat and Al-Zeaud
(2011) justified this measure by arguing that mathematically, logarithm of relative price is producing a time
series of continuously compounded returns. Using the same approach of Srinivasan (2010), stock market returns
are defined as continuously compounded or log returns at time t. Furthermore, as per Lauterbach and Ungar
(1995), continuously compounded returns are additive and their distribution follows the normal distribution more
closely than arithmetic returns. Therefore, stock returns are calculated by the log difference change in the price
index.
Dickey-Fuller Unit Root Test with Drift. Most researchers used the unit root test in order to test for the non-
stationary which is the necessary condition for the presence of random walk. Equation (1) presents the simple
form of unit root, where current price is expected to be totally explained by lagged price by one period (slope
coefficient = 1). If this is not true, then the current price is explained by a constant (drift) which is α, and a
coefficient for the lagged price to be less than 1. The null hypothesis in this case is: Ho: β=1 against Ha: β<1.
Pit = αααα + ββββPit-1 + εεεεit
(1)
where:
2
Each GCC country has one market and the UAE has two markets: the Abu Dhabi Secruities Market and Dubai
Financial Market.
5. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
39
α = Expected price change or drift
β = Expected to be unity
Pit = Current daily share price for firm i
Pit-1 = Lagged one period current daily share price for firm i
εit = Independently and identically distributed with mean 0 and constant
variance σ2
, IID (0, σ2
).
The independence in the error (εit) implies that increments are uncorrelated and that any non-linear function of
the increments is also uncorrelated. In addition, the model is assuming that increments are identically distributed
and the error term (ε) is assumed to be white noise.
Formulating the above equation in the first difference, as considered by Dickey and Fuller, Pit-1 is subtracted
from both sides and the model is:
∆∆∆∆Pit = αααα + ρρρρ Pit-1 + εεεεit
(2)
where:
∆Pit = First difference in share price for firm i
α = Expected price change or drift
ρ = (Slope – 1)
Pit-1 = Lagged one period current daily share price for firm i
Since the actual price is changed to the first difference, the hypothesis testing would change to Ho: ρ = 0 against
Ha: ρ < 0. Model (1) is testing for a coefficient of 1, while model 2 is testing for a coefficient of 0. The more
negative the ρ, the better the t-value would be to reject the null hypothesis and conclude that prices are stationary
and do not follow random walks.
Pearson Product-Moment Correlation Coefficient. Applying the same method used by Kendall (1953), the
correlation coefficient between the current return on an index and the one period lag-return should indicate if
there is a serial correlation. A positive coefficient indicates a tendency towards a possible continuation
momentum of abnormal returns on the next day, while a negative sign is a tendency towards a possible reversal
of returns. If the sign is significant, then that is a hint of possible market inefficiencies, and today's returns can be
used to predict future expected returns. However, if serial correlation coefficients are small, there is no
'systematic' correlation but rather a 'negligible' relation between one price change and the subsequent ones, and
would be consistent with the weak-form efficiency.
Autocorrelation test via the Durbin-Watson (D-W) Statistic. Gupta (2010) argued that Durbin-Watson test is
the best test to detect autocorrelation as such:
∑
∑
=
=
−−
= n
t
t
n
t
tt
e
ee
d
1
2
2
2
1)(
(3)
where:
d = Durbin-Watson Statistics
et = the residuals from a regression for time period t
et-1 = the residuals from a regression fro time period t-1
To test for positive autocorrelation at significance α, the test statistic d is compared to lower and upper critical
values (dL and dU):
If d < dL = error terms are positively autocorrelated
If d > dU = error terms are not positively autocorrelated
If dL < d < dU = the test is inconclusive
Statistically, the absence of statistical significance in autocorrelation test implies that the series follow a random
walk, which means that the market is efficient at the weak-form. The assumption of normally distributed
random errors is needed to derive the probability distribution of the test statistic used in the D-W test. This
method has also been used extensively by: Kendall (1953), Fama (1965), Fama and French (1989), Worthington
and Higgs (2006), Squalli (2006), Sharma and Mahendru (2009), Rao and Shankaraiah (2003), Awad and
Daraghma (2009), and Omran and Farrar (2006).
