Stock Market Efficiency

What is the relationship between the risk and expected return of an investment? The capital asset pricing model (CAPM) provides an initial framework for answering this question. The CAPM (Sharpe, 1964; Lintner, 1965) marks the birth of asset pricing theory. This model is based on the idea that not all risk should affect asset prices. The model thus provides insight into the kind of risk that is related to return. Four decades later, the CAPM is still widely used in applications. The CAPM provides a methodology for translating risk into estimates of expected ROE. Its application continues to generate debate: many scholars argued that the CAPM is based on unrealistic assumptions. This paper lays out the key ideas of the CAPM, the history of empirical work on the CAPM and the implications of this work on the shortcomings of the CAPM.

Abstract
This study examines the diverse methods practitioners of money management use in order to choose stock investments. We discover they use discounted cash flow, multiples, balance sheet approaches. Additionally, they consider industry forces such as demographics and psychographics.

The objective of this study was to establish the effects of dividend announcement to current market prices at the Nairobi Securities Exchange, with four specific objectives; to determine the information content of dividend announcements, to determine the extent to which prices converge to new values after dividend announcements on a sector by sector basis, to establish the market reaction to announced information and also to establish whether investors can secure excess returns by acting on announced information. A 66 days event timeline was employed from 2005 to 2015 on daily closing stock prices. A sample of 179 dividend announcements from 22 listed companies in 8 sectors were drawn and analysed using an OLS Market Model. Findings of the research conclude that; dividend announcements do have an impact on stock prices for the Agricultural, Banking, Commercial, Construction, Manufacturing and Telecomm Sectors and not for the Energy Sector, Insurance Sector and the Nairobi Securities...

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This paper studies time-varying market efficiency in twenty emerging and five developed equity markets for the period covering from January 2000 to June 2017 by using daily returns from MSCI indices and draws a comparison between emerging and developed market efficiency. I used four methods to test for efficiency in emerging market, GARCH-M (1,1) model (Generalised autoregressive conditional heteroscedasticity in mean) to test degree of volatility over the time, Autocorrelation test to test for correlation between two values, Runs test to test for randomness of values and Long memory by using rolling regression estimates. The results from these tests show that, most of the emerging markets are inefficient in weak form and developed markets are efficient in weak form. Some of the emerging markets like Brazil, India, China, Taiwan, Korea and Turkey show significant improvement in recent years. Comparison between emerging and developed market reveals that, information flows efficiently and symmetrically in developed markets compare to emerging markets. In addition, I observed that subprime crisis had a huge impact on emerging markets and created economic imbalance around the world.

One of the most important principles used in measuring the market's efficiency is the ability of prices to reflect all currently available information. The Efficient Market Hypothesis (EMH) is the proposition that current stock prices fully reflect all available information about the value of the firm and that there is no way to earn excess profits by using this information. The EMH has received an abundance of attention since its inception. However, evidence against the EMH is growing, and numerous studies have documented return predictability. In fact, despite its relative simplicity, this hypothesis has also generated considerable controversy. After all, the EMH questions the ability of investors to consistently detect mispriced securities. For these reasons, scholars have recently been studying the calendar anomalies that are one of the characteristics of financial markets, and these anomalies are found to contradict the EMH. The purpose of this paper is to present a systematic review of the existing literature on calendar anomalies. This critical examination of the relationship between the EMH and calendar anomalies provides new insights for scholars and executives.

The research empirically examines the stock market’s reaction to M&A announcements
on the Zimbabwe Stock Exchange (ZSE) over the period, 2009 to 2017. The research consist of fourdifferent types of M&A namely horizontal, conglomerate, cross border and an acquisition of anon-listed entity. Basing on the Efficient Market Hypothesis (EMH), the study used the widelyadopted Event Study Methodology (EVM) to determine the existence of abnormal returns (AR)and cumulative abnormal returns (CAR) following M&A announcements hence assessed the semi-strong form efficiency of the local bourse on such news. t-Tests were run at 95%confidence level to determine the significance of abnormal and cumulative abnormal returns.The empirical results show that significant AR and CAR have been negative for acquiring firmsand positive for target firms conforming to general market reactions to M&A announcementsas presented by past studies. The irregular AR and CAR patterns across counters suggest thatinvestors do not quickly react to M&A news possibly inferring a weak form efficiency of the ZSE. There appears to be share price reactions days leading to the announcement, confirmedwith significant pre-announcement period CAR, this suggests that there are informationleakages prior to public announcement. Based on these results, it can be concluded that thelocal stock market significantly reacts to M&A announcements and that the ZSE exhibits aweak form efficient on M&A announcements.

