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Axioma Quant Forum Returns, September 2014

Join us for the Axioma Quant Forum in New York and London this September.

Leading practitioners and researchers will present their latest work on effective risk management, superior portfolio construction and optimal portfolio trading.

Join Axioma for a full day of illuminating presentations and thought-provoking discussion.

Axioma Quant Forum - New York

Date: September 8, 2014, 8:30 AM- 6:00 PM
Location: The Princeton Club, 14 W 43rd St., New York

Axioma Quant Forum - London

Date: September 24, 2014, 8:30 - 6:00 PM
Location: Andaz Liverpool Street Hotel, London, EC2M 7QN

The London events offers plenary sessions and split sessions to provide a greater variety of relevant content for attendees. We invite you to view the agenda so you can plan your day accordingly: Download PDF Agenda

London Speakers

APG: How Your Portfolio Can Benefit From Forecasting Trade Volumes show abstract
Equity investors use a wide range of sophisticated models to forecast risk, but when it comes down to estimating trade volumes their preferred estimator is a naïve average or median of recent volume. Based on a literature study we have created an estimator which improves the ADV estimates by 20%. As trade volumes are the main driver of impact costs, differences in estimates impact the optimal after-cost portfolio. We demonstrate how volumes may impact this optimal portfolio, and what the potential gains are of having better volume estimates. hide abstract
Peter Korteweg, PhD, CFA, Senior Portfolio Manager show bio

Peter is responsible for the development of mathematical models and analysis tools in a team which oversees the quantitative equity investments of APG, an asset manager for pension funds. He is the co-portfolio manager of the team's low-volatility portfolio and has extensive knowledge of the theory and practice of risk factor models and trade cost models for institutional investors. He holds a PhD in Applied Mathematics and is a CFA charterholder. hide bio

BNP Paribas Asset Management: Beyond Smart Beta: A Risk-Budgeting Approach for Multi-Factor Equity Portfolios show abstract
Recent research recognises that a number of strategies that go under the name of Smart Beta and include Minimum Variance, Maximum Diversification, Risk Parity and Fundamental indexation are in fact deriving their excess returns and risk exposures from well-known factor risk premiums like value, small cap and low volatility. Moreover, it has been suggested that these Smart Beta strategies are clumsy approaches to gain exposure to such factor risk premiums and that optimal combinations of such strategies are difficult to construct. In this research we propose a framework for portfolio construction of multi-factor risk premium portfolios which addresses these pitfalls. The frameworks starts with the selection of the factor premiums to add to a portfolio, followed by the allocation of a risk budget to each of those factor risk premiums and finally the construction of an efficient portfolio which delivers those factor risk premiums under realistic portfolio constraints, e.g. long-only with a limited number of stocks. hide abstract
Raul Leote de Carvalho, Head of Quantitative Research and Investment Solutions show bio

Raul Leote de Carvalho has 14 years of experience in Finance and is the Head of Quantitative Research and Investment Solutions in the Financial and Engineering team of BNP Paribas Asset Management in Paris since 2007. He is responsible for carrying out innovative quantitative research applicable in the development of quantitative strategies for different investment teams in either equities, fixed income or asset allocation and also for the use of advanced quantitative approaches in the design of investment client solutions.

Prior to that, from 2003 to 2007 he held the position of Senior Quantitative Strategist in the Global Strategy team of BNP Paribas Investment Partners located in Paris where he was member of the Asset Allocation Committees and developed a number of quantitative models and strategies for asset allocation. He joined Paribas Asset Management in 1999 in London as a Quantitative Analyst, a position he held until 2002, working mainly on the application of robust portfolio optimisation techniques to portfolio construction, the development of FX and fixed income models and also as fund manager of asset allocation portfolios.

