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Senior Management Programme in Banking Module IV: Asset Management Professor Andrew Clare Cass Business School October 2012 Overview Strategic asset allocation Tactical asset allocation The tactical asset allocation game Alternative investments – how alternative are they? Liability driven investment Alpha – what value do active fund managers add? Choosing a fund manager Investment strategies – simple strategies for generating alpha Strategic asset allocation Professor Andrew Clare Overview Asset allocation: what’s it all about Long-term expected returns Risk premia Expected risk & risk aversion Appendix: Yale university's endowment fund Asset allocation Emphasis on broad asset categories: Equities, Bonds, Property, Currencies etc US v UK equities etc Main Practitioners: Life Companies Pension Funds Funds of funds Family offices Page 4 A historic perspective on asset allocation Real indices, logarithmic scale 100000 10000 UK equity Gilts T-Bills 1000 100 10 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Its simple: just buy equities !!! Page 5 Long-term asset holdings of UK’s DB industry 100 % of total holdings 80 60 40 20 0 2003 2004 2005 2006 Equities 2007 Bonds 2008 2009 2010 2011 Other But most institutional investors do not hold only equities. Page 6 Strategic asset allocation Strategic refers to longer-term outlook, bedrock of investment goals Defining a benchmark for tactical asset allocation Getting it wrong can be very costly Should the aim be to maximise expected return, or maximise expected return, while simultaneously seeking to minimise expected risk ? Page 7 Using the MVE framework A mean-variance frontier for asset classes Expected return Efficient frontier Individual asset classes Standard deviation, risk Often asset allocators make use of the MV framework But to do so we need to know: expected returns, variances and covariances to construct the frontier Page 8 Long-term expected returns Determining expected returns Historic returns could be misleading – over the last ten years the FTSE-100 has fallen !!! So asset allocators try to take a forward-looking view. We will try to do the same and apply this view to: Cash Government bonds Corporate bonds Equity Page 10 Long-term expected return components There are three components of expected return on all assets Ex ante real return Compensation for future inflation Compensation for risk Let’s begin by determining the “neutral rate”, which comprises the first two components Page 11 The ex ante real return In a world with no inflation and no risk, investors would still require a return from their investments, but how much ? It would depend upon the ‘opportunity cost’ of foregone consumption It’s closely related to the potential growth rate of the real economy Page 12 Average real GDP growth since 1970 Average annual, real GDP growth since 1970 3.50% Average real GDP growth, %pa 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% Australia Canada France Japan UK USA Long-run economic growth low: ex ante real return should be low too Page 13 The ex ante real return Despite many new inventions - railways, telephones, microchip, the internet etc - economic growth has actually been remarkably stable Perhaps then historic GDP growth will be a good guide to long term future real GDP growth On the other hand, is the credit crunch a paradigm shifting event … the end of capitalism as we know it ? Such estimates probably a good proxy for the long term ex ante real return Yields on long-dated index-linked gilt market can give us a clue to what the market thinks about trend growth Page 14 Yields on long-dated index-linked gilt Real, long term govt bond yield (UK) 6.0 6.0 5.0 5.0 4.0 4.0 3.0 3.0 2.0 2.0 1.0 1.0 0.0 0.0 -1.0 -1.0 -2.0 -2.0 -3.0 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 -3.0 Yield on index-linked gilt, %pa Yield on index-linked gilt, %pa UK recessions UK’s real long-term economic growth (was) similar to index-linked bond yield Page 15 Yields on long-dated index-linked bonds Short term real yields (pre-crisis) Short term real yields (post-crisis) 4.0% 3.0% 3.5% Short-term, real yields, %pa Short-term, real yields, %pa 2.0% 3.0% 2.5% 2.0% 1.5% 1.0% 1.0% 0.0% -1.0% 0.5% 0.0% -2.0% Australia France Italy Japan Sweden UK USA Australia France Italy Japan Sweden UK USA There’s clearly more to default-free real yields Page 16 Compensation for future inflation Inflation expectations affect the nominal expected return on assets How does one go about forecasting inflation ? Page 17 The recent low inflation environment Inflation in a selection of developed economies