The process of gathering and analyzing Twitter data to predict stock returns EC115. Economics
|
|
- Allison Stone
- 8 years ago
- Views:
Transcription
1 The process of gathering and analyzing Twitter data to predict stock returns EC115 Economics
2 Purpose Many Americans save for retirement through plans such as 401k s and IRA s and these retirement plans save money through mutual funds, which are groups of stocks. Sometimes these mutual funds can actually lose money for potential retirees. In 2008, on average, employees lost $10,000 on their retirement savings (Brandon, 2009). Currently, investors seeking information about public entities traditionally gather the majority of their data from financial publications and documents filed by a company with the Securities Exchange Commission, which sources typically contain financial data including revenues, earnings per share, price earnings ratios, cash flows, dividend yields, product launches and company management strategies (Rader, 2006). However, this purely financial approach to market prediction neglects the bullish or bearish sentiments of the public that play a significant role in movement of the market. Due to this total dependence on financial data from investors, stock market predictions are generally inaccurate (Ferri, 2013). By 2008, CXO had collected and graded more than 5,000 predictions and the accuracy of these predictions have stabilized at about 48 percent ever since (Figure 1). Figure 1. Data collected on the accuracy of stock market predictions by the CXO advisory group.
3 Hypothesis The experiment sought a correlation between the calculated social media sentiment value and the stock returns of the company. The hypothesis was that a positive social media sentiment would result in an increase in stock returns and a negative social media sentiment would result in a decrease in stock returns. The null hypothesis was that social media sentiment would have no impact on stock returns. Background Literature Review Social Media is an outlet for instant news which is valuable to investors since accurate news about a company is a reliable predictor of that company's stock value. In one study, principal components analysis was used to reduce the approximately 400 features extracted from social media to about 30 features, capturing about 25% of the variance. An Ordinary Least Squares regression was used to forecast stock price movements from the approximately 30 variables (Sisk, 2013). By conducting these statistical processes on data collected from social media, news metadata can inform short term future price movements and volatility. In a study done by Fisher and Statman (2000), there was no significant relationship between change in sentiment in one month and stock returns in the following month. For large market capitalization stock returns, the relationship was negative for all sentiment groups but never statistically significant. The relationship between change in sentiment during a month and the following month's stock returns was positive for the small market capitalization stocks of the Center for Research in Security Prices (CRSP) 9 10, but that relationship also was not statistically significant.
4 Economists at the University of Rochester, Cornell University, and the University of Texas concluded that individual investor sentiment predicts future stock returns, and that investor sentiment is independent from data involving past returns or past volume (Kaniel et. al, 2004). Furthermore, the trading of these individual investors predicts weekly returns for stocks of all market capitalizations, while data involving past returns are only predictive of stock with a small market capitalization over the same time period. These findings show that the sentiment of the individual investor is highly indicative of the movement of stock price. When the propensity of investors to speculate is high and when the stock is volatile, sentiment is a significant predictor of the fluctuations in the stock price (Baker et. al, 2007). However, when a stock is stable and investors are calm, sentiment has less bearing on the movement of stock price. Using the Facebook's Gross National Happiness Index (FGNHI), which determined the average optimism and pessimism of its users in a particular region, researchers found a significant positive relation between sentiment and contemporaneous stock market returns, showing that optimistic sentiment is related to gains in the market index and pessimistic sentiment is related to losses in the market index (Siganos, 2014). However, the procedure of using public sentiment as an indicator of the market may be flawed since the relation between sentiment and stock returns is subject to reverse causality. For example, when investors profit or loss from the market, those sentiments may be expressed through social media. These specific sentiments are not indicative of what the movement of the market will be tomorrow. Bollen, Mao, and Zeng (2011) investigated whether measurements of collective mood states derived from large scale Twitter feeds are correlated to the value of the Dow Jones
5 Industrial Average (DJIA) over time. They used OpinionFinder to measure positive vs. negative mood and Google Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). Through this process, an accuracy of 86.7% was achieved in predicting the daily up and down changes in the closing values of the DJIA and the Mean Average Percentage Error (MAPE) was reduced by more than 6%. Research Methodology Six companies were chosen for the calculations: Kirkland (KIRK), Zynga (ZNGA), Aramark (ARMK), Foot Locker (FL), Verizon (VZ), and Disney (DIS). These companies were chosen from the Russell Index Member Lists. Kirkland and Zynga were chosen from the Russell Microcap List (Russell Investments, 2011), which lists the stocks of highly successful small companies; Aramark and Foot Locker were chosen from the Russell Midcap List (Russell Investments, 2011), which lists the stocks of highly successful mid size companies; Verizon and Disney were chosen from the Russell 1000 Index List, which lists the stocks of highly successful large companies. These companies were chosen for their varying product fields, their importance to consumer markets, and their distinctive names. A Python program, entitled StockPile was developed. The program asked for a company name to predict the stock price of. Using the Twitter REST API, all the tweets mentioning the name of the specified company in the last eight days was collected. As the Twitter REST API has a rate limit on the number of queries possible per fifteen minute intervals, multiple API accounts were created and cycled through each time one hit the limit. Python s Natural Language Toolkit (NLTk) associated a sentiment and polarity value for each Tweet and the Twitter API associated the number of favorites, the number of retweets, and the number of followers of the
