A seminar presenting a new approach to equity investing referred to as smart factor investing, taking place in New York on 23 October, 2014, Los Angeles on 10 December, 2014, San Francisco on 11 December, 2014 and Toronto on 12 December, 2014

Overview

The Risk Allocation and Smart Beta seminar will present a new approach to equity investing referred to as smart factor investing, showing how to select desired factor exposures, addressing how to design efficient and investable proxies for risk premia, demonstrating the benefits of an efficient risk allocation to smart factor indices, and presenting case studies on dynamic allocation to smart factors and factor risk parity constraints on the one hand, and dynamic allocation to smart beta and relative risk constraints on the other. 

Smart beta has been a great success for several years now, both in business terms and from a financial point of view, since the performances that were announced on the basis of track records have now been confirmed. This success corresponds to the development of new indices and also the change of paradigm in the passive investment industry, which, from an objective of replicating the average performance of the market that is given by cap-weighted indices, has moved on today to a promise of outperformance. Naturally, this change in paradigm in investment that is termed passive is not without its consequences.

Certain major players in index investment do not wish these new forms of indices to be considered passive investment, by defining passive investment as investment that is not supposed to have any index rebalancing (passive = static) and that, especially, should only reflect the average performance of the market.

Other players consider on the contrary that the real debate is situated pragmatically between index investment and non-index investment, and smart beta can be delivered in either an indexed or active form. The former version of smart beta is supposed to be systematic and completely transparent, and the latter introduces the manager’s talent in a discretionary manner, notably when it involves selecting the stocks that make up the portfolio, which will have a quantitative or fundamental smart weighting applied to it. Finally, when it involved analysing, or indeed criticising, the value added by smart beta, some have considered that the value came from rebalancing and others from the exposure to factors, even though many smart beta providers spoke instead of the diversification effect.

While the rebalancing effect is questionable and in any event cannot be equated with either a mean reversion effect in the sense of the life-cycle approach to equities, or even a contrarian effect in the anti-momentum sense, it is obvious on the other hand that a fair share of the performance of first-generation smart beta indices comes from exposure to risk factors, such as Value or Size, that are well rewarded over the long run. In Smart Beta 1.0 this factor exposure is often unwanted, ill-documented and in any case not explicitly controlled. As such it is liable in the short term, given the specific risks of the Value or Size factors, to lead to large relative drawdowns, often well above 50% (1).

In addition, the diversification effect, which is intended to be a response to the very high level of concentration of cap-weighted indices and their strong exposure to non-rewarded specific risks, is often not distinguished from the factor effect, to the extent that the investor can with reason doubt their existence, given that the outperformance argument does not give sufficient insight on the combination and the risks of the implementation of factor choices and diversification methods, which all contain model risks.

The problem of analysing the added value and the robustness of the smart beta performances is made even more difficult by the opacity of the index industry and the restrictions on the access to data that make the creation of an efficient index market impossible (2).

Recently, EDHEC-Risk Institute tried to clarify the subject of the added value of smart beta on the basis of a Smart Beta 2.0 approach by clearly differentiating the performance that comes from an explicit choice of factor exposure on the one hand, and the implementation for a given factor tilt of a diversification method that is efficient in the sense that it sharply reduces the specific risk. We have called this approach “smart factor investing.” (3) It has given rise to the production by our ERI Scientific Beta entity of 207 multi-strategy factor indices benefitting both from a choice of factors and a robust method for diversifying specific risk.

The results of applying the smart factor concept are attractive; on average and over the long term, the improvement in the Sharpe ratio compared to traditional indices is 52% (4).

Naturally, this improvement in the Sharpe ratio does not resolve the question of the risk of the smart beta investment, notably when it appreciates in relative value compared to the equity allocation reference, which remains the cap-weighted index for the vast majority of investors. (5) It is in this context that EDHEC-Risk Institute has developed research on smart beta risk allocation.

This research shows that it is possible to reconcile the performance of smart beta with control over the risk of the investment.

Starting with the observation that if the performance of smart beta comes from efficient allocation to smart factor indices maximising the risk-adjusted performance for a given factor exposure, EDHEC’s researchers show that the implementation of a risk allocation solution to support this efficient allocation to smart beta enables the risk constraints to be respected in both absolute and relative terms.

