Northfield s 25th Annual Research Conference San Diego August 7 9, 22 Quantitative Asset Management for Turbulent Markets Michel Crouhy Head of Research & Development NATIXIS Corporate & Investment Bank michel.crouhy@natixis.com
BCPE Group Natixis is the corporate and investment banking arm of the BPCE Group. BPCE Group is the: 9 th Banking Group in Europe ranked by net profit, $3.68Bn (FY 2 Results) () 23 rd Banking Group in the World in terms of total assets, $2,52.57Bn (December 3, 2) (2) Groupe BPCE, at a glance (Figures as of December 3, 2) 2nd-largest banking player in France 36 million clients 8. million cooperative shareholders 7, employees 8, bank branches Net Banking Income***: $32.5 bn Net income (group share)***: $3.74 bn Tier capital**: $53.35 bn Core Tier- ratio: 9.% 9 BANQUE POPULAIRE BANKS Commercial banking and insurance: subsidiaries 5% 5% 72.3% 7 CAISSE D EPARGNE BANKS Financial stakes: Coface Float 27.7% () Source: banksdaily.com; (2) Source: www.relbanks.com ** Exchange rate: = $.298, *** Exchange rates: For 2: = $.39955; for 2: = $.32577 2 2
Natixis - One Company, Three Core Businesses Natixis Key Figures Corporate & Investment Banking Equity Markets Fixed Income Financing Investment Solutions Asset Management (NGA) Insurance Private Banking Private Equity Specialized Financial Services Factoring Sureties & Guaranties Leasing Consumer Finance Long-term ratings as of June 9, 22 Standard & Poor s A (stable) Moody s A2 (stable) Fitch Ratings A+ (negative) Consistent performance** as of December 3, 2 Net income (group share) $2.74Bn -5% vs. 2 Net revenues $9.35Bn +8% vs. 2 Revenue Breakdown by core businesses (2 Results) INVESTMENT SOLUTIONS $2.62bn +% Vs. 2 CIB 32% 2% Financial structure as of December 3, 2 Core Tier ratio.2% Including P3CI transaction impact Tier ratio.9% Including P3CI transaction impact Tier capital $2.3Bn SFS $.6bn +2% Vs. 2 $3.84bn -4% Vs. 2 48% Source Natixis Exchange rates: For 22: = $.3343; For 2: = $.39955;for 2: = $.32577 * *Including non operating items, o/w own senior debt fair-value adjustment included in net revenues 3
Natixis Global Asset Management (Affiliated Companies) Industry-leading investment thinkers in key markets globally Expertise: Asian & emerging Asian equities Founded: 998 Headquarters: Singapore AUM: $772 M Expertise: Customized hedge fund solutions Founded: 24 Headquarters: Paris, France Expertise: European multi-strategy specialists Founded: 984 Headquarters: Paris, France AUM: $386. B 2 Expertise: Index-based solutions Founded: 22 Headquarters: Oakland, CA AUM: $394 M Expertise: Hedged equity strategies Founded: 977 Headquarters: Cincinnati, OH AUM: $8.5 B Expertise: Multi-style, multimanager funds Founded: 2 Headquarters: Paris, France AUM: $2.3 B EUROPE Expertise: Real estate investments Founded: 98 Headquarters: Boston, MA AUM: $4.8 B Expertise: European real estate Founded: 2 Headquarters: Paris, France AUM: $24.6 B Expertise: Absolute return strategies Founded: 999 Headquarters: Cambridge, MA AUM: $3.9 B Expertise: Alternative investment mgmt. Founded: 988 Headquarters: Chicago, IL AUM: $.6 B Expertise: Concentrated equity portfolios Founded: 99 Headquarters: Boston, MA AUM: $4.7 B Expertise: U.S. private equity Founded: 28 Headquarters: New York, NY AUM: $846 M Source: Natixis Global Asset Management Expertise: Alternative global fixed-income and global macro management Founded: 2 Headquarters: London, UK AUM: $2.5 B Expertise: Global/international investments Founded: 994 Headquarters: Ft. Lauderdale, FL AUM: $7.5 B Expertise: Value investments Founded: 976 Headquarters: Chicago, IL AUM: $74.6 B Expertise: Indian equity and fixed-income investments Founded: 2 