So Sources ces of of Per Perfor orman mance ce an and d the - - PowerPoint PPT Presentation

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So Sources ces of of Per Perfor orman mance ce an and d the - - PowerPoint PPT Presentation

INTEGRATING ALL SOURCES OF PERFORMANCE TO CREATE MORE EFFECTIVE PORTFOLIOS So Sources ces of of Per Perfor orman mance ce an and d the he Val alue e of of Fo Forecas asts ts Jacques Lussier , Chief Investment Officer October 2015


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SLIDE 1

INTEGRATING ALL SOURCES OF PERFORMANCE TO CREATE MORE EFFECTIVE PORTFOLIOS

So Sources ces of

  • f Per

Perfor

  • rman

mance ce an and d the he Val alue e of

  • f Fo

Forecas asts ts

Jacques Lussier, Chief Investment Officer

October 2015

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SLIDE 2

2

We Can do Better er Sources ces of Excess xcess Perfor

  • rma

manc nce e Changes ges in Po Portfol folio io Design sign Beta, a, Alph pha a & Luck How w to St Structu ucture e a Prod

  • duc

uct When n Perfor

  • rma

mance nce is Not Ther ere An Analy alysis is using g the Multi-Fact actor

  • r App

pproac

  • ach

An Example ample of a C Comp mplete e Produc

  • duct

Concl clus usion ion and d Recom

  • mmen

mendat ation ion TABLE OF CONTENTS

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SLIDE 3

WE CAN DO BETTER, BUT HOW?

3

An asset reaches its maximum weight when it is most highly overvalued.

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SLIDE 4

4

It is the philosophy, not the methodology, that determines the capacity to perform.

Indexing Active Underperforms Outperforms Luck Expertise Unique skill - forecasting

Diversification – pricing errors Diversification – effective statistics Balance of risk premiums

Management approaches

Market structure Nature of performance Skill: Portfolio Structuring Skill: Forecasting

STRUCTURE OF MANAGERS‟ PERFORMANCES

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SLIDE 5

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𝑁𝑏𝑦. 𝑆𝑓𝑢𝑣𝑠𝑜 𝑆𝑗𝑡𝑙 =

Diversifying uncompensated risks effectively (Volatility management approach)

Identifying and/or diversifying pricing error (Naive approach) +

Identifying and diversifying risk factors (Factor-based approach) +

Return = Beta + Alpha + Luck

Exposu sure re to risk premiums ums

Market + Size Value Trends Quality etc.

Unique expertise tise

Forecasting returns Better integration of risk premiums Exposure to unknown risk premium

Diver ersi sificat ation

  • n of pricing

ng error Exposu sure re to uncomp mpen ensat sated d risk

Good luck – Announcement of better profit than anticipated Bad luck – Report indicating a particular drug increases cancer risk

UNDERSTANDING SOURCES OF PERFORMANCE

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SLIDE 6

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DIFFERENT APPROACHES TO PORTFOLIO STRUCTURING

Equal-weight Weight based on historical moving average Weight based on accounting variables (RAFI)

Naive approach Volatility management approach Factor-based approach

Low volatility Maximum Diversification (TOBAM) Sampling on risk measures Equal weighting Low-Beta market Small cap Value style Trend/momentum style Multi-factor approach (AQR)

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SLIDE 7

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Traditional indexes are fully exposed to market risk (β market = 1) and have no exposure to the other factors (βs of other factors = 0).

Source: IPSOL

Performance of key factors – U.S. equities

Period Market + Size Value Momentum 72-75

  • 5.8%
  • 6.6%

11.0% 11.3% 76-79 6.8% 16.6% 6.3% 14.4% 80-83 6.9% 7.9% 7.0% 10.7% 84-87 7.2%

  • 6.4%

5.6% 7.2% 88-91 10.7%

  • 2.0%
  • 3.6%

12.2% 92-95 9.2% 1.3% 9.3% 10.3% 96-99 19.3%

  • 3.2%
  • 7.1%

15.9% 00-03

  • 6.5%

11.2% 16.8% 6.5% 04-07 6.3%

  • 0.8%

4.3% 7.3% 08-11 0.7% 5.7%

  • 1.6%
  • 7.7%

12-15 (June) 17.2% 1.0%

  • 0.9%

3.8% 72-15 (June) 8.2% 3.4% 3.8% 7.5%

BETA – IDENTIFYING AND DIVERSIFYING FACTORS

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SLIDE 8

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LUCK – DIVERSIFYING UNCOMPENSATED RISKS

