Sampling Practices of Internal Auditors at Corporations on the Standard & Poor's Toronto Stock Exchange Composite Index*

2009 ◽  
Vol 8 (3) ◽  
pp. 215-234 ◽  
Author(s):  
Michael Maingot ◽  
Tony K. Quon
Keyword(s):  
Stock Exchange ◽  
Composite Index ◽  
Toronto Stock Exchange ◽  
Internal Auditors

scholarly journals Converting TSX 300 Index to S&P/TSX Composite Index: Effects on the Index’s Capitalization and Performance

2016 ◽  
Vol 8 (6) ◽  
pp. 250 ◽  
Author(s):  
Shamsul Alam ◽  
Ebenezer Asem ◽  
Shirin Shams
Keyword(s):  
Important Determinant ◽  
Stock Exchange ◽  
Tracking Error ◽  
Market Performance ◽  
Composite Index ◽  
Equity Market ◽  
Toronto Stock Exchange ◽  
And Performance

<p style="margin: 0in 0in 8pt; text-align: justify; line-height: normal;">In May 2002, the TSX (Toronto Stock Exchange) 300 Index was converted to S&amp;P/TSX Composite Index, increasing the flexibility of stock addition to, and deletion from, the Index. We study whether the increased flexibility enhances the Index’s ability to mimic the Canadian equity market performance and to represent the equity market. Our results show that the S&amp;P/TSX Composite Index captures a higher proportion of the equity market and has a lower tracking error than the TSX 300 Index. This suggests that flexibility in updating the constituents of an index is an important determinant of the index’s ability to represent the underlying market.</p>

scholarly journals The Performance of Canadian Listed Cannabis Equities: 1996-2020

2021 ◽  
Vol 14 (8) ◽  
pp. 17
Author(s):  
Raymond A.K. Cox ◽  
Quan Cheng
Keyword(s):  
Stock Exchange ◽  
Composite Index ◽  
Medical Marijuana ◽  
Investment Performance ◽  
Over The Counter ◽  
Toronto Stock Exchange ◽  
The Us ◽  
Money Managers ◽  
High Investment ◽  
Skewness And Kurtosis

This research investigates the investment performance of Canadian listed cannabis stocks. Canada legalized medical marijuana in 2001, following the initiation of medical marijuana authorization by some states in the US starting in 1996, and completely approved cannabis products in 2018. Investing in the 89 Canadian cannabis equities (listed on the Toronto Stock Exchange, Canadian Securities Exchange, Toronto Venture Stock Exchange, and Over-the-Counter Market) as an industry portfolio, based on weekly returns for the 1996 to 2020 period, generated high mean returns, standard deviation, positive skewness, and kurtosis. Robustness tests taking the winsorised returns (deleting the top and bottom 10 percent of returns) produced qualitatively similar results. Further, both the portfolio alpha and beta were extremely high. More so, the Canadian cannabis portfolio garnered excess returns when compared to the Standard and Poor&rsquo;s Toronto Stock Exchange Composite Index. Money managers, financial analysts, and investors should contemplate including Canadian listed &nbsp;cannabis stocks based on their high investment return.&nbsp;

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

scholarly journals The Influence of Trading Volume, Market Trend, and Monetary Policy on Characteristics of the Chinese Stock Exchange: An Econophysics Perspective

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 985-998
Author(s):  
Meng Ran ◽  
Zhenpeng Tang ◽  
Weihong Chen
Keyword(s):  
Monetary Policy ◽  
Trading Volume ◽  
Stock Exchange ◽  
Composite Index ◽  
Policy Formulation ◽  
Time Intervals ◽  
Monetary Policies ◽  
Policy Cycles ◽  
Trading Volumes ◽  
Healthy Growth

Abstract The paper adopts the financial physics approach to investigate influence of trading volume, market trend, as well as monetary policy on characteristics of the Chinese Stock Exchange. Utilizing 1-minute high-frequency data at various time intervals, the study examines the probability distribution density, autocorrelation and multi-fractal of the Shanghai Composite Index. Our study finds that the scale of trading volume, stock market trends, and monetary policy cycles all exert significant influences on micro characteristics of Shanghai Composite Index. More specifically, under the conditions of large trading volumes, loose monetary policies, and downward stock trends, the market possesses better fitting on Levy’s distribution, the volatility self-correlation is stronger, and multifractal trait is more salient. We hope our study could provide better guidance for investment decisions, and form the basis for policy formulation aiming for a healthy growth of the financial market.

Does tick size influence price discovery? Evidence from the Toronto Stock Exchange

2002 ◽  
Vol 23 (1) ◽  
pp. 49-66 ◽  
Author(s):  
Marie-Claude Beaulieu ◽  
Shafiq K. Ebrahim ◽  
Ieuan G. Morgan
Keyword(s):  
Price Discovery ◽  
Stock Exchange ◽  
Tick Size ◽  
Toronto Stock Exchange

Financial statement effects of adopting IFRS: the Canadian experience

2018 ◽  
Vol 26 (4) ◽  
pp. 466-491 ◽  
Author(s):  
Eva K. Jermakowicz ◽  
Chun-Da Chen ◽  
Han Donker
Keyword(s):  
Financial Reporting ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Financial Statement ◽  
Net Income ◽  
Cross Sectional ◽  
Toronto Stock Exchange ◽  
Content Type ◽  
Publicly Traded Companies ◽  
Interaction Terms

Purpose The purpose of this study is to examine the effects of adopting International Financial Reporting Standards (IFRS) on financial statements of the largest Canadian firms (S&P/TSX 60) listed on the Toronto Stock Exchange (TSX). Design/methodology/approach This study investigates the financial statement effects of 46 companies from the S&P/TSX 60 index which report under IFRS in 2011 and switched to IFRS from CGAAP. This study used panel data analysis, which can be considered as more powerful when conducting cross-sectional and in time analysis among companies. Because of weakness of Cramer statistic on R-square, the authors used interaction terms as suggested by Hope (2007). Findings Consistent with the authors’ perceptions, this study finds that significant effects of adopting IFRS are associated with industry practices. The empirical results show that the adoption of IFRS in Canada created more relevant financial reporting for book value of equity and net income in the post-adoption periods. Originality/value This study should be of interest to the US regulators considering IFRS adoption by US publicly traded companies as well as to regulators, standard setters and listed companies in all countries worldwide that are in transition to IFRS.

scholarly journals Stock Market Prediction Using Artificial Neural Networks

2012 ◽  
Vol 6-7 ◽  
pp. 1055-1060 ◽  
Author(s):  
Yang Bing ◽  
Jian Kun Hao ◽  
Si Chang Zhang
Keyword(s):  
Neural Network ◽  
Prediction Models ◽  
Learning Algorithm ◽  
Stock Exchange ◽  
Back Propagation ◽  
Composite Index ◽  
Network Models ◽  
Back Propagation Neural Network ◽  
Neural Network Models ◽  
The Neural Network

In this study we apply back propagation Neural Network models to predict the daily Shanghai Stock Exchange Composite Index. The learning algorithm and gradient search technique are constructed in the models. We evaluate the prediction models and conclude that the Shanghai Stock Exchange Composite Index is predictable in the short term. Empirical study shows that the Neural Network models is successfully applied to predict the daily highest, lowest, and closing value of the Shanghai Stock Exchange Composite Index, but it can not predict the return rate of the Shanghai Stock Exchange Composite Index in short terms.

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