Wald-Wolfowitz Runs Test. Fama (1965) argued that this test examines the serial dependence in share price
movements. If no influence exists, then it can be said that the observations are independent. The runs test is a
nonparametric test, which can be used to test for independence between successive series without requiring
normality of the distribution. After observing the number of ‘runs’ in a sequence of price changes, randomness is
6. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
40
tested at 5% significance level with an absolute Z value greater than 1.96 and 1% significance level with an
absolute Z value greater than 2.58 indicating non-randomness.
= (4)
where:
Z = standard normal variable
R = number of runs
M = 1 +
( × )
( )
= mean number of runs
σ =
( ) – –
( )! – "
#
$
!
= standard deviation
nu, nd = number of ups and down in observations in each category
5. The Findings
Table 2 presents a summary of the descriptive statistics of the daily returns for All Share indices and sectors,
measured in log. Figure 1 clearly shows the simple pattern of randomness in All Share prices. Figure 2
highlights the normality of the returns for All Share index which is one of the conditions for the unit root test.
The Dickey-Fuller (DF) Test. Table 3 summarizes the main statistics derived from running the OLS for the
current closing index for All Share as a function of the lagged one period index. At the 1% level of significance,
the most important statistic, which is the t-value on β, is providing evidence that the slope β is insignificantly
different from 1 (t-value -2 < -2.862). T-test for the intercept (α = 0, i.e. no drift) indicates that the t-value is
insignificant to reject the null hypothesis. In other words, the model is a random walk without drift. Therefore,
it is concluded that prices in the KSA Stock Exchange are following a random walk. The best prediction of the
current price is the last price. R2
indicates that 99.30% of the variation in the current price is explained by the
lagged share price. Figure 3 supports the above findings, and it clearly shows that the current share price (index)
could not generate any excess return in the next period, with the exception of few unusual observation.
Changing the dependent variable to the “first difference of the closing price” (∆Pt) as a function of lagged
closing price and the white noise, is providing an alternative test to stationarity. The hypothesis to be tested is
Ho: β = 0 against the alternative Ha: β < 0. Table 3 presents the summary results for the unit root tests (actual
closing price and first difference in price) which provide evidence that share prices in Tadawul are following
random walk. The coefficient for lagged price is close to zero (β=-0.003) and t-value (-1.609) suggests that there
is not enough evidence to reject the null hypothesis that the slope coefficient is not significantly different from
zero. If this is the case, then the series exhibits a unit root and is non-stationary. D-W of 2.054 rejects the
problem of autocorrelation in the model. Testing individual indices for the 15 sectors, it is found that only Banks
and Financial Services do not follow random walk (t-value = -4.67).
Pearson Correlation Coefficient. It is found that out of 16 indices in Tadawul tested (All Share Index and 15
sectoral indices), none of them showed any strong or even moderate relationship between the daily returns and
the lagged return with correlation of coefficient varying between 0.203 for the Energy and Utilities and 0.028 for
the Media and Publishing sector. Thus, the current daily prices change of the indices is independent from the
previous day's change. Table 4 summarizes the coefficients for all sectors which are found to be very weak.
Autocorrelation test (D-W Statistic). No positive autocorrelation is found in the All Share Indexes or their
sectoral indices. All of the d-statistics are very close to 2, which lead to the conclusion that there is no positive
autocorrelation in the Saudi Market, and hence the market is weak-form efficient. From the 16 indices tested, we
could not find a positive serial correlation between the residuals in any index, and thus all of the indices tested
have met the criteria of an efficient market hypothesis at the weak-form (Table 4).
Runs-Test. From this test, it is found that at 5% level of significance, the All Share “TASI” returns from the
market index follow random walk, and from the 15 sectors, 11 exhibited daily returns that followed random
walks. The four that do not follow random walk are Banks and Financial Services (Z= -2.442), Energy and
Utilities (Z= 2.414), Insurance (Z= -2.855), and Building and Construction (Z= -2.733). Testing at 1% level of
significance, only two sectors are not following random walks: Insurance and Building and Constructions.
These results are shown in table 4.
