A itrisic approach to performace measuremet of portfolio maager skill Prepared by Marti Hicklig Preseted to the Istitute of Actuaries of Australia 4 th Fiacial Services Forum 19-2 May 28 Melboure, Australia This paper has bee prepared for the Istitute of Actuaries of Australia s (Istitute) 4 th Fiacial Services Forum 28. The Istitute Coucil wishes it to be uderstood that opiios put forward herei are ot ecessarily those of the Istitute ad the Coucil is ot resposible for those opiios. Cocord Capital The Istitute will esure that all reproductios of the paper ackowledge the Author/s as the author/s, ad iclude the above copyright statemet: The Istitute of Actuaries of Australia Level 7 Challis House 4 Marti Place Sydey NSW Australia 2 Telephoe: +61 2 9233 3466 Facsimile: +61 2 9233 3446 Email: actuaries@actuaries.as.au Website: www.actuaries.as.au
Ackowledgemets I would like to thak my work colleagues at Cocord Capital for their cotributios to this paper ad their feedback o earlier drafts of the paper. I particular, to Ae Percet for her help o the performace measuremet compoets of the paper ad to Richard Douglas for his commets o the uderlyig priciples of the paper. I would also like to thak Ada Kucukalic at Credit Suisse for his cotributios, especially for the earigs data ad factor aalysis. A special thaks goes to Mike Barker for his iput ito earlier drafts of the paper ad for his time spet i the peer review of the paper. His commets were, as usual, thoughtful ad isightful. Ay errors i this paper remai my sole resposibility. The views expressed i this paper are those of the author ad ot ecessarily those of the compay with which he is associated. This paper should ot be cosidered as fiacial advice. Abstract This paper ivestigates the use of fudametally based measures of portfolio maager skill rather tha the traditioal market value based measures. Due to the volatility of market prices aroud the itrisic value of a fud s ivestmets, over short time periods, traditioal market value based performace measures of active retur may ot be the best measures of portfolio maagemet skill. Alteratively, measuremet of the uderlyig alpha geeratio i the itrisic value of the portfolio may provide a better measure of portfolio maager skill. This is expected to particularly be the case for deep value ivestors. This paper discusses these issues ad looks at possible alterative measures for calculatig the uderlyig alpha geeratio of a ivestmet portfolio. Keywords: active retur, itrisic value, skill, luck, volatility, portfolio maagemet 2
1. Itroductio The stadard measure of the relative performace of a ivestmet portfolio is the total retur of the portfolio less the retur of the appropriate accumulatio based bechmark. Performace i excess of the idex is typically kow as alpha. Geeratig positive alpha is the life blood of the active fuds maagemet idustry. However, as ASIC s Executive Director of Cosumer Protectio, Mr Greg Tazer has commeted Past performace is ot a reliable idicator of future performace. A udue emphasis o past returs ca lead to cosumers havig urealistic expectatios ad makig poor ivestmet decisios. I 23, ASIC commissioed the Fuds Maagemet Research Cetre to report ito the usefuless of past performace iformatio whe cosumers (or their advisers) are selectig a Australia maaged fud. The report cocluded that good past performace seems to be, at best, a weak ad ureliable predictor of future good performace over the medium to log term. The report said a plausible explaatio for the coclusio about the low persistece of past performace was that the future retur o ivestmets is extremely hard to predict, so a sigificat part of a fud s performace (compared to its peers) may be radom luck. A fudametal teet of active fuds maagemet is that ivestmet markets are ot fully efficiet ad that there exist opportuities to ivest i a maer that geerates alpha for a cliet. This implies it is possible to idetify securities with market prices that are ot tradig at their uderlyig itrisic fair value ad, withi the cliet s time horizo, the market price will retur sufficietly to this itrisic value. Active fuds maagemet through research or alterative methods (such as quat models) aims to idetify these mis-priced securities ad to the take advatage of that mis-pricig. Give active fuds maagemet is based o the premise that securities ca be mis-priced (sometimes for log periods) it is therefore somewhat icogruous that the stadard measure for assessig the performace of the active fuds maagemet idustry is based o the chage i market value of the portfolio from start of period to ed of period. I Warre Buffett s 1997 letter to shareholders he advised If you expect to be a et saver durig the ext five years, should you hope for a higher or lower stock market durig that period? May ivestors get this oe wrog. Eve though they are goig to be et buyers of stocks for may years to come, they are elated whe stock prices rise ad depressed whe they fall. This reactio makes o sese. Oly those who will be sellers of equities i the ear future should be happy at seeig stocks rise. Prospective purchasers should much prefer sikig prices. If a share price has falle the key thig to determie is if the fudametals of the busiess have deteriorated or if the compay has become cheaper. Assumig the market is ot fully efficiet, the share price move o its ow will ot tell you which of these is true. Bejami Graham observed that I the short ru, the market is a votig machie, but i the log ru it is a weighig machie. This paper looks at alteratives to the votig machie (ie. traditioal performace measuremet usig chages i share prices) to measure how much weight (i.e. measures based o chages i itrisic value) is beig added to portfolios. 3
