Edhec-Risk Institute - Quarterly Newsletter
September/October 2019
Veronique Le Sourd Insights from the 12th EDHEC European ETF, Smart Beta and Factor Investing Survey
EDHEC-Risk Institute conducted its 12th survey as part of the Amundi research chair on "ETF, Indexing and Smart Beta Investment Strategies" at EDHEC-Risk Institute. The aim of this study is to analyse current European investor practices and perceptions on ETFs, smart beta and factor investing strategies, as well as future plans in these domains. By comparing our results to those of our previous surveys, over more than a decade, we aim to shed light on trends within the ETF market and within the smart beta and factor investing strategy offering. This survey brings together the main vehicles of passive investment, namely ETFs – standard and very liquid products that track indices – and strategies based on the new forms of indices.

Table of Contents
1. Feature | 2. Interview | 3. Industry Analysis | 4. Research Publications | 5. In Video | 6. News | 7. Events | 8. Press Review

A Financially Justifiable and Practical Approach to Coherent Stress Testing
This article presents the key features introduced in a recent paper on stress testing (Rebonato, 2019) that is both practical and firmly rooted in well-established financial theory. The results are presented in a Bayesian-net context, but the approach can be extended to different settings. We show i) how the consistency and continuity conditions are satisfied; ii) how the result of a scenario can be consistently cascaded from a small number of macrofinancial variables to the constituents of a granular portfolio; and iii) how an approximate but robust estimate of the likelihood of a given scenario can be estimated. This is particularly important for regulatory and capital-adequacy applications. In the wake of the 2007-2009 financial crisis, a broad consensus has been reached that relying on purely statistical (usually frequentist) techniques to manage financial risk is both unwise and difficult to justify. Stress testing has often been touted as the answer (or at least one of the answers) to the shortcomings of managing financial risk using purely statistical tools. Regulators have given additional reasons to 'treat stress testing seriously' through the association of how much capital systemically important financial institutions (SIFIs) should hold and the outcomes of stress-testing exercises.