6 author for each Tweet. However, the number of followers metric was removed after its statistical insignificance was noted. The Tweet, with the corresponding data, was stored as a TweetObj Object as shown in Figure 2. The metrics of the TweetObjs were then related with the relevant stock prices of that company with a two day time shift in the future. The TweetObjs were saved in a Pickle file. This process was repeated for each of the tested companies: Kirkland (KIRK), Zynga (ZNGA), Aramark (ARMK), Foot Locker (FL), Verizon (VZ), and Disney (DIS). Figure 2. Class Diagram for the TweetObj class. A Least Squares Multiple regression was conducted on the metrics of the TweetObjs and the stock prices with a certain time shift. The most accurate time shift was determined by conducting a Least Squares Multiple regression on all the different time shifts from a zero time shift to a time shift of a week. Whichever regression model provides the least p value and the greatest correlation coefficient of the predictive model will determine the delay in the sentiment on twitter of a company affecting the stock price of that company. The predictive model with the most accurate time shift will provide an equation to predict the stock price in the following form:
7 [ n C if i ] + K = P t i=1 Where n is the number of features, C i is the coefficient of the feature value, F i is the feature value, K is a constant, and P t is the stock price after a certain time delay. Figure 3. Data Flow Diagram for the StockPile algorithm. After the algorithms were developed, for the following three days, a testing algorithm, encapsulated in testing.py, was run after the markets closed at 3:00 PM EST. This program collected Tweets via the Twitter REST API for a period of one day, and ran the values through the predictive equation to determine a predicted stock price associated with each Tweet. These stock prices were then compared to the actual stock price at the germane time. An R 2 score was then calculated comparing the predicted values to the actual values.
8 Figure 4. Tweets referencing a certain company are collected using the Twitter Streaming API. Each terminal window is collecting Tweets about a certain company. Figure 5. The output the computer program that collects the Tweets and associates them with a stock price is shown above. The output shows each Tweets ID, properties of that Tweet, and the associated stock price with that Tweet. The last line of the output shows the coefficients and the constant for the predicted model. The coefficients are in the brackets. The companies being run
9 in the terminals from the top left terminal to bottom left terminal clockwise are Kirkland, Zynga, Aramark, Foot Locker, Verizon, and Disney. Figure 6. Using the predictive model provided by the previous program, this program tests the accuracy of the predictive model. The R 2 value is shown at the bottom of the terminal window. The companies being run in the terminals from the top left terminal to bottom left terminal clockwise are Kirkland, Zynga, Aramark, Foot Locker, Verizon, and Disney. Results Kirkland (KIRK) Average volume of Tweets per day: 3442 Equation: e 01a e 05b e 02c Where a is the sentiment, b is the number of favorites, and c is the number of retweets Day R 2 Value Day Day Day Figure 7. Data for Kirkland
10 Zynga (ZNGA) Average volume of Tweets per day: 938 Equation: a b c Where a is the sentiment, b is the number of favorites, and c is the number of retweets Day R 2 Value Day Day Day Figure 8. Data for Zynga Aramark (ARMK) Average volume of Tweets per day: 179 Equation: a b c Where a is the sentiment, b is the number of favorites, and c is the number of retweets Day R 2 Value Day Day Day Figure 9. Data for Aramark Foot Locker (FL) Average volume of Tweets per day: 1103 Equation: a b c Where a is the sentiment, b is the number of favorites, and c is the number of retweets Day R 2 Value Day Day
11 Day Figure 10. Data for Foot Locker Verizon (VZ) Average volume of Tweets per day: Equation: e 01a e 05b e 03c Where a is the sentiment, b is the number of favorites, and c is the number of retweets Day R 2 Value Day Day Day Figure 11. Data for Verizon Disney (DIS) Average volume of Tweets per day: Equation: e 01a e 06b e 02c Where a is the sentiment, b is the number of favorites, and c is the number of retweets Day R 2 Value Day Day Day Figure 12. Data for Disney Conclusions The R 2 value is the coefficient of determination. The coefficient of determination is the proportion of the variance in the dependent variable that is predictable from the independent
12 variable. The higher the R 2 value, the datasets are more correlative with an upper bound of 1. The lower the R 2 value, the less correlated the datasets. The datasets compared in this experiment are the sets of predicted stock values using the model based on Tweets, related features, and the actual stock price. All but one of the trials in the experiment had a negative coefficient of determination. This means the model predicted the stock price inaccurately. The Efficient Market Hypothesis states that information relevant to stock price will immediately affect the stock price. Since the social media was highly uncorrelated with the stock price according the values of the coefficient of determination, the Efficient Market Hypothesis proves that information on social media is not relevant to the fluctuation in stock price. The results of this experiment also prove that stock movement follows a Markov Chain. A Markov Chain means that the state of something currently is not related at all to the previous states that it has been in. An extension of this type of movement is a random walk. A random walk is a succession of random steps. In the case of stocks, the movement of stocks can go either up or down. These movements represent the total randomness of fluctuations in the stock market. Nobel Prize winning Economist, Gene Fama (1965) finds that empirical evidence provides strong support for the random walk model. He notes that economists must prove that models can predict prices better than simply randomly choosing buy or sell. As Figure 1 showed, the average accuracy of predictive models is only 48 percent, less than the fifty fifty chance of choosing randomly. The results of this experiment corroborate his findings. The major finding of this experiment was that social media is irrelevant to determining stock returns. Further research to seek a correlation between Social Media and stock returns may include taking into account longer periods of time for data gathering and testing, using more sensitive natural
13 text analysis tools, and calculating based on a time shift, with an assumption that sentiment data from the previous days would impact future days.