since 1960 30.0 25.0 US Japan Germany UK Canada Italy Annual inflation % 20.0 15.0 Source: Thomson Financial 10.0 5.0 0.0 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 -5.0 Will the low inflation environment stick this time? Page 18 Inflation targeting Inflation targeting: the 1990’s epedemic Number of inflation targeting central banks 60 50 40 30 20 10 0 1970s 1980s 1990 1991 1992 1993 1994 1995 1996 1997 1998 Source: Bank of England Inflation targeting has had a big impact upon the inflation environment Page 19 Inflation targeting Inflation targets in a selection of developed economies Country/region Euro-area UK Australia Canada New Zealand Sweden USA Target/inflation goal ECB aims to keep CPI inflation below ceiling of 2.0% MPC aims to keep CPI inflation within 1.0% of 2.0% target Australia’s FRB target inflation between 2.0% to 3.0% Bank of Canada aims to keep CPI inflation within 1.0% of 2.0% target Reserve Bank of New Zealand aims to keep CPI between 1.0% to 3.0% Riksbank aims to keep CPI inflation within 1.0% of 2.0% target Indications from Fed officials that 2.0% for core PCE inflation is “preferred” Most seem to target between 2 to 3% Why not target 10% or 0% ? Page 20 Market “inflation expectations” Are market inflation expectations consistent with targets ? Break evens over time Ten-year break evens 4.0% 10.0 Pre-crisis USA Australia 8.0 6.0 4.0 2.0 Dec-11 3.5% Break even inflation rates, %pa Ten-year break evens, %pa UK 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0 1985 0.0% 1988 1991 1994 1997 2000 2003 2006 2009 Australia Canada France Italy Japan UK USA Page 21 Compensation for future inflation In the UK it seemed reasonable in the past to assume inflation of around 2.0% (CPI), that is, 2.5% (RPI). But what about now ? In Europe 2.0% In USA – the Fed have just launched QE3 – an indefinite commitment to expand the money supply Today, arguably, the inflation picture hasn’t been this uncertain for some time Page 22 Putting it all together: an example Putting together an estimate of trend growth and expected inflation gives a neutral policy rate for an economy Neutral rate will be close to expected return on cash For the UK prior to the credit crunch it might have been: 2.25% for growth 2.5% (RPI) for inflation Giving a grand total of 4.75% But what about now ? Page 23 The ‘neutral rate’ Policy rates will cycle around their ‘neutral rates’ The return on cash will be closely related These neutral rates can change themselves if: trend growth changes (productivity improvements, labour migration, credit crunch) monetary policy regime changes The return on cash is the basis for future expected returns on all assets The risk premium is what distinguishes them Page 24 Pre and post crisis policy rates Policy rates in Jun ’07 and Dec ‘11 14.0 12.0 Jun-07 Dec-11 8.0 6.0 4.0 2.0 U SA K U ia Ja pa n M ex ic o Po la nd R us So si a ut h Af So ric a ut h Ko re a Ta iw an In d EU na C hi a ad C an az il 0.0 Br Policy rate, %pa 10.0 Page 25 Risk premia Risk premia Why do we want to be compensated for bearing risk ? Risk inherent in investment classes distinguishes expected returns Measuring risk premia is very problematic Page 27 Risk premia on main asset classes Government bonds – an ‘inflation risk premium’ Corporate bonds – a credit risk premium Equities – the equity risk premium Page 28 The “inflation risk premium” Biggest risk in holding conventional, govt bonds is inflation In past governments have arguably “inflated away” their debts – they may be tempted to do this again Investors demand an additional return, mainly because future inflation is uncertain (other risks too) It will depend upon the: the monetary policy framework and the credibility of monetary authorities Page 29 Calculating an “inflation risk premium” Yield on Conventional government bond (Gilt) Minus Yield on index-linked government bond (ILG) Minus Estimate of expected inflation (survey based) Equals Measure of inflation risk premium This gives a good proxy for the risk premium on government bonds Page 30 Inflation risk premia Measure of the inflation risk premium for gilts Change in BRP (2007-2011) 3.0 Australia Canada France Italy Japan UK USA 0.0% Inflation risk premium Moving average 2.0 Change in bond risk premia, %pa Bank of England policy rate, %pa 2.5 1.5 1.0 0.5 0.0 -0.5 -1.0 1993 -0.5% -1.0% -1.5% -2.0% -2.5% 1995 1997 1999 2001 2003 2005 2007 2009 -3.0% It’s fallen everywhere, but not because of receding fears of inflation Page 31 Risk premia on main asset classes Government bonds – an inflation risk premium = 0.50% to 1.00% ? Corporate bonds – a credit risk premium Equities – the