Background

AI, Machine Learning and Sentiment Analysis Applied to Finance, London, 14 – 15 July 2016

AI and Machine Learning have emerged as a central aspect of analytics which is applied to multiple domains. AI and Machine Learning, Pattern classifiers and natural language processing (NLP) underpin Sentiment Analysis (SA); SA is a technology that makes rapid assessment of the sentiments expressed in news releases as well as other media sources such as Twitter and blogs. This conference addresses and explains how to extract sentiment from these multiple sources of information and showcases the advances that have taken place in the field of financial innovation.

This conference builds on the findings of the six previous highly-regarded conferences on this topic. It highlights the recent developments in the application of AI and machine learning to trading strategies including automatic and algorithmic trading, quantitative fund management.

Programme

  • 09:00 -

    Registration and Coffee

  • 09:30 -
    Gautam-Mitra

    Welcome and Introduction – Professor Gautam Mitra, OptiRisk Systems Ltd

    Speakers:
    Gautam-Mitra

    Gautam Mitra

  • 09:45 -
    Elijah-DePalma

    Using AI to Integrate Behavioral Insights into Investment Strategies

    Elijah DePalma, Thomson Reuters

    Machine learning algorithms analyze multilingual professional news and unstructured social media to provide meaningful investment signals for both fundamental and quantitative strategies. Furthermore, research applications of News & Social Media Analytics are expanding beyond equities to encompass Global Macro, Systemic Risk, Supply-Chain Economics and FX Markets. We demonstrate the importance of integrating behavioral insights into long-term investment decisions, and we discuss cutting-edge AI applications for short-term trading strategies.

    Speakers:
    Elijah-DePalma

    Elijah DePalma

  • 10:30 -

    Coffee

  • 11:00 -
    Merve-Alanyali

    From news to protests: Measuring human behaviour around the world

    Merve Alanyali, Data Science Lab, Warwick Business School, University of Warwick

    A mammoth amount of data is being generated by our daily interactions with technological devices and online services. Compared to existing approaches, these new forms of data offer faster and cheaper measurements of human behaviour at a global scale. Examples I will showcase range from using online newspapers to quantify the relationship between financial news and the stock market, to analysing photographs shared on Flickr to track protest outbreaks around the world.

    Speakers:
    Merve-Alanyali

    Merve Alanyali

  • 11:30 -
    peter-hafiz

    Exploiting Alternative Data in the Investment Process

    Peter Hafez, Chief Data Scientist, RavenPack

    The emergence of big data in finance has shifted the alpha focus away from being faster to being smarter than the competition. Access to alternative data sources is considered a key input to such process. Peter Hafez, Chief Data Scientist, will provide an overview of RavenPack’s Big Data Analytics and the future development of the RavenPack product suite. In addition, he will present on his latest work on thematic alpha streams as well as providing an overview of general use cases of RavenPack data across various trading and investment applications.

    Speakers:
    peter-hafiz

    Peter Hafez

  • 12:15 -
    tilmal-sayer1
    Xiang-Yu

    Beating Markowitz with Sentiment and Downside Risk Control

    Tilman Sayer and Xiang Yu, OptiRisk Systems

    We have created an innovative and dynamic trading strategy for equities, with a particular focus on controlling downside risk. The mathematical concept behind the approach is called stochastic dominance, where investment decisions are based on distributions rather than moments. A major contribution of news sentiment is in the prediction of future distributions. Regression analysis on news sentiment and regime switching models are employed to digest market moods and account for changing market situations.

    Speakers:
    tilmal-sayer1

    Tilman Sayer

    Xiang-Yu

    Xiang Yu

  • 13:00 -

    Lunch

  • 14:00 -

    Panel: Adoption of AI, Machine Learning & Classical models in trading strategies and risk control

    Moderator: Professor Gautam Mitra, OptiRisk Systems

    Panellists: James Cantarella, Thomson Reuters; Saeed Amen, Cuemacro; Pierce Crosby, StockTwits; Anders Bally, Sentifi; Peter Hafez, RavenPack; Stephen Morse, Twitter.

  • 14:30 -
    Saeed-Amen

    Innovative ways of gauging sentiment to trade FX & open source software in finance

    Saeed Amen, Cuemacro

    We discuss several unusual sentiment datasets for trading FX. We begin by discussing how we can infer market sentiment from TIM Group sell side trade recommendation data, and how we can use that to trade FX markets in a systematic manner. We also briefly present a model which uses Prattle sentiment data gleaned from central bank communications to trade FX. Later, we discuss the benefits of using open source software in finance. We present our own open source Python trading library, PyThalesians, which includes a live demo.

    Speakers:
    Saeed-Amen

    Saeed Amen

  • 15:00 -

    Tea

  • 15:30 -

    Title TBA

    Edin Zajmovic, Thomson Reuters

  • 16:00 -
    Enza-Messina

    Text mining and deep learning for sentiment analysis

    Enza Messina, Professor in Operations Research, University of Milano-Bicocca

    In this talk we addresses the challenges of sentiment analysis of microblogs. We show how combining post contents and network structure information may lead to significant improvements in the polarity classification of the sentiment both at post and at user level. We also discuss the potential of deep learning for enhancing the classification performance through a high level feature representation.

