PowerPoint Presentation...Title: PowerPoint Presentation Author: Carlin, Stephen Created Date: 11/2/2017 7:36:32 AM

Stochastic Modelling for ALM: The What,

How and Why?

Phil Bowyer, Solutions Specialist, ERS

2

1. Introduction to using stochastic models for investments

2. How to address the challenge of liability and asset interaction.

3. Uses for multi-asset product design, forward looking risk analysis

and Governance

4. ESG Product Update

Agenda

South Africa Insurance and Pensions Conference, 2017

Strategic Asset Allocation

• The last 15 years has seen the full spectrum of highs

and lows in global markets

• Lackluster returns, low interest rates

• Increasing uncertainty around political events

• Investors revisiting what is an appropriate mix of risks

for their long term financial goals and constraints.

• Goal to determine their optimal long term investment

strategy, which could be challenging due to:

• Wealth of investment options and opportunities

• Adhering to liability constraints as well as investment risk

• Capturing the possibility of “tail events” in such strategy setting

4

The Investment Decision Hierarchy


Dynamic Asset Allocation

Security Selection


5

» Optimal Long term investment strategy

– How much should I invest in bonds, equities and property?

› This is arguably the biggest decision investors make

» SAA explains between 80% and 100% of long term fund performance

– SAA is quintessentially linked to market movements



6

» Dynamic Asset Allocation concerned with shorter time lines

– Active management

– Capture short-term opportunities in the market

» DAA contribution of marginal long term incremental returns

Dynamic Asset Allocation


7

Setting objectives for Initial SAA

» Understand objectives of the investor

– How much risk in the short-term is one willing take on board?

– Is a negative return in any given year a disaster?

– Is a return of –5% in any given year a disaster?

– Where is the pain threshold of yearly losses?

– Is there an absolute return target (e.g. 8%)?

– Is there a relative return target (e.g. outperform an index by

200 basis points)?

– What is the time horizon for the strategy?

– How long is the long-term? 3 years? 5 years? 100 years?

– Are there any liabilities underlying the assets?

– Is the money earmarked to be spent in any particular way in

the mandate’s foreseeable future?

58.6%22.9%

10.0%

8.6%

SAA for portfolio A

Bonds Equites Property Alternatives


The SAA Process

Economic Assumptions Governance

Strategic View (SAA)

Monitor through

economic cycle

Tactical View (TAA

Risk & Return

Attribution

Liability Modelling

1 Introduction to using stochastic

models for investments

10

» Widely known and studied

» Mayor short coming:

– Single time horizon

» These models do not explicitly allow adjusting decisions along the planning horizon when new

information arrives

Where to Begin?Modern Portfolio Theory


11

Where to Begin?Modern Portfolio Theory

Expected

Return

Risk


12

Portfolio Construction: MVO +

• Allows alternative views to be incorporated, but

• Weighting between data and subjective views is arbitrary

• Application often ends up being a fudge w/o sufficient transparency

Black Litterman

• Attempts to address sensitivity to assumptions

• The most common method recalculates means and covariances using different historical data windows

• This still leaves other problems unsolved, e.g. simple Gaussian distributions are often assumed

Resampling


13

Efficient Frontier MVO+

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.0%

0.7%

1.3%

2.0%

2.6%

3.3%

4.0%

4.6%

5.3%

5.9%

6.6%

7.3%

7.9%

8.6%

9.2%

9.9%

10.6%

11.2%

11.9%

12.5%

13.2%

13.9%

14.5%

15.2%

15.8%

Po

rtfo

lio A

sse

t A

lloca

tio

n

Portfolio Volatility (% p.a)

Gilts InflationLinked Corporates P_GBP GlobalEquities


14

Efficient Frontier: BL combination of equilibrium and

views

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0.0%

0.7%

1.3%

2.0%

2.6%

3.3%

4.0%

4.6%

5.3%

5.9%

6.6%

7.3%

7.9%

8.6%

9.2%

9.9%

10.5%

11.2%

11.9%

12.5%

13.2%

13.8%

14.5%

15.2%

15.8%

Po

rtfo

lio A

sse

t A

lloca

tio

n

Portfolio Volatility (% p.a)

Gilts InflationLinked Corporates P_GBP GlobalEquities


Scenario Generation for SAA

16

Real World ESG UsageSimple portfolio construction using one period assumptions

Advanced techniques: Multi-period, time-dependent, structural Real

World ESG

Mean Variance

Optimisation

Pension Scheme

Asset Liability

Modelling

Test portfolio in an Asset

Liability Model

Capturing and

Analysing Tail Risks

Retail – annuity income

and income drawdown

Dynamic asset

allocation

Accounting

constraints

Returns Correlations Liability proxy


17

Economic Scenario Generator What is it?