Headquarters: Mumbai, India AUM: $4.8 B Expertise: Actively managed, research-driven equity and fixed-income portfolios Founded: 926 Headquarters: Boston, MA AUM: $69.4 B Expertise: Overlay management Founded: 25 2 Headquarters: Oakland, CA AUM: $9.3 B Expertise: ETFs and quantitative strategies Founded: 29 Headquarters: Paris, France AUM: $48 M Expertise: Money market funds & cash management services Founded: 97 Headquarters: New York, NY AUM: $3. B Expertise: U.S. small- and mid-cap value investments Founded: 984 Headquarters: San Francisco, CA AUM: $.9 B Expertise: Value equity investments Founded: 97 Headquarters: Houston, TX AUM: $7.4 B AUM as of 3 March 22. Caspian Private Equity is a joint venture between Natixis Global Asset Management, Natixis Private Equity and Caspian Holdings. 2 A division of NGAM Advisors, L.P. 4 August 7, 22 4
Agenda I. Introduction II. III. Advanced Risk Perception Indicator and Risk Control Framework Rolling Volatility Strategies 5
I. Introduction 6
Asset Allocators have to cope with tail risk The rewards of risk premium are wiped out by a small number of extreme risk events 7
Mitigating Tail Risk Approach Description Remarks Stop Loss Mechanism Divest from risky assets when the market drops to a predetermined barrier Simple Reactive Use Derivatives Subjective approach Derivatives such as options or futures to provide downside protection For example bonus smoothing Gradually divest from equities in good years Timing sensitive Potentially expensive Subjective Perceived as black box Quantitative Models [Reactive] Rule based asset allocation such as CPPI or volatility target strategies Reactive Objective Quantitative Models [Forecasting] Fundamental research based quantitative models Equity Markets ARPI and Risk Control Framework 8
II. Advanced Risk Perception Indicator and Risk Control Framework 9
Equity Markets - ARPI and Risk Control Framework Natixis Equity Markets has developed a family of investable indexes: Rule-based Quantitative technology developed in-house Allocation occurs between liquid market instruments With these indexes, it is possible to: Build cheap passive indexed funds Provide increasingly sophisticated guarantees and enhance investor protection The investment can be structured through: Mutual Funds - Physical - Synthetic Debt Wrappers
What is the Advanced Risk Perception Indicator? The ARPI is an indicator of perceived market risk. Among the numerous potential measures of investor risk aversion (in the US market), we have selected three classes of observable indicators: IMPLIED VOLATILITY Implied Volatility of Equity Markets (VIX) Strong and robust anti-correlation with equity markets Implied volatilities (vs. historical) can anticipate / estimate future realised volatility CREDIT SPREADS CDX Investment Grade non-financials CDX High Yield Risk aversion measure expressing expectations of default rates Quantifies the conditions of access to credit and the cost of cash US YIELD CURVE DYNAMICS Slope Y-5Y Difference Y-Annual Moving Average Y Measures medium term growth expectations Captures the effects of investor flight to quality and movements in liquidity preference resulting from changes in the FED monetary policy Average of Normalized Market Observables ARPI
Extracting Regimes from ARPI the HMM Methodology Natixis Quantitative Research implemented an algorithm that is based on a statistical model called the HMM (Hidden Markov Model) A recursive filter enables us convert the time series of the ARPI into a time series of regimes The filter takes three types of information into account: Where we are (the current level of ARPI gained from the new information) Where we have come from (the level of the regime at the previous date) How fast we are moving (incorporates the historical probability for change of regime - the inertia) A change of regime occurs when the current level of ARPI becomes statistically incompatible with the current regime. Insignificant Market Changes and White Noise are ignored ARPI Regime t- HMM Filter Regime t Life-long learning detects new trends 2
HMM Risk Regimes Are Stable Changes of Regime per Year since Inception Regime Regime 2 Regime 3 Regime 4 8 6 4 2 9 4 4 3 2 2 23 24 25 26 27 28 29 2 2 Regime Regime 2 Regime 3 Regime 4 99.7%.6%.%.%.93% 99.3%.39%.%.%.36% 98.63%.2%.%.%.98% 98.98% Key observations: There is a high degree of inertia in the HMM model (probability of remaining in the current regime from one day to another over 95%) Helps to minimize transaction costs in implementing a reallocation strategy Probability Density US ARPI Distribution by regime Regime Regime 2 Regime 3 Regime 4,,2,4,6,8, US ARPI 3
History of the US ARPI Regimes vs S&P 5 Index Observing historical data from July, 999 to July 6, 22, we have identified 4 regimes within the perceived risk indicator..2 8.8 6 4 2.6.4 8 6.2 4 2 Jul-99 Jul- Jul- Jul-2 Jul-3 Jul-4 Jul-5 Jul-6 Jul-7 Jul-8 Jul-9 Jul- Jul- Jul-2 Regime Regime 2 Regime 3 Regime 4 US ARPI SPX Index Sources : Bloomberg, Natixis from July, 999 to July 6, 22 4
Contributions of the US ARPI Components Renormalization of 3 market observations Aggregation into an Advanced Risk Perception Indicator (ARPI) ranging from % (min risk) to.2 % (max risk). Contributions of the US ARPI Components from July, 999 to July 6, 22..8.6.4.2. Jul-99 Jul- Jul- Jul-2 Jul-3 Jul-4 Jul-5 Jul-6 Jul-7 Jul-8 Jul-9 Jul- Jul- Jul-2 Equity Volatility Contribution Rates Contribution Credit Contribution US ARPI Sources : Bloomberg, Natixis from July 4, 999 to July 6, 22 5
Putting it all together The final step in the process is to allocate between asserts, based on the prevailing regime of the day The allocation weights between assets are generally fixed at the beginning of the strategy, and are aligned with the differing perceived risk levels associated with each regime As seen, in the majority of cases there is no change to the prevailing regime Market Data ARPI HMM Regime Highly Aggressive Allocation Regime Rule Regime 2 Moderately Aggressive Allocation Regime 3 Moderately Conservative Allocation Regime 4 Highly Conservative Allocation Allocation Assets Proprietary Strategy 6
Overview of the application: The NXS SHARPe Series ARPI Regime Regime Offensive Profile Regime 2 Dynamic Profile Regime 3 Balanced Profile Regime 4 Conservative Profile Allocation RISK: Low Moderate High Very high Flagship Index SHARPe US Equity Index % 25% 25% 75% 75% % Equity Risk Free Asset SHARPe Multi Asset Worldwide Index 25% % % % 35% 25% % 5% Equity Real Estate Commodity 25% 5% 2% 25% 35% % % 35% 5% Hedge Funds Bonds MLT Bonds ST Cash 7 August 7, 22 7
NXS SHARPe Multi Asset Worldwide USD Dynamic reallocation between 4 distinct management profiles Offensive, dynamic, balanced and conservative 7 asset classes in the worldwide markets through liquid indices Equity : US, Europe and Emerging Markets Real-Estate : Listed REITsindex (US & Europe) Commodities : Listed Commodity index Hedge Funds : Natixis HF replicating Index ie NXS-AIR Index (Ticker Bloomberg : IQHGIXIS Index) Medium Long Term Bonds : LT US and Europe Government bond index (duration > 3 years) Short Term Bonds : LT US and Europe Government bond index (duration < 3 years) Cash : Compounded overnight US rate A portfolio fully invested at any time, without leverage and no short positions Offensive Profile 25% 25% 5% Dynamic Profile % % 35% 2% 25% 7 Balanced Profile % % 25% 7 35% % % % Conservative Profile 2% 5% 3% Equity Real-Estate Commodity Hedge Funds Bond MLT Bond ST Cash 8