Before he spent 3 years working as a Research Associate in Computational and Theoretical Physics at the University College of London, at the École Normale Supérieure de Lyon and at the University of Wuppertal. He obtained a PhD in Theoretical Physics from the University of Bristol in 1996, an MSc in Condensed Matter Physics in 1992 and a BSc in Chemistry in 1990 both from the University of Lisbon. He is a member of Inquire Europe and the author of a many refereed papers in Finance and Physics published in several academic journals. He passed the Investment Management Certificate in London in 2001. hide bio

Cantab Capital Partners: How slow can you go? show abstract
We find that turnover from a cross-sectional equity strategy can be broken down into:
  • Turnover from changes in the signal. This turnover is a function of the cross-sectional correlation between periods. For monthly rebalancing this leads to almost 3 times annual turnover for our value signals and 5 times annual turnover for momentum.
  • Turnover from rebalancing to a fixed portfolio value or dollar risk target. Based on 25% annual market risk this leads to 0.8 times annual turnover for monthly rebalances but rises to 3.5 times annual turnover for daily rebalance.
We find smoothing a signal does improve the turnover. Using an n-day smoothed signal results in signal turnover almost the same as rebalancing every n-days. However if we rebalance daily even with a smoothed signal any reduction in signal-induced turnover are offset by increased turnover from daily resetting the portfolio's size and fixed dollar volatility targeting. hide abstract
Massoud Mussavian, PhD, Senior Scientist show bio

Massoud joined Cantab in 2013 as a senior scientist working on strategy development and portfolio construction. His main area of focus is equities, and developing new strategies in this area. Massoud was previously Managing Director at Goldman Sachs in London. He has worked in a number of quantitative roles in the equities and asset management division. Massoud joined Goldman Sachs in 2001 to head the derivatives strategies group in Europe working with clients on the strategic uses of equity derivatives. He built up the one-delta strategies group in Europe focussing on quantitative trading strategies, risk management, algorithmic trading, internalisation and trading automation. Massoud also headed up the research and technology department for the quantitative proprietary trading desk, working on both low and high frequency trading strategies in European equities.

Prior to working at Goldman Sachs, Massoud was an Assistant Professor of Finance at London Business School. There he taught equity investment management and PhD level courses in asset pricing. Massoud has a PhD in Finance from New York University. His research interests include Empirical Asset Pricing Models and Contract Theory. Massoud also holds a BSc in Mathematics from Imperial College London. hide bio

HOLT Investment Strategy: Generating Excess Returns Across the Road Less Travelled show abstract
The efficacy of stock selection models are frequently examined across a range of parameters and regimes such a size, region, sector, and style. One metric that is commonly overlooked is the depth of analyst coverage. In this presentation we examine whether there is a relationship between the number of analysts covering a company and the power of stock selection. Using a global universe, we examine stock selection performance per analyst coverage grouping and look into the correlation of coverage to company size and valuation multiples. The insights obtained are consistent across a range of samples. hide abstract
Siebert Kruger, Director, Credit Suisse (CS), HOLT Division - Director show bio

Siebert is Director in HOLT and manages the EMEA and Asia Investment Strategy Groups which is responsible for designing and implementing HOLT systematic strategies. Siebert holds a Masters in Business Administration from London Business School and also a Baccalaureus Scientiae (Hons) in Information Sciences from the University of Pretoria in South Africa.hide bio

Macquarie Securities Group: Managing risk, return and active share (by Giuliano De Rossi) show abstract
The concept of active share has received considerable attention since the work of Cremers and Petajisto (2009) who showed that funds with high active share tend to outperform [How Active Is Your Fund Manager? A New Measure That Predicts Performance, Review of Financial Studies 22, 3329-3365]. More and more portfolio managers are incorporating explicit active share targets in their portfolio construction process, in addition to or as a substitute for tracking error targets. We analyse the problem of optimising an active risk / active return objective function subject to active share constraints and derive the resulting efficient frontiers. Moreover, we show that imposing active share constraints can be interpreted as a robust portfolio construction approach. In particular, building on the existing literature on optimisation with gross exposure constraints, we highlight: 1) the equivalence between portfolio optimisation with active share limits and regularisation of the covariance matrix 2) the connection between portfolio construction and lasso regression 3) a Bayesian interpretation of active share constraints. Monte Carlo experiments are used to assess the robustness of the method out of sample. Our research has important implications for portfolio managers: Active share targets should depend on skill and on the number of stocks and concentration of the benchmark. In addition, we argue that active share targets should change over time to reflect changes in market conditions. hide abstract
Ioan Mirciov, PhD, Analyst, The Quant Team show bio

Ioan Mirciov joined the Quantitative team at Macquarie from a buy-side role, where he investigated investment strategies based on volatility derivatives. Prior to that, he worked on the design and efficient replication of credit benchmarks at Barclays Capital. Ioan holds a PhD in Finance from Kellogg School of Management, where he focused on earnings surprises. hide bio