Efficiency of markets has been much debated and theory evolved from the efficient market hypothesis (EMH) in its three forms to the adaptive market hypothesis (AMH). We study the US technology sector, finding that stocks traded inefficiently during the financial crisis and rejecting the conventional all-or-nothing EMH in favour of the AMH. We also analyse Bitcoin, rejecting a move-to-efficiency as suggested by EMH literature and showing support for the AMH. Finally, we apply an original Double Runs Test to high-frequency Bitcoin prices to develop the notion of sticky efficiency and show that it exists in the Bitcoin market.

A stock market, equity market or share market is the aggregation of buyers and sellers (a loose network of economic transactions, not a physical facility or discrete entity) of stocks (also called shares); these may include securities listed on a stock exchange as well as those only traded privately.

This short paper establishes the credibility and viability of this research topic to progress towards a PhD award through further research.

The original contribution of the work proposed can be summarised as; (1) the analysis of 2002-2014 dual listed company (DLC) panel trading data, (2) investigation into the explanatory power of both implied and historical stock and index volatility (available since 2008) regarding changes in DLC spreads, (3) linkage between established DLC’s and emerging Chinese Hong-Kong DLC’s and (4) establishing commonalities in value distortion between DLC’s and other financial instruments and structures.

This research has implications for the Law of One Price, the efficient market hypothesis, noise trading theory, international capital markets, trading profitability and the distortion of equity values by geographic locality.

Financial time series forecasting is a popular application of machine learning methods. Previous studies report that advanced forecasting methods predict price changes in financial markets with high accuracy and that profit can be made trading on these predictions. However, financial economists point to the informational efficiency of financial markets, which questions price predictability and opportunities for profitable trading. The objective of the paper is to resolve this contradiction. To this end, we undertake an extensive forecasting simulation, based on data from thirty-four financial indices over six years. These simulations confirm that the best machine learning methods produce more accurate forecasts than the best econometric methods. We also examine the methodological factors that impact the predictive accuracy of machine learning forecasting experiments. The results suggest that the predictability of a financial market and the feasibility of profitable model-based trading are significantly influenced by the maturity of the market, the forecasting method employed, the horizon for which it generates predictions and the methodology used to assess the model and simulate model-based trading. We also find evidence against the informational value of indicators from the field of technical analysis. Overall, we confirm that advanced forecasting methods can be used to predict price changes in some financial markets and we discuss whether these results question the prevailing view in the financial economics literature that financial markets are efficient.

This paper studies the abnormal stock performance around inclusion/exclusion from the Euro STOXX 50 index for the period 1998-2015 in order to extend the abundant evidence on the index effect which shows conflicting results for different indices and time periods studied.
The study on abnormal stock returns for deletions and additions shows only temporary effect among European blue chip stocks and supports the Price pressure hypothesis. Further investigation of companies’ operating performance does not produce any convincing evidence that the inclusion in the Euro STOXX 50 index has any significant effect on companies’ profitability.

"This paper examines the weak-form market efficiency of Indian stock markets namely Bombay Stock Exchange and National Stock Exchange for the period August 1998 to July 2010. The data is also divided into intervals of three years, to find out the weak form efficiency over periods. Daily returns are examined for random walks using Unit Root Test, Auto correlation and runs tests. From the Unit Root, It has been found that data is stationary. From the analysis of whole period, it is found that Autocorrelation prevails in the market. But in the Interval of three year data, significant Autocorrelation is found only in the period
August 2001 to July 2004. But thereafter, market became random walk because no significant autocorrelation found after 2004. Runs Test conclude that the whole period null hypothesis of random walk was not accepted. In all months, null hypothesis is accepted of random walk except January month. But in all days random walk is prevailing. The period of 2004 to 2010 support weak form Market Efficiency."