» Collection of stochastic models which are structured and correlated

together in such a way that they collectively produce plausible and

sensible projections of risk factors

» This collection of models can produce many “trials”, each trial

representing the movement of the risk factors across the time horizon


18

In a Real-World framework, the modelling goal is to assign realistic probabilities to a set of future outcomes,

effectively producing forecasts. The advantage of this is quantifying levels of uncertainty and risk, allowing to

derive meaningful and quantitative answers to genuine risk management questions, such as:

» How severe can my losses be under my current strategic asset allocation?

» What are the range of possible outcomes?

» What if my yields were to drop, how does this impact my portfolio?

» What are a range of candidate portfolios for my client’s return and risk appetite?

Economic Scenario GeneratorWhat is it?


19

Portfolio Construction

» Portfolio modelling with an ESG provides the ability to:

– The ability to capture tail risk events

– Dynamic correlation between various risk factors

– Assess the most useful metrics of risk and return

– Create bespoke portfolios to satisfy complex requirements and

constraints

– Compare portfolio performance in a range of market conditions

– Analyse portfolios on a multi-timestep basis

– Include cashflows in portfolio projections

– Monitor Fund Risk


20

Monitoring Fund Risk


21

Monitoring Fund Risk


22

» VaR

» Conditional VaR

» Tracking error

» Shortfall

» Liability

» ….

» Any output/risk metric to suit the investors requirements.

Optimising more than Standard Deviation Several Options


23

Portfolio Construction: Generic

Optimisation


24

Portfolio Construction: Generic

Optimisation


25

Strategic Asset Allocation : The Need For A

Stochastic Scenario Generator

Objective MV Asset Model Scenario Generator

Diversify across risks

Where risk are defined with respect to

liabilities?

Aligns level of risk with risk tolerance ?

Bias towards risks which are expected

improve the overall portfolio performance

Regularly rebalance in line with evolving

liabilities?

Set a clear benchmark for TAA, and other

value adders

Set realistic expectations given current market

conditions?


26

Using ESG for SAA & InvestmentKey Benefits (Client)

» Increased client understanding and confidence

» Quick recalibration of models to account for new economic conditions

» Imposing client specific views

» Ownership of scenario generator and entire SAA process


Case Studies

28

Case Study – Insurance ALM: Duration Matching» Large US Life Insurer

» Looking to rebalance asset portfolios

on each line of business to target

liability matching duration

» Simultaneously looking to find

portfolios that minimise tail risk for PV

Earnings and maximise average PV of

earnings

» Strategies include rebalancing rules

» For each investment strategy run

a set of stochastic real-world

scenarios

» Calculate PV of earnings for each

scenario


29

Case Study – DB Scheme SAA accounting for

De-Risking Journey Plan

» Large Government backed DB scheme

» Objective was to find optimal SAA

accounting for a de-risking journey plan for

DB scheme.

» Needed to account for a dynamic investment

strategy, i.e. altering asset SAA throughout

projection based on scheme Funding Level

» Compare multiple SAAs and de-risking over

a range of scheme metrics, e.g. contribution

level, Funding Level.

» Compare risk profile of strategies through

risk decomposition to understand

sensitivities.


How to address the challenge of

liability and asset interaction.2

31

» Exploit power of Moody’s Analytics ESG for asset allocation, portfolio design and ALM applications

» Make it easier for clients to use our models to address range of investment planning problems:

asset allocation, liability-based portfolio design & optimization, management communication, pension ALM

– Evaluate impact of investment strategy on capital and other solvency balance sheet metrics

– Optimise asset portfolios, investment strategy & risk management process to business & capital objectives

» Improve alignment & collaboration between Actuarial and Investment departments

» Flexible modelling and API supports integration into client’s business process: capital market assumptions,

investment objectives, portfolio rebalancing rules, constraints, data & model granularity requirements.