Comparing the results of the four tests on each sector, we find some contradictory results, and thus we have
controversial findings and cannot reach to a final conclusion whether the daily returns of these indices are
informationally efficient in the weak-form. In general, sector-wise, the market of Saudi Arabia’s Tadawul is
found to be closer to the properties of the weak-form efficiency of EMH. Accordingly, it is not expected that
there will be investors in the market of Saudi Arabia whom can generate excessive returns by simply depending
on past information and technical analysis to formulate trading decision beating the market on a continuous and
7. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
41
systematical basis. In addition, All Share Index has met the properties of the weak-form efficiency in all the
models tested along with 11 out of the 15 sectors. Table 4 summarizes the findings of the four tests used for the
different indices in the Saudi Arabia.
Testing the random walk for share prices during and post financial crisis confirmed the main findings for All
Share index in most of the tests conducted (see Table 5). Furthermore, figure 4 compares the random walks
during these two periods.
6. Conclusion
The purpose of this study is to explore and test the random walk and weak-form informational market efficiency
in the Saudi Arabia. In order to examine the behavior of the daily returns of the stock markets, both overall and
sector-wise, four tests are applied: Dicky-Fuller unit root, Pearson correlation coefficient, Durbin-Watson
(autocorrelation), and Wald-Wolfowitz runs-tests. The findings show empirical evidence that Saudi stock prices
exhibit unit root for the All Share index and for the individual sectors with the exception of Banking and
Financial Services sector. In addition, All Share indices showed no significant correlation between the daily
returns, and the remaining indices did not show any strong or even moderate relationship between the daily
returns. Using the Durbin-Watson statistic, none of the indices exhibit a positive autocorrelation during the
period of the study. However, using the runs-test for testing randomness, at 5% level of significance, only four
indices out of the total 16 indices, did not qualify to behave similar to a RWM. While at 1% level of
significance, only two sectors did not follow random walk. As a result, a final conclusion cannot be reached
whether or not the daily returns of these indices follow a random walk and are informationally efficient in the
weak-form for the whole market. However, by using four tests, most of the results provide evidence to conclude
that in general, sector-wise, the market of Saudi Arabia’s Tadawul is weak-form efficient. Moreover, with
confidence, we can say that the All Share general market index of Saudi Arabia and 11 indices have met the
properties of the weak-form efficiency of EMH using all of the models tested.
Consequently, it is not expected that there will be investors in the market of Saudi Arabia who can generate
excessive returns by simply depending on past information and technical analysis to formulate trading decision
beating the market on a continuous and systematical basis. The findings of this study are considered to be an
added value to the literature concerning the random walk and testing the weak-form market efficiency in the
emerging markets, especially in the MENA region and GCC countries. These results can be a starting point for
further studies testing the semi-strong form of EMH in Saudi Arabia.
References
Abraham, A., Seyyed, F. J. and Alsakran, S. A. (2002), “Testing the Random Walk Behavior and Efficiency of
the Gulf Stock Markets”, The Financial Review, Vol. 37, No. (3), pp. 469-480.
Abrosimova, N., Dissanaike, G. and Linowski, D. (2002), “Testing Weak-Form Efficiency of the Russian Stock
Market”, Working Paper Presented at the EFA Berlin Meetings, 20 February.
Alexander, S. S. (1964), “Price Movements in Speculative Markets: Trends or Random Walk, Number 2”,
Industrial Management Review, Vol. V (Spring), pp. 25-46.
Al-Jafari, M. K. (2011). “Random Walks and Market Efficiency Tests: Evidence from Emerging Equity Market
of Kuwait”, European Journal of Economics, Finance and Administrative Sciences, Vol. 36, pp. 19-28.
Al-Jafari, M. K. and Altaee, H. H. A. (2011), “Testing the Random Walk Behavior and Efficiency of the
Egyptian Equity Market”, Journal of Money, Investment and Banking, Issue 22, pp. 132-146.
AlKhazali, O. (2011), “Does Infrequent Trading Make a Difference on Stock Market Efficiency? Evidence from
the Gulf Cooperation Council (GCC) Countries”, Studies in Economics and Finance, Vol. 28, No. 2, 2011, pp.
96-110.