In recent decades business organisations as well as governments are realizing the importance of capital markets in general and particularly stock markets in the economic growth and development of a country. A truly efficient capital market has great role to play in the development of a country. A market is said to be efficient if prices in the market reflects all private or publicly available or historical information of the concerned security in the market. Empirical testing of market efficiency in India revealed mixed results-some concluded it is weak form efficient and others have concluded that it is not even weak form efficient. So, in this paper an attempt has been made to test weak form of market efficiency of Bombay Stock Exchange and National Stock Exchange. Daily values of S & P BSE Sensex and Nifty 50 from January 1, 2014 to December 31, 2018 have been used and daily returns have been calculated. The Kolmogorov-Smirnov Goodness of Fit Test result shows non-normal daily returns of both the Sensex and Nifty. Then run test with mean, median and zero as base have been used to test the weak form market efficiency. All the test results for both the Nifty and Sensex have evidenced that the markets are not even efficient in the weak form. To substantiate the conclusion the Augmented Dickey-Fuller test and Philips-Perron test of Stationarity have been used and the results revealed that both Sensex and Nifty return series are stationary at level. As one can model the stationary series and predict the future movements so the market cannot be regarded as efficient. So, it can be concluded that the Indian stock market is not efficient in the weak form and security prices do not reflect all past information and it is possible to earn super-normal gain by utilizing past information as share prices do not adjust instantaneously in response to any new information release in the market.

Tal como predice la hipótesis de eficiencia débil de mercado, la evidencia empírica de esta
investigación respalda el supuesto de que no es posible obtener beneficios económicos
significativos y estadísticamente robustos al implementar estrategias de inversión basadas
en díez reglas de Análisis técnico (medias móviles, filtros optimizados y ocho estrategias
de velas japonesas), en 19 acciones colombianas. A diferencia de otras investigaciones
similares, este estudio implementa pruebas a nivel de estrategias de inversión y no de
autocorrelaciones, e incorpora pruebas "out-of-sample" para evitar “Data snooping”,
consideraciones de costos de transacción, y estimación de significancia estadística de la
rentabilidad de las reglas con el uso de la metodología Bootstrapping. Es de anotar que en
algunos pocos casos las reglas presentan rendimientos en exceso sobre la estrategia pasiva,
pero no de una manera tanto estable como estadísticamente significativa.

This paper determines the causal relationship between stock prices and the macroeconomic variables representing the real sector of the Pakistani economy. In order to substantiate the purpose annual data has been acquired from the websites of State Bank of Pakistan and Federal Bureau of Statistics, from
the period of 1979 to 2013. Further to get the results Unit Root, Cointegration, Error correction model has been applied. Which indicate the presence of long term relation between stock prices and macroeconomic variables including gross domestic product (GDP), Consumption and Investment. Moreover, the result shows the existence of one-way causation between macroeconomic variables such as GDP, real consumption expenditure, and real investment expenditure. This one-way causation lead to the conclusion that the stock market of Pakistan is not developed to that extinct where it could influence GDP, real consumption expenditure, and real investment expenditure. Therefore, it is finally concluded that the stock market of Pakistan is not a leading indicator of any activity of economy.

This study explores the weak-form efficiency of the Philippine Stock Exchange (PSE) and its different sectoral markets using modern inference techniques with robust statistical properties. The research is motivated by the lack of consensus in the literature on the informational efficiency of the country’s stock market and the apparent scarcity of studies on the same issue using data covering the period of massive modernization of the exchange, geared toward transparent disclosures and integrity of transactions. The study may also be considered a fitting assessment of why the PSE is setting the pace over most stock exchanges in Asia in terms of growth levels across key stock market indicators, culminating in a highly successful year 2012 when it ranked ninth among the ten best-performing stock markets of the world. Evidence presented by the results of the study suggests the presence of overall informational efficiency in the Philippine Stock Exchange during the period under review.

