What we're about
Upcoming events (4)
PLEASE NOTE THAT THIS WEBINAR WILL START ON WEDNESDAY, 19 AUGUST, 2020, AT 6:30 PM ***BST (LONDON TIME)*** (1.30 PM ***EDT (NEW YORK TIME)***) TITLE: The Executive Guide to Blockchain ABSTRACT: The talk provides an overview of the development of blockchain technology from its humble beginning as a community experiment to the deployment by some members of the banking sector. We will discuss how the technology could deliver new financial instruments, who are the first mover in this market and the key role of worldwide legislation. The talk will be delivered in an engaging and informative way, free of technical and unnecessary jargon. The talk will be partially based on the "Executive Guide to Blockchain" (Plagrave Macmillan) which is available to major bookstores: https://www.amazon.co.uk/dp/3030211061?tag=duckduckgo-ffab-uk-21&linkCode=osi&th=1&psc=1 BIOGRAPHY Maria G. Vigliotti is the first author of “The Executive Guide to Blockchain”( Palgrave Macmillam) The book demystifies blockchain by offering a jargon-free explanation on all aspects of the technology – an indispensable guide even if you alredy know what blockchain and cryptocurrencies are! Maria runs Sandblocks Consulting (https://www.sandblocksconsulting.co.uk/), a boutique consultancy specialising in blockchain technology and cybersecurity. And she holds an honorary visiting fellowship at the Department of Computing at Imperial College London. Her career in computing spans more than twenty years, many as an academic at Imperial College London specialising in writing AI algorithms to aid in cybersecurity and formal code verification. She convened and led the development of the cybersecurity strategy for the entire British railway industry and worked on prevention of cryptographic attacks on the European Railway Traffic Management Systems (ERTMS). She has also advised most of the major players in the UK nuclear industry on smart device security. She is a member of the Blockchain committee of the International Standards Organisation and the Chief Editor for the Journal Frontiers in Blockchain, the first peer-reviewed academic journal in the field. Maria holds a PhD inComputing from Imperial College London and has published over thirtypapers in peer-reviewed international academic journals and conferences. Maria is a Fellow of the British Computing Society.
PLEASE NOTE THAT THIS WEBINAR WILL START ON WEDNESDAY, 2 SEPTEMBER, 2020, AT 6:30 PM ***BST (LONDON TIME)*** (1.30 PM ***EDT (NEW YORK TIME)***) TITLE: The Book of Alternative Data ABSTRACT: The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. BIOGRAPHIES ALEXANDER DENEV leads AI and Data Science team for Financial Services - Risk Advisory. His responsibilities include development of AI products and advisory around risks and ethical implementation of AI. He also focusses on Alternative Data, AI for Data Quality and AI for Retail Banking. Alexander is a former Head of Quantitative Research & Advanced Analytics at IHS Markit. Prior to that, Alexander has worked in Risk Dynamics (McKinsey & Company), The Royal Bank of Scotland, European Investment Bank (EIB) and European Investment Fund (EIF), National Bank of Greece and Societe Generale. Alexander holds a degree in Mathematical Finance from University of Oxford where he is a Visiting Lecturer on Bayesian Risk Management and Alternative Data. He wrote several papers and books on quantitative topics, ranging from stress testing and scenario analysis to asset allocation through Machine Learning techniques and alternative data. Alexander has often thought leadership engagements in conferences, journals and global fora. SAEED AMEN is the founder of Cuemacro and co-founder of Thalesians. Over the past fifteen years, Saeed Amen has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. He is also the author of Trading Thalesians: What the ancient world can teach us about trading today (Palgrave Macmillan) and is the coauthor of The Book of Alternative Data (Wiley), due in 2020. Through Cuemacro, he now consults and publishes research for clients in the area of systematic trading. He has developed many Python libraries including finmarketpy and tcapy for transaction cost analysis. His clients have included major quant funds and data companies such as Bloomberg. He has presented his work at many conferences and institutions which include the ECB, IMF, Bank of England, and Federal Reserve Board.