    Speakers:
    Enza-Messina

    Enza Messina

  • 16:30 -
    Peiran-Jiao

    Social Media, News Media and the Stock Market

    Peiran Jiao, University of Oxford

    We contrast the impact of traditional news media and social media coverage on stock market volatility and trading volume. Stocks with high social media coverage in one month experience high idiosyncratic volatility of returns and trading volume in the following month. This result is consistent with the “stale news” hypothesis. Conversely, stocks with high traditional news media coverage experience low volatility and low trading volume in the following month. This result is consistent with some traders exhibiting overconfidence when interpreting signals from news media.

    Speakers:
    Peiran-Jiao

    Peiran Jiao

  • 17:15 -

    Close of Day 1 - Drinks reception and networking

  • 09:30 -
    Anders-Bally

    Social Listening & Financial Crowd-Intelligence

    Anders Bally, Sentifi

    In the early 90’s the majority of financial market participants used news mainly from services like Bloomberg and Reuters to inform themselves. 20 years later, they still do. During the same period, our society went through a communication paradigm shift. Today more than 2 Billion people walk around with mobile devices and communicate what they see and think on social media. These billions of voices, when structured, can generate insights which can help investors make better investment decisions. This presentation will touch on how Sentifi structures and delivers these insights, providing an information advantage for media platforms globally.

    Speakers:
    Anders-Bally

    Anders Bally

  • 10:30 -
    Debora-Nozza
    Enza-Messina

    Deep learning in natural language processing

    Enza Messina and Debora Nozza, University of Milano-Bicocca

    Recently, deep learning approaches have obtained promising results across many different NLP applications.

    Deep learning has in particular aimed at handling efficiently huge amount of texts in an unsupervised setting by capturing, in a intuitive way, the complexity of natural language.

    We show how deep learning goes beyond the traditional “bag of words” representation by constructing a so-called "neural embedding" or vector space representation of each word or document. We illustrate how this representation can be exploited for sentiment analysis.

    Speakers:
    Debora-Nozza

    Debora Nozza

    Enza-Messina

    Enza Messina

  • 11:30 -

    Coffee break

  • 12:00 -
    Pierce-Crossby

    An Era of Emerging Data: APIs, Unstructured Text, and Crowd Trading

    Pierce Crosby, StockTwits

    The digitizing of disparate data has led to a new wave of “emerging data” in the industry, applicable specifically to existing risk and trading models. Translating these data into repeatable results is the new frontier for many asset managers and hedge funds. The discussion will draw specifically from examples of earnings crowdsourcing, satellite imagery forecasting, and social data as it applies to investor sentiment and volatility modeling. We will also cover the diversity of methods used to deliver these data sources and what is considered the new standard for asset managers when it comes to the consumption of data.

    Speakers:
    Pierce-Crossby

    Pierce Crosby

  • 13:00 -

    Close of conference

Speakers

Merve-Alanyali

Merve Alanyali

University of Warwick

Saeed-Amen

Saeed Amen

Founder, Cuemacro

Anders-Bally

Anders Bally

Sentifi

James-Cantarella

James Cantarella

Thomson Reuters

Pierce-Crossby

Pierce Crosby

StockTwits

Elijah-DePalma

Elijah DePalma

Thomson Reuters

peter-hafiz

Peter Hafez

RavenPack

Peiran-Jiao

Peiran Jiao

University of Oxford

Enza-Messina

Enza Messina

University of Milano-Bicocca

Gautam-Mitra

Gautam Mitra

OptiRisk Systems

Debora-Nozza

Debora Nozza

University of Milano-Bicocca

Tobias-Preis

Tobias Preis

Warwick Business School

tilmal-sayer1

Tilman Sayer

OptiRisk Systems

Xiang-Yu

Xiang Yu

OptiRisk Systems

Edin-Zajmovic

Edin Zajmovic

Thomson Reuters

Platinum Sponsors

optirisk
thomsom

Gold Sponsors

Bronze Sponsors

marketpsych
Cuemacro
sentifi
stocktwits

Media Partners

automated1
Infosecurity-Magazine
c2b
investorlogo

 

mindcommerce

Professional Society Partners

garp
prmia
cqflogo

Knowledge Partner

CAIA-logo

Tickets

Delegates

250 GBP
  • Early Bird until 1 July - £250 + VAT
  • Standard Rate - £350 + VAT
  • Buy Ticket

Vendors

550 GBP
  • Super Early Bird until 3 June - £550
  • Early Bird until 1 July - £650
  • Standard Rate - £750
  • Buy Ticket

Event venue

  • Millennium Gloucester Hotel, 4-18 Harrington Gardens, London, SW7 4LH
  • 01895 256484
  • info@unicom.co.uk