A market is said to be efficient if prices in the market reflect all private or publicly available or historical information of the concerned security in the market. Fama, E. divided the efficient market hypothesis into three sub hypotheses – weak, semi-strong and strong depending on the types of information reflected in the stock prices. In this study an attempt has been made to describe each of these forms and tests designed to check each. Further attempt has been made to empirically test the weak form of efficient market hypothesis in the Indian context.   
National Stock Exchange (NSE) of India has a total market capitalization of more than US$2.27 trillion, making it the world's 11th-largest stock exchange as of April 2018 and the largest in India, so I have selected NSE Midcap Liquid 15 Index companies and collected daily prices of each of the 15 companies for a period from January 1, 2017 to December 31, 2018. Then the daily continuously compounded rates of returns have been calculated. Kolmogorov-Smirnov Goodness of Fit Test (K-S test) has been applied to daily returns of each of the 15 companies to test whether the returns follow normal distribution or not. The Result showed out of 15 companies 14 companies’ returns does not follow normal distribution. As for the 14 companies returns does not follow normal distribution, hence a non-parametric test i.e. run test has been applied to test for weak form of market efficiency and result showed that the null hypothesis of the weak form of efficiency can be rejected with 99% level of confidence. For the one company whose return follows normal distribution the auto-correlation test and Ljung-Box Q (LBQ) statistic have been applied and here also the result rejected the null hypothesis of weak form of efficiency.
Hence, all the test results unanimously showed that the Indian Stock Market in general and particularly the NSE Midcap Liquid 15 Index is not efficient even in the weak form, so the security prices do not reflect all past information and it is possible to earn super-normal gain by utilizing past information as share prices do not adjust instantaneously in response to any new information release in the market.

Efficient Market Hypotheses (EMH) suggests that stock prices fully reflect all available information on a stock market thus investors cannot gain abnormal returns. However, the researchers have observed some evidences against the EMH and it is called as anomaly. There is a vast number of studies for intra-month effect, turn of the month effect and the turn of the year effect in Turkey and BIST-100 is often used in these studies are the starting point of this research. For this purpose unlike other studies, it is tested whether there is intra-month effect, turn of the month effect and the turn of the year effect by using daily data for 24 Borsa Istanbul indexes for the period January 2005-February 2015. Results show that there is evidence for intra-month effect in one index and turn of the month effect is found in 14 indexes. Furthermore there is no evidence for turn of the year effect in all 24 indexes.

Stock market price index prediction is a challenging task for investors and scholars. Artificial neural networks have been widely employed to predict financial stock market levels thanks to their ability to model nonlinear functions. The accuracy of backpropagation neural networks trained with different heuristic and numerical algorithms is measured for comparison purpose. It is found that numerical algorithm outperform heuristic techniques.

Although HFT has become a main feature of financial markets internationally, its impact on equity markets’ functioning is still under discussion, since HFT can negatively affect market quality and stability. Regulatory measures recently adopted on both sides of the Atlantic to better control HFT-related risks chiefly focus on markets’ stability, orderly functioning, and integrity, but poorly consider how HFT interacts with the allocative function of price discovery. In order to fill this gap, this article focuses on how HFT-related informational inequalities among investors threaten equity markets’ (long-term) efficiency. Subscription to news wires and market data-feeds, along with co-location, grant HFTs early access to market-moving information that allows for latency arbitrage and trading ahead of other investors, which can discourage informed (slower) traders from undertaking costly fundamental analysis. Therefore, HFT challenges the theoretical framework underlying the Efficient Capital Markets Hypothesis, and can negatively affect price accuracy, real resource allocation and equity markets’ allocative efficiency. Against this backdrop, this article develops a conceptual framework for possible regulatory strategies aimed at limiting the negative effects of HFT on allocative market efficiency by reducing HFTs’ speed advantage or incentivizing fundamental informed traders to enter markets where they face costly pressures to compete with HFTs. Restricting the sale of trade data feeds or mandating speed bumps may discourage HFT and weaken its positive effects in terms of increased liquidity and better short-term price discovery, without definitely curbing HFT-related risks concerning price long-term accuracy, while replacing the current continuous trading regime with a batched auctions-based regime would ask for major regulatory changes. Introducing an EU-like continuous, event-driven, and timelier, disclosure regime could limit these possible drawbacks by providing informed traders with more frequent and cheaper access to relevant information.