14 Bibliography Baker, M. and Wurgler, J. (2007). Investor Sentiment in the Stock Market. Bollen, J., Mao, H. and Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), pp.1 8. Fama, E. (1965). Random Walks in Stock Market Prices. Financial Analysts Journal, 21(5), pp Brandon, E. (2009, February 12). How Did Your 401(k) Really Stack Up in 2008? [online] US News. Available at: did your 401k reallystack up in 2008 Ferri, R. (2013). It's Official! Gurus Can't Accurately Predict Markets. [online] Forbes. Available at: official gurus cant accurately predictmarkets/ [Accessed 28 Dec. 2014]. Fisher, K. and Statman, M. (2000). Investor Sentiment and Stock Returns. Financial Analysts Journal, 56(2), pp Kaniel, R., Saar, G. and Titman, S. (2004). Individual Investor Sentiment and Stock Returns. Li, X., Xie, H., Chen, L., Wang, J. and Deng, X. (2014). News impact on stock price return via sentiment analysis. Knowledge Based Systems, 69, pp
15 Minh, D. (2013). Sentiment and Influence Analysis of Twitter Tweets. US A1. Paniagua, J. and Sapena, J. (2014). Business performance and social media: Love or hate?. Business Horizons, 57(6), pp Rader, J. (2006). Method and system for conducting sentiment analysis for securities research. US A1. Russell Investments, (2011). Russell 1000 Index Member List. Washington: Russell Investments. Russell Investments, (2011). Russell Microcap Index Membership List. Washington: Russell Investments. Russell Investments, (2011). Russell Midcap Index Member List. Washington: Russell Investments. Siganos, A., Vagenas Nanos, E. and Verwijmeren, P. (2014). Facebook's daily sentiment and international stock markets. Journal of Economic Behavior & Organization, 107, pp Sisk, J. (2013). Methods and systems for predicting market behavior based on news and sentiment analysis. US A1.
16 Acknowledgements We would like to acknowledge and thank several people for providing us with an abundance of support and assistance. We would like to express our gratitude to Dr. Alex Tabarrok of George Mason University, Professor Francis DiTraglia of the University of Pennsylvania, Dr. Andrew Lo of the Massachusetts Institute of Technology, and William Li of the Massachusetts Institute of Technology for their highly supportive feedback on the Economic and programming side. We would also like to thank Dr. Csaba Gabor and Mr. Phillip Ero of the Thomas Jefferson High School for Science and Technology for providing us with support in understanding our statistical analyses. We are grateful to our lab director, Dr. Dan Burden of the Thomas Jefferson High School for Science and Technology, for patiently and proactively ensuring that we had everything we needed to conduct our experiment. Finally, and most importantly, we want to appreciate our families for their unparalleled support.
Sentiment Analysis of Twitter Feeds for the Prediction of Stock Market Movement
Sentiment Analysis of Twitter Feeds for the Prediction of Stock Market Movement Ray Chen, Marius Lazer Abstract In this paper, we investigate the relationship between Twitter feed content and stock market
More informationHow To Predict Stock Price With Mood Based Models
Twitter Mood Predicts the Stock Market Xiao-Jun Zeng School of Computer Science University of Manchester x.zeng@manchester.ac.uk Outline Introduction and Motivation Approach Framework Twitter mood model
More informationThe Viability of StockTwits and Google Trends to Predict the Stock Market. By Chris Loughlin and Erik Harnisch
The Viability of StockTwits and Google Trends to Predict the Stock Market By Chris Loughlin and Erik Harnisch Spring 2013 Introduction Investors are always looking to gain an edge on the rest of the market.
More informationSentiment Analysis. D. Skrepetos 1. University of Waterloo. NLP Presenation, 06/17/2015
Sentiment Analysis D. Skrepetos 1 1 Department of Computer Science University of Waterloo NLP Presenation, 06/17/2015 D. Skrepetos (University of Waterloo) Sentiment Analysis NLP Presenation, 06/17/2015
More informationQUANTIFYING THE EFFECTS OF ONLINE BULLISHNESS ON INTERNATIONAL FINANCIAL MARKETS
QUANTIFYING THE EFFECTS OF ONLINE BULLISHNESS ON INTERNATIONAL FINANCIAL MARKETS Huina Mao School of Informatics and Computing Indiana University, Bloomington, USA ECB Workshop on Using Big Data for Forecasting
More informationDo Tweets Matter for Shareholders? An Empirical Analysis
Do Tweets Matter for Shareholders? An Empirical Analysis Brittany Cole University of Mississippi Jonathan Daigle University of Mississippi Bonnie F. Van Ness University of Mississippi We identify the 215
More informationUsing Tweets to Predict the Stock Market
1. Abstract Using Tweets to Predict the Stock Market Zhiang Hu, Jian Jiao, Jialu Zhu In this project we would like to find the relationship between tweets of one important Twitter user and the corresponding
More informationCS 229, Autumn 2011 Modeling the Stock Market Using Twitter Sentiment Analysis
CS 229, Autumn 2011 Modeling the Stock Market Using Twitter Sentiment Analysis Team members: Daniel Debbini, Philippe Estin, Maxime Goutagny Supervisor: Mihai Surdeanu (with John Bauer) 1 Introduction
More informationCan Twitter provide enough information for predicting the stock market?
