18 May 2017
Royal Geographical Society
1 Kensington Gore
SW7 2AR London
from 08:45 to 17:00 (BST)
For this year’s spring seminar we have again gathered six excellent speakers who will deliver their recent research and insights in an open forum that encourages discussion and debate. The engaging and thought provoking talks provide theoretical and practical insights to take away and implement.
Enhance your industry connections while absorbing cutting edge quantitative research.
This seminar returns to the elegant surroundings of the Royal Geographical Society. Lunch and coffee is included for £300 plus VAT and booking fee. Spaces are limited – so book your place(s) now.
There will also be an informal after seminar dinner at a local restaurant paid individually on the night.
Cost and Registration
The fee for this seminar is £300
Registration is closed.
Speakers, and links to their presentations
- Andrew Harvey, University of Cambridge,
Testing Against Changing Correlation, slides
- Nick Baltas, UBS,
The Crowding of Factor Investing, (contact presenter directly)
- Mike Howell, CrossBorder Capital,
Macro-Investment Risks and Style Selection, slides
- Mike Kollo, AXA,
Smart Beta, (contact the presenter directly)
- Raul Leote de Carvahlo, BNP Paribas Investment Partners,
Diversify and Purify Factor Premiums in Equity Markets, slides
- Lior Jassur, MFS,
Portfolio Diversification and the Merton Model, slides
Talk abstracts and speakers’ biographies
- Andrew Harvey, Testing against changing correlationDynamic conditional score models are designed to extract a signal from heavy-tailed observations. Such models are robust to outliers, have excellent theoretical properties and work well in practice. The talk will focus on recent developments, including the generalized-t EGARCH model, time-varying correlations and the EGARCH-M model for capturing the interactions between returns, risk and volatility.Andrew Harvey is Emeritus Professor of Econometrics in the Faculty of Economics, University of Cambridge, and a Fellow of Corpus Christi College. Prior to that he was Professor of Econometrics at the London School of Economics. He is a Fellow of the Econometric Society and a Fellow of the British Academy (FBA). He has published over one hundred articles in journals and edited volumes. He is the author of two textbooks, The Econometric Analysis of Time Series and Time Series Models, and two research monographs, Forecasting, Structural Time Series Models and the Kalman Filter (1989) and, most recently, Dynamic Models for Volatility and Heavy Tails (2013). He is one of the developers of the STAMP package.
- Nick Baltas, The crowding of factor investingNick’s research interests include systematic cross-asset strategies, portfolio construction, risk analysis and performance evaluation. Nick joined UBS in February 2013 and since then he additionally maintains a visiting academic position at Imperial College Business School. His research has been awarded with numerous grants and prizes and quoted by the financial press. Prior to his current role, Nick spent two years as Lecturer in Finance at Imperial College Business School, when he was awarded the Star Teacher of the Year award for both years in recognition of his teaching, and almost a year as risk manager in a London-based hedge fund. He holds a DEng in electrical and computer engineering from the National Technical University of Athens, an MSc in communications & signal processing from Imperial College London and a PhD in finance from Imperial College Business School.
- Michael Howell, Macro-Investment Risks and Style SelectionMichael J. Howell is a managing director of CrossBorder Capital, a London-based advisory firm, where he heads the research division. CrossBorder Capital specialises in providing unique datasets on credit flows and investors’ risk appetite that are widely used by quant funds. Previously Head of Research at ING Barings and Research Director at Salomon Brothers, Michael was educated at Bristol and London Universities. He has published papers on yield curve and duration management, and managing risk in forex and in Emerging Markets. He is currently engaged in the analysis of term premia drivers and the application of cross-asset signals in other markets.
- Mike Kollo, Smart BetaMike Kollo leads research efforts across a wide range of quantitative products from SmartBeta and factor strategies, semi-passive, fully-active and short-extension strategies. He contributes to the production of investment signal design and testing primarily using Matlab/Sas, and a range of sophisticated econometric and non-linear (machine-learning, and genetic algorithm) techniques.
- Raul Leote de Carvahlo, Diversify and Purify Factor Premiums in Equity MarketsHow removing unwanted risk exposures in equity factor investing can improve information ratio of factors, in particular the importance of hedging the market exposures, hedging size exposures, controlling volatility, and the importance of the shorts for factor performance, as well as the added value form diversifying across a large number of factors in each style.Raul has 16 years of experience in the financial industry and is deputy head of financial engineering at BNP Paribas Investment Partners since 2014. This team is responsible for the development of quantitative strategies for investment teams managing equity, fixed income and asset allocation portfolios and also for the use of quantitative approaches in the design of client investment solutions. He joined this team in 2007 as head of quantitative strategies and research.
- Lior Jassur, Portfolio Diversification and the Merton ModelUsing structural models for pricing real world credit instruments leads to results that are far from satisfactory. Rather than using structural models to price a specific bond, my approach uses a relatively simple version of the Merton model to calculate a credit quality ratio for a company. When these credit quality ratios are calculated for a set of companies it is possible to rank them from lowest to highest risk. Back-testing this approach using real world data suggests that the credits rejected by this method are the ones who tend to underperform a credit index. A further enhancement to the investment process is to use the credit spread as an additional criterion in order to select sub-set of the investible credit universe that combines both good credit quality and attractive risk premium.Lior currently works as a credit analyst at MFS International (UK) Ltd. Prior to joining MFS he was Head of Credit Research EMEA at HSBC and previous roles included proprietary trading at a capital structure arbitrage desk of a major bank, high yield and distressed investment analysis at buy-side firms and high yield credit analysis at three sell-side institutions.
- Andrew Harvey, University of Cambridge,