equity risk premium Page 32 The credit risk premium Credit premium additional return over equivalent govt bond to compensate for credit risk Varies according to the type of firm (AAA, AA, A, BBB etc) Outside US not much history to guide us as to likely future credit risk premium It’s also very volatile … Page 33 Credit premium varies over time 6.0% 6.0% 5.0% 5.0% 4.0% 4.0% 3.0% 3.0% BAA Spread 2.0% Credit spread, %pa Credit spread, %pa The credit risk premia 2.0% 1.0% 1.0% AAA Spread 0.0% 1926 0.0% 1936 1946 1956 1966 1976 1986 1996 2006 34 Credit premium varies by rating 25.0 25.0 Aaa 20.0 A Baa 15.0 15.0 Spec 10.0 10.0 5.0 5.0 0.0 1973 0.0 1978 1983 1988 1993 1998 2003 Credit spread, %pa Credit spread, %pa 20.0 2008 35 Credit premium varies by sector 8.0 7.0 Banking Industrial 7.0 6.0 Telecoms Utilities 6.0 5.0 5.0 4.0 4.0 3.0 3.0 2.0 2.0 1.0 1.0 0.0 1993 0.0 1995 1997 1999 2001 2003 2005 2007 2009 Sectoral credit spread, %pa Sectoral credit spread, %pa 8.0 2011 36 Company specific factors European high yield interest rate coverage European high yield debt/EBITDA 5.0 5.0 4.0 4.0 3.0 3.0 2.0 2.0 1.0 1.0 0.0 0.0 2008 • 2009 2010 2011 2008 2009 2010 2011 Company fundamentals play an important part in the premium too 37 Risk neutrality and the credit premium • However, if investors are risk neutral then they will only asked to be compensated for the potential additional loss compared with a default-free investment Expected loss = probability of loss x (1 – recovery rate) • What we expect to lose from investing in a credit risky entity is simply the product of the probability of experiencing and the scale of that potential loss 38 The probability of loss (1920-2008) 80.0 70.0 Year 5 Year 10 Year 15 Year 20 60.0 Percentage 50.0 40.0 30.0 20.0 10.0 0.0 AAA Aa A Baa Ba B Caa-C 39 Recovery rates – (rating 5 years before default) 100.0% Sr. Sec Sr. Unsec 1992 1997 Sub. Recovery rates, % 80.0% 60.0% 40.0% 20.0% 0.0% 1982 1987 2002 2007 40 The “risk neutral” credit premium • • Credit premium = prob. of loss x (1 – recovery rate) For example: Expected loss rate for Baa over ten years = 5% x 40% = 2% • • Or something like that The degree to which the actual spread differs from the risk neutral, or ‘fair’ spread reflects the additional return required by risk averse investors 41 de ed at R eG ra de Al l at iv -C aa C en t-G ra tm ul Sp ec ve s In B Ba a Ba A Aa a Aa Loss rates Loss rates (1982-2008) 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% 42 Risk premia on main asset classes Government bonds – an inflation risk premium = 0.25% to 0.50% Corporate bonds – a credit risk premium, the starting point should be the historic loss rate, let’s say = 1.50% to 2.00% for Baa Equities – the equity risk premium Page 43 The equity risk premium ERP is the additional return required over long-dated government bond for bearing equity risk But what is equity risk ? profitability ongoing viability of company Page 44 Equities are a poor hedge against recessions UK real equity returns Historic equity risk premia 100% 100% 80% 80% 60% 60% 8.0 Equities 40% 20% 20% 0% 0% Real return, %pa 40% 5.0 Real return Real return 6.0 4.0 Bonds ERP 6.0 3.8 3.2 4.9 4.5 3.9 3.6 3.9 2.1 2.0 0.0 -20% -20% -40% -40% -60% 1900 -2.0 -60% 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 Page 45 The Dividend Discount Model (DDM) When we buy equities we purchase a future stream of dividends All we need to do is calculate the “present value” of each of these dividends and add them all up But dividends are paid over a long period and are uncertain However, if we assume that they grow at a constant growth rate, maths can help us out … Page 46 The Dividend Discount Model (DDM) ERP + Risk free rate = Dividend Yield + Dividend growth or ERP = Dividend Yield + Dividend growth Risk free rate Dividend yield can be observed Risk free rate can be observed (government bond yield) Dividend growth – unobservable If we apply some macroeconomic theory then we can arrive at a very simple measure of the equity risk premium … Page 47 Simplifying the DDM ERP = Dividend Yield + Growth in dividends Risk free rate if dividends grow in line with real economy over long periods of time and if real risk free rate is close to trend growth of the economy then (for the UK): ERP = Dividend Yield + 2.25% 2.25% ERP = Dividend Yield Page 48 UK’s equity risk premium A measure of the UK’s equity risk premium Implied equity risk premium, % pa 12.0 10.0 8.0 6.0 4.0 2.0 0.0 1965 1970 1975 1980 1985 1990 1995 2000 2005 In 1970s required additional compensation was high Page 49 A DDM matrix Real risk free rate 0.70% Real Earnings Growth % 1.50% 1.75% 2.00% 2.25% 