Over the log-term, the votig machie should be roughly equivalet to the weighig machie, but i the short-term alterative measures are eeded to assess if positive relative performace has bee geerated through skill or good luck, or for egative relative performace if it has bee geerated through a lack of skill or bad luck. 2. Market Efficiecy A efficiet market is oe where the market price is a ubiased estimate of the true value of the ivestmet. This does ot require that the market price be equal to true value at every poit i time. All it requires is that errors i the market price be ubiased, i.e., that prices ca be greater tha or less tha true value, as log as these deviatios are radom. The fact that the deviatios from true value are radom implies, i a rough sese, that there is a equal chace that stocks are uder or over valued at ay poit i time, ad that these deviatios are ucorrelated with ay observable variable. For istace, i a efficiet market, stocks with lower PE ratios should be o more or less likely to be udervalued tha stocks with high PE ratios. If the deviatios of market price from true value are radom, it follows that o group of ivestors should be able to cosistetly fid uder or over valued stocks usig ay ivestmet strategy. [Source: http://pages.ster.yu.edu] Uder the Efficiet Market Hypothesis a 'efficiet' market is defied by Fama as a market where there are large umbers of ratioal, profit-maximizers actively competig, with each tryig to predict future market values of idividual securities, ad where importat curret iformatio is almost freely available to all participats. I a efficiet market, competitio amog the may itelliget participats leads to a situatio where, at ay poit i time, actual prices of idividual securities already reflect the effects of iformatio based both o evets that have already occurred ad o evets which, as of ow, the market expects to take place i the future. I other words, i a efficiet market at ay poit i time the actual price of a security will be a good estimate of its itrisic value..although ucertaity cocerig itrisic values will remai, actual prices of securities will wader radomly about their itrisic values [Source: Eugee Fama, Radom Walks i Stock Market Prices]. This paper does ot attempt to debate the degree of market efficiecy i ivestmet markets. The active fud maagemet idustry relies upo idetifyig iefficiecies i markets, ad this paper is focused o measurig the success, or otherwise, of active maagemet through the use of fudametal itrisic value measures. The success of active maagers will deped upo a umber of factors, icludig the sophisticatio of other participats i the market i which they operate. Active fud maagers also eed to create sufficiet value to offset their geerally higher maagemet fees, trasactio costs (icludig the market impact of demadig liquidity ad brokerage costs) ad taxatio costs. Some historically successful active strategies, particularly quatitative strategies, ca be replicated by others, thereby egatig prospective value creatio. That said, there is iteratioal research that shows log-term persistecy i performace from some strategies such as value ad small cap ivestig. It is most likely that behavioural fiace provides the greatest isights as to why, despite the research, this seems to remai the case. Oe compoet may be that there is evidece that ivestmet maagers are proe to herdig. [Source: http://wwwdocs.fce.usw.edu.au]. However, as discussed later i this paper, i more recet periods, value factors ad small cap have ot proved to be successful quatitative factors for the Australia market. This may reflect that the prior systematic 4
discrepacies have bee idetified ad eutralised by market participats utilisig those factors i their ivestmet strategies. Whether the market is efficiet, or ot, there appears to be a lack of measuremet, aalysis ad reportig of ay value created through active Portfolio Maagemet by growig the itrisic value of their portfolios. This paper looks to address some of these issues. 