Old Mutual Global Investors: The Benefits Of Allocating To Market Neutral Strategies show abstract
As financial markets have globalised, correlations among regional equity indices have increased markedly over the last 20 years, diminishing the scope for diversification within equities. Alternatives can offer some diversification, but some of the popular hedge fund strategies, such as equity long short, in practice can exhibit high correlation with equities. Equity market neutral stands out as the hedge fund strategy that has exhibited one of the lowest level of correlation against traditional asset classes. We show in asset allocation historical simulations that these correlations can be useful in improving the risk return characteristics of portfolios, particularly for low risk investors. Hedge fund strategies are now more widely available to investors via UCITS funds, making investment in these alternative asset classes much more accessible, in terms of funds being regulated, liquid and transparent. But equity market neutral is not a homogeneous space, and fund selection is key if one is to take advantage of the potential diversification benefit this asset class can provide. hide abstract
Amadeo Alentorn, CFA, PhD, Head of Research and Fund Manager - Global Equity Team show bio

Amadeo Alentorn joined Old Mutual Global Investors in 2005. He is Head of Research and Portfolio Manager in the global equities team, responsible for managing over $3bn in assets across global equity hedge funds, absolute return and long only equity funds. He has extensive experience in investment research and software development. Prior to joining Old Mutual, he developed simulation models for systemic and liquidity risk at the Bank of England (2004-2005), and worked as a software developer for CAD systems (2001-2004) and for robotic applications (1998-1999). Amadeo holds a BEng in Robotics (2000) from the University of Plymouth, an MSc in Computer Science (2001) and a PhD in Computational Finance (2006) from the University of Essex. During his doctoral research he developed a new option pricing model based on extreme value theory, and published on the subject. He is a CFA charterholder. hide bio

Pioneer Global Asset Management: Targeting Individual Liabilities for DC Pension Funds Using Stochastic Programming show abstract
Within the realm of the pension funds, the recurring trend of the past years have been that of transitioning from the Defined Benefit (DB) schema to a Defined Contribution (DC). Consequent household exposure to market dynamics increases the likelihood of gaps between post-retirement funding obligations and income. From the perspective of a pension fund sponsor, minimizing such likelihood increases the plans' visibility and utility. To achieve this, we propose the application of Asset Liability Management (ALM) techniques using a multistage dynamic stochastic optimization in our analysis. The results of such dynamic ALM approach to a wide range of risk profiles show conclusively an improvement in plan participant post-retirement solvency over the traditional fixed-mix balanced fund approach. hide abstract
Jung Hum Kim, ALM Analyst show bio

Jung Hum Kim is an Asset-Liability Management (ALM) analyst at Pioneer Investments based in Milan, Italy since May 2012. Jung is responsible for developing and maintaining the dynamic stochastic programming platform to simulate asset class scenarios and optimize ensuing portfolios. Jung has over extensive experience in quantitative analysis across Financial Industry Regulatory Authority (FINRA) in the US and IBM Consulting. He holds a B.A. degree from Brown University and a M. Eng. from Johns Hopkins University. hide bio

Robeco: The Rise of Factor Investing: Is it just hype, and other practical questions show abstract
Factor Investing is increasingly in the spotlight. Financial magazines run features on it, seminars are organized on the subject, and investors consider adopting its approach. Yet you might wonder: is it just hype? Is the increased interest in Factor Investing no more than a passing trend? The first part of the talk will focus on answering this important question. Next, we will discuss different approaches to Factor Investing and what the implications of these differences are. Finally we will discuss several practical considerations on how to implement Factor Investing strategies and answer questions on, e.g., how to optimally combine different factors, and whether to invest using a long-only or a long-short approach. hide abstract
Simon Lansdorp, Ph.D., Quant Researcher, Investment Solutions and Research show bio

Simon is Researcher at Robeco's Investment Solutions & Research department. His areas of expertise include mutual funds and stock selection research. Moreover, at Robeco, Simon is responsible for creating optimal, client-specific factor investing solutions. Simon joined Robeco as a researcher in 2009 while he was simultaneously working on his doctorate dissertation. He holds a MSc in Economics from the Erasmus University Rotterdam and holds a PhD in Finance from the Tinbergen Institute.hide bio