Caroline Prevost "EDHEC-RISK is Launching the World's First Online Finance Course on Machine Learning Applied to Investment Management"
In this month's interview, Caroline Prévost discusses the newly launched Investment Management with Python and Machine Learning specialisation. She explains why EDHEC-Risk decided to partner with Coursera to develop this online programme and why they chose to explore asset management through the prism of machine learning. She provides further details of the 4 MOOCs available and tells us how these online courses fit into EDHEC-Risk Institute’s Executive Education offering.
Industry Analysis
Machine Learning for Investment Decisions: A Brief Guided Tour
Recent developments in data science and machine learning have the potential to improve investment decisions. The fast growth of machine learning algorithms has occurred along with the expanding availability of data at the micro-level. These data hold the key to new breakthroughs. On the other side, there are several challenges to full implementation in investing. One of these is the evolving nature of the investment landscape, where new products and services arise and quickly become widely available and possibly reducing future performance. A potential example is factor investing. Privacy and security are continuing concerns. We review a few curated applications and speculate on the impacts on finance broadly.
Factor Investing in Fixed-Income Markets: A promising start, but more work is needed
Market weighted bond indices favour the interests of debt issuers over investors, argue professors Martellini, Rebonato, and Maeso. Despite this, there has been relatively little research into what alternatives might look like. What research exists suggests that factor-based approaches – even simple ones like targeting the term premium – can help load the dice in investors' favour.
Improving Digital MiFID Profiling Using Behavioral Smarts
For investor profiling purposes it is standard practice that investors are appointed to the profile that best fits their balance between risk and reward, based on a number of standardised questions. This approach suffers from at least two shortcomings. First, as stated by Nobel laureate Daniel Kahneman (2009), "people are poor forecasters of their future emotions and future tastes". Questionnaires are unlikely to be good predictors of actual future behaviour. Second, investor profiles restrict to an assessment of the client's willingness to bear risk in order to obtain higher returns. Behavioural finance convincingly argues that actual human behaviour is more refined.
Research Publications
Factor Investing in Sovereign Bond Markets – A Time-Series Perspective Factor Investing in Sovereign Bond Markets – A Time-Series Perspective
This paper, "Factor Investing in Sovereign Bond Markets – A Time-Series Perspective", provides a detailed analysis of the theoretical, statistical and practical challenges related to factor investing in sovereign bond markets, with a focus on factors such as the "level" or "slope" of the yield curve that explain, for any maturity, a large fraction of differences over time in bond returns. Using a comprehensive database of individual bond returns in the US over the 1973-2018 sample period, we find that a conditional version of a carry strategy based upon a time-varying exposure to the level factor can generate up to 200 basis points of excess performance.
The Journal Portfolio Management - July 2019 Factor Investing in Fixed-Income - Cross-Sectional and Time-Series Momentum in Sovereign Bond Markets
Individuals preparing for retirement are currently left with an unsatisfactory choice between security with no flexibility with annuity products, and flexibility without security with investment products such as balance funds or target date funds. To get out of this impasse, the authors introduce a range of flexicure retirement goal-based investing strategies that offer both security and flexibility with respect to the objective of generating replacement income in decumulation. Recent advances in financial engineering and digital technologies make it possible to apply goal-based investing principles to a much broader population of investors than the few traditional clients who can afford cutomised mandates of private banking services, which suggests that these flexicure retirement solutions can be used as part of the solution to the global pension crisis.
Assets' Correlation Implications for Portfolio Insurance Strategies Performance Assets' Correlation Implications for Portfolio Insurance Strategies Performance
Studies that address the estimation of the maximum multiplier of portfolio insurance strategies have been limited to the case in which the safe asset is a short-term bank account paying a constant rate of return. Authors explore the implications of taking into account the expected co-movements of the PSA and the benchmark asset for the estimation of the multiplier upper bound. In Monte Carlo simulations, they find that the maximum multiplier almost doubles in size across scenarios and the long-term returns of the strategy using this approach present stochastic dominance of order one to four over the previously tested strategies that used a multiplier that ignore expected co-movements.
Investment Management with Python and Machine Learning - with Lionel Martellini, Professor of Finance at EDHEC Business School. There is a revolution taking place between investment management and data science. Just being aware of these changes is not enough to be a leader in the financial industry. EDHEC-Risk Institute, the leading academic think-tank for investment management, is offering a new programme, different from other financial certifications as it will help learners in unlocking the power of Machine learning techniques in Asset management.