Firm Date β S&P500 ret. Firm ret. Explanation Microsoft 24/04/2015 0.78 0.22% 10.45% Profits better than anticipated ResMed 24/04/2015 0.48 0.22%

  • 10.47%

Sales lower than anticipated

Market portfolios are not necessarily the most efficient at diversifying uncompensated risk. The objective is to reduce the volatility attributed to uncompensated risks per unit of periodic return.

Lower volatility = Higher compounded return The objective is to manage volatility more efficiently

Uncompensated risks cannot be forecasted but they can be diversified. This explains why a portfolio‟s risk is lower than the average risk of its components.

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SLIDE 9

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ALPHA – IDENTIFYING / DIVERSIFYING PRICING ERRORS Alpha is also related to diversification

The objective is either to forecast returns (which is difficult) or to diversify pricing error more efficiently than an index based on market capitalization. This can be achieved using an allocation method that is not correlated with pricing error. Traditional indexes assign too much weight to overvalued securities and too little to undervalued securities.

Firm Period Initial index weight Initial price Final price Return Comment Nortel 3/27/2000 to 6/15/2001 35% 143.06 9.86

  • 93%

Large loss on large position Ford 3/9/2009 to 3/9/2010 0.12% 1.74 12.80 635% Large gain on small position

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SLIDE 10

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A combination of 3 processes:

 A sampling process – which securities are authorized in the portfolio

 S&P500, equal-weight: Authorized securities in the S&P500 market capitalization  RAFI US 1000: 1000 securities with the highest score based on the Fundamental Index measure on the NYSE, the AMEX and the NASDAQ. The score is based on a combination of 5-year averages for the sales, accounting value, cash flow and dividend variables.

 An allocation process –weights allocated to the securities

 S&P500, equal-weight: 1/N  RAFI US 1000: weight based on score

 A rebalancing process

 S&P500 – equal-weight: quarterly  RAFI US 1000: annual

An allocation process necessarily creates factor bias, whether intentional or not.

PUTTING TOGETHER A PORTFOLIO – EXAMPLE OF U.S. EQUITIES

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SLIDE 11

 When risks other than market risk are not compensated

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 When the impact of uncompensated risks dominates in the short term. E.g. positive surprises regarding the profits of large growth companies such as Apple in 2014 and Google in July 2015 and/or when large countries dominate performance, as in the case of China in 2014 and early 2015.

WHEN DO FACTOR-BASED PRODUCTS UNDERPERFORM?

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SLIDE 12

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A FEW STRATEGIES AND PRODUCTS EXPLAINED USING THE FACTOR-BASED APPROACH

* Five-star Morningstar rating. 0.46% and 0.80% management fees respectively have been added to returns from both Fidelity Funds to ensure that all portfolios are comparable.

One-factor model Equal weighting Fundamental Index Maximum Diversification Fidelity Large Cap Value Enhanced* Fidelity Blue Chip Growth* Alpha „ 1.59% „ 2.14% „ 2.50%

  • 1.44%

1.16% Beta market 1.04 0.94 0.82 0.88 1.03 Five-factor model Alpha 0.70%

  • 0.23%
  • 0.51%
  • 0.99%

2.34% Market 1.01 0.99 0.82 0.92 1.02 Size 0.01

  • 0.08

0.20

  • 0.22
  • 0.07

Value 0.27 0.32 0.15 0.33

  • 0.15

Momentum

  • 0.03

0.03

  • 0.08 „

0.16

  • 0.04

Low Beta 0.07 0.07 0.26 0.03

  • 0.05
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SLIDE 13
  • Highly diversified:
  • U.S. and international equities – Approximately 200 positions each
  • Emerging markets – Exposure to 20 countries
  • Resources – Exposure to 24 contracts
  • Balanced exposure to all risk premiums:
  • Equities - Value, trend/momentum, size, current yield, asymmetry, etc.
  • Resources, currency – Value, trend/momentum
  • Managing uncompensated risks to improve geometric return

13

IMAGINE A GLOBAL PORTFOLIO THAT INTEGRATES ALL OF THESE MANAGEMENT APPROACHES

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SLIDE 14

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PERFORMANCE (CAD)

Absolute return – Annualized Relative return (60/40) – Annualized

You cannot win all of the time, but you can do much better in the long term.