NXS SHARPe Multi Asset Worldwide USD Performance 6 5 4 3 2 Comparison of performances SHARPe Multi Asset Worldw ide Static Strategy Equity Real-Estate Commodity Hedge Funds Bond MLT Bond ST Cash Annual return 2% % 8% 6% 4% Hedge Funds Comparison of the annual risk / return between asset classes SHARPe Multi Asset Worldw ide Bond MLT Bond ST Commodity Real-Estate Equity 2% Cash % 999 2 2 22 23 24 25 26 27 28 29 2 2 % 5% % 5% 2% 25% 3% Volatility Investment in the strategy and asset classes achieved from /7/99 to 2/2/ 9
3 Protection Layers for a Resilient Investment Solution Layer Risky Asset Allocation : The Risky Asset Allocation is designed to embed a Natixis SHARPe Quantitative Allocation Layer 2 Performance Engine: The performance engine implements a Volatility Control mechanism A Systematic rebalancing occurs between the Natixis SHARPe Allocation and a Safe Asset The rebalancing follows the ratio of the Target Volatility to the Realised Volatility Layer 3 Smart CPPI on the Performance Engine : A classic CPPI portfolio management technique is at risk of Cash-lock Using Natixis ARPI and HMM, the Cash-lock is eliminated for higher risk regimes 2
Constant Proportion Portfolio Insurance (CPPI) Basic Structure: The CPPI Protects a fixed percentage (typically 8%) of the maximum observed NAV by dynamically re-balancing between risky and risk-free assets, on the basis of a predefined mechanism In the most simple case, the difference between current NAV and the protection level (the cushion ) is calculated. A constant proportion of the cushion is then invested in the risky asset As the risky asset moves, the portfolio is rebalanced in accordance with the cushion available FUND NAV = % PROTECTION = 8% CUSHION = NAV PROTECTION = 2% MULTIPLIER = 3 FUND NAV = 25% PROTECTION = % CUSHION = NAV PROTECTION = 25% MULTIPLIER = 3 FUND NAV = 9% PROTECTION = 8% CUSHION = NAV PROTECTION = % MULTIPLIER = 3 6% RISK ASSET 75% RISK ASSET 3% RISK ASSET 4% CASH 25% CASH 7% CASH 2
Natixis Smart CPPI Key drawbacks of traditional CPPI: Cash-Lock: In a falling market, cushion can become zero leading to the structure becoming cash-locked Path dependence: Fund performance has path dependency and suffers from weak recovery dynamics Solution: A Smart CPPI product offering based on Natixis proprietary/ quantitative assetallocation model (SHARPe) with the main product benefits: Not path-dependent (typical of standard CPPI/ Vol control offering) Asset allocation rebalancing process is risk-regime switching-based The ability to remove market movement sensitivity allow the product design to be less Greeks hedging sensitive Efficient protection in sharp market downside allow the product to react more positively in draw-down scenarios An optimal product feature which can allow more flexibility on actuarial (behavioral assumptions, fund switching, lapse...) through a constant protection mechanism (no cash lock-in) Ability to be packaged in multiple offerings (Asset-Allocation expertise, Separate Managed Account and Derivatives) with no direct credit exposure to the model provider 22
Smart CPPI using the ARPI The Smart CPPI makes use of the ARPI for allocation purposes. Allocation is made according to a variable Multiplier. The Multiplier is scaled according to the ARPI Allocation is conservative during periods of high risk aversion Allocation is aggressive during periods of low risk aversion RISK ASSET EXPOSURE = CUSHION x Function of Risk Regime VARIABLE MULTIPLIER Variable Multiplier Regime Highly Aggressive Allocation 5 Regime 2 Moderately Aggressive Allocation 3 Regime 3 Moderately Conservative Allocation Regime 4 Highly Conservative Allocation Cushion 2% X Bond Floor 3 8% Risk Asset 6% 23
