23-24 June 2021, Online Knowledge Partners Event Partners Professional Bodies Media Partners A www.unicom.co.uk 23-24 June 2021 Online Background Innovations in Finance and harnessing of Technology have resulted in making the term Fintech a portmanteau word. In the evolution of the BFSI sector Fintech has assumed a pivotal role; but it has also disrupted traditional order. The rise of AI and Machine learning has impacted many aspects of investment models and technologies at the same time it has disrupted some other. Applications of Alternative Data in Fintech are growing at a great pace; the question is how to discover new sources of alpha and create strategies and signals. Here the challenge is to discover hidden coupling of multiple data sources. Text analysis, Natural Language Processing and analysis of News, Micro blogs, investor sentiment are well established. Bringing all these advances together new applications in trading, fund management and risk control have continued to emerge. Today Fintech has influenced all aspects of the finance industry – banking and capital markets, asset and wealth management, insurance, and funds transfer and payments. There are three main themes for this Two-Day Online Event Theme 1: Disruptive Progress in AI and ML Progress in (i) News Analysis, (ii) Micro Blog Analysis (Filtered Twitter feed for finance), (iii) Online searches (iv) Data Analytics, Alternative Data and AI and Quant models DISRUPTIONS: Predicting the Market directions and ‘Timing the Market’ Other Topics: üNew directions of discovering Alpha in Low frequency Systematic Trading üOpportunities and challenges of machine learning in quantitative wealth and investment management Theme 2: Progress in Derivative Products üMachine Learning and Derivatives Artificial Neural Networks and Derivatives Pricing üExploiting Index Futures and VIX to construct Trade Portfolios Theme 3: Impact of SRI and ESG in the Investment Industry üThe Rise and Rise of ESG in the domain of Finance üMultiple Facets of ESG in finance. Event Time This event is mainly focused on participants from Europe and UK. The event time is set so that participants from UK or Europe may attend in the morning from 9:30 GMT or 10:30 CEST Attend this event and earn GARP/CPD credit hours. UNICOM has registered this program with GARP for Continuing Professional Development (CPD) credits. Attending this program qualifies for 14 GARP CPD credit hours. If you are a Certified Financial Risk Manager (FRM®), or Energy Risk Professional (ERP®), please record this activity in your Credit Tracker. Discounted attendance offer: If you are a GARP Alumni, that is, an ERP or FRM certificate holder then avail yourself a 20% discount offer for the event registration fee. To know more about the offer contact us [email: [email protected] ; [email protected] ] Call for Participation We are inviting speakers – thought leaders, subject experts and start up entrepreneurs – to share their knowledge and enthusiasm about their work and their vision in the field of AI, Machine Learning, Sentiment Analysis. Please complete the speaker’s response form and submit a proposal to present at this event. www.unicom.co.uk 23-24 June 2021 Online Programme Please Note That the Times Stated in the Programme are in BST DAY 1 (23 JUNE) [09:30 BST] INTRODUCTION Gautam Mitra, CEO, OptiRisk / UNICOM THEME: DISRUPTIVE PROGRESS IN AI AND ML [09:37 BST] KEYNOTE SPEAKER: BLACKJACK, OPTIONS AND THE S&P 500: THE INTERSECTION OF GAMBLING AND INVESTING Blair Hull, Founder and Chairman, HULL TACTICAL Applying what has been called a disruptive innovation, Mr. Hull beat the casinos counting cards in blackjack in the 1970s. He parlayed this success into the securities business, building a flagship global options market firm acquired by Goldman Sachs in 1999. Today Mr. Hull applies AI, ML, and the latest academic findings to guide investment decisions and alpha creation in futures and options trading at Hull Tactical. [10:02 BST] PROGRESSION OF SOCIAL SENTIMENT + BIFURCATION OF MEDIA PLATFORMS AND KEEPING TRACK OF ALL THIS DATA AS A COMPETITIVE EDGE Pierce Crosby, General Manager, TradingView Even a year ago, the idea of a crowd moving a $15 billion dollar company in a meaningful way was unheard of. Today, we see the bifurcation of platforms across the financial web that commence coordinated investing efforts in an open and transparent way. Staying on top of these conversations is essential to every asset manager. [10:29 BST] HOW FEATURES SELECTION CAN HELP IMPROVE TRADING STRATEGIES Dr. Ernie Chan, Founder, PredictNow.ai Inc One major impediment to widespread adoption of machine learning (ML) in investment management is their black-box nature: how would you explain to an investor why the machine makes a certain prediction? If you don’t understand the underlying mechanisms of a predictive model, you may not trust its predictions. Feature importance ranking goes a long way towards providing better interpretability to ML models, and feature selection improves out-of-sample performance of ML models. [10:51 