Can Twitter provide enough information for predicting the stock market? Maria Dolores Priego Porcuna Introduction Nowadays a huge percentage of financial companies are investing a lot of money on Social
More informationIt has often been said that stock
Twitter Mood as a Stock Market Predictor Johan Bollen and Huina Mao Indiana University Bloomington Behavioral finance researchers can apply computational methods to large-scale social media data to better
More informationIs the Forward Exchange Rate a Useful Indicator of the Future Exchange Rate?
Is the Forward Exchange Rate a Useful Indicator of the Future Exchange Rate? Emily Polito, Trinity College In the past two decades, there have been many empirical studies both in support of and opposing
More informationAnalysis of Tweets for Prediction of Indian Stock Markets
Analysis of Tweets for Prediction of Indian Stock Markets Phillip Tichaona Sumbureru Department of Computer Science and Engineering, JNTU College of Engineering Hyderabad, Kukatpally, Hyderabad-500 085,
More informationUsing Text and Data Mining Techniques to extract Stock Market Sentiment from Live News Streams
2012 International Conference on Computer Technology and Science (ICCTS 2012) IPCSIT vol. XX (2012) (2012) IACSIT Press, Singapore Using Text and Data Mining Techniques to extract Stock Market Sentiment
More informationThe Influence of Sentimental Analysis on Corporate Event Study
Volume-4, Issue-4, August-2014, ISSN No.: 2250-0758 International Journal of Engineering and Management Research Available at: www.ijemr.net Page Number: 10-16 The Influence of Sentimental Analysis on
More informationNeural Networks for Sentiment Detection in Financial Text
Neural Networks for Sentiment Detection in Financial Text Caslav Bozic* and Detlef Seese* With a rise of algorithmic trading volume in recent years, the need for automatic analysis of financial news emerged.
More informationSentiment analysis on tweets in a financial domain
Sentiment analysis on tweets in a financial domain Jasmina Smailović 1,2, Miha Grčar 1, Martin Žnidaršič 1 1 Dept of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, Slovenia 2 Jožef Stefan International
More informationMarket Efficiency and Behavioral Finance. Chapter 12
Market Efficiency and Behavioral Finance Chapter 12 Market Efficiency if stock prices reflect firm performance, should we be able to predict them? if prices were to be predictable, that would create the
More informationIMPACT OF SOCIAL MEDIA ON THE STOCK MARKET: EVIDENCE FROM TWEETS
IMPACT OF SOCIAL MEDIA ON THE STOCK MARKET: EVIDENCE FROM TWEETS Vojtěch Fiala 1, Svatopluk Kapounek 1, Ondřej Veselý 1 1 Mendel University in Brno Volume 1 Issue 1 ISSN 2336-6494 www.ejobsat.com ABSTRACT
More informationStock Market Forecasting Using Machine Learning Algorithms
Stock Market Forecasting Using Machine Learning Algorithms Shunrong Shen, Haomiao Jiang Department of Electrical Engineering Stanford University {conank,hjiang36}@stanford.edu Tongda Zhang Department of
More informationPrediction of Stock Performance Using Analytical Techniques
136 JOURNAL OF EMERGING TECHNOLOGIES IN WEB INTELLIGENCE, VOL. 5, NO. 2, MAY 2013 Prediction of Stock Performance Using Analytical Techniques Carol Hargreaves Institute of Systems Science National University
More informationStock Prediction Using Twitter Sentiment Analysis
Stock Prediction Using Twitter Sentiment Analysis Anshul Mittal Stanford University anmittal@stanford.edu Arpit Goel Stanford University argoel@stanford.edu ABSTRACT In this paper, we apply sentiment analysis
More informationBig Data and High Quality Sentiment Analysis for Stock Trading and Business Intelligence. Dr. Sulkhan Metreveli Leo Keller
Big Data and High Quality Sentiment Analysis for Stock Trading and Business Intelligence Dr. Sulkhan Metreveli Leo Keller The greed https://www.youtube.com/watch?v=r8y6djaeolo The money https://www.youtube.com/watch?v=x_6oogojnaw
More informationThe Use of Twitter Activity as a Stock Market Predictor
National College of Ireland Higher Diploma in Science in Data Analytics 2013/2014 Robert Coyle X13109278 robert.coyle@student.ncirl.ie The Use of Twitter Activity as a Stock Market Predictor Table of Contents
More informationA Review of Cross Sectional Regression for Financial Data You should already know this material from previous study
A Review of Cross Sectional Regression for Financial Data You should already know this material from previous study But I will offer a review, with a focus on issues which arise in finance 1 TYPES OF FINANCIAL
More informationItalian Journal of Accounting and Economia Aziendale. International Area. Year CXIV - 2014 - n. 1, 2 e 3
Italian Journal of Accounting and Economia Aziendale International Area Year CXIV - 2014 - n. 1, 2 e 3 Could we make better prediction of stock market indicators through Twitter sentiment analysis? ALEXANDER
More informationMarket Efficiency and Stock Market Predictability
Mphil Subject 301 Market Efficiency and Stock Market Predictability M. Hashem Pesaran March 2003 1 1 Stock Return Regressions R t+1 r t = a+b 1 x 1t +b 2 x 2t +...+b k x kt +ε t+1, (1) R t+1 is the one-period
More informationOn the Predictability of Stock Market Behavior using StockTwits Sentiment and Posting Volume
On the Predictability of Stock Market Behavior using StockTwits Sentiment and Posting Volume Abstract. In this study, we explored data from StockTwits, a microblogging platform exclusively dedicated to
More informationAdvantages and disadvantages of investing in the Stock Market
Advantages and disadvantages of investing in the Stock Market There are many benefits to investing in shares and we will explore how this common form of investment can be an effective way to make money.