Al-Khazali, O. M., Ding, D. K., and Pyun, C. S. (2007), “A New Variance Ratio Test of Random Walk in
Emerging Markets: A Revisit”, The Financial Review, Vol. 42, pp. 303-317.
Al-Loughani, N. E. (1995), “Random Walk in Thinly Traded Stock Market: The Case of Kuwait”, Arab Journal
of Administrative Science, Vol. 3, Issue No. 1, pp. 189-209.
_____, and Chappell, D. (1997). On the validity of the weak form efficient market hypothesis applied to the
London Stock Exchange, Applied Financial Economics, Vol. 7, 173-176.
Asiri, B. K. (2000), “Random walk in the Kuwaiti security prices”, paper presented at the Portuguese Finance
Network – First Finance Conference, 28 June-1 July.
_____ (2004), “Test of market efficiency – a case of Kuwait stock market”, paper presented at the Gulf Stock
Exchange Role on the Support and Activation of the Economic Development Potentials in the GCC Countries
Conference, Muscat, Oman, 2-3 October
8. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
42
_____ (2007), “Measuring the Efficiency of Kuwait Stock Market”, Arab Journal of Administrative Sciences,
Vol. 14, No. 2, pp. 265-280.
_____ (2008), “Testing Weak-Form Efficiency in the Bahrain Stock Market”, International Journal of Emerging
Markets, Vol. 3, (No. 1), pp. 38-53.
Awad, I., and Daraghma, Z. (2009), “Testing the Weak-Form Efficiency of the Palestinian Securities Market”,
International Research Journal of Finance and Economics, Issue 32, pp. 7-17.
Babaker, M. (2004), “Some Empirical Investigations about the Efficiency of Arab Stock Markets”, paper
presented at the Gulf Stock Exchange Role on the Support and Activation of the economic Development
Potentials in the GCC Countries Conference, Muscat, Oman.
Bachelier, L. (1900), “Theorie de la Speculation, Gauthier-Villars, Paris, 1900”, A Thesis submitted to the
Faculty of the Academy of Paris on March 29, 1900 and Reprinted in English (A. J. Boness, trans.) “Theory of
Speculation”.
Balaban, E. (1995), “Informational Efficiency of the Istanbul Securities Exchange and Some Rationale for Public
Regulation”, The Central Bank of the Republic of Turkey Research Department, Discussion Paper No. 9502,
February.
Bashir, T., Ilyas, M., and Furrukh, A. (2011-a), “Testing the Weak-Form Efficiency of Pakistani Stock Markets –
An Empirical Study in Banking Sector”, European Journal of Economics, Finance and Administrative Sciences,
Issue 31, pp. 160-175.
_____, Ahmad, M., Ilyas, M. and Malik, M. U. (2011-b), “Weak-Form Efficiency of Textile Sector: An
Empirical Evidence from Pakistan”, Interdisciplinary Journal of Contemporary Research in Business, Vol. 2, No.
12, pp. 600-617.
Benjelloun, H. & Squalli, J. (2008), “Do General Indexes Mask Sectoral Efficiency? A Multiple Variance Ratio
Assessment of Middle Eastern Equity Markets”, International Journal of Managerial Finance, Vol. 4, No. (2),
pp. 136-151.
Beveridge, S. and Nelson, C. R. (1981), “A New Approach to Decomposition of Economic Time Series into
Permanent and Transitory Components with Particular Attention to Measurement of the Business Cycle”,
Journal of Monetary Economics, Vol. 7, pp. 151-174.
Butler, K. C., and Malaikah, S. J. (1992), “Efficiency and Inefficiency in Thinly Traded Stock Markets: Kuwait
and Saudi Arabia”, Journal of Banking & Finance, Vol. 16, Issue No. 1, pp. 197-210.
Civelek, M. A. (1991), “Stock Market Efficiency Revisited: Evidence from the Amman Stock Exchange”, The
Middle East Business & Economic Review, Vol. 3, pp. 27-31.
Conrad, J. and Kaul, G. (1988), “Time-Variation in Expected Returns”, Journal of Business, Vol. 61 (October
1988), pp. 409-425.