BST] Q/A SESSION FOLLOWED BY COMFORT BREAK [11:16 BST] MACHINE LEARNING AND DERIVATIVES ARTIFICIAL NEURAL NETWORKS AND DERIVATIVES PRICING Mario Dell’Era, Quantiative Market Risk Sr. Group Manager, Citi In computational finance, numerical methods are commonly used for the valuation of financial derivatives. These price models are often multi-dimensional and heavy from the time consuming view point. Artificial Neural Networks (ANNs) with multiple hidden layer became successful machine learning methods to extract features and detect patterns from a large data set. [11:46 BST] NEW DIRECTIONS AND FINDING NEW ALPHA IN LOW FREQUENCY SYSTEMATIC TRADING Andrea Nardon, Chief Quant Officer, Fund Manager, Black Alpha Capital Machine learning tools have started to be widely accepted within the investor base. On one hand this allows quant researchers to explore newer input-output relationships that human eyes struggle to identify but on the other hand when these tools are not properly used, they can introduce new risks which can cause undesired outcomes. [12:11 BST] PANEL1: DISRUPTIVE PROGRESS IN AI AND ML Moderator: Gautam Mitra Panellist: Blair Hull, Pierce Crosby, Dr. Ernie Chan, Thomas Oesch, Andrea Nardon [12:51 BST] ICE BREAKING SESSION INTRODUCING SPONSORS www.unicom.co.uk 23-24 June 2021 Online Programme THEME: ESG AND SRI (PART 1) [13:03 BST] APPLYING NLP TO THEMATIC INVESTING Simon Wicks, Managing Director, Multi-Asset Quantitative Solutions, Charles Schwab Thematic Investing has seen significant growth in recent years, driven by interest in both innovation and sustainability related themes. Natural Language Processing – from BM25 to BERT – can combine with human insight to power thematic research, increasing both the depth and efficiency of the research process. [13:27 BST] CAN WE FORECAST CARBON? David Jessop, Head Of Investment Risk, Columbia Threadneedle Investments EMEA APAC The path to a low carbon economy involves encouraging companies to lower their carbon intensity. It could be beneficial to find the companies where they are lowering their carbon output. But can we forecast this? The problem is a very short time series of carbon data – perhaps 10 years at best, which means [13:47 BST] ESG AND SRI Q/A SESSION FOLLOWED BY- PANEL SESSION Moderator: Gautam Mitra Panellist: David Jessop, Kevin Spellman. DAY 2 (24 JUNE) [09:30 BST] INTRODUCTION Gautam Mitra, CEO, OptiRisk / UNICOM THEME: PROGRESS IN DERIVATIVE PRODUCTS [09:35 BST] KEYNOTE: ANOTHER STEP IN THE EVOLUTION OF FINANCIAL MARKETS? Dan diBartolomeo, President and Founder, Northfield Information Services Abnormal market behaviour, speculative bubbles and busts, are not new phenomena. Speculative trading has no doubt occurred since the dawn of time, often fuelled by over confidence, greed, easy access to credit, and the siren song of watching other people get rich. As risk model providers, how can we deal with market data that is disconnected from underlying economic reality? In this presentation we discuss the innovative approaches Northfield has pioneered to make risk models adapt to real-world problems with market data, harnessing alternative data and looking for regimes in volatility. [10:04 BST] AI & ML PREDICT THE MARKET: METHODOLOGY OF STRAGERY CREATION ILLUSTRATED BY USE CASE Gautam Mitra, CEO, OptiRisk / UNICOM [10:29 BST] Q/A SESSION FOLLOWED BY COMFORT BREAK [10:54 BST] DEEP REINFORCEMENT LEARNING FOR ASSET ALLOCATION IN US EQUITIES Miquel Noguer I Alonso, Head of Development, Global AI We consider an application of reinforcement learning to create a financial model-free asset allocation paradigm which uses deep neural networks. For an asset universe of top 24 US stocks we show that the deep reinforcement learning approach gives better results than traditional portfolio management approaches. Our method uses a time series of daily data of stock prices and a simple reward function. [11:15 BST] HOW TO BUILD A MONEY PRINTING MACHINE WITH AI Raul Glavan, Consultant Artificial Intelligence & Asset Management | Trader | Speaker | UBI Enthusiast www.unicom.co.uk 23-24 June 2021 Online Programme [11:40 BST] THE CROSS-SECTION OF NEWS SENTIMENT, RISK, AND RETURNS Thomas Oesch, Senior Portfolio Manager, UBS We study the relationship between news sentiment and stock risks and returns by applying news sentiment scores from four different datasets to a comprehensive global single stock universe. We find that the sentiment scores from the different datasets differ in terms of sources and sentiment scores, making them complementary as opposed to competing in a holistic portfolio analysis as we have undertaken. [12:01 BST] Q/A SESSION FOLLOWED BY COMFORT BREAK [12:26 BST] PRESENTATION BY SPONSORS THEME: ESG AND SRI (PART 2) [12:36 BST] ESG MATTERS Dr. G. Kevin Spellman, Director of Investment Management, University of Wisconsin Milwaukee ESG investing can take on several forms. One can invest in companies to make an impact, avoid certain industries, and in recent research, it has been shown that a focus on firms with good ESG may enhance returns.