Presentation at Yale University Ramu Thiagarajan

1. September 16, 2013 Fixed Income Asset Management Presentation at Yale University Ramu Thiagarajan Global Head - Fixed Income Quantitative Research

2. Agenda • Issues in Fixed Income Asset Management • Size of the Market and Performance of the market • Risks in Fixed Income Assets • How do you make money in Fixed Income • When does quant fail? • Security Selection Issues in FI • Use of FI in Other Strategies • Asset Allocation Issues (depending on time) • Q&A

3. Fixed Income Asset Management – Size of the Market • Fixed Income Market vs. the Equity * • Market Cap: Equity Market • Market Cap: Bond market ? 53 Trillion 92 Trillion • What are the different type of FI securities FIX (Agency, Local Authority…) (Financials, Utility, Industrial...) (MBS, ABS, CMBS...) • * Source: Bond—BIS consolidated “Debt security statistics”, Equity—WorldBank “Market Capitalization”, as of 2012

4. Performance of Equity vs. Bonds

5. Fixed Income Asset Management • What drives FI returns • Role of Systematic Risk vs. Idiosyncratic Risk • How do you make money in FI portfolios • Tools for Positioning on Systematic Risk • Tools for Positioning for Alpha • Alpha in Rates • Alpha in Credit

6. Fixed Income Asset Management • Has its own Lingo • Confusing array of indices • BarCap US Aggregate / US Aggregate Intermediate • BarCap US High Yield / US High Yield 2% Issuer Cap • J.P. Morgan EMBI+ / EMBIG / EMBIG Diversified / GBI-EM / GBI-EM Global… • Complex set of derivatives • Interest rate swap, futures, FRA; Swaptions, Caps & Floors • CDS, CDX, TRS; CLN, CDO Caps, Floors Floaters Strips CDS CMTs Swaptions Spread Duration, Bull Duration, Bear Duration Bull Steepeners, Bear Flatteners Caplets, Floorlets

7. Many moving parts in a FI security • Yield curve -- • Duration, Slope and Convexity • Spread Risks • Mortgages • Corporates • Municipals • TIPS • Currency rate movements • Volatility and Prepayment Risk – specific to MBS • Liquidity Risk

8. What drives risk in fixed income securities • Systematic Risk • Level, Slope & Curvature • Volatility • Idiosyncratic Risk • Security Specific Risk • Argentinian Bonds

9. Beta Explains 90-95% of the Volatility of a Diversified Portfolio US Investment Grade Corporate Index Brokerage Reits Finance Companies Excess Return (%)  April-Sept 2009 Insurance Banking Basic Industry Consumer Cyclical Capital Goods Consumer Non-Cyclical Historical data to be used for illustrative purposes only. As of: September 30, 2009 Source: Barclays Capital and AllianceBernstein

10. Systematic Risk vsIdiosycratic Risk • Systematic Risk in Yield Curve (Litterman and Scheinkman [1991]) • 3-factor model(Level, steepness and curvature) explains more than 95% or Variance of excess returns

11. How do you make money when systematic Risk contributes to such a high proportion of variance explained • You need to get a feel for the risk regime you are in. • Can you forecast risk regimes? • Many different methods • Regime switching models • Hidden Markov models • A simpler way of looking at Risk Regime Indicators • Supply of Liquidity • Demand for Liquidity

12. The Slope of the Yield Curve as a Leading Indicator of Future Real Economic Activity As of September 2011 Source: St. Louis Fed Economic Data 11

13. Unemployment Rate Goes Up When The Curve Is Inverted… Historical data to be used for illustrative purposes only. As of January 2010 Source: Adrian, Estella and Shin (2010), New York Fed

14. …However Slope Is Not a Good Predictor of Future Market Movement Historical data to be used for illustrative purposes only. As of February 2010 Source: AllianceBernstein 13

15. Capital Markets Lag the Slope of the Yield Curve • Get out of the market too early • Enter the market too early Index Slope As of August 2011, Global Credit Opportunities Portfolio (Michael Weisman:NY) Source: AllianceBernstein 14

16. VIX Alone Cannot Be Used As Market Regime Indicator • The percentage of positive 6-month-forward returns does not decline monotonically as VIX increases across the quintiles • Q1 – lowest VIX quintile, Q5 – highest VIX quintile Percent Positive Return VIX Quintiles As of August 31, 2011 Source: Bloomberg and AllianceBernstein