Dahel, R. and Laabas, B. (1999), “The Behavior of Stock Prices in the GCC Markets”, Journal of Development
& Economic Policies, Vol. 1, pp. 89-105.
Ebid, S. (1990), “Characteristics and Behavior of UAE Stock Market”, Journal of Economic and Administrative
Sciences, Vol. 6, pp. 19-61.
Elango, R. and Hussein, M. I. (2008), “An Empirical Analysis on the Weak-Form Efficiency of the GCC
Markets Applying Selected Statistical Tests”, International Review of Business Research Papers, Vol. 4, No. 1,
pp. 140-159.
El-Erian, M. A. and Kumar, M. S. (1995), “Emerging Equity Markets in Middle Eastern Countries in
development of financial makets in the Arab countries, Iran and Turkey.”, IMF Staff Papers, IMF, Vol. 42, No. 2,
pp. 313-343.
Fama, E. F. (1965), “The Behavior of Stock-Market Prices”, Journal of Business, Vol. 38, No. 1, (January).
_____ (1970), “Efficient Capital Markets: A Review of Theory and Empirical Work”, The Journal of Finance,
Vol. 25, No. (2), pp. 383-417.
_____ (1991), “Efficient Capital Markets: II”, The Journal of Finance, Vol. 46, No. 5, pp. 1575-1617.
_____ and Blume, M. (1966), “Filter Rules and Stock Market Trading Profits”, Journal of Business ,Vol. 39,
Issue 1, (Part 2: Supplement on Security Prices, January 1966), pp. 226-241.
_____ and French, K. R. (1988), “Permanent and Temporary Components of Stock Prices”, Journal of Political
Economy, Vol. 96 No. 2, pp. 246-273.
_____ and _____ (1989), “Business Conditions and Expected Returns on Stocks and Bonds”, Journal of
Financial Economics, Vol. 25, Issue (1), pp. 23-49.
Gandhi, D., Saunders, A. and Woodward, R. (1980), “Thin Capital Markets: A Case Study of the Kuwaiti Stock
Market”, Applied Economics, Vol. 12, pp. 341-349.
9. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
43
Gupta, A. (2010), “A Critical Analysis of Weak Form Efficiency in Indian Stock Market”, Asian Journal of
Management Research, Vol. 1, No. 2, pp. 657-665.
Hassan, K. M., Al-Sultan, W. S. and Al-Saleem, J. A. (2003), “Stock Market Efficiency in the Gulf Cooperation
Council Countries (GCC): The Case of Kuwait Stock Exchange”, Scientific Journal of Administrative
Development, Vol. 1, No. 1, I.A.D. 2003, pp. 1-21.
Huber, P. (1995), “Random walks in Stock Exchanges Prices and the Vienna Stock Exchange”, Working Paper,
Economic Series, No. 2, 1-25.
Jaradat, M. A. and Al-Zeaud, H. A. (2011), “Testing the Weak-Form Efficiency of Amman Stock Exchange”,
International Research Journal of Finance and Economics, Issue 65, pp. 93-97.
Jensen, M. C. (1968), “The Performance of Mutual Funds in the Period 1945-1964”, The Journal of Finance,
Vol. 23, No. 2, Issue No. 2, pp. 389-416.
Keim, D. and Stambaugh, R. (1986), “Predicting returns in stock and bon markets”, Journal of Financial
Economics, Vol. 17, pp. 357-90.
Kendall, M. G. (1953), “The Analysis of Economic Time-Series-Part I: Prices”, Journal of the Royal Statistical
Society 96, Series A (General), Vol. 116, Issue No.1, pp. 11–25.
Khababa, N. (1998), “Behavior of Stock Prices in the Saudi Arabian Financial Market: Empirical Research
Findings”, Journal of Financial Management & Analysis, Vol. 11 (1) Jan-June, pp. 48-55.
Kompa, K. and Matuszewska-Janica, A. (2009), “Efficiency of the Warsaw Stock Exchange: Analysis of
Selected Properties”, International advances in Economic Research, Vol. 15 (1), pp. 59-70.
Kvedaras, V. and Basdevant, O. (2004), “Testing the Efficiency of Emerging Capital Markets: The Case of the
Baltic States”, Journal of Probability and Statistical Science, Vol. 2 No. 1, pp. 111-138.