The Effect of Macroeconomic Variables on Stock Market Returns in Ghana (2000-2013) by Charles Barnor MBA-Professional Accountancy, University of Canberra, Australia, 2000 MBA-Finance, University of Canberra, Australia, 1999 BSc. Administration, Banking and Finance, University of Ghana, Ghana, 1994 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Management Walden University December 2014 Abstract Variations in macroeconomic indicators affect the performance of the stock markets. In Ghana, although the performance of the Ghana Stock Exchange (GSE) has been affected by macroeconomic variables from January 2000 to December 2013, the mechanisms of these relationships have not been studied. The purpose of this research was to examine the relationships between selected macroeconomic variables and their effect on the stock market returns on the Ghana stock market. The research questions addressed whether macroeconomic variables had si...

The present research investigates the effects of cash conversion cycle on economic value added among companies listed on Tehran's stock exchange. The sample of study includes 118 companies. The multivariate-regression method has been used for analysis of research hypotheses. Results indicated that a reverse and statistically significant relationship exists between companies' cash conversion cycle and their economic value added. In other words, by reducing the length of cash conversion cycle within reasonable limits, companies are able to increase their economic value added.

Modern corporate organizations listed in the security markets periodically communicate their financial
performance to stakeholders through earnings announcements. Efficient markets immediately absorb and reflect
the new information into the share prices. This paper examines the effect of annual earnings announcement at the
Nairobi Securities Exchange (NSE) by analyzing changes in share prices and trading volumes for the period from
2006 to 2010. Abnormal returns during the event window of 91 days were determined using the event study
methodology employing the market model on data from 5 listed companies. Further, the volume reactions were
examined by use of the trading activity ratio (TAR). Inferential and descriptive statistics were used to test for
significant effect on TAR and price changes. The results obtained indicate that the abnormal returns and TAR
were not significant at 5% probability level. Thus the NSE is of semi-strong efficiency, whereby it is not possible
to earn abnormal returns in the NSE using the publicly available information

Purpose − The purpose of this study is to examine stock price and trading volume reactions to name changes of the Toronto Stock Exchange listed companies. Previous studies present conflicting evidence on reactions to corporate name changes in U.S. and other capital markets.
Design/methodology/approach − This study uses the event study methodology to calculate abnormal returns and trading volume around the announcement, approval, and effective dates of corporate name changes. It also contrasts abnormal returns between major and minor name changes, signaling focused and diversified strategies, accompanied with a ticker symbol change and without a ticker change, structural and pure name changes, as well as brand adoption and radical name changes.
Findings − Companies tend to experience a significant run-up in stock price in the period preceding the announcement of a name change. The stocks also show a significant positive abnormal return around the effective date. In addition, corporate name changes are associated with significant increases in trading volume for several days starting from the approval date. Most importantly, the type of a name change matters, as reflected in significance levels of abnormal return and trading volume reactions to various types of corporate name changes.
Research limitations/implications − The limitation of this study comes from the difficulty to precisely identify the date when the market learns about a possible corporate name change.
Originality/value – This study is the first to examine market reactions to name changes of Toronto Stock Exchange listed companies. Most importantly, whereas previous studies focus on the announcement day, this paper also considers the approval and effective days. It also contrasts responses between name changes accompanied with a new ticker and name changes without a ticker change.

This Research Project is undertaken to acquire the Degree of Master of Business Administration (MBA). It can be helpful for all future researches related to Reversal and Momentum effects.