State Street Global Advisors: Low Volatility Investing: Lower Risk with Market-Like Returns show abstract
Since the global financial crisis of 2007-2008, increased interest in low volatility investing has spawned many different ways investors can capture the low volatility anomaly. This paper categorizes the various low volatility investment choices into two main approaches: heuristic and optimized; and looks at several prominent implementations within each. It compares construction methodologies, historic performance, drawdown, turnover, and other portfolio characteristics of the various implementations. Investors looking to allocate to low volatility should find a strategy whose characteristics best match the requirements and constraints of their investment objectives. This paper helps identify these characteristics. hide abstract
Christopher Cheung, Senior Researcher, Global Equity Beta Solutions show bio

Chris is a Vice President of State Street Global Advisors and a Senior Portfolio Manager and Research Analyst in Global Equity Beta Solutions. He specializes in optimized, tax-efficient and Advanced Beta strategies for the passive indexing group. His responsibilities include managing portfolios for institutional and high net worth clients in addition to performing quantitative research in alternative equity products.

Chris holds a Bachelor degree in Electrical Engineering and a Master degree in Engineering Management from Cornell University. He was awarded a graduate fellowship at the Carroll Graduate School of Management at Boston College where he earned Master degrees in Business Administration and in Finance. Chris has also earned the Chartered Financial Analyst designation, and is a member of the CFA Institute and the Hong Kong Society of Financial Analysts. hide bio

UBS: From Forecasts to Portfolios: Making the Most of Your Insights show abstract
This talk describes a framework for analysing and using single and multiple forecasts. As a first step the forecasts are decomposed into factor and stock specific views. For single forecasts it is then possible to estimate the breadth of the forecast. For multiple forecasts, the forecasts can be scaled and checked for consistency. Finally any inconsistencies must be resolved – a process which involves the judgement and knowledge of a portfolio manager. Once these inconsistencies have been removed the amended forecasts can be combined and a portfolio constructed. hide abstract
David Jessop, Managing Director – Global Head of Equities Quantitative Research show bio

David Jessop is the Global Head of Equities Quantitative Research at UBS. His areas of interest include risk modelling and portfolio construction. David joined the quantitative research team at UBS in 2002. Prior to this, he spent seven years at Citigroup as Head of Global Quantitative Marketing. Before moving to the sell side, he spent six years at Morgan Grenfell Asset Management, where he managed index funds, asset allocation funds and also an option overwriting fund. David graduated from Trinity College, Cambridge with an MA in Mathematics. hide bio

Axioma, Inc.: Multi-Period Portfolio Optimization with Alpha-Decay show abstract

For all there is to like about traditional Markowitz mean variance optimization (MVO), it is essentially a one-move game that ignores next steps. Yet decisions driven by single-period MVO may have very significant consequences for investors with long-term horizons. Fortunately, there is a way to address the problem. Multi-period optimization gives investors the ability to make “wait and see” decisions, by including approximate forecasts and long-term policy decisions that extend beyond the time horizon of a current rebalancing. In doing so, investors can maintain their focus on the long term, while obtaining flexibility in the short term.

Here we consider portfolio optimization with a composite alpha signal that is composed of a short-term and a long-term alpha signal. The short-term alpha better predicts returns at the end of the rebalancing period but it decays quickly. The long-term alpha has less predictive power than the short-term alpha but it decays slowly. We develop a multi-period portfolio that incorporates this alpha model to construct the optimal portfolio at the end of the rebalancing period. We compare this model with the traditional single-period MVO model on several simulated backtests and show that the multi-period model has a superior realized performance. hide abstract

Sebastian Ceria, PhD show bio

Before founding Axioma, Ceria was an Associate Professor of Decision, Risk and Operations at Columbia Business School from 1993 to 1998. Sebastian has worked extensively in the area of optimization and its application to portfolio management. He is the author of many articles in publications including Management Science, Mathematical Programming, Optima and Operations Research. Most recently, Sebastian's work has focused on the area of robust optimization in portfolio management. He has co-authored numerous papers on the topic, including, "Incorporating Estimation Errors into Portfolio Selection: Robust Portfolio Construction," published in The Journal of Asset Management, “To Optimize or Not to Optimize: Is That the Question?” published in the Oxford Handbook of Quantitative Management, and “Factor Alignment Problems and Quantitative Portfolio Management,” published in the Journal of Portfolio Management. He is a recipient of the Career Award for Operations Research from the National Science Foundation. Ceria completed his PhD in Operations Research at Carnegie Mellon University's Graduate School of Industrial Administration. hide bio

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