Lauterbach, B. and Ungar, M. (1995), “Real vs. Nominal Stock Return Seasonalities: Empirical Evidence”
International Review of Economics and Finance, Vol. 4, Issue No. (2), pp. 133-147.
Lo, A.W. and MacKinlay, A. C. (1988), “Stock Market Prices Do Not Follow Random Walks: Evidence from a
Simple Specification Test”, The Review of Financial Studies, Vol. 1, No. (1), (Spring 1988), pp. 41-66.
_____ and _____ (1989), “The size and power of variance ratio test in finite samples: a Monte Carlo
investigation”, Journal of Econometrics, Vol. 40, pp. 203-38.
Malkiel, B. G. (1992), “Efficient Market Hypothesis”, in Newman, P., Milgate, M. and Eatwell J. (eds.), “New
Palgrave Dictionary of Money and Finance”, Macmillan, London.
Marashdeh, H. and Shrestha, M. B. (2008), “Efficiency in Emerging Markets- Evidence from the Emirates
Securities Market”, European Journal of Economics, Finance and Administrative Sciences, Issue 12, pp.143-150.
McQueen, G., Pinegar, M. and Thorley, S. (1996), “Delayed reaction to good news and the cross-autocorrelation
of portfolio returns”, Journal of Finance, Vol. 51 No. 3, pp. 889-920.
Moustafa, M. A. (2004), “Testing the Weak-Form Efficiency of the United Arab Emirates Stock market”,
Omran, M. and Farrar, S. (2006), “Tests of Weak Form Efficiency in the Middle East Emerging Markets”,
Studies in Economics and Finance, Vol. 23, No.1, pp. 13-26.
Osborne, M. F. (1959), “Brownian Motion in the Stock Market”, Operations Research, Vol. 7, No. 2, pp.145-
173.
Pearson, K. (1905), “The Problem of the Random Walk”, Nature, Vol. 72, No. 1867, pp. 294; 318; 342.
Rao, D.N. and Shankaraiah, K. (2003), “Stock Market Efficiency and Strategies for Developing GCC Financial
Markets: A Case Study of the Bahrain Stock Market”, The Arab Bank Review, Vol. 5 (No. 2), pp. 16-21.
Salameh, H. M., Twairesh, A. E., Al-Jafari, M. K. and Altaee, H. H. A. (2011), “Are Arab Stock Exchanges
Efficient at the Weak-Form Level? Evidence from Twelve Arab Stock Markets”, European Journal of
Economics, Finance and Administrative Sciences, Issue 39, pp. 18-31.
Samuelson, P.A. (1965), “Proof That Properly Anticipated Prices Fluctuate Randomly”, Industrial Management
Review, Vol. 6, No. 2, pp. 41-49.
Seiler, M.J. and Rom, W. (1997), “A historical analysis of market efficiency: Do historical returns follow a
random walk?”, Journal of Financial and Strategic Decisions, Vol. 10 No. 2, pp. 49-57.
Sharma, G. D. and Mahendru, M. (2009), “Efficiency Hypothesis of the Stock Markets: A Case of Indian
Securities”, International Journal of Business and Management, Vol. 4, No.3, March 2009, pp.136-144.
Smith, G. (2007), “Random Walks in Middle Eastern Stock Markets”, Applied Financial Economics, Vol. 17, pp.
587-596.
Squalli, J. (2006), “A Non-Parametric Assessment of Weak-Form Efficiency in the UAE Financial Markets”,
Applied Financial Economics, Vol. 16, Issue No. 18, pp. 1365-1373.
Srinivasan, P. (2010), “Testing Weak-Form Efficiency of Indian Stock Markets”, Asia Pacific Journal
of Research in Business Management, Vol. 1, Issue 2, pp. 134-140.
10. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
44
Worthington, A. C., and Higgs, H. (2006), “Evaluating Financial Development in Emerging Capital Markets
with Efficiency Benchmarks”, Journal of Economic Development, Vol. 31, Issue 1, pp. 17-44.