» Access Moody’s Analytics comprehensive library of economic content and insight

Client Benefits

Portfolio Module


32

The Investment Problem

Managed Portfolio Models

Liabilities

Assets

Economic Risk Factors:

credit, rates, inflation

Asset Specification

Multiple multi-year

liability cashflows

Investment targets:

earnings, return, cashflows, risk,

duration, book yield

Time dependent or dynamic

rebalancing

Market Value

Earnings

Realised Gains, Impairment

Capital

Duration

Portfolio Transactions & Costs


33

Apply static or dynamic

rebalancing rules between assets

Model Structure


Cash

Account

Rebalancing Rules

Real Estate Equity High Yield Short Duration Credit Long Duration Credit

• Portfolio of direct

Japanese property

investments

• Diversified across

sectors

• Benchmarked against

IPD UK Index

• Portfolio of JPY Stocks

• Diversified across

sectors

• Benchmarked against

MSCI UK Index

• Portfolio of Investment

grade JPY long dated

corporate bonds

• Min credit class BBB

• Duration target 12-15Y

• Portfolio of Investment

grade JPY short dated

corporate bonds

• Min credit class BBB


• Portfolio of Global High

Yield corporate bonds

• Credit class CC - BBB


Liabilities


34

Model Structure


LiabilitiesCash

Account

Rebalancing Rules

Real Estate Equity High Yield Long Duration Credit

HoldingsCash

Account

Sell

Rules

Buy

Rules

Rebalancing Rules

Sell on

DemandInitial holdings of each asset

specified in fair (market) and

book value terms

Asset Level transaction

management & investment

strategy

Direct investment

cashflows to pay liabilities

Fair and book values for

individual securities,

asset indices or

portfolios. Balance sheet

and P&L measures.

Apply on-demand sell orders to

create liquidity for rebalancing


3 ESG Product Update

36

Market Consistent Interest Rate Models

» MC LMM+ 10% Displacement Calibrations

– During the Q3 Delivery we will release additional LMM+ calibrations with 10% displacement for a subset of economies

– MC Premium, MC Solvency II and MC Standard calibrations will remain unaffected and use a 45% displacement

– Beta calibrations for end Dec 2016 & June 2017 covering CHF, EUR, GBP, JPY and USD are available on the

Customer Portal

– The recently published document ‘Market Consistent LMM+ Nominal Yield Curve Calibrations with a Semi-Static

Displacement Parameter’ provides more details on the rationale for the introduction of these calibrations

» MC Displaced E2FBK Calibrations

– From Q3 we will be adding MC displaced E2FBK calibrations to the MC Standard calibration service for CHF, CNY,

EUR, GBP, JPY, USD and ZAR

– End June 2017 beta MC displaced E2FBK calibrations for the same economies are already available on the Customer

Portal

Displacement parameter choice


37

Planned Changes in 2018

» Medium-term interest rate and inflation assumptions review

– “Real World ESG Research Update” session will provide insight into this project

– Review paths of interest rate and inflation models to better reflect expectations over the medium term on an economy

specific basis.

– Aim to both fit index linked bonds and target inflation paths accurately

– Scope is currently RW, however, devised methodology could be used in MC calibrations.

» 1-Year VaR Corporate Spread Modelling

– We plan to review the methodology for setting corporate spread volatility targets. This could result in the eventual

withdrawal of G2 Single Term Premium calibrations and replacement with G2 Dual term premium calibrations.

» Market Consistent Hull White Calibrations


Product Update

39

Recent and Upcoming Releases

Dec 2016

Beta – Preview Release for client feedback

Gold – Production Ready Release

SG 8.5.0

May 2017

SG 8.5.1

June 2017

ESG Automation Module 3.3.1

Calibration Tools 4.8.0:

RW Equity Tool

Aug 2017

Portfolio Projection Module (Beta)


FX Calibration Tool

Nov 2017

ESG 9.0.0 (Gold)/Portfolio

Projection Module

Asset Scenario Generator (Beta)

Q1 2018

ESG 9.1.0 + DB ALM


API Phase 1

Q2/Q3 2018

Asset Scenario

Generator (Gold)

Scenario Hub

In the past 3.5 years, we’ve had 30 significant releases of ESG

software:11 ESG & RSG, 10 Calibration Tools, 9 Automation Module


40

Developments Highlights

» Process streamlining features

– Processors feature

– New Analysis Tests (Asset Return, Tail Dependence)

– Charting

– Create .BHC files from ESG

– Bulk import improvements

– Yield Curve Builder in ESG Automation Module

» Modelling enhancements

– SVJD Jump Correlations

– Daily step modelling

– Copula functionality in ESG

– Actuarial Rate and Equity models

– New deterministic re-calibration options for 2F

Vasicek

– Strong Mean Reversion in E2FBK

– New risk drivers in RSG

– Addable Macro Models

– Credit Transition Probability Outputs

» Miscellaneous

– Automation API

– Hull-White compatibility in ESG AM

– Custom Stress method in ESG AM

– G3 Credit model in ESG AM

– Calibration Tools: 64bit compatibility with excel

– Stochastic Interest Adjustment for equity calibrations

under LMM+ and 2F Hull-White

– Market Consistent Hull-White calibration feature in the

Swaption Tool


41

Calibration Tools 4.8.0Real World Equity Tool

Create an Equity calibration file using one tool

Calibrate the correlation between equities and

interest rates. Run Cycle button runs ESG

validations to improve quality of fit.