3. Portfolio Maagemet The term portfolio maagemet is widely used, but it is ot ofte clear what it actually meas. Typically it is defied as somethig similar to The process of maagig the assets of a mutual fud, icludig choosig ad moitorig appropriate ivestmets ad allocatig fuds accordigly. [Source: http://www.ivestorwords.com/] A Portfolio Maager is resposible for the security selectio i a portfolio, but ofte it is ot well defied how the portfolio is actually maaged, other tha the Portfolio Maager is accoutable for the ultimate performace that results from the stock selectio. As Portfolio Maagers ca t cotrol idividual security prices, they are, as such, uable to maage ivestmet performace, at least over the short-term. Portfolio Maagers are, however, able to maage the purchase ad sale of securities i a way to purchase a iitially udervalued portfolio ad the grow the uderlyig itrisic value of their fud. Subject to the holdig period, those that do this well will create value for their ivestors ad those that do this badly will destroy value for their ivestors. Over the log-term, quality Portfolio Maagers are those that are able to grow the itrisic value of their portfolios at a rate sigificatly i excess of the broader market, i cojuctio with ot overpayig for the iitial portfolio ivestmet. The key data poits for a Portfolio Maager to maage are therefore: the discout of market value to itrisic valuatio for the portfolio at the time of iitial ivestmet the rate of chage i itrisic value of the portfolio i periods followig the iitial ivestmet; ad Over the log-term the first poit should become less importat ad the success of the Portfolio Maager should be determied by the secod poit. As such, over the log-term, the performace of the Portfolio Maager should be determied by the rate of chage i the itrisic value of the portfolio. This should therefore be the primary focus of the Portfolio Maager ad if this is to be maaged the it should be advatageous for it to be measured. 5
Berkshire Hathaway s A Ower s Maual sets out Warre Buffet s ower-related busiess priciples for the iformatio of Class A ad Class B shareholders. Withi this documet, his log-term ecoomic goal (subject to some qualificatios) is defied as to maximise Berkshire s average aual rate of gai i itrisic value o a per-share basis. This is oe example where itrisic value is beig measured ad maaged, if ot directly reported. 4. Itrisic Value Some defiitios of itrisic value iclude: The actual value of a security, as opposed to its market price or book value. The itrisic value icludes other variables such as brad ame, trademarks, ad copyrights that are ofte difficult to calculate ad sometimes ot accurately reflected i the market price. Oe way to look at it is that the market capitalizatio is the price (i.e. what ivestors are willig to pay for the compay) ad itrisic value is the value (i.e. what the compay is really worth). Differet ivestors use differet techiques to calculate itrisic value. [Source: http://www.ivestorwords.com/] The value of a security, justified by factors such as assets, divideds, earigs, ad maagemet quality. Itrisic value is at the core of fudametal aalysis sice it is used i a attempt to calculate the value for a idividual stock ad the compare it with the market price. Because aalysts view facts differetly, there is ofte a wide disparity i estimates of a particular stock's itrisic value. [Source: http://fiacialdictioary.thefreedictioary.com/itrisic+value] Berkshire Hathaway s A Ower s Maual says Itrisic value is a all-importat cocept that offers the oly logical approach to evaluatig the relative attractiveess of ivestmets ad busiesses. Itrisic value ca be defied simply: It is the discouted value of the cash that ca be take out of a busiess durig its remaiig life. Warre Buffett adds The calculatio of itrisic value, though is ot simple. As our defiitio suggests, itrisic value is a estimate rather tha a precise figure, ad it is additioally a estimate that must be chaged if iterest rates move or forecasts of future cash flows are revised. Two people lookig at the same set of facts, moreover ad this would apply eve to Charlie ad me will almost ievitably come up with at least slightly differet itrisic value figures. That is oe reaso we ever give you our estimates of itrisic value. What our aual reports do supply, though, are the facts that we ourselves use to calculate this value. Essetially itrisic value is the uderlyig value of the icome steams of a ivestmet as it will beefit the ivestor. If a compay s free cashflows are ot paid to ivestors i terms of divideds, the itrisic value will be heavily depedet o how those cashflows are reivested by the compay. Berkshire Hathaway has ever paid a divided to its shareholders. Part of its success has bee Warre Buffett s ability to reivest retaied earigs (ad the isurace float) at high rates of retur. 6
Ivestors will make their ow estimates of itrisic value usig either explicit or implicit forecasts of free cashflows ad discout rate assumptios. Itrisic value will, however, oly become evidet over time as the cashflows are paid to shareholders. As such, ex ate, itrisic value ca oly be estimated but clearly compaies with strog free cashflows ad the ability to reivest some or all of their cashflows at high margial retur o capital will have sigificatly more itrisic value tha those with poor free cashflows which are reivested at low margial retur o capital. 