Working, H. (1934), “A Random-Difference Series for the Use in the Analysis of Time series”, Journal of the
American Statistics Association, Vol. 29, (March), pp. 11-24.
Wright, J. (2000), “Alternative Variance-Ratio Tests Using Ranks and Signs”, Journal of Business and
Economics Statistics, Vol. 18, pp. 1-9.
Figure 1: Closing Indices for Tadawul All-Share "TASI"
Figure 2: Distribution of returns for Tadawul All-Share Index “TASI”
Figure 3: Closing prices against Lag prices for All-Share "TASI"
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
0
100
200
300
400
500
11. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
45
During Crisis
After Crisis
Figure 4: Financial crisis and random walk in TASI
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
1
23
45
67
89
111
133
155
177
199
221
243
265
287
309
331
353
375
397
419
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
1
53
105
157
209
261
313
365
417
469
521
573
625
677
729
781
833
885
937
989
12. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
46
Table 1: Tadawul Market Structure
Sector code Sector Name No. of companies in the index
TASI Tadawul All Share Index 150
TBFSI Banks & Financial Services Sector 11
TPISI Petrochemical Industries Sector 14
TCESI Cement Sector 10
TRESI Retail Sector 10
TEUSI Energy & Utilities Sector 2
TAFSI Agriculture & Food Industries Sector 15
TTISI Telecom & Information Technology Sector 5
TINSI Insurance Sector 31
TMISI Multi-Investment Sector 7
TIVSI Industrial Investment Sector 13
TBCSI Building & Construction Sector 15
TRDSI Real Estate Development Sector 8
TTRSI Transport Sector 4
TMPSI Media and Publishing Sector 3
THTSI Hotel & Tourism Sector 2
Table 2: Summary Statistics for Tadawul
Daily Returns Min Max Mean Std. Dev. Skewness Kurtosis
All Share TASI -.0998 .2489 -.000106 .0206400 -.247 6.500
TAFSI -.0963 .0953 .000130 .0188385 -.429 5.968
TBCSI -.0991 .0987 -.000226 .0221368 -.607 4.861
TBFSI -.0978 .0913 -.000244 .0175964 .014 6.197
TCESI -.0986 .0975 -.000043 .0152281 -.249 10.400
TEUSI -.0982 .0956 .000089 .0181705 .178 6.154
THTSI -.0993 .2489 .000302 .0261277 .587 9.668
TINSI -.0956 .0974 -.000131 .0226482 -.541 3.177
TIVSI -.0981 .0979 .000250 .0213593 -.646 4.556
TMISI -.0979 .1207 -.000475 .0230984 -.487 4.935
TMPSI -.0996 .1003 -.000646 .0216263 -.150 4.851
TPISI -.0992 .0989 .000441 .0233343 -.476 4.405
TRDSI -.0995 .0990 -.000492 .0189798 -.326 6.253
TRESI -.0987 .0991 .000214 .0181629 -.457 7.432
TTISI -.0998 .0990 -.000368 .0174865 -.285 6.988
TTRSI -.0991 .0977 -.000392 .0221046 -.146 5.149
13. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
47
Table 3: Summary results for the unit root test
Sectors Index
Dependent Variable: Price
Expected β = 1
Dependent Variable:
change in price3
Expected β = 0
Slope:
β
Drift: α
Se β T
(DF)
R2
Slope: β Drift: α
All-Share TASI 0.996 23.65 .002 -2 0.993 -.003 23.267
1 TBFSI 0.986* 279* .003 -4.67 0.977 -.004 66.525
2 TPISI 0.997 147.9 .002 -1.5 0.969 -.003 21.613
3 TCESI 0.997 12.94 .002 -1.5 0.996 -.002 10.833
4 TRESI 0.991 43.87** .004 -2.25 0.980 -.009** 42.980**
5 TEUSI 0.989 50.63* .004 -2.75 0.980 -.010** 46.556**
6 TAFSI 0.989 54.82* .004 -2.75 0.978 -.011** 53.020**
7 TTISI 0.995 46.91* .002 -2.5 0.982 -.005** 9.286
8 TINSI 0.998 2.01 .002 -1 0.996 -.002 1.653
9 TMISI 0.998 21.66*** .002 -1 0.990 -.002 4.888
10 TIVSI 0.992 96.47* .004 -2 0.973 -.008** 40.800**
11 TBCSI 0.998 7.61 .002 -1 0.995 -.002 7.616
12 TRDSI 0.998 13.56 .002 -1 0.992 -.002 6.189
13 TTRSI 0.995 32.69** .003 -1.67 0.983 -.005 15.354
14 TMPSI 0.995 10.48 .002 -2.5 0.991 -.004** 7.689
15 THTSI 0.986 159* .005 -2.2 0.959 -.014** 75.222*
* significant at 1% ** significant at 5% *** significant at 10%
3
Since returns on index is calculated as "change in index", using first difference or returns as a variable provided
similar results.