Reversal effect is a theory that stock prices overreact to relevant news so that extreme investment performance tends to reverse itself. Reversal effect means “A change in the direction of a price trend”.
Momentum effect says that what was strongly going up in the past will probably continue to go up in the near future.

This study was conducted to analyse the reversal and momentum effect in BRICS nations. The BRICS nations consist of five countries including Brazil, Russia, India, China and South Africa. To study the reversal and momentum effect on BRICS Nations, monthly closing data from various organizations (the stock exchanges) were extracted. The stock exchanges selected were Bolsa de Valores de São Paulo, Mercadorias & Futuros de São Paulo (BM&F BOVESPA) of Brazil, Moscow Exchange (MOEX) of Russia, National Stock Exchange (NSE) of India, Hong Kong Stock Exchange (HKE) of China and Johannesburg Stock Exchange (JSE) of South Africa.
 
In this project I have used Fama French 3 Factor Model to analyze the Reversal and Momentum effect in BRICS countries during the period 1st January 2009 to 31st December 2014.In this project work the index of a particular country is divided into two group’s winners group and losers group. The winners group and loser group is further divided into three sub categories Value, Neutral and Growth. On the basis of value, Neutral and Growth the SMB and HML calculations are done for each country.

In this project Brazil shows Momentum effects for all the sample periods starting from Jan 09 till Dec 14,
India and South Africa shows Reversal effects for all the sample periods starting from Jan 09 till Dec 14. 
In case of Russia reversal effect is observed in Jan-June 10 and Jul –Dec 10 only. 
In case of China reversal is observed in 5 sample periods out of 12 sample periods. 
Emerging countries experienced inflated momentum effect which is good for investor.

The presence of seasonal effects in monthly returns has been reported in several developed and emerging stock markets. The objective of this study is to explore the interplay between the month-of-the-year effect and market crash effects on monthly returns in Indian stock markets. The study uses dummy variable multiple linear regression to assess the seasonality of stock market returns and the impact of market crashes on the same. The results of the study provide evidence for a month-of-the-year effect in Indian stock markets, particularly positive November, August, and December effects, and a negative March effect. Further, the study suggests that the incidence of market crashes reduces the seasonal effects.

The objective of this study was to establish the effects of dividend announcement to current market prices at the Nairobi Securities Exchange, with four specific objectives; to determine the information content of dividend announcements, to determine the extent to which prices converge to new values after dividend announcements on a sector by sector basis, to establish the market reaction to announced information and also to establish whether investors can secure excess returns by acting on announced information. A 66 days event timeline was employed from 2005 to 2015 on daily closing stock prices. A sample of 179 dividend announcements from 22 listed companies in 8 sectors were drawn and analysed using an OLS Market Model. Findings of the research conclude that; dividend announcements do have an impact on stock prices for the Agricultural, Banking, Commercial, Construction, Manufacturing and Telecomm Sectors and not for the Energy Sector, Insurance Sector and the Nairobi Securities Exchange Market. It takes more than five days for prices to adjust to their correct values and this makes it possible for market players to profit from the inefficiency by earning abnormal returns. We conclude that the Nairobi Securities Exchange is not semi-strong form efficient.

The purpose of this study is to test whether the Indian pharmaceutical companies support efficient market hypotheses (EMH) and examine the efficiency of the Indian stock market in three forms, i.e., the weak, the semi-strong, and the strong form of market efficiency. For testing the weak form of efficiency, researchers collected stock price data of 10 listed pharmaceutical companies for the past 6 years, from 2012 to 2017 from the NSE website, and conducted a run test. To test the efficiency of semi-strong form, researchers collected data on the announcement of events like buyback, stock split, rights issue, dividend, bonus issue. They conducted an event study on the data. For testing the strong form of efficiency, researchers collected data consisting of NAV of some mutual funds (pharmaceutical funds) and the returns of a benchmarking index to compare. The study concludes that the pharmaceutical companies and Indian stock market is efficient in the weak form of EMH and not efficient in the semi-strong and strong form of EMH.