2.50% 2.75% 3.00% 2.5% 10,412 12,207 14,750 - 3.5% 6,556 7,224 8,045 9,077 - Risk premium 4.55% 3.5% 4,720 6,556 5,057 7,224 5,446 8,045 5,900 9,077 6,436 10,412 12,207 - 4.5% 4,784 5,130 5,531 6,000 6,556 7,224 8,045 5.5% 3,766 3,978 4,214 4,481 4,784 5,130 5,531 Real risk free rate 2.25% Real Earnings Growth % 1.50 1.75 2.00 2.25 2.50 2.75 3.00 2.0% 6,436 7,080 7,867 - 2.5% 5,446 5,900 6,436 7,080 - Risk premium 3.00% 3.5% 4,720 4,165 5,057 4,425 5,446 4,720 5,900 5,057 6,436 5,446 5,900 - 4.0% 3,726 3,933 4,165 4,425 4,720 5,057 5,446 4.5% 3,371 3,540 3,726 3,933 4,165 4,425 4,720 FTSE-100 = 5,900 on this day Page 50 Issues with this simplification What if firms increase dividends temporarily ? What if firms pay no dividends ? What about share buy backs ? What if the profits earned by the market are not derived from the underlying economy ? Adjustments to the model can be made to account for all these issues, but will require considerable user discretion Page 51 Assembling the building blocks Once the asset allocator has come to a view about expected: economic growth rates inflation and risk premia on a range of asset classes then the expected return jigsaw puzzle can be put together … Page 52 Putting it all together: an example Example of “building block approach” to forecasting long-run asset class returns Expected return/expected return component 9.0% Long-run expected return 8.0% 7.0% 6.0% 5.0% 4.0% Expected return component 3.0% 2.0% 1.0% 0.0% Real economic growth Expected inflation Inflation risk premium Equity risk premium Index-linked gilts Cash Gilts Equity This was the orthodox view just under four years ago Page 53 Questions about the building block approach What might change the asset allocator’s views ? Should we revisit the pre-crisis assumptions? What about developing economy asset classes ? What about the starting point ? (the tactical aspect) Page 54 Expected risk: Measuring volatilities and correlations Expected returns is the first ingredient Expected return: established via 'building block approach' A mean-variance efficient frontier for asset classes Efficient frontier Individual asset classes Standard deviation, risk How do we get the other ingredients ? Page 56 Historic measures of volatility and correlation Having determined the expected return, most use historic measures of volatility and correlation A MVEF can then be constructed But variances and co-variances change over time … Page 57 Time-varying volatility UK & US equity return volatility over time Equity market volatility, standard deviation, %pa 12.0% 10.0% USA UK 8.0% 6.0% 4.0% 2.0% 0.0% 1970 1975 1980 1985 1990 1995 2000 2005 2010 Asset class volatility can vary substantially over time Page 58 Time-varying correlations Correlation between UK & US equity returns over time Equity market correlation, US and UK equities 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 1970 1975 1980 1985 1990 1995 2000 2005 2010 Asset class correlation can vary substantially over time too Page 59 Forecasting volatility and correlations Time variation of volatility and correlation is a problem Many fancy statistical techniques for forecasting future volatility and correlations But once again, there is no “correct” way to forecast volatilities and correlations Page 60 What about client risk tolerance ? We now have: expected returns expected variances and correlations an efficient frontier But what is the client’s appetite for risk ? May be dictated by “return needs” Psychologists and economists now put a lot of effort in to trying to determine this Page 61 Measuring risk aversion Risk aversion is very difficult to gauge Answer depends heavily on the utility function assumed to describe investors’ risk-return trade off Investment professionals in US use experiments of this kind to determine risk aversion of their clients These techniques are now in widespread use elsewhere too Page 62 Risk aversion is the final ingredient Expected return: established via 'building block approach' Choosing a position on the efficient frontier B E D Efficient frontier A Individual asset classes Source: Fathom C F Standard deviation, risk: established using historic estimates of volatilities and correlations But remember: ALL optimizers essentially ‘tell’ us what we have ‘told’ them!!! Page 63 Appendix: Yale University Endowment fund Overview Yale University's endowment is seen as a "best of breed" multi asset class investment fund Has made substantial use of alternative asset classes The fund aims to support the University's academic activities And has managed to increase both the absolute size of the fund and the absolute size of the