12th EDHEC European ETF, Smart Beta and Factor Investing Survey – an exclusive interview by Amundi with Lionel Martellini, Professor of Finance at EDHEC Business School. He examines the main findings of this year's survey and the trends that can be identified over the long term, in the European ETF market. In a second part he discusses the main drivers of investors' use and adoption of Smart Beta and Factor Investing Strategies. Finally, looking at future developments, he describes the needs expressed by investors.
Investment Management with Python and Machine Learning - with Lionel Martellini 12th EDHEC European ETF, Smart Beta and Factor Investing Survey - with Lionel Martellini
Learn more in video by subscribing to our YouTube channel.
Journal of Fixed Income - Summer 2019 EDHEC-Risk Institute Paper on Value in Sovereign Bond Markets accepted by the Journal of Fixed Income
The authors propose a definition of value in Treasury bonds that, they believe, is more satisfactory than definitions found in the recent literature, and that allows for statistically significant and economically relevant predictions of cross-sectional excess returns. Their value pricing factor exploits the differences between the market and the theoretical values of Treasury bonds, where the theoretical value is assessed using an economically-justifiable Gaussian dynamic term structure model. The authors show that the profitability of the strategy they build using their value signal is statistically and economically significant and is closely linked to the Treasury market volatility.
Riccardo Rebonato unveiled the results of the ETF Survey Riccardo Rebonato Unveiled the Results of the 12th EDHEC-Risk European ETF, Smart Beta and Factor Investing Survey on Sept 23 in London
Riccardo Rebonato, Professor of Finance, EDHEC-Risk Institute, was invited to speak on the theme of ETF and Smart Beta at the Big Call: Fixed Income Forum, hosted by ETF Stream, at a panel session titled "The Development of Passive Investment in Europe: presentation of the results of the EDHEC-Risk European ETF Survey 2019".
MOOCs in machine-learning techniques EDHEC Teams up with Coursera to Launch MOOCs in Machine-Learning Techniques for Financial-Sector Professionals
Data science is revolutionizing the asset-management industry, but financial professionals trained in machine learning are rare and very much sought after. To lead the transformational charge these technological advancements will bring, financial-sector specialists need to be more than just aware of them. That's why EDHEC-Risk Institute, recognised globally for its financial-sector research, is launching a new digital programme, entitled Investment Management with Python and Machine Learning.
The Quant Conference Lionel Martellini Invited to Join the Board of Advisors of The Quant Conference
In October 2019, The Quant Conference invited Lionel Martellini, Director of EDHEC-Risk Institute to join its Board of Advisors, whose main purpose is to help engage better with EDHEC Business School and its students. The rise of big data, the application of machine learning and other technological developments in recent years have transformed the quantitative finance industry. The Quant Conference brings together prominent industry practitioners, hedge fund managers, allocators and academics.
Campus around the world
CFA Institute European Investment Conference, Madrid
EDHEC Climate Finance Conference, Paris
Press Review
EDHEC-Risk Institute has been cited widely in the business and industry press. A selection of articles may be found below.
"L'EDHEC lance une série de MOOC avec Coursera", Esteval Editions (02/10/2019)
"L'Edhec crée une série de MOOC dédiés au machine learning", Newsmanagers.com (30/09/2019)
"EDHEC-Risk Institute ETF Survey Reports Ethical, Fixed Income Smart Beta in Demand", Traders Magazine (01/10/2019)
"European Survey Highlights Increasing ETF Usage", ETF Trends (27/09/2019)
"Growing demand for SRI/Ethical ETFs and significant interest in fixed-income Smart Beta solutions", Money Marketing (26/09/2019)
"Designing a new Retirement System and Goal-Based Wealth Management", Kiwi Investor (23/09/2019)
"Smart Beta Bond ETFs May Be Beginning to Attract Attention", ETF Trends (23/09/2019)
"Investors call on ETF issuers to develop fixed income smart beta products further", ETF Stream (23/09/2019)
"Buzz around factor investing in fixed income is growing", Financial Times (23/09/2019)
"Recherche Allocations d'actifs en vue de la retraite : comment allier sécurité et flexibilité", Option Finance (16/09/2019)
"Value und Momentum bei Anleiheninvestments", Absolut Return (10/09/2019)
"EDHEC-Risk Institute: The (Many) Problems of an Inverted Yield Curve", MondoVisione (09/09/2019)
"EDHEC's Rebonato predicts 'new dawn' in fixed income investing", ETF Stream (22/08/2019)
Stay tuned for more research, outreach, education and industry partnership developments on investment solutions for institutions or individuals
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About EDHEC-Risk Institute:

Part of EDHEC Business School and established in 2001, EDHEC-Risk Institute has become the premier academic centre for industry-relevant financial research. In partnership with large financial institutions, its team of permanent professors, engineers, and support staff, and research associates and affiliate professors, implements seven research programmes and six research, industrial partnerships and private research projects focusing on asset allocation and risk management. Additionally, it has developed an ambitious portfolio of research and educational initiatives in the domain of investment solutions for institutional and individual investors. As part of its "Make an Impact" signature, EDHEC-Risk plays a noted role in furthering applied financial research and systematically highlighting its practical uses.

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E-mail: [email protected]
Telephone: +33 493 187 887
Web: https://risk.edhec.edu
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