17. Market Cycle Indicator: Identify Current Regime and Regime Trend • US IG Corp • US HY Corp • S&P • EMD • Currency • CMBS Our Market Cycle Indicator (MCI) is a proprietary tool we use to identify the macro phase Phase I Phase II Phase III Phase IV 12/31/2003 2/28/2010 Q2 2011 3/31/2007 10/31/2000 10/31/2008 Historical data to be used for illustrative purposes only. As of February 1, 2010 Green dots are representations of points in time. Returns are annualized monthly excess returns to Treasuries. Currency returns are top five minus bottom five G10 currencies as measured by interest-rate differentials. US HY Corp.: August 31, 1998–February 28, 2010; US IG Corp: August 31, 1998–February 28, 2010; EMD: January 31, 1993– February 28, 2010; Currency: June 30, 1979–February 28, 2010. S&P: June 30, 1979-February 28, 2010. CMBS: June 30, 1999-February 28, 2010. Source: Barclays Capital, Bloomberg and AllianceBernstein 16

18. Macro Insights: Market Cycle Indicator Identifies Signals Amongst Noise • Macro Economy • Monetary Policy • Liquidity • Volatility • Macro Economy • Monetary Policy • Liquidity • Volatility • Macro Economy • Monetary Policy • Liquidity • Volatility Income Bias • Asset Return • Correlation Risk Averse • Asset Return • Correlation Measured Risk • Asset Return • Correlation Risk Seeking • Asset Return • Correlation Phase I Phase II Phase III Phase IV • MCI is above average and increasing • MCI is above averageand decreasing • MCI is below averageand decreasing • MCI is below averageand increasing Typical Conditions of Market Factors • Macro Economy • Monetary Policy • Liquidity • Volatility Typical Market Performance As of February 2010 Source: AllianceBernstein 17

19. Market Cycle Indicator Market Cycle Indicator Score As of August 31, 2011 Source: AllianceBernstein 18

20. Market Cycle Indicator Continues to Diverge by Region AllianceBernstein MCI As of Jul 24, 2013 Source: AllianceBernstein 19

21. Components of the new Euro Crisis Indicator • Fundamental Variables : • Unemployment Rate • PMI • YoY Private sector credit growth • YoY Government debt growth. Market-based Variables: • CDS on USD senior 5 year (solvency) • EURIBOR-OIS (liquidity) • 2 year yield in local currency and • Corporate Credit OAS (risk premium) Choice of Variables: We picked reasonable proxies ex-ante for the following underlying constructs – Solvency, Liquidity and risk premia. • We use the spread between PIIGS country and Germany for the variables. • We use the sum of the equally weighted z-scores (4 market and 4 fundamental) as our Euro crisis indicator.

22. Euro-Crisis Indicator

23. A side note on the importance of risk regime indicators for Equity selection strategies • Equity stock selection model • Valuation • Quality • Momentum • Analyst behavior • Size • How do those behave in different risk regimes?

24. Equity Factor Returns Under Different Regimes • Analyst behavior • Earning Momentum • Expected Growth • Valuation • Price Reversal • Relative Value • Quality • Profit Trend • Momentum • Price Momentum • Size Percent As of August 31, 2011 Source: Credit Suisse and AllianceBernstein

25. ALPHA MODELS IN FIXED INCOME

26. Building Factor Models for Fixed Income • Deterministic Components of the yield curve • Carry • Roll down • Stochastic Components of the yield Curve • Changes in the yield curve

27. Global Country/Yield Curve Model: Multiple Integrated Elements Term Structure Movement Carry and Roll Down Bond Return + =

28. Global Country/Yield Curve Model:Outputs • January 2011 Expected Returns: • Point to an Underweight in Canada January 2012 Expected Returns: Point to an Overweight in Canada Composition of Forecast Change in Global “Level” by Factor* 5 4 3 2 1 0 (1) 0.15 0.10 0.5 0 (0.05) (0.10) (0.15) (0.20) (0.25) 4.5 3.5 2.5 1.5 0.5 (0.5) EUR USD Globe Percent Percent Percent CAD CAD JPY EUR Globe JPY USD Expected returns are over 6 months, annualized, hedged to USD. *Percentage change over six months • Source: AllianceBernstein 27