Background: Gold exchange-traded funds, since introduction, are primarily aimed at tracking the price of physical gold in the financial market. This, a category of exchange-traded funds, whose units represent physical gold, is traded on exchanges like any other financial instrument. In the Indian financial market, gold exchange traded funds were introduced a decade ago to facilitate ordinary households' participation in the bullion market. They were also designed to assist in the price discovery mechanism of the bullion market. Presentation of the hypothesis: In this paper, it is attempted to check if one of the constituents of price discovery mechanism, informational efficiency, has been achieved in gold exchange-traded funds' market. Information efficiency becomes evident only when all available information is reflected in the market price of the instrument. Testing the hypothesis: Therefore, in order to assess the weak-form efficiency of the gold exchange-traded funds market, the daily returns of five gold exchange-traded funds traded on the Indian Stock Exchange over the period March 22, 2010, to August 28, 2015, were used. The non-parametric runs test, the parametric serial correlation test, and the augmented Dickey-Fuller unit root test are employed.

Tax is one of the most major political tools of governments and the most important source of their incomes and costs supplement. The dependency to the oil incomes can be reduced to zero by prevention of tax evasion. For decreasing the dependency to the oil incomes, we are needful to increase the levies in country. The optimized levies and actual taxes not only increase the government's tax incomes but lead to a tax justice. The disclosure of accounting information was notified as one of the most important subjects for researchers from long time ago and the final product is considered as an accounting system. Actually, the final purpose of accounting system is providing information for benefited persons in the form of in and out-organization reports and the complete information disclosure can be an underlie of fiscal justice. This study surveys the relationship between the influences of effective tax rate and the level of financial statements disclosure of accepted companies in Tehran Stock Exchange. In this research, the multi variable regression analysis according to the panel data in order to survey the relationship of effective tax rate with the level of financial statements disclosure during the years of 2011 to 2015. The study sample is included of 94 listed companies in Tehran Stock Exchange for a temporal duration of 5 years. The results show that there is a reverse meaningful relationship between the effective tax rate and the level of mandatory financial statements disclosure; means, as effective tax rate gets higher, the level of mandatory disclosure gets lower and also there isn't any meaningful relationship between effective tax rate and the level of voluntary financial statements disclosure.

Financial time series forecasting and the feelings control are two complex problems, together decreasing the probabilities for the traders to be successful. This article shows a new and original development to be used in the financial markets, with special interest in the Colombian market development, which improves the return on transactions while decreases the risk taken, due to forecasts made via artificial intelligence, econometric techniques or even classic technical analysis but avoiding the impact of feelings like fear and greed. The best forecast technique by its capability to fit the original time series in a test sample is applied in a trading robot that we call SANTI3; the Robot (also known as Algo) composition and the main rules in their decision taking as the process to develop their modules is shown in different tables and graphics. A Special emphasis is made in the risk management module algorithm and the " trailing stop " technique. The positive results of an active strategy in different markets such as EURUSD, S&P 500 and Gold, and their testing results with the iColcap© compared with a passive strategy brings ideas to improve further the research.

The aim of the paper is to evaluate the effects of the intervention of the Chinese government undertaken during the 2015–2016 crisis on the Shanghai Stock Exchange (SSI). The following research hypothesis was set up: in the long run, both the initial efforts of the Chinese authorities to drive individual investors to invest in stock exchanges along with the interventions launched by the government to stop the market falls were not relevant to stock valuation. The study results have proven that in the analysed time monetary authorities, as well as government and regulatory bodies, generated many decisions and announcements which were expected to influence the behaviour of the stock exchange investors. In short term it created artificially market anomalies, observed between the Q4 2014 and Q1 2016. The interventions interfered with the long term growth trend of SSI index, however did not shift this trend and after interventions ended it was apparently ongoing and not disturbed until 2...

