Forum Asset Liability Management

Forum on Asset Liability Management Gautam Mitra Forum on Asset Liability Management • Background and overview of Asset and Liability Management • Asset and Liability Management applied to Banks • Asset and Liability Management applied to Insurance Companies • Asset and Liability Management applied to Pension Funds • Asset and Liability Management: Other application areas • Industry insights, technology, products and services • Directory of Asset Liability Management Solution and Service Providers • Bibliography Forum on Asset Liability Management Con Keating Asset and Liability Management Some Issues It is impossible to achieve demonstrably true knowledge about our universe or ourselves Nor is logic decisive No kind of reasoning can ever give rise to a new idea Hume London November 2009 Con Keating Liability Driven Investment The PPF • • • • • • • • • • The PPF reported investment returns for 2008/9 of 13.4% including swaps versus a target of 6.2% Ex swaps the return was -3.4% Long dated gilts moved just basis points in this year But swaps versus gilts (25 year) compressed by 61 basis points This is a return equivalent of 14.5% This is the principal source of the swap performance Swaps were trading 45 basis points through gilts Having been 100 basis points through earlier in the crisis It is a staggering basis risk for the ALM position Why does the PPF own swaps which yield less than gilts? Hedging • • • • • • • • • A UK corporate borrowed £100 million as a 12 year floating rate note paying 5/8% over interbank offered two years ago They swapped this for fixed paying 5.5% They entered a credit support agreement for the swap, under which cash collateral could be called Swap rates declined to 4.00% They were called for collateral of £12.2 million This was cash they did not have and were forced to borrow from their bank on adverse terms The cost of the financing has risen dramatically The effective term of the financing has shortened The basis risk is enormous The individual • • Only 20% of personal wealth takes the form of financial assets and property 80% is human capital to be consumed and converted to other wealth over the future life time • Many other institutions share this property of future income • Pension schemes are one example • The status quo is simply an accrued endowment - the present value of future contributions can dominate this entirely A pension scheme • • • • • • • • • • Once future contributions are considered The optimisation problem is no longer maximisation of current asset values at either short or long horizons The new contributions can be thought of as consuming investments And for those we want the price of investments to remain low The ALM problem is dramatically different Think about a coupon bond when prices decline and yields rise The realised total return increases due to the higher reinvestment rates We no longer want high market (beta) returns since these hurt our new money contributions But we want returns which are independent of the market And that is the case for Alpha BrightonRock Policy • • • • • Institutionalises this insight contractually It stabilises the current value of the portfolio By removing short term concerns Allowing long term investment And lowering scheme financing costs Evolution of investment strategy Static perspective: spend risk budget as efficiently as possible Typical current investment policy Possible intermediate solution ‘Ideal’ future investment policy Liability hedge Liability hedge Equity β and constrained α Diversified α Bond α Diversified β and α Diversified β  Simple  Hedge unrewarded risks  Hedge unrewarded risks  Unrewarded risks  Diversify risk budget  Diversified beta unhedged  Constraints inhibit performance  Constrained ability to  Diversified alpha 37 grasp opportunities Private and confidential Not for public distribution Professional investors only 932028 Bonds Eyes on the prize Dynamic perspective: risk is being taken in order to bring assets into balance with liabilities 110% New target path 100% 90% 80% 70% Realised performance 2% p.a a p % Initial target path 60% Start Year Year Year Year Year Year Year Year Year Year 10 If realised returns above target, can afford to target lower return (And if returns below target, may need to target higher return) 38 Private and confidential Not for public distribution Professional investors only Dynamic portfolio allocation process As the return target changes, so must the portfolio allocation Private Equity Dynamic rather than static portfolio Equity Emerging Market Equity Return Property Infrastructure Emerging Market Debt Gilts & Swaps High Yield Bonds Corporate Bonds Risk 39 Private and confidential Not for public distribution Professional investors only Commodities Cumulative impact of dynamic asset allocation policy Distribution of outcomes no longer so wide; significant downside benefit 40 Private and confidential Not for public distribution Professional investors only Practical considerations 41 Private and confidential Not for public distribution Professional investors only Adding a floor Minimum as well as target funding level 42 Private and confidential Not for public distribution Professional investors only Contributions This is not just an investment problem Sponsor covenant Investment policy 43 Private and confidential Not for public distribution Professional investors only Contributions Putting it all together Monitoring and action • Overall framework is best set in advance • Clear goal • Create framework for appropriate real-time engagement • Delegation • Market opportunities • Beyond capital allocation • Some assets easier to move than others -> use derivatives • Monitoring and reporting framework crucial • Aggregation 44 Private and confidential Not for public distribution Professional investors only Conclusions • Pension plans changing their focus from static weights to fixed target • Dynamic strategies to support this are intuitive • Complex dynamics 45 Private and confidential Not for public distribution Professional investors only Forum on Asset Liability Management Marcus Hurd Pensions – Asset Liability Modelling Traditional deterministic Simple Stochastic Slide 47 Pensions – Asset Liability Modelling Investment optimisation Contribution optimisation Slide 48 Asset and Liability Management: Handbook Contributors: • • • • • • • • • • Dr Moorad Choudhry, Europe Arab Bank Prof Michael Dempster, Judge Business School, Cambridge University Dan diBartolomeo, Northfield Information Services Con Keating, Head of Research, BrightonRock Group Prof Lionel Martellini et al., EDHEC Business School Dr Elena Medova, Judge Business School, Cambridge University Prof Gautam Mitra, CARISMA, Brunel University and OptiRisk Systems Dr H Sadhak, CEO Life Insurance Corporation, India Dr Katharina Schwaiger, CARISMA, Brunel University and OptiRisk Systems Prof Frank Sortino, Emeritus Professor in Finance, San Francisco State University and Director of the Pension Research Institute Asset and Liability Management: Handbook • Sponsorship Opportunity • Contact us: info@optirisk-systems.com