29. Global Country/Yield Curve Model:Outputs

30. Global Credit Model: Multiple Integrated Elements Spread Movement Carry Excess Return + = *Peer group refers to issuers within the same duration and spread range

31. Global Credit Model:Outputs Expected Excess Returns Suggest Positioning Changes • Three-month forward expected excess returns for intermediate maturities, derived from AllianceBernstein quantitative forecasts Source: AllianceBernstein

32. Risks in Corporate Bonds Corporate Bonds carry a lot of Idiosyncratic Risk If Spreads widen on a bond, it will take 20 winners to over that loss Example: Enron Bonds

33. Fundamental Credit Model Framework

34. Model Framework

35. Correlation of Factors

36. Factor Performance Source: AB Research, Barclays, Compustat, FactSet

37. Our Fundamental Alpha Score is a strong predictor of forward returns that has worked well over time. Source: AB Research, Barclays, Compustat, FactSet

38. Batting Average

39. Staying in Low Composite Group is More Likely to Suffer Blow-up • Looking at the data from 2008 to 2010, names in Quintile One is more likely to suffer the blow-up in spread • We define blow-up as spread widens more than two standard deviation from the mean spread movement at the same period of time

40. Fundamental Model Live Performance (2012- 2013)

41. What have we done so far? • Built Built Risk Regime Models – To get beta positioning right • Built Alpha Models - To get security level positioning right • Build Risk Models – To monitor risk in portfolios

42. Fundamental vs Quant • Failure of Quant Models: • Why Do quant models fail? • Failure of Risk Regime Models • A steep slope is an environment for risk taking, but our FED has engineered a steep slope and has not be necessarily been a great environment for risk taking • Failure of Alpha Models • Mean reversion factor in the country-to-slope model – failed during crisis • Failure of Fundamental Credit Models • Event Risk • BOTTOM LINE – WATCHING MONEY FLOWS IS IMPORTANT IN FI MANDATES • COMBINING QUANT AND FUNDAMENTAL SIGNALS IS VERY IMPORTANT

43. Yield Curve Model failure during crisis -- Total Return Ranking 12 DM countries: We rank the countries based on Total Return Forecast and put highest 1/3 in the top bracket and the lowest 1/3 in the top bracket. For each of the brackets, we add the average of the 6 month forward total return. (divided by 6 in this monthly plot) for the countries in the bracket.

44. FCM Model Risk • Potential high turnover and related transaction cost can eat up the excess return • High turnover from equity return and earning revision • OAS is not a clean credit risk measure, hence valuation can be misleading due to: • Risk aversion, driven by macro-environment and investor sentiment • Liquidity premium, which is driven by supply and demand and institutional preference • The model works at the portfolio level and it should be used with great caution when picking one or two names rather than a basket of names simply based on the composite score

45. FCM Model Failure Examples • AMGN: It was a low score name because of negative contribution from cash accruals factor. However, it didn’t consider the nature of its one time litigation cash payment. Stripping away that component, it will make the name more favorable • DELL: Event risk (LBO). Dell was a high score name driven by attractive spread and positive equity performance. However, the bonds failed to perform because the spread is priced in the forward-looking increase of leverage and the company was transferring the wealth from debt holder to equity holder

46. Managing Risks in FI Portfolios – Rate Volatility is important Source: Bloomberg. Unit: bps, annual implied Vol

47. Managing Risk in FI Portfolios -- Scenario Analysis • When volatility spikes, historical correlations fail and even small exposures can be hurtful US Rates sell-off

48. What Happens when Both Fundamental and Quant Fails Pray…

49. Asset Allocation and Risk Parity • What is Risk Parity? • Ways to Accomplish Risk Parity • Lessons from Studies in Risk Parity • Applications of Risk Parity

50. Magic of Portfolio diversification Introduction ReturnYear One ReturnYear Two Asset A 100% -50% Asset B -50% 100% • Portfolio composed of two risky assets with 50% allocation to each (rebalanced) delivers high return zero volatility (in this case) ReturnYear One ReturnYear Two 50/50Portfolio 25% 25% • Diversification is only free lunch?