More informationApplying Machine Learning to Stock Market Trading Bryce Taylor
Applying Machine Learning to Stock Market Trading Bryce Taylor Abstract: In an effort to emulate human investors who read publicly available materials in order to make decisions about their investments,
More informationEquity forecast: Predicting long term stock price movement using machine learning
Equity forecast: Predicting long term stock price movement using machine learning Nikola Milosevic School of Computer Science, University of Manchester, UK Nikola.milosevic@manchester.ac.uk Abstract Long
More informationHow Wall Street Works Nightly Business Report
Notes from the PBS video How Wall Street Works Nightly Business Report The New York Stock Exchange located on Wall Street in New York City, is traders can buy and sell stocks and bonds. Two major types
More informationDeriving Investor Sentiment from Options Markets
Deriving Investor Sentiment from Options Markets Chikashi TSUJI February 28, 29 Abstract The purpose of this paper is to introduce the put call ratio (PCR) as an investor sentiment index, and show the
More informationA Description of Consumer Activity in Twitter
Justin Stewart A Description of Consumer Activity in Twitter At least for the astute economist, the introduction of techniques from computational science into economics has and is continuing to change
More informationAutomated news based
Automated news based ULIP fund switching model ULIP funds switching model recommends the fund switching Parikh Satyen Professor & Head A.M. Patel Institute of Computer Sciences Ganpat University satyen.parikh@ganpatuniver
More informationThese Two Words Just Made Us 37% In 3 Months. "These Two Words. Just Made Us 37% In 3 Months"
These Two Words Just Made Us 37% In 3 Months "These Two Words Just Made Us 37% In 3 Months" Using these "two words" in your 401k, IRA or any other investment account can make you very wealthy... What are
More informationDiscussion of Momentum and Autocorrelation in Stock Returns
Discussion of Momentum and Autocorrelation in Stock Returns Joseph Chen University of Southern California Harrison Hong Stanford University Jegadeesh and Titman (1993) document individual stock momentum:
More informationGLOSSARY OF INVESTMENT-RELATED TERMS FOR NATIONAL ELECTRICAL ANNUITY PLAN PARTICIPANTS
GLOSSARY OF INVESTMENT-RELATED TERMS FOR NATIONAL ELECTRICAL ANNUITY PLAN PARTICIPANTS General Information This Glossary of Investment-Related Terms for National Electrical Annuity Plan Participants (the
More informationFrom Saving to Investing: An Examination of Risk in Companies with Direct Stock Purchase Plans that Pay Dividends
From Saving to Investing: An Examination of Risk in Companies with Direct Stock Purchase Plans that Pay Dividends Raymond M. Johnson, Ph.D. Auburn University at Montgomery College of Business Economics
More informationWILL TWITTER MAKE YOU A BETTER INVESTOR? A LOOK AT SENTIMENT, USER REPUTATION AND THEIR EFFECT ON THE STOCK MARKET
WILL TWITTER MAKE YOU A BETTER INVESTOR? A LOOK AT SENTIMENT, USER REPUTATION AND THEIR EFFECT ON THE STOCK MARKET ABSTRACT Eric D. Brown Dakota State University edbrown@dsu.edu The use of social networks
More informationGoals: What are you saving your money for college, a car, retirement? Decide what you want and how much you will need for each item.
Mr. Kaufman Investing Notes: You want to invest in order to create wealth. Are you guaranteed to be wealthy if you invest? NO! However, if you do not save money and invest it then there is no chance for
More informationWeek TSX Index 1 8480 2 8470 3 8475 4 8510 5 8500 6 8480
1) The S & P/TSX Composite Index is based on common stock prices of a group of Canadian stocks. The weekly close level of the TSX for 6 weeks are shown: Week TSX Index 1 8480 2 8470 3 8475 4 8510 5 8500
More informationUsing Twitter as a source of information for stock market prediction
Using Twitter as a source of information for stock market prediction Ramon Xuriguera (rxuriguera@lsi.upc.edu) Joint work with Marta Arias and Argimiro Arratia ERCIM 2011, 17-19 Dec. 2011, University of
More informationMarket Timing Approaches: Non- financial & Technical Indicators. Aswath Damodaran
Market Timing Approaches: Non- financial & Technical Indicators Aswath Damodaran I. Non- financial Indicators Spurious indicators that may seem to be correlated with the market but have no raconal basis.
More informationTHE STOCK EXCHANGE. Agócs Adrienne
THE STOCK EXCHANGE Agócs Adrienne OUTLINE The stock exchange shares, bonds and securities The main roles of the stock exchange Bulls and bears Types of securities Different information about the performance
More information2. Discuss the implications of the interest rate parity for the exchange rate determination.