annual support for these University activities Annual spend Fund value 1996 $170m $676m 2010 $1.1bn $16.6bn (Though the fund has received substantial donations over this period too) Source: "The Yale Endowment" 2010 65 Yale University revenue Endowment revenue makes up over 40% of total uni revenue 66 The "liabilities" The fund is used to support all University activities. Many of the donations are given with pre-defined activities that the donor wishes to support, but for investment purposes the funds are "co-mingled" In 2010 the fund supported 41% of the University's $2,681m operating budget 67 "Spending" policy Conflicting goal: desire to support as much current spending as possible, but preserving the value of assets to support future spending Goal 1: Aim to produce stable/smooth stream of income for university Goal 2: protect value of investments relative to inflation Long-term spending rate, combined with "smoothing rule" The smoothing rule ensures that income does not fall too far (if at all) in bad years, but does not rise too much (if at all) in good years (Life companies use similar rules) 68 "Spending" policy Spending growth has outstripped the University's specific inflation measure, that is, spending has increased in real terms Rate of growth is smooth, due to smoothing rule 69 Spending rate The crisis had a big impact on the “smoothed” spending rule 70 Fund value Combination of high annual returns and ongoing contributions has led to a massive increase in the fund's value over time 71 Investment policy A combination of academic theory and "informed market judgement" MVA is the starting point, stress tested for different return, vol and correlation assumptions etc Aim to invest predominantly in asset classes with "equity-like" returns Avoid the "home bias" of investing in only domestic asset classes The long-term horizon means that capital can be committed to illiquid asset classes 72 Yale’s performance 73 Yale’s asset allocation 74 Asset allocation: actual & target The assets used to support the spending aspirations (the liabilities) are relatively diverse This asset allocation structure is quite different from similar US University funds, and very different from the sort of allocations made by UK life and pension funds 75 Yale’s illiquidity ‘budget’ 76 Yale’s fiscal highlights 77 Absolute returns In 1990 first sizeable institution to invest in absolute return strategies Identify managers that can enhance long-term real returns by exploiting market inefficiencies. 50% Event driven, other 50% "Value driven strategies" Expected real return: 5-6% Expected risk: 10% volatility (event driven) Expected risk: 15% "Value strat" Policy: performance-related fees hurdle rates clawback provisions manager invests own net worth in fund Performance: 11.5% pa with low correlation to bonds and equities 78 Domestic equities Lower weighting than similar institutions (7% target) Expected real return: 6% Expected standard deviation: 20% Benchmarked against Wilshire 5000 index Policy: commitment to active management prefer managers with bottom-up research capabilities acknowledgement that this will focus on small stocks Performance: over last ten years 6.7%pa outperforming Wilshire 5000 by 7.4%pa 79 Overseas equities Raison d'etre: exposure to global economy One half of portfolio invested in high growth, emerging markets Expected real return: 7% Expected standard deviation: 22.5% Again commitment to active fund management 80 Fixed income Attracted by "certainty" of nominal cash flow; a hedge against "financial accidents", but allocation of just 4% Expected real return: 2% Expected standard deviation: 10% Benchmark index: Lehman Brothers US Treasury Index Policy: (internal) active management avoiding market timing strategies, call options & credit risk 81 Private equity Attraction: long-term, risk adjusted returns Including buy-out funds and venture funds Expected real return: 10.5% Expected standard deviation: 27.7% Policy: avoid PE funds sponsored by financial institutions because of potential conflicts of interest and staff instability Actual returns since inception: 30.3%pa 82 Real assets Investments in real estate, oil and gas and "timberland" Attractions: real assets so hedge against expected and unexpected inflation visible cash flows low correlation with other asset classes illiquidity of such assets creates barrier to entry and raises long-term returns Expected real return: 6%pa Expected standard deviation: 15.5%pa Over last ten years the portfolio has returned 10.9%pa 83 Investment performance All components of portfolio have outperformed active benchmarks over the last ten years 84