The Vol Target Smart CPPI Strategy Function of Risk Regime RISK ASSET EXPOSURE = CUSHION x VARIABLE MULTIPLIER x Volatility Adjustment Factor 24
The Vol Target Smart CPPI Strategy Back-tested Simulations from July 999 to July 22 Smart & Smooth TIPP SPX Backtest 8 % 9% 6 8% Performance 4 2 7% 6% 5% Risky Allocation 4% 3% 8 2% % 6 % Jul-99 Jun- Jun- Jun-2 Jun-3 Jun-4 Jun-5 Jun-6 Jun-7 Jun-8 Jun-9 Jun- Jun- Jun-2 Effective Risky Alloc (RHS) SPX TR Smart & Smooth TIPP Protected Level Standard TIPP (Multiplier = 3) Sources : Bloomberg, Natixis * Past performance does not guarantee and is not indicative for future results 25
The Vol Target Smart CPPI Strategy What about Cash Lock Event risk? Such an event could occur only in regime or 2 Using the SPX as an example: In REGIME (multiplier = 5): monetization risk if SPX draw downs > -2% between 2 rebalancing dates In REGIME 2 (multiplier = 3): monetization if the SPX draw downs > -33.3% between 2 rebalancing dates In REGIME 3 (multiplier = ): no risk of monetization In REGIME 4 (multiplier = ): no risk of monetization 2% 8% t Risky asset = 2 x M Cash = 2 M t + Risky asset = 2 x M ( - ) Cash = 2 M ( 2 M) + 2 M ( - ) > 8 < /M 26
Resilience of a Smart CPPI in Higher Risk Regime 27
III. Rolling Volatility Strategies 28
How It Works Benefit from long volatility exposure in stressed market, and from reduced cost in calm market Natixis Rolling Volatility Strategy Stressed Market High negative correlation to equities Rapid & strong response to market selloff Earn positive carry when the volatility term structure inverts Calm Market More decoupled from equities Monetize upward sloping volatility term structure by selling front month Future Potentially profit from the negative roll yield Rolling mechanism of Long/ Short Volatility depending on Volatility Shape 35 Backw ardation Volatility Shape 23 Contango Volatility Shape 22 33 3 Protection + positive slide 2 2 Protection 29 ' 9 Earn Carry 8 27 25 7 6 downward slide m 2m 3m 4m 5m 6m 7m m 2m 3m 4m 5m 6m 7m 29
Evolution of VIX Futures Term Structures VIX Futures Term Structures are often in contango during calm markets in backwardation during stressed markets 3
How It Works Select an allocation with Volatility Term Structure Frequency of Contango - Monthly Data since Jan 27 SPX & TS Indicator - Data since Nov 26 27 28 29 2 2 22 Jan % 48% % % % % Feb % 45% 2% % % % Mar 5% 4% 8% % 87% % Apr % % % % % % May % % % 35% % % Jun % % % 68% % % Jul 8% 36% % % 95% % Aug % 95% % % % Sep 32% 38% % % 24% Oct % % % % 8% Nov 62% % 8% % % Dec % 45% % % % VIX vs. TS Indicator - Data since Jan 27.4 TS.3.2..9 Nov-6 Aug-7 Apr-8 Jan-9 Sep-9 Jun- Feb- Nov- Jul-2 SPX Contango Backwardation The term structure is measured with SPX options of different expirations. Dark bands mark periods where short term volatility (as measured by the VIX) exceeds medium term volatility (as measured by the VXV). TS = Term Structure Indicator TS < - Contango TS > - Backwardation 8 6 4 2 8 6 4 2.8.7 27 28 29 2 2 22.6 VIX 2 4 6 8 TS = Vix / Vxv where Vxv = CBOE S&P 5 3-Month Volatility Index All sources for tables & graphs: Natixis, Bloomberg as of July 3st 22 3
Flexible Investment Choices Investing in the Natixis Rolling Volatility Strategy can be available through a choice of vehicles: SPX Overlay: Example of a combined allocation Swap, Note linked to the strategy performance Combined with other assets as a macro-hedged portfolio fund 3% 25% SPX/NXS Rolling Volatility Strategy Allocation 5%/5% SPX/NXS Rolling Volatility Strategy Allocation 75%/25% SPX Multiple users Insurance Company Asset Manager Pensions & Endowments Registered Investment advisors (RIAs) Hedge Fund, Fund of Fund Credit Fund Sovereign fund 2% 5% % 5% % Nov-6 Dec-7 Jan-9 Feb- Apr- May-2 Past performances are not reliable indicators for future results or performance. Variations may be material. All sources for tables & graphs: Natixis, Bloomberg as of May 3 st 22 32