CHAPTER 6 INTERNATIONAL PARITY RELATIONSHIPS AND FORECASTING FOREIGN EXCHANGE RATES SUGGESTED ANSWERS AND SOLUTIONS TO END-OF-CHAPTER QUESTIONS AND PROBLEMS QUESTIONS 1. Give a full definition of arbitrage.
More informationVanguard U.S. Stock ETFs Prospectus
Vanguard U.S. Stock ETFs Prospectus April 27, 2016 Exchange-traded fund shares that are not individually redeemable and are listed on NYSE Arca Vanguard Total Stock Market Index Fund ETF Shares (VTI) Vanguard
More informationFuzzy logic decision support for long-term investing in the financial market
Fuzzy logic decision support for long-term investing in the financial market Abstract This paper discusses the use of fuzzy logic and modeling as a decision making support for long-term investment decisions
More informationThe Hollywood Stock Exchange: Efficiency and The Power of Twitter
The Hollywood Stock Exchange: Efficiency and The Power of Twitter by Nathaniel Harley A special thanks to Professor Richard Walker for advising on this thesis. Also, thanks to Professor Joseph Ferrie,
More informationThere are two types of returns that an investor can expect to earn from an investment.
Benefits of investing in the Stock Market There are many benefits to investing in shares and we will explore how this common form of investment can be an effective way to make money. We will discuss some
More informationConstructing Social Intentional Corpora to Predict Click-Through Rate for Search Advertising
Constructing Social Intentional Corpora to Predict Click-Through Rate for Search Advertising Yi-Ting Chen, Hung-Yu Kao Department of Computer Science and Information Engineering National Cheng Kung University
More informationUnderstanding the Technical Market Indicators
Understanding the Technical Market Indicators Revised: October 2009 Article Written By: Md Saeed Ul Hoque Golden Gate University San Francisco, CA Sharif Gias Assistant Professor of Finance University
More informationMARKETS, INFORMATION AND THEIR FRACTAL ANALYSIS. Mária Bohdalová and Michal Greguš Comenius University, Faculty of Management Slovak republic
MARKETS, INFORMATION AND THEIR FRACTAL ANALYSIS Mária Bohdalová and Michal Greguš Comenius University, Faculty of Management Slovak republic Abstract: We will summarize the impact of the conflict between
More informationSOCIAL MEDIA AND MARKETS: The New Frontier
WHITEPAPER Gnip, Inc. www.gnip.com 888.777.7405 trading@gnip.com @gnip SOCIAL MEDIA AND MARKETS: The New Frontier Source: Gnip, Inc. For the first time in history, access to the observations, wisdom and
More informationPlease note trading advice and risk statement on pages three and four
FTSE Buzz FTSE Sentiment 6,75 7,25 1 7, 5 6,5 1 % 6,75 6,5-5 6,25 6,25-1 12 12 Euro/US Dollar Buzz Euro/US Dollar Sentiment 1.36 1.36 5 1.34 1 % 1.34 1.32 1.32-5 26 26 Realtime data and updates on s tockpuls
More informationIs Your Financial Plan Worth the Paper It s Printed On?
T e c h n o l o g y & P l a n n i n g Is Your Financial Plan Worth the Paper It s Printed On? By Patrick Sullivan and Dr. David Lazenby, PhD www.scenarionow.com 2002-2005 ScenarioNow Inc. All Rights Reserved.
More informationTechnical analysis is one of the most popular methods
Comparing Profitability of Day Trading Using ORB Strategies on Index Futures Markets in Taiwan, Hong-Kong, and USA Yi-Cheng Tsai, Mu-En Wu, Chin-Laung Lei, Chung-Shu Wu, and Jan-Ming Ho Abstract In literature,
More informationThe impact of social media is pervasive. It has
Infosys Labs Briefings VOL 12 NO 1 2014 Social Enablement of Online Trading Platforms By Sivaram V. Thangam, Swaminathan Natarajan and Venugopal Subbarao Socially connected retail stock traders make better
More informationStock Price Prediction Using Sentiment Detection of Twitter
Stock Price Prediction Using Sentiment Detection of Twitter C. Lee Fanzilli March 18, 2015 Abstract If Amazon can predict what books we want to read, Netflix can predict what movies we want to watch, and
More informationQuantitative Methods for Finance
Quantitative Methods for Finance Module 1: The Time Value of Money 1 Learning how to interpret interest rates as required rates of return, discount rates, or opportunity costs. 2 Learning how to explain
More informationTest3. Pessimistic Most Likely Optimistic Total Revenues 30 50 65 Total Costs -25-20 -15
Test3 1. The market value of Charcoal Corporation's common stock is $20 million, and the market value of its riskfree debt is $5 million. The beta of the company's common stock is 1.25, and the market
More informationPrediction of Stock Market Shift using Sentiment Analysis of Twitter Feeds, Clustering and Ranking
382 Prediction of Stock Market Shift using Sentiment Analysis of Twitter Feeds, Clustering and Ranking 1 Tejas Sathe, 2 Siddhartha Gupta, 3 Shreya Nair, 4 Sukhada Bhingarkar 1,2,3,4 Dept. of Computer Engineering
More informationPredicting Stock Market Fluctuations. from Twitter
Predicting Stock Market Fluctuations from Twitter An analysis of the predictive powers of real-time social media Sang Chung & Sandy Liu Stat 157 Professor ALdous Dec 12, 2011 Chung & Liu 2 1. Introduction
More informationINVESTING & TRADING WITH THE JSE PRICE/EARNINGS (P/E) RATIO
INVESTING & TRADING WITH THE JSE PRICE/EARNINGS (P/E) RATIO "At the end of the day, all stock price movements can be traced back to earnings." Page 1 INTRODUCTION This e-book shows how to use the daily
More informationSupplement to the Prospectus and Summary Prospectuses Dated April 28, 2015
Vanguard Large-Cap ETF Vanguard Growth ETF Vanguard Value ETF Vanguard Mid-Cap ETF Vanguard Mid-Cap Growth ETF Vanguard Mid-Cap Value ETF Vanguard Small-Cap ETF Vanguard Small-Cap Growth ETF Vanguard Small-Cap
More informationCHAPTER 11: THE EFFICIENT MARKET HYPOTHESIS
CHAPTER 11: THE EFFICIENT MARKET HYPOTHESIS PROBLEM SETS 1. The correlation coefficient between stock returns for two non-overlapping periods should be zero. If not, one could use returns from one period
More informationEVIDENCE IN FAVOR OF MARKET EFFICIENCY
Appendix to Chapter 7 Evidence on the Efficient Market Hypothesis Early evidence on the efficient market hypothesis was quite favorable to it. In recent years, however, deeper analysis of the evidence
More informationThe Stability of Moving Average Technical Trading Rules on the. Dow Jones Index
The Stability of Moving Average Technical Trading Rules on the Dow Jones Index Blake LeBaron Brandeis University NBER August 1999 Revised: November 1999 Abstract This paper analyzes the behavior of moving
More informationPITFALLS IN TIME SERIES ANALYSIS. Cliff Hurvich Stern School, NYU
PITFALLS IN TIME SERIES ANALYSIS Cliff Hurvich Stern School, NYU The t -Test If x 1,..., x n are independent and identically distributed with mean 0, and n is not too small, then t = x 0 s n has a standard
More informationVerizon 401(k) Savings Plan Investment Advice
Verizon 401(k) Savings Plan Investment Advice This message is intended to provide guidance to Verizon corporation employees to assist them in investing their savings plan assets more efficiently. If you
More informationNorthCoast Investment Advisory Team 203.532.7000 info@northcoastam.com
NorthCoast Investment Advisory Team 203.532.7000 info@northcoastam.com NORTHCOAST ASSET MANAGEMENT An established leader in the field of tactical investment management, specializing in quantitative research
More informationDivergence of Sentiment and Stock Market Trading
Divergence of Sentiment and Stock Market Trading Antonios Siganos University of Glasgow antonios.siganos@glasgow.ac.uk Evangelos Vagenas-Nanos University of Glasgow evangelos.vagenas-nanos@glasgow.ac.uk
More informationProspectus Socially Responsible Funds
Prospectus Socially Responsible Funds Calvert Social Investment Fund (CSIF) Balanced Portfolio Equity Portfolio Enhanced Equity Portfolio Bond Portfolio Money Market Portfolio Calvert Social Index Fund
More informationIntroduction To Financial Markets & Investing
Introduction To Financial Markets & Investing Matthew Lawson, M.D. Getting Started A true story Internal Medicine Intern Recently married Husband has Financial Planner assigned through his employer Neither
More informationYour model to successful individual retirement investment plans
Your model to successful individual retirement investment plans Tim Noonan Managing Director, Capital Markets Insights Russell Investments WWW.RISYMPOSIUM.COM Presented by: Important Information Please
More informationFinancial Wellness & Education. Understanding mutual funds
Financial Wellness & Education Understanding mutual funds Benefits of mutual funds Foresters Financial Services provides everyday families and individuals with financial solutions, guidance and tools,
More informationFinancial Trading System using Combination of Textual and Numerical Data
Financial Trading System using Combination of Textual and Numerical Data Shital N. Dange Computer Science Department, Walchand Institute of Rajesh V. Argiddi Assistant Prof. Computer Science Department,
More informationUsing Twitter to Analyze Stock Market and Assist Stock and Options Trading
University of Connecticut DigitalCommons@UConn Doctoral Dissertations University of Connecticut Graduate School 12-17-2015 Using Twitter to Analyze Stock Market and Assist Stock and Options Trading Yuexin
More informationForecasting stock markets with Twitter
Forecasting stock markets with Twitter Argimiro Arratia argimiro@lsi.upc.edu Joint work with Marta Arias and Ramón Xuriguera To appear in: ACM Transactions on Intelligent Systems and Technology, 2013,
More informationFund Manager s Portfolio Choice
Fund Manager s Portfolio Choice Zhiqing Zhang Advised by: Gu Wang September 5, 2014 Abstract Fund manager is allowed to invest the fund s assets and his personal wealth in two separate risky assets, modeled
More informationDynamic Relationship between Interest Rate and Stock Price: Empirical Evidence from Colombo Stock Exchange
International Journal of Business and Social Science Vol. 6, No. 4; April 2015 Dynamic Relationship between Interest Rate and Stock Price: Empirical Evidence from Colombo Stock Exchange AAMD Amarasinghe
More informationMultiple Linear Regression in Data Mining
Multiple Linear Regression in Data Mining Contents 2.1. A Review of Multiple Linear Regression 2.2. Illustration of the Regression Process 2.3. Subset Selection in Linear Regression 1 2 Chap. 2 Multiple
More informationChapter 2.3. Technical Analysis: Technical Indicators
Chapter 2.3 Technical Analysis: Technical Indicators 0 TECHNICAL ANALYSIS: TECHNICAL INDICATORS Charts always have a story to tell. However, from time to time those charts may be speaking a language you
More informationMorgan Stanley Institutional Fund Trust
INVESTMENT MANAGEMENT Morgan Stanley Institutional Fund Trust U.S. Equity Portfolios U.S. Mid Cap Value Portfolio U.S. Small Cap Value Portfolio Value Portfolio Prospectus Share Class and Ticker Symbol
More informationPattern Recognition and Prediction in Equity Market
Pattern Recognition and Prediction in Equity Market Lang Lang, Kai Wang 1. Introduction In finance, technical analysis is a security analysis discipline used for forecasting the direction of prices through
More informationSensex Realized Volatility Index
Sensex Realized Volatility Index Introduction: Volatility modelling has traditionally relied on complex econometric procedures in order to accommodate the inherent latent character of volatility. Realized
More informationUsing News Articles to Predict Stock Price Movements
Using News Articles to Predict Stock Price Movements Győző Gidófalvi Department of Computer Science and Engineering University of California, San Diego La Jolla, CA 9237 gyozo@cs.ucsd.edu 21, June 15,
More informationHIGH-RISK STOCK TRADING: INVESTMENT OR GAMBLING?