Two results deserve to be highlighted in our view.

The first is that in relative terms, it is possible to sharply reduce the tracking error and the relative drawdown of the smart beta investment with robust risk allocation techniques in a portfolio of smart beta indices. As such, a Relative Equal Risk Contribution (ERC) or Relative Global Minimum Variance (GMV) approach for a Developed World universe gives tracking error of around 2.5% with relative drawdown of 5%.

The second is that in absolute terms and as part of a long-only allocation, even though investable smart beta indices are never pure in the long-only space, it is possible to respect factor risk parity constraints. This result means that it is not necessary to turn to long/short or highly concentrated factor indices that present investability problems and are particularly poorly diversified when reaching objectives on controlled exposure to risk factors.

For EDHEC-Risk Institute, the challenge with smart beta investing today is not only to avail of smart factor indices with good risk-adjusted performance but also to allocate to these smart factor indices in a risk-efficient way.

• The first part of the seminar will present how to select desired factor exposures.
• The second part of the seminar will address how to design efficient and investable proxies for risk premia.
• The third part of the seminar will show the benefits of an efficient risk allocation to smart factor indices.
•  The fourth part of the seminar will present case studies on dynamic allocation to smart factors and factor risk parity constraints on the one hand, and dynamic allocation to smart beta and relative risk constraints on the other.

1 - Amenc, N. F. Goltz, A. Lodh and L. Martellini. Diversifying the Diversifiers and Tracking the Tracking Error: Outperforming Cap-Weighted Indices with Limited Risk of Underperformance, Spring 2012, Journal of Portfolio Management and Amenc, N. and F. Goltz. Smart Beta 2.0, Winter 2013, Journal of Index Investing.
2 - Amenc, N. and F. Ducoulombier. March 2014. Index Transparency – A Survey of European Investors’ Perceptions, Needs and Expectations. EDHEC-Risk Institute Publication
3 - Amenc, N., F. Goltz, A. Lodh and L. Martellini. May 2014. Scientific Beta Multi-Strategy Factor Indices: Combining Factor Tilts and Improved Diversification. ERI Scientific Beta Publication.
4 - Average of the differences in Sharpe ratio observed between 31/12/1973 and 31/12/2013 for all long-term track record multi-strategy factor indices and their cap-weighted factor equivalent calculated on a universe of the 500 largest capitalisation US stocks. All the details on the calculations and the indices are available on the www.scientificbeta.com website.
5 - Amenc, N., F. Goltz and L. Tang. October 2011. EDHEC-Risk European Index Survey 2011. EDHEC-Risk Institute Publication. Amenc, N., F. Goltz, L. Tang and V. Vaidyanathan. April 2012. EDHEC-Risk North American Index Survey 2011.

Programme

Part 1: Selecting Desired Factor Exposures

Part 2: Designing Efficient and Investable Proxies for Risk Premia

Part 3: Risk Allocation with Smart Factor Indices

Part 4: Case Studies

Seminar Instructor

Eric Shirbini is Global Product Specialist with ERI Scientific Beta. Prior to joining EDHEC-Risk Institute, Eric was a quantitative analyst at UBS, BNP Paribas and Nomura International. During this time he worked on a diverse range of topics including multi-factor models, fundamental stock valuation, equity market indices, portfolio construction and portfolio trading. At BNP Paribas, Eric managed a team of analysts who were responsible for the Global Equity Research Database. He holds a BSc and PhD from University College London and an MBA from CASS Business School.

Who Should Attend

The programme is intended for all professionals involved in passive investment and active management. More generally, this seminar is intended to be a reference for investment management professionals who advise on or participate in the design and implementation of asset allocation policies, equity portfolio models, and for sell-side practitioners who develop new equity investment solutions. The approach to diversifying the different forms of smart beta is also of great interest for diversified managers and multi-managers.

Venues and Timing

Schedule:

Registration

Admission to the seminar is complimentary and by invitation only.

To request an invitation, please contact Séverine Cibelly at severine.cibelly@scientificbeta.com or on +33 493 187 863 or click on one of the links below:

Contact

For further information, please contact: