Unlisted Assets and Enterprise Risk Management. Emilian Belev, CFA and Richard Gold Newport June 7, 2013

Transcription

1 Unlisted Assets and Enterprise Risk Management Emilian Belev, CFA and Richard Gold Newport June 7, 2013

2 Unlisted Asset Classes Real Estate Private Equity Infrastructure Slide 2

3 Unlisted Assets: A practical problem for Total Risk Fama-French is not common jargon in real estate investment departments Unlisted investment experts tend to think of risk in terms of first distributional moment. Location, Location is not an obvious quantity Estimation of duration of cash flows pertaining to unlisted assets are often over-simplified in the practice of ALM for pensions and insurance Broad asset class indexes, or marketable-proxies, attempt to battle the quantification aspect while compromising on investment s idiosyncratic nature and appraisal bias Slide 3

4 Unlisted Asset Classes Real Estate Slide 4

5 Risk & Private Equity Real Estate Current indices (NCREIF, IPD, etc.) do not use observable prices: Appraisal-driven and therefore appraisal-biased Smoothed, dampened: Exhibit serial correlation Repeat Sales Indices: Sample size & little property-level info Current indices: Good for: Long-term trends and absolute returns (See: Cheng, Lin, & Liu 2011) Not good for: Short-term analysis Uncertainty of returns Risk components and/or their contribution at the property and/or portfolio levels Slide 5

6 Public Versus Private Property Returns 40% NCREIF vs. NAREIT Quarterly Returns (94Q1-11Q3) 30% NAREIT NCREIF Quarterly Return 20% 10% 0% -10% -20% -30% Annual Standard Deviation NCREIF: 4.9% NAREIT: 20.6% -40% 94Q1 96Q1 98Q1 00Q1 02Q1 04Q1 06Q1 08Q1 10Q1 Slide 6

7 Appraisal Bias Remains an Issue Return Persistence Lagged NCREIF Correlations LAG 5 LAG 4 LAG 3 LAG Q1-2011Q3 1Q Lagged Correlations NCREIF =.85 NAREIT =.19 NCREIF: 00Q1 TO 11Q3 NCREIF: 78Q1-11Q3 LAG Slide 7

8 Northfield s Property Risk Approach A bottom-up property-by-property model that is not appraisal-based Each property is a composite asset with: Risks based on steady-state cash flow assumptions for existing and expected leases Uses lease structure, renewal, credit quality of tenants, vacancy dynamics, revenue and expense schedules Risks related to mortgage financing (if property is levered) Takes into consideration floating rate, fixed rate, interest-only, balloon clauses, and prepayment behavior Risks of future fluctuations in rents Takes into consideration the combined impact of lease rollover, vacancy, renewal, and market volatility of rents Each component has risk exposures to common risk factors plus idiosyncratic risks Slide 8

9 Northfield s Property Risk Approach Two versions of the model: A fully granular version that requires a detailed set of input variables per property. Usually applicable for directly owned real estate properties A generic version where input availability to user is limited (e.g. holdings through third party funds) Both approaches involve same analytical process and benefits with similar output. For generics, Northfield assumes missing data items to be the average characteristics for the specific market. An automated processing service called EENIAC handles in streamlined way, assuring client s data security and confidentiality Slide 9

10 Real Estate Model Structure MORTGAGE FINANCING (SHORT) STEADY STATE CASH FLOW (LONG) RENT VOLATILITY TIME VALUE OF MONEY CREDIT RISK CHANGE IN RENT RISK FACTORS RISK FACTORS RISK FACTORS EE MODEL PROPERTY/ PORTFOLIO RISK Slide 10

11 Components of Property-Level Risk Rent Risk Interest Rate Risk Credit Risk Specific Risk TOTAL RISK Slide 11

12 Components of Portfolio Risk Rent Risk Interest Rate Risk Credit Risk Idiosyncratic Risk Still Present But Largely Diversified Away as Portfolio Size Increases TOTAL RISK Slide 12

13 Model Results Portfolio Profile Portfolio: Core portfolio as defined by investment strategy Conservative leverage (<15%) 14 properties Apartment, industrial, office, and retail 10 metro areas Boston, New York, Washington, D.C., Miami, Seattle, Sacramento, San Jose, Inland Empire, San Diego, Phoenix Slide 13

