AZFinText
Encyclopedia
Arizona Financial Text System (AZFinText) is a quantitative textual financial prediction system written by Robert P. Schumaker of Cleveland State University
and Hsinchun Chen
of the University of Arizona
. This system differs from other quants because it uses financial text as one of its key means of predicting stock price movement. This reduces the information lag-time problem evident in many similar systems where new information must be transcribed (e.g., such as losing a costly court battle or having a product recall), before the quant can react appropriately. AZFinText overcomes these limitations by utilizing the terms used in financial news articles to predict future stock prices twenty minutes after the news article has been released . It is believed that certain article terms can move stocks more than others. Terms such as factory exploded or workers strike will have a depressing effect on stock prices whereas terms such as earnings rose will tend to increase stock prices. When a human trading expert sees certain terms, they will react in a somewhat predictable fashion. AZFinText capitalizes on the arbitrage opportunities that exist when investment experts over and under-react to certain news stories. By analyzing breaking financial news articles and focusing on specific parts of speech, portfolio selection, term weighting and even article sentiment, the AZFinText system becomes a powerful tool and is a radically different way of looking at stock market prediction.
AZFinText was then extended to study what combination of peer organizations help to best train the system. Using the premise that IBM
has more in common with Microsoft
than GM
, AZFinText studied the effect of varying peer-based training sets. To do this, AZFinText trained on the various levels of GICS and evaluated the results. It was found that sector-based training was most effective, netting an 8.50% trading return, outperforming Jim Cramer, Jim Jubak and DayTraders.com during the study period. AZFinText was also compared against the top 10 quantitative systems and outperformed 6 of them.
A third study investigated the role of portfolio building in a textual financial prediction system. From this study, Momentum and Contrarian stock portfolios were created and tested. Using the premise that past winning stocks will continue to win and past losing stocks will continue to lose, AZFinText netted a 20.79% return during the study period. It was also noted that traders were generally over-reacting to news events, creating the opportunity of abnormal returns.
A fourth study looked into using author sentiment as an added predictive variable. Using the premise that an author can unwittingly influence market trades simply by the terms they use, AZFinText was tested using tone and polarity features. It was found that Contrarian activity was occurring within the market, where articles of a positive tone would decrease in price and articles of a negative tone would increase in price.
A further study investigated what article verbs have the most influence on stock price movement. From this work, it was found that planted, announcing, front, smaller and crude had the highest positive impact on stock price.
, MIT's Technology Review
, Motley Fool
, Crossing Wall Street, WBIR in Knoxville, TN and Motherboard TV.
Cleveland State University
Cleveland State University is a public university located in downtown Cleveland, Ohio. It was established in 1964 when the state of Ohio assumed control of Fenn College, and it absorbed the Cleveland-Marshall College of Law in 1969...
and Hsinchun Chen
Hsinchun Chen
Hsinchun Chen is the McClelland Professor of Management Information Systems at the University of Arizona and the Director and founder of the Artificial Intelligence Lab . He received a B.S. degree from National Chiao Tung University in Taiwan, an MBA from SUNY Buffalo and an M.S. and Ph.D...
of the University of Arizona
University of Arizona
The University of Arizona is a land-grant and space-grant public institution of higher education and research located in Tucson, Arizona, United States. The University of Arizona was the first university in the state of Arizona, founded in 1885...
. This system differs from other quants because it uses financial text as one of its key means of predicting stock price movement. This reduces the information lag-time problem evident in many similar systems where new information must be transcribed (e.g., such as losing a costly court battle or having a product recall), before the quant can react appropriately. AZFinText overcomes these limitations by utilizing the terms used in financial news articles to predict future stock prices twenty minutes after the news article has been released . It is believed that certain article terms can move stocks more than others. Terms such as factory exploded or workers strike will have a depressing effect on stock prices whereas terms such as earnings rose will tend to increase stock prices. When a human trading expert sees certain terms, they will react in a somewhat predictable fashion. AZFinText capitalizes on the arbitrage opportunities that exist when investment experts over and under-react to certain news stories. By analyzing breaking financial news articles and focusing on specific parts of speech, portfolio selection, term weighting and even article sentiment, the AZFinText system becomes a powerful tool and is a radically different way of looking at stock market prediction.
Overview of research
The foundation of AZFinText can be found in the ACM TOIS article. Within this paper, the authors tested several different prediction models and linguistic textual representations. From this work, it was found that using the article terms and the price of the stock at the time the article was released was the most effective model and using proper nouns was the most effective textual representation technique. Combining the two, AZFinText netted a 2.84% trading return over the five-week study period.AZFinText was then extended to study what combination of peer organizations help to best train the system. Using the premise that IBM
IBM
International Business Machines Corporation or IBM is an American multinational technology and consulting corporation headquartered in Armonk, New York, United States. IBM manufactures and sells computer hardware and software, and it offers infrastructure, hosting and consulting services in areas...
has more in common with Microsoft
Microsoft
Microsoft Corporation is an American public multinational corporation headquartered in Redmond, Washington, USA that develops, manufactures, licenses, and supports a wide range of products and services predominantly related to computing through its various product divisions...
than GM
General Motors
General Motors Company , commonly known as GM, formerly incorporated as General Motors Corporation, is an American multinational automotive corporation headquartered in Detroit, Michigan and the world's second-largest automaker in 2010...
, AZFinText studied the effect of varying peer-based training sets. To do this, AZFinText trained on the various levels of GICS and evaluated the results. It was found that sector-based training was most effective, netting an 8.50% trading return, outperforming Jim Cramer, Jim Jubak and DayTraders.com during the study period. AZFinText was also compared against the top 10 quantitative systems and outperformed 6 of them.
A third study investigated the role of portfolio building in a textual financial prediction system. From this study, Momentum and Contrarian stock portfolios were created and tested. Using the premise that past winning stocks will continue to win and past losing stocks will continue to lose, AZFinText netted a 20.79% return during the study period. It was also noted that traders were generally over-reacting to news events, creating the opportunity of abnormal returns.
A fourth study looked into using author sentiment as an added predictive variable. Using the premise that an author can unwittingly influence market trades simply by the terms they use, AZFinText was tested using tone and polarity features. It was found that Contrarian activity was occurring within the market, where articles of a positive tone would decrease in price and articles of a negative tone would increase in price.
A further study investigated what article verbs have the most influence on stock price movement. From this work, it was found that planted, announcing, front, smaller and crude had the highest positive impact on stock price.
Notable publicity
Because of its revolutionary way of looking at price prediction, AZFinText has been the topic of discussion by numerous media outlets in many different languages. Some of the more notable ones include the Wall Street Journal, SlashdotSlashdot
Slashdot is a technology-related news website owned by Geeknet, Inc. The site, which bills itself as "News for Nerds. Stuff that Matters", features user-submitted and ‑evaluated current affairs news stories about science- and technology-related topics. Each story has a comments section...
, MIT's Technology Review
Technology Review
Technology Review is a magazine published by the Massachusetts Institute of Technology. It was founded in 1899 as "The Technology Review", and was re-launched without the "The" in its name on April 23, 1998 under then publisher R. Bruce Journey...
, Motley Fool
Motley Fool
The Motley Fool is a multimedia financial-services company that provides financial solutions for investors through various stock, investing, and personal finance products. The Alexandria, Virginia-based private company was founded in July 1993 by co-chairmen and brothers David and Tom Gardner, and...
, Crossing Wall Street, WBIR in Knoxville, TN and Motherboard TV.