PLEASE NOTE THAT THIS WEBINAR WILL START ON WEDNESDAY, 9 SEPTEMBER, 2020, AT 6:30 PM ***BST (LONDON TIME)*** (1.30 PM ***EDT (NEW YORK TIME)***) TITLE: Deep Hedging of Derivatives using Reinforcement Learning ABSTRACT: We show how reinforcement learning can be used to derive optimal hedging strategies for derivatives when there are transaction costs. We illustrate our approach by showing the diﬀerence between using delta hedging and optimal hedging for a short position in a call option when the objective is to minimize a function equal to the mean hedging cost plus a constant times the standard deviation of the hedging cost. Two situations are considered. In the ﬁrst, the asset price follows a geometric Brownian motion. In the second, the asset price follows a stochastic volatility process. The basic reinforcement learning approach is extended in a number of ways. First, it uses two diﬀerent Q-functions so that both the expected value of the cost and the expected value of the square of the cost are tracked for diﬀerent state/action combinations. This approach increases the range of objective functions that can be used. Second, it uses a learning algorithm that allows for continuous state and action space. Third, it compares the accounting P&L approach (where the hedged position is valued at each step) and the cash ﬂow approach (where cash inﬂows and outﬂows are used). We ﬁnd that a hybrid approach involving the use of an accounting P&L approach that incorporates a relatively simple valuation model works well. The valuation model does not have to correspond to the process assumed for the underlying asset price. BIOGRAPHIES Jay Cao is a Senior Research Associate at the Rotman TD Management Data and Analytics Lab. He holds a Ph.D. in Economics from University of Toronto. His current research interest is in the area of applied machine learning in finance. Jacky Chen is a senior analyst at OPTrust and a research assistant at the Rotman Financial Innovation Hub(FinHub). He has experience in systematic investment strategy development, trade execution, and risk management. His current research with FinHub focuses on applying machine learning to derivative pricing and risk management. He graduated from University of Toronto with a B.Sc in financial economics and statistics and a master degree in financial risk management. John Hull is the Maple Financial Professor of Derivatives and Risk Management at the Joseph L. Rotman School of Management, University of Toronto. His research has considered many different aspects of the pricing and hedging of derivatives. He has written four books: “Risk Management and Financial Institutions” (now in its 5th edition); "Options, Futures, and Other Derivatives" (now in its 10th edition); "Fundamentals of Futures and Options Markets" (now in its 9th edition); and “Machine Learning in Business: An Introduction to the World of Data Science” (now in its 2nd edition). The books have been translated into many languages and are widely used by practicing managers as well as in the classroom. Zissis Poulos received a Diploma in Electrical and Computer Engineering from the National Technical University of Athens in 2011, an M.A.Sc. degree in Electrical and Computer Engineering from the University of Toronto in 2014, and a Ph.D. degree in Electrical and Computer Engineering from the University of Toronto in 2018. He is currently a Postdoctoral Fellow at Rotman School of Management at the University of Toronto. His research interests include applied machine learning in finance, deep learning acceleration, statistical diagnosis and debugging of VLSI systems, modeling and optimization of information/influence diffusion in social graphs, and distributed ledger technologies. He is a member of IEEE and ACM. REFERENCES The latest version of our paper is available on http://ssrn.com/abstract=3514586 and http://www-2.rotman.utoronto.ca/~hull/DownloadablePublications/RL_Deep_Hedging.pdf
PLEASE NOTE THAT THIS WEBINAR WILL START ON WEDNESDAY, 30 September, 2020, AT 6:30 PM ***BST (LONDON TIME)*** (1.30 PM ***EDT (NEW YORK TIME)***) TITLE: Forecasting the dollar using capital flow data ABSTRACT: One of the key factors for understanding exchange rates is that of capital flows. If a country experiences large capital inflows it helps to support its currency, whilst large outflows will weaken it. In order to forecast currency moves, we need to be able to forecast these underlying capital flows in a timely way. In this webinar, Jens will discuss how capital flow data can be used to forecast the dollar, in particular using high frequency estimates of these capital flows from Exante Data. BIOGRAPHY Jens Nordvig serves as CEO of exante data and exante advisors. exante data and exante advisors were founded by Jens Nordvig in 2016. Jens Nordvig has a 18-year track record as a leading market economist and strategist. exante data provides analytical tools and smart data solutions to institutional investors globally. exante advisors provides discretionary macro strategy to CIOs of a select number of high profile macro-focused investment managers. Jens Nordvig has been ranked #1 in currency strategy by Institutional Investor in 2011, 2012, 2013, 2014 and 2015 [The Institutional Investor All-American Research Team Survey] Jens was awarded Wolfson Economics finalist prize in 2012 and the Rybczynski Young Economist Prize in 2001. He is also the author of “The Fall of the Euro: Reinventing the Eurozone and the Future of Global Investing”, McGrawHill, 2013. Jens Nordvig was previously a Managing Director at Goldman Sachs, a Senior Investment Associate at Bridgewater Associates and Head of Fixed Income Research and Global Currency Strategy at Nomura Securities. Jens holds masters and PhD degrees in economics from University of Aarhus and University of Southern Denmark (Thesis: Essays on the Euro Crisis).