14 Model Results Portfolio Profile PORTFOLIO PROFILE Metro Apartment Office Industrial Retail Boston 1 DC 2 Inland Empire 1 Miami 1 1 New York Phoenix 1 Sacramento 1 San Diego 1 Seattle 1 San Jose 1 Slide 14

15 Model Results: Model Output Portfolio Risk Report Subject Portfolio Factor PortExp BenchExp ActiveExp FactorVar VarContr ENGLISH-SPEAKING COUNTRIES INDUSTRIAL SECTOR CONSUMER SECTOR TECHNOLOGY&HEALTH SECTOR INTEREST RATE SENSITIVE SECTR NON-ENERGY MINERALS ENERGY MINERAL SECTOR S B WORLD GOVT BOND INDEX OIL PRICES IN USD DEVELOPING MARKET SIZE VALUE/GROWTH TREASURY CURVE FACTOR TREASURY CURVE FACTOR TREASURY CURVE FACTOR Factor Tracking Variance Stock Specific Tracking Variance Total Tracking Variance Tracking Error Total Risk of Portfolio Slide 15

16 Model Results: Model Output Individual Property Risk Report Apartment Building - San Diego, CA Factor PortExp BenchExp ActiveExp FactorVar VarContr ENGLISH-SPEAKING COUNTRIES INDUSTRIAL SECTOR CONSUMER SECTOR TECHNOLOGY&HEALTH SECTOR INTEREST RATE SENSITIVE SECTR NON-ENERGY MINERALS ENERGY MINERAL SECTOR S B WORLD GOVT BOND INDEX OIL PRICES IN USD DEVELOPING MARKET SIZE VALUE/GROWTH TREASURY CURVE FACTOR TREASURY CURVE FACTOR TREASURY CURVE FACTOR Factor Tracking Variance Stock Specific Tracking Variance Total Tracking Variance Tracking Error Total Risk of Portfolio Slide 16

17 Model Results Risk by Source Risk Profile: Apartment Building San Diego, CA 16.1% 5.1% 3.9% Interest Rate Risk Rent Risk Credit Risk 17.3% XX% Total Risk Slide 17

18 Model Results Property Risk Risk Profile: Apartment Building San Diego, CA Rent Risk Factor: 1.06% Credit Risk Factor: 3.85% Interest Rate Risk 16.1% Total 17.3% Specific: Specific: 4.99%.25% Slide 18

19 Model Results Incremental Risk Average Incremental Contribution to Risk by Location (All Leverage Removed) Incremental Risk by Metro Area Metro Area Std Dev # Props Properties San Diego Apartment Phoenix Apartment NYC Apartment, Office, Retail DC Office Miami Industrial, Office Sacramento Retail San Jose Retail Seattle Industrial Inland Empire Industrial Boston Office Slide 19

20 Effects of Leverage on Equity Risk Standard Deviation NYC Office Building Risk (Std Dev) Per Percent Debt/Equity Ratio As leverage exceeds 95%, negative equity quickly accumulates and predicted variance in values falls. Leading to a decline in the expected variability of net value. For every 1% increase in leverage between 60%-90%, risk increases by 3.2% 20 0 Debt as a Percent of Asset/Portfolio Value Slide 20

21 Model Results Incremental Risk Incremental Risk by Property Type Per Percent of Portfolio Share (All Leverage Removed) Apartment 2.08% Office 2.35% Retail 2.54% Industrial 2.61% Slide 21

22 Model Results: Portfolio Risk by Acquisition Portfolio Acquisition Schedule and Impact on Risk (Standard Deviation) Location Property Type Individual Property Total Risk Individual Property Specific Risk Portfolio Total Risk Portfolio Specific Risk New York City Multifamily Inland Empire Industrial Seattle Industrial Miami Office Miami Industrial New York City Office New York City Retail San Jose Retail San Diego Multifamily Boston Office D.C. Office Sacramento Retail D.C. Office Phoenix Multifamily Slide 22

23 Model Results: Incremental Risk Idiosyncratic Risk Quickly Disappears Total Risk Can Still Increase as Portfolio Grows Incremental Idiosyncratic Risk Incre mental Total Risk Risk - Std Dev Trendline Specific Risk Risk - Std Dev Systematic Does Not Diversity Away & Is Asset-Specific. However, Incremental Impact Smaller as Portfolio Size Increases Number of Properties & Standard Deviation Number of Properties Slide 23

24 Expected One Year Equity Risk by Asset Class 35% Expected Annualized Risk by Asset Class 30% 25% Expected Hist Adjusted Hist (06Q3-11Q2) 20% 15% 10% 5% 0% Subject Portfolio All NCREIF ODCE NCREIF NAREIT Bond Index S&P 500 Expected One Year Annualized Risk as of 2011Q3 Bond Index: Historic Barclay s 30 Year Treasury Bellweather Bond Index Expected NIS-Generated 30-Year Bond Index Slide 24

25 Alternative Asset Classes Infrastructure Slide 25

26 Northfield s Infrastructure Approach A granular project-specific approach Each project is analyzed in respect to: Deterministic cash flows from existing and future usage/contracts of use of the infrastructure facility Usage specifics, contract provisions, capacity, credit quality of contract counterparties, operating cash flows Risks related to financial gearing Floating rate, fixed rate, interest-only, balloon clauses, and prepayment behavior Risks of future fluctuations in cash flows from business All components have risk exposures to common risk factors plus idiosyncratic risks Slide 26

27 Northfield s Infrastructure Approach: An Airport Example (cont d) The business cash flow volatility component is modeled using portfolios of appropriately chosen businesses. For an airport those will be: - Airline Gate Operators - Retail Companies Fully-granular approach: - Use time series of operating cash flows from that segment (business sub-portfolio) of the infrastructure project and estimate sensitivities to risk model factors Fully-granular / Generic approach: - Use the volatility of the equity of the contractual counterparties (Airlines, Retailers), to estimate the volatility of demand for project capacity by adjusting for metrics of facility usage and for three types of leverage: - Financial Leverage - Operating Leverage (Fixed Costs) - Operating Leverage (Variable Cost per Unit of Output) Slide 27

28 Northfield s Infrastructure Approach: An Airport Example (cont d) Percent of Total Holdings Airport Example 12/21/2012 Port. Ending Market Portfolio Symbol Composite Assets Value Weight Total Direct A_1_0_1 Gate Lease A_1_1_1 Gate Lease A_1_2_1 Gate Lease A_1_3_1 Gate Lease A_1_4_1 Gate Lease A_1_5_1 Gate Lease A_1_6_1 Gate Lease A_1_7_1 Gate Lease OFFSEC RNT_AIRPORTGATE Rent volitility synthetic S security (Gate RNT_AIRPORTRETAI Rent volitility synthetic L security (Reta A_0_0_1 Retail Lease A_0_1_1 Retail Lease A_0_2_1 Retail Lease A_0_3_1 Retail Lease A_0_4_1 Retail Lease A_0_5_1 Retail Lease A_0_6_1 Retail Lease A_0_7_1 Retail Lease A_0_8_1 Retail Lease Slide 28

29 Northfield s Infrastructure Approach: An Airport Example (cont d) Summary Report AIRPORT_EXAMPLE 12/31/2012 NIS EE Model Factor Contribution (Std Dev) Total Risk (Std Dev) Percent Contribution Stock Specific Risk % Factor Risk Factor Contribution (Std Dev) Region % Super Sectors % Economic % Fundamental % Blind Factors -- Currency -- Curve % Slide 29

30 Alternative Asset Classes Private Equity Slide 30

31 Private Equity Model each fund holding as a composite asset comprised of privately held businesses Each private company is attributed with the risk characteristics (factor exposures and asset specific risk) of the industry and country cohort Those characteristics get modified to account for leverage, maturity of the business, and the health of the IPO market At the fund level, the aggregate risk characteristics get modified to account for a stochastic liquidity shortfall respective to lockout provisions, and unfunded commitments (cash calls) Slide 31

32 Unlisted Asset Classes Integration with ERM Slide 32

33 Application in Risk Management The broad risk drivers generated by the Everything Everywhere model provide two very important dimensions of flexibility in risk management The overlap of the EE model factors used for alternative investments and marketable securities, allows for any degree of total portfolio risk adjustments, even if part of the risk comes from highly illiquid assets. E.g. the interest rate risk from a property s long term lease cash flows can be hedged using a bond futures contract. An oil pipe facility near Houston is effectively a bet on the oil industry which can be balanced with selling stock in oil companies. A retail center exposure to a major anchor tenant can be fine-tuned by manipulating weights of the stocks and bonds of the same or similar retailer. A common risk model can tell us by how much. The granularity by infrastructure project and property allows for tailored analysis of the impact of adding new investments and selling existing ones, not attainable in public proxy alternative assets risk approaches. Slide 33