In Depth: Strong responsiveness in market downturns Convexity of the Natixis Rolling Volatility Strategy to SPX return - Data since Nov 26 Tail Events Focus 3% 25% 2% 5% % Strong reactivity in market downturn Natixis Rolling Volatility Strategy SPX Year 28 +8.% -38.5% 2 Flash Crash [Apr-Jul] +5.6% -6.% 2 S&P Downgrade [Jul-Oct] +65.6% -8.3% 5% % -5% -% NXSRVS 5d %chg* -5% Controlled downside risk -2% SPX 5d %chg* *Overlapped data -2% -5% -% -5% % 5% % 5% 2% Past performances are not reliable indicators for future results or performance. Variations may be material. All sources for tables & graphs: Natixis, Bloomberg as of May 3 st 22 33
In Depth: Comparison to SPX y ATM Puts Relative Performance to S&P Index Puts from Jan 2 to Jan 22 P & L ( $ ) 5-5 Comparison of Rolling Volatility Strategy to SPX Year Puts Both strategies rebalanced quarterly to a $ investment. Strong Bleeding - Natixis Rolling Vol Strategy SPX 2M Puts ATM -5 Jan- May- Sep- Jan- May- Sep- Jan-2 Cumulative P & L Spread ( $ ) 5 5-5 - Relative Performance of Rolling Vol Strategy to SPX year Puts Spread: Natixis Rolling Vol Strategy - Puts Net + $ 64-5 Jan- May- Sep- Jan- May- Sep- Jan-2 Jan 2-Jan 22 Focus P & L ( $ ) 5-5 Comparison of Rolling Volatility Strategy to SPX year Puts Both strategies rebalanced quarterly to a $ investment. - Natixis Rolling Vol Strategy SPX 2M Puts ATM -5 Jan- May- Sep- Jan-2 Cumulative P & L Spread ( $ ) 5 5-5 Relative Performance of Rolling Volatility Strategy to SPX year Puts - Spread: Natixis Rolling Vol Strategy - Puts -5 Jan- May- Sep- Jan-2 Net + $ 6 All sources for tables & graphs: Natixis, Bloomberg as of May 3 st 22 34
Natixis Rolling Volatility Strategy Implementation Based on exchange-traded VIX Futures contracts Dynamic long/short allocation, always net positive volatility exposure Allocation between near term and far term maturities Cost control through monitoring the volatility yield cost Macro Behaviors Step-up or Spike-up behavior during crises and crashes Carry cost management in periods of stable volatility Strong sensitivity to equity without strike levels (contrast to put options) An alternative to timing the market or timing the hedge Monthly Performances - Data since Jan 27 27 28 29 2 2 22 Jan -3.4% -.3% 2.8% -.4% -7.4% -4.6% Feb -3.% 2.7% 7.5%.3% -.5% 3.7% Mar -2.7% -.3% 5.% -.7% -2.6% -8.6% Apr.% -4.7% -5.% 2.3% -2.4%.3% May 3.% 6.% -6.%.8% -.6% 7.% Jun 3.6% -.5%.4%.% -.4% Jul 5.4% -4.7% 4.% -4.% -4.3% Aug 8.% 3.4% 3.9% 8.2% 32.% Sep -7.9%.5%.4% -.4% 2.7% Oct 6.4% 67.9% -.7% -4.9% -6.3% Nov 8.2% 2.3% 2.% -.3% 5.4% Dec 2.6% -2.5% -.% -7.% -6.4% Annual Return 33.3% 8.% 3.% 4.4% 8.2% -2.8% 6% 5% 4% 3% 2% Cumulative Performance - Data since Nov 26 A staircase-like progression 28 Flash Crash 2 S&P USA Downgrade 2 % NXS Rolling Volatility Strategy % VXZ (SPVXMTR Index) Nov-6 Dec-7 Jan-9 Feb- Apr- May-2 Return & Volatility - Data since Nov 26 Natixis Rolling Volatility Strategy Index SPX Index Annualized Return +27.3% -.4% Best Month +67.9% +2.% Average Monthly +2.7% +% Max Drawdown -2.5% -9% Annualized vol 29.3% 25.6% % Winning Month 5.8% 6.6% Past performances are not reliable indicators for future results or performance. Variations may be material. All sources for tables & graphs: Natixis, Bloomberg as of May3st 22 35
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