14. Research Journal of Finance and Accounting www.iiste.org
ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)
Vol.4, No.6, 2013
48
Table 4: Summary results for the four tests
Sample size = 23,488 observations
Sectors Index
DF Unit Root
Ho: Unit root
Correlation
Ho: No
correlation
Durbin-Watson Ho:
No autocorrelation
Runs-Test
Ho: Random Series
B Unit
root
Value
Random
Walk
d
statistics
Random
Walk
Z
statistic
Random
Walk
All-
Share
TASI 0.996
Don't
Reject
0.084
Don't
Reject
2.008
Don't
Reject
-1.438
Don't
Reject
1 TBFSI 0.986 Reject 0.109
Don't
Reject
2.003
Don't
Reject
-2.442 Reject
2 TPISI 0.997
Don't
Reject
0.046
Don't
Reject
2.006
Don't
Reject
-0.698
Don't
Reject
3 TCESI 0.997
Don't
Reject
0.060
Don't
Reject
2.003
Don't
Reject
-0.638
Don't
Reject
4 TRESI
0.991 Don't
Reject
0.034
Don't
Reject
1.998
Don't
Reject
0.582
Don't
Reject
5 TEUSI
0.989 Don't
Reject
0.203
Don't
Reject
2.003
Don't
Reject
2.414 Reject
6 TAFSI
0.989 Don't
Reject
0.081
Don't
Reject
2.003
Don't
Reject
-1.511
Don't
Reject
7 TTISI 0.995
Don't
Reject
0.061
Don't
Reject
2.003
Don't
Reject
-1.341
Don't
Reject
8 TINSI
0.998 Don't
Reject
0.114
Don't
Reject
2.008
Don't
Reject
-2.855 Reject
9 TMISI
0.998 Don't
Reject
0.094
Don't
Reject
1.998
Don't
Reject
1.014
Don't
Reject
10 TIVSI
0.992 Don't
Reject
0.035
Don't
Reject
2.005
Don't
Reject
0.930
Don't
Reject
11 TBCSI
0.998 Don't
Reject
0.130
Don't
Reject
2.008
Don't
Reject
-2.733 Reject
12 TRDSI
0.998 Don't
Reject
0.067
Don't
Reject
2.003
Don't
Reject
0.582
Don't
Reject
13 TTRSI
0.995 Don't
Reject
0.043
Don't
Reject
1.996
Don't
Reject
0.584
Don't
Reject
14 TMPSI
0.995 Don't
Reject
0.028
Don't
Reject
1.998
Don't
Reject
1.221
Don't
Reject
15 THTSI 0.986
Don't
Reject
0.037
Don't
Reject
2.002
Don't
Reject
0.001
Don't
Reject
Table 5: Financial crisis and the randomness of share prices for TASI
States df
DF Unit Root
Ho: Unit root
Correlation
Ho: No
correlation
Durbin-Watson Ho:
No autocorrelation
Runs-Test
Ho: Random
Series
B
Unit
root
Value
Random
Walk
d
statistics
Random
Walk
Z
statistic
Random
Walk
During-crisis 439 0.992
Don’t
Reject
0.146
Don’t
Reject
1.977
Don’t
Reject
-2.339
Don’t
Reject*
Post crisis 1023 0.990
Don’t
Reject
0.053
Don’t
Reject
1.903
Don’t
Reject
-0.469
Don’t
Reject
* at 1% level of significance