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Important Study Confirms Non-Linear Evidence of Causal Effects of Social Media on Market Prices using PSYCHSIGNAL dataset
Bjorn Simundson
posted
API Papers Machine Learning Sentiment Research

Hi Everyone,

This study at the following link is a very interesting study, which was conducted by University College London and published as a whitepaper last week.

Link to study found here:
http://arxiv.org/pdf/1601.04535v1.pdf

In this study, the researcher (Thársis T.P. Souza, studying under professor Dr. Tomaso Aste at University College London Computer Science Department) investigates using some deeper methodologies than previous studies to find out exactly why and how the online chatter from Twitter, StockTwits and private institutional chatrooms can consistently predict the market's behavior. The groundbreaking study is important because it goes beyond previous studies which confirmed weak causality, but were previously unable to explain the reasons why the sentiment analysis was predicting the market behavior. The reason for these previous limitations were because previous studies were limiting their scope to linear activity only, and failing to use more sophisticated methodologies which this study employs and describes.

For reference, the way that PsychSignal's technology works, is by applying a proprietary Natural Language Processing Engines to determine the bullishness and bearishness of the trading public, using the raw 100% firehose feeds from multiple sources like Twitter. The PsychSignal dataset consistently outperforms all other sentiment analysis products because it delivers simultaneous Bull and Bear, to 2 decimal places on a scale of 0 to 4, and can be understood using non-linear causal relationships as investigated in this paper.

For those seeking to learn more and try out market sentiment using PsychSignals datafeed, are encouraged to try it out with a starter kit feed through Quantopian here at the following LINK:
https://www.quantopian.com/data/psychsignal/twitter_noretweets_limited

Go to https://PSYCHSIGNAL.com to learn more about the company
Go to https://uk.linkedin.com/in/tharsissouza to learn more about the researcher at University College London who authored the study.

1 response
Josh Payne

As a follow up, today we launched a fuller set of PsychSignal data sets. These sets are available built-into Quantopian for use both in Research and within your trading algorithms via the pipeline API.

Both StockTwits and Twitter are used as sources for these products.

Interestingly, the free samples for each of these data sets are all the way up to 2 months from the current date. You can work with 6 years of historic data, for free.

Head over and check them out: https://www.quantopian.com/data?searchq=PsychSignal

Maybe someone can replicate the paper Bjorn pointed out with this data in an algo now!

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.