This paper examines the relationship between stock market index and macroeconomic policies (Fiscal and Monetary) on Iran's economy using quarterly data in the period 1999-2013. This study employed cointegration test and vector autoregressive models (VAR) to examine relationships between the stock market index and the macroeconomic variables. The empirical results reveal that a positive money shock can increase stocks return. According to impulse responses, the government expenditure had a slight impact on stocks return in the short term. But the government expenditure has a positive effect on exchange index in long run. Also the effect of taxes on the stock's price index is negative, so that it reaches its maximum level after the third lag and then alleviates. The GDP shock has positive effect on the stock's price index. Increase in production level leads to increase in earnings and profitability, leading to a positive response from stocks index. Therefore the results sh...

We all know that what gets measured gets done. However, the organizations which pursuing the knowledge management don't have any process for measuring the organizational knowledge or intellectual capitals of assets. The traditional financial reporting cannot measure the actual value of the company (or company) and will suffice the measurement of short-term balance sheet and tangible assets. In fact, the intellectual capital provides a new complete model for observing the actual value of the organizations and through its using; the future value of company can be also measured. Due to the willingness to assess and consider the real value of intangible assets, the intellectual capital has increased more than ever to company, shareholders (investors) and other stakeholder groups. In this study, according to the justified Pulic model (e-VAIC™), the intellectual capital value of listed companies in Tehran Stock Exchange during 10 years period from 2005 to 2015 got measured and then, the relationship between components of intellectual capital and companies' performance was evaluated. In the current study, the statistics method was used and data analysis was conducted with multifold regression and correlation coefficient. The sampling was continuously for a period of 10 years which the company size and financial leverage were considered as control variable. The results indicate that there is a meaningful positive relationship between intellectual capital and financial performance of listed companies in Tehran Stock Exchange. According to the results, using this model for achieving higher profit can be intensely recommended for utilizing companies, shareholders, investors and other beneficiaries.

CAPM has been a great milestone in asset pricing theory, explaining the risk-return characteristic of financial assets. However, over a few decades the validity of CAPM has been put to test by a large number of researchers. In this study, we test the validity of CAPM in India on the stocks listed on the National Stock Exchange by using Fama and McBeth (1973) two step procedure. Our results show absence of any significant relationship between betas and risk premiums and therefore we conclude that CAPM is not a valid test in explaining the risk-return characteristics of assets listed on the National Stock Exchange over the sample period.

We conduct a rigorous analysis to find out the speed of adjustments in futures and spot indices on NSE NIFTY 50 in short run as a part of examining the efficiency of financial futures market in India. Towards that, we undertake the analysis of long run and short run efficiencies separately, and use Engle-Granger's Error Correction Mechanism (ECM) so that a clear picture of short run efficiency in terms of speed of adjustments can emerge. The rigour manifests in the analysis of 412538 data points that breed from (i) the choice of five different time intervals spanning from 1-minute to 120-minutes using high frequency data, and (ii) examining 100 lags of 1-minute interval. Long run efficiency is a precondition for examining short run efficiency. We document an excellent state of affairs for long run efficiency across all five intervals of time. Most of the price discovery takes place in futures market, and the spot market follows it with a lag of 9 minutes, effectively. However, it takes 35 minutes to completely return to the desired relationship once a drift has taken place. The increase in the speed of adjustments, as compared to the speed documented in previous studies can be attributed to the large-scale adoption of the high frequency (i.e. algorithmic) trading, in recent times. Our findings suggest that traders can effectively use the near month contract of NIFTY 50 Futures to hedge their open positions in the index or any other stock. JEL Classification: G10, G14, G19

This paper employs GRS test to empirically compare the applicability of five alternatives of asset pricing models for
55 shares listed on the EGX100 for the Egyptian stock market: 1) the CAPM, 2) the Fama-French three factor model,
3) the Cahart four factor model, 4) liquidity-augmented four factor model, 5) and the five factor model (liquidity and
momentum-augmented Fama-French three factor model. The sample is split into six portfolios sorted on size and
book-to market ratio and 45 shares are excluded due to data unavailability. Our results based on GRS (1989) show
evidence that Fama-French model is the best and reject the other models.