HIGH-RISK STOCK TRADING: INVESTMENT OR GAMBLING? Jennifer Arthur, M.Sc. PhD Candidate, University of Adelaide Co-Authors: Dr. Paul Delfabbro & Dr. Robert Williams 14 th Annual Alberta Research Gambling
More informationThe High-Volume Return Premium: Evidence from Chinese Stock Markets
The High-Volume Return Premium: Evidence from Chinese Stock Markets 1. Introduction If price and quantity are two fundamental elements in any market interaction, then the importance of trading volume in
More informationDetermining the Social Network Worth: Analysis, Quantitative Approach, and Application
Determining the Social Network Worth: Analysis, Quantitative Approach, and Application Sujata Jindal Computer Science Engineering Department, SGT Institute of Engg. & Technology, Gurgaon, India Dr. Ritu
More informationNeural Network Stock Trading Systems Donn S. Fishbein, MD, PhD Neuroquant.com
Neural Network Stock Trading Systems Donn S. Fishbein, MD, PhD Neuroquant.com There are at least as many ways to trade stocks and other financial instruments as there are traders. Remarkably, most people
More informationChapter 4.3. News Analysis
1 Chapter 4.3 News Analysis 0 NEWS ANALYSIS Fundamentals move currency pairs, and news moves fundamentals. News of an interest-rate hike or news of a sub-prime meltdown can cause a currency pair to change
More informationACCELERATING SALES DEVELOPMENT WITH CRM. A best practice guide to integrating sales and CRM
ACCELERATING SALES DEVELOPMENT WITH CRM A best practice guide to integrating sales and CRM Accelerating Sales Development with CRM A best practice guide to integrating sales and CRM In a web enabled business
More informationFacebook Friend Suggestion Eytan Daniyalzade and Tim Lipus
Facebook Friend Suggestion Eytan Daniyalzade and Tim Lipus 1. Introduction Facebook is a social networking website with an open platform that enables developers to extract and utilize user information
More informationThe relation between news events and stock price jump: an analysis based on neural network
20th International Congress on Modelling and Simulation, Adelaide, Australia, 1 6 December 2013 www.mssanz.org.au/modsim2013 The relation between news events and stock price jump: an analysis based on
More informationHow to Win the Stock Market Game
How to Win the Stock Market Game 1 Developing Short-Term Stock Trading Strategies by Vladimir Daragan PART 1 Table of Contents 1. Introduction 2. Comparison of trading strategies 3. Return per trade 4.
More informationISSN: 2321-7782 (Online) Volume 2, Issue 3, March 2014 International Journal of Advance Research in Computer Science and Management Studies
ISSN: 2321-7782 (Online) Volume 2, Issue 3, March 2014 International Journal of Advance Research in Computer Science and Management Studies Research Article / Paper / Case Study Available online at: www.ijarcsms.com
More informationChap 3 CAPM, Arbitrage, and Linear Factor Models
Chap 3 CAPM, Arbitrage, and Linear Factor Models 1 Asset Pricing Model a logical extension of portfolio selection theory is to consider the equilibrium asset pricing consequences of investors individually
More informationEmpirical Analysis on the impact of working capital management. Hong ming, Chen & Sha Liu
Empirical Analysis on the impact of working capital management Hong ming, Chen & Sha Liu (School Of Economics and Management in Changsha University of Science and Technology Changsha, Hunan, China 410076)
More informationSelecting the Right Social Media Monitoring Tools!
Selecting the Right Social Media Monitoring Tools! Exposing the real weaknesses and strengths of web and enterprise technology products Jarrod Gingras Analyst / Director of Advisory Services Real Story
More informationInvesting on hope? Small Cap and Growth Investing!
Investing on hope? Small Cap and Growth Investing! Aswath Damodaran Aswath Damodaran! 1! Who is a growth investor?! The Conventional definition: An investor who buys high price earnings ratio stocks or
More information