34 Application in Risk Management (cont d) Another useful aspect of flexibility which the broad risk drivers of the Everything Everywhere model provide: The model output can be readily integrated in the Northfield Enterprise Risk Management system (MARS ERM) alongside all other components of the total portfolio The data estimation results can be integrated in any other risk model / platform as long as it also has a sufficiently broad factor set. This can be accomplished in two ways: Translate Alternative Investments EE factor exposures into generic risk model factor exposures, for a Markowitz-style cross-asset class risk estimation and optimization on a third-party risk system Generate economic scenario values based on Northfield s risk model output, that can be imported on third-party risk systems, where distributional estimation of the total portfolio can be performed, inclusive of the difficult alternative assets. Slide 34

35 Summary Methodology which: Provides integrated and consistent risk measurement and management capability comparable to other asset classes Poses manageable data requirements, but yet does not cut corners in respect to granularity, locality, and other difficult aspects of the analysis Features fundamental, bottom-up approach which integrates intuitively the economic forces that drive return for these asset classes Uses broad risk drivers that allow identification of the types of risks that can be hedged using liquid market instruments (e.g. discount rate risk = interest rate risk) Produces output that is fully flexible for use on any risk platform Slide 35

36 ERM Enterprise Risk Management Presented at Northfield s 18th Annual Summer Seminar, June 7, 2013

37 Portfolio Contents Overview

38 Bottomline Risk Overview

39

40 Factor Variance Contribution

41 Expected Tail Loss

42 Factor Variance

43 Total Risk Overview

44 Sub-Portfolio Risk Contribution

45 Sub-Portfolio Correlations

46 Forensic Browser

47 Introducing Enterprise Risk Management Northfield s new advanced risk analytics Real time risk data for missing securities Dynamic rule based filters and groups Aggregate portfolio by groups or sub groups

48 ERM A 360 view of your entire risk profile Drill down using any criteria or user defined attribute Customized reports Scripting language Local or remote processing Web and windows interface

49 ERM Risk Analytics and Reports Distributional Qualities and Extreme Events Report 1. Parametric Analysis VaR, CVaR, Kurtosis, Skewness. 2. Non-Parametric Analysis VaR, CVaR, Kurtosis, Skewness. 3. Degrees of Freedom for 1 and 2 5, 12, Confidence intervals for 1 and 2 90%, 95%, 99%. 5. User defined Degrees of Freedom for 1 and 2.

50 ERM Risk Analytics and Reports (cont d) Market Exposure Report 1. OTC exposures Choice of issuer; country; industry; credit rating. 2. OTC exposures netted against overall exposures Choice of issuer; country; industry. 3. OTC exposures netted against bond exposures Choice of issuer; country; industry; rating

51 ERM Risk Analytics and Reports (cont d) Hedging Firm-wide Risks 1. Hedging risks across portfolios without capital movement. 2. Hedging risks across portfolios with capital movement. Risk Decomposition and Funding Assumption Changes 1. Breaking up VaR, Variance and Standard Deviation down to security level. 2. Allow user to specify funding assumption

52 Risk model coverage Provides direct connectivity to Northfield seeniac server Highly secure connection over secure sockets One click resolves all exceptions

53 Risk model coverage (cont d) User will be able to proxy risk data of all the assets for which risk data does not exist in the NIS EE risk data file i.e: Municipal Bonds Mortgage Pool Bonds Derivative Instruments Government/corporate bonds for which terms and conditions are known Composites constituents unknown CMO/ABS securities MBS Pool Securities

54 The user interface is made of loosely coupled components, using Composite UI Application Block (CAB)

55 4 Tier architecture

56 Logical view

57 Northfield Information Services, Inc. 77 North Washington St. 9th Floor Boston, MA Sales: Support: Main Office: Fax: SoftPak Financial Systems, Inc 51 River Street Wellesley, MA Sales: x100 Support: x100 Main Office: Fax: Thank you!