Calibrate equity-equity correlations using the factor

model. New analytical fit method speeds up

calibration.

Calibrate skew, kurtosis and volatility of equity

return distributions using SVJD. Import Assets

button makes it quicker to initialise the tool.

Equity Correlations (Factor Calibration) SVJD Calibration

Equity-Bond Correlations

Calibrate child equity asset volatility, return and

correlation with parent. The calibration method is

chosen based on the available inputs.

Child Equity Calibration

Workflow automatically moves data between modules


42

Calibration Tool 4.9.0FX Calibration Tool

1Target FX level at multiple horizons. The tool

is capable of giving an exact fit to FX level

targets for multiple horizons.

2Target FX volatility. In addition to targeting the

level of FX rates, the tool can also target FX

volatility.

3IRP and PPP models supported. Both the

Interest Rate Parity and Purchasing Power

Parity models are supported so you won’t need

to change model when using the FX Tool.

0

0.5

1

1.5

2

2.5

3

3.5

0 1 2 3 4 5 6 7 8 9 10

No

min

al

FX

Lev

el

Time steps (years)


43

Software Support and End-of-Life schedule

ESG Versions

» ESG 8.2.0 was retired in July 2017

» ESG 8.2.2 will be retired in December 2017

Calibration Tools

» CT 4.5.0 was retired in July 2017

» CT 4.5.1 will be retired in December 2017

ESG Automation Module

» ESG AM 3.1.0 was retired in August 2017

» ESG AM 3.1.1 will be retired in December 2017

Full details can be

found on the

Client Support

Web.


Looking AheadInformation regarding products, features,

specifications and functionality in the ERS

Insurance product roadmaps is intended to

outline general product direction but is not

guaranteed. Future products will be sold

only when and if available. Moody’s

Analytics reserves our right to change the

development, release, and timing of features

and functionality discussed in our product

roadmap at any time.

45

Moody’s Cloud Platform

The MA-wide Cloud Platform (based on AWS and Azure)

are now in ‘Production’ mode.

New Products

New Insurance products are now purpose-built for

Cloud or Software-as-a-Service (SaaS) deployment

(e.g. Portfolio Risk Analytics, RiskIntegrity™ Insight).

Cloud Virtual Machines

A number of users install the ESG on cloud-hosted

VMs (AWS or Azure) with cloud based HPC GRIDs

ESG Software-as-a-Service

We’ll be building-out a suite of SaaS Scenario Generation solutions.

We are keen to understand users’ specific requirements.

Cloud and SaaS


• Cloud Hosted

• Enterprise features

• API

• User Experience

One place for all

your Scenario

Generation needs!

Scenario Hub

47

Scenario HubOverview

Cloud hosted

The application will be hosted on Microsoft Azure Cloud,

so the only IT requirement for users will be to have

access to a web browser. Resources will be scalable

based on user needs.

Enterprise features

The application will allow users within a client workspace

to share projects. Client admin users will be able to

specify Read-Write rights. All actions will be captured

within an audit log.

API

The application will come with its own Application

Programming Interface allowing it to be connected with

other tools.

Improved User Experience

Users do not have to be ESG experts. The application

will do all the heavy lifting when it comes to modelling

allowing users to focus on other added value activities.

Calibration Capabilities

Users will be able to augment standard calibrations to hit

their own targets or views. The underlying calibration

framework will be the same as the one used by MA for

quarterly calibrations.

Calibration Library

Based on user entitlements, MA standard calibrations will

be accessible in user accounts every quarter. Users will

be able to store their own calibrations as well.

Scenario Hub is the technology and analytics platform that we use to deliver our scenario-

based SaaS solutions.


48

Additional Development Themes

1ESG Performance. We have identified a number of

areas where performance can be improved [RNG,

model data structures, C#, thread modes, …]

2Calibration API. We are working on formalizing a

Calibration Tool API – starting with YCB, MC Equity

and MC Swaptions.

3Implied Volatility Projection. We have developed a

new approach to projecting implied volatility. This uses

the new Processors feature to create better dynamics.


Thank you

Questions?

50

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PowerPoint Presentation...Title: PowerPoint Presentation Author: Carlin, Stephen Created Date: 11/2/2017 7:36:32 AM