Scatter plot – Portfolio vs 60/40

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SLIDE 15

CONCLUSION AND RECOMMENDATIONS

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SLIDE 16

KEY MESSAGES

  • The best managers do not outperform systematically.
  • Only 20% to 30% of active managers beat their targets after fees. This percentage is

structural and is not affected by participant quality but instead by fees.

  • Luck is always a significant factor in performance.
  • Forecasting returns is not the main source of performance.

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Three forms of diversification explain much of the long term performance.

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SLIDE 17

WHICH APPROACH IS PREFERABLE – FUNDAMENTAL OR QUANTITATIVE?

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What does matter: The process (not necessarily the methodology) and total fees It doesn‟t matter!

  • You cannot tolerate underperformance over 3 to 5 years.
  • Sources of creation of enigmatic value
  • “Closet Indexing”
  • If fees are unreasonable

AVOID ACTIVE MANAGEMENT IN THE FOLLOWING SCENARIOS:

The best managers share a similar philosophy even if the implementation methodology is different.

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SLIDE 18

JACQUES LUSSIER, President & Chief Investment Officer

514-842-2224, jacques.lussier@ipsolcapital.com

HUGUES LANGLOIS, Director of Research

646-583-2092, hugues.langlois@ipsolcapital.com

GUY DESROCHERS, VP & Chief Compliance Officer

514-842-2225, guy.desrochers@ipsolcapital.com

LUC GOSSELIN, Director of Operations

514-842-2022, luc.gosselin@ipsolcapital.com 18 This document has been prepared for information purpose only, and does not constitute an offer or solicitation to buy or sell any securities, products or services and should not be construed as specific investment advice. The content of this presentation is proprietary and should not be further distributed without prior consent of IPSOL Capital Inc. Les informations et les opinions exprimées dans ce document sont offertes à titre informatif seulement et ne doivent pas être considérées comme une

  • ffre ou une sollicitation visant l‟achat ou la vente d‟un titre, d‟un produit ou d‟un service quelconque, ni interprétées comme un conseil de placement

précis. Le contenu du présent document est la propriété exclusive d‟IPSOL Capital Inc. et ne doit pas être distribué sans son consentement préalable.

368 Notre-Dame West, Suite 301, Montreal, Québec, H2Y 1T9, www.IPSOLCAPITAL.com

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SLIDE 19

Jacques Lussier is a former academician at HEC Montreal and has worked within the financial industry for 18 years at Desjardins Global Asset Management (DGAM) where he was Chief Investment Strategist until March 2013. During his career, Jacques has been involved in most segments of the asset management industry: portfolio policy and global asset allocation for institutional clients, fund of funds management both alternatives and traditional, research leading to product design and product management in the equity, commodity and asset allocation space and management of high net worth platforms.

  • Jacques earned a M.Sc. in Finance from HEC Montreal and a Ph.D. in International Business from the University
  • f South Carolina.
  • He was President of the CFA Society Montreal from 2013 to 2014 and CFA Institute‟s volunteer of the year in
  • 2015. Jacques is also one of four members of the CFA Institute‟s Research Council for America responsible for

proposing new research avenues.

  • He is a board member of Régie des Rentes du Québec and a member of its investment and audit committees. He

is also a member of the advisory board of InvestorLit and the author of the book “Successful Investing Is a Process” published by Wiley and Bloomberg Press in December 2012. Jacques is currently working on another book to be published in 2016.

  • Jacques is CEO and CIO of IPSOL CAPITAL.

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JACQUES LUSSIER

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