5. Decomposig ivestmet performace ito its compoets Relative ivestmet performace = [PM t / PM o ] - [BM t / BM o ] where PM t is the portfolio s market price at time t; ad BM t is the bechmark s market price at time t I log space, for periods, this relative outperformace ca be expressed as: α = l [PM / PM o ] l [BM / BM o ] This relative ivestmet performace ca be broke ito three compoets: (1) The relative growth of the portfolio s itrisic value versus the bechmark s growth i itrisic value (2) The relative iitial cheapess of the portfolio versus the bechmark s iitial cheapess (3) The relative degree of covergece betwee the market value of the portfolio ad bechmark to the respective itrisic value of the portfolio ad bechmark. These three compoets represet: i) the excess growth i the portfolio s istrisic value above the bechmark growth i itrisic value, plus; ii) a compoet for the relative cheapess of the portfolio whe it was acquired, plus; iii) a compoet to adjust for ed of period prices ot havig aliged fully with the itrisic values of the portfolio ad bechmark. The first compoet, the growth of the portfolio s itrisic value relative to the growth of the bechmark s itrisic value, will be the ratio of [PIV t / PIV o ] to [BIV t / BIV o ]. where PIV t is the portfolio s itrisic value after t periods; ad BIV t is the bechmark s itrisic value after t periods I log space, for periods, this ca be expressed as: α Ig = = PIV l BIV l PIV BIV PIV BIV l PIV BIV 7
= PIV l PIV BIV BIV Provided that the itrisic value of the portfolio cotiues to grow at a rate i excess of that of the growth i itrisic value of the bechmark, this term, whe aualised by dividig by, will ot ted to zero as becomes large. The secod compoet, the relative iitial cheapess of the portfolio versus the bechmark s iitial cheapess, will be drive by the ratio of PIV o / PM o to BIV o / BM o. I log space, this ca be expressed as: α I = = = PIV l PM l PIV PM PIV l PM BIV l BM BIV BM BM BIV This term, whe aualised by dividig by, teds to zero as icreases, but may still be importat, eve over medium term time horizos, where the relative iitial cheapess of the portfolio is sufficietly large. The third compoet, the relative degree of covergece betwee the market value of the bechmark ad portfolio, to the respective itrisic value of the bechmark ad portfolio will be drive by the ratio of BIV / BM to PIV / PM. Relative ivestmet performace will be depressed if PM has ot sufficietly coverged to PIV relative to the degree of covergece of BM to BIV. This compoet is out of the cotrol of the Portfolio Maager. As such, this compoet has some of the characteristics of a error term i assessig Portfolio Maager performace. I log space, this ca be expressed as: ε I = = = BIV l BM BIV l BM BIV l BM PIV l PM PIV PM PM PIV 8
This term, whe aualised by dividig by, teds to zero as icreases, but agai may be importat depedig o the relative degree of covergece of the portfolio ad bechmark to itrisic value. The additio of the above three compoets ca be show to equal the market value based alpha, or relative ivestmet performace of the portfolio. α Ig + α I + ε I PIV = l PIV PIV = l PIV PM = l PM PM = l PM PM = l PM = α BIV PIV + l BIV PM BIV PIV BIV PM BM BM BM BM BM l BM BM BIV + l BIV BM BM BIV BIV BM PM PIV PM PIV The coclusio is that, over log time periods, the key driver of portfolio maagemet alpha geeratio is the ability to grow the itrisic value of a portfolio at a rate i excess of the growth i itrisic value of the broader market. Over log periods this is the mai compoet of portfolio maager skill. Log-term outperformace will be drive by maagig the rate of chage i a portfolio s itrisic value i excess of that for the broader market ad the level of this compoet of alpha will be determied by the level of growth i excess of that of the broader market. There is also a compoet of skill i acquirig the iitial portfolio at relatively cheap prices, although this compoet becomes less importat over loger periods of time. Fially, there is a compoet of performace out of the cotrol of the Portfolio Maager. This is the compoet of performace drive by the degree of covergece betwee BM to BIV ad PM to PIV. This compoet becomes less importat over loger periods of time. 6. Measuremet of Itrisic Value PIV ad BIV eed to be measured i order to assess portfolio maagemet skill. They should be calculated o a accumulatio basis (ie. icludig divideds) ad be adjusted for cashflows (ie. time weighted). A Portfolio Maager wishig to maage a portfolio s itrisic value at a rate above the market will have either a explicit or implicit view o PIV ad BIV. Explicit views may well 9
be i the form of a proxy measure of itrisic value. This sectio discusses the suitability of some proxies of itrisic value. Aalyst valuatios as a proxy measure of itrisic value Stock aalysts typically calculate compay valuatios as part of their stock research ad aalysis. These valuatios ca be based o a variety of measures. Commo methods iclude: DCF based valuatios; PE based valuatios; EBIT, EBITA or EBITDA based valuatios; divided yield based valuatios; ad price to book value based valuatios. For resource stocks, project based NPVs are commoly used. Cosesus data is geerally available for a rage of valuatio variables icludig: EPS per share (up to 2 years forward) DPS per share (up to 2 years forward) NAV per share NTA per share EBIT, EBITDA ad et debt Aalyst valuatios could be used as a proxy for the estimated uderlyig itrisic value of a ivestmet. Aalyst valuatios are geerally ot captured by data vedors, so data would eed to be sourced directly from the relevat fud maager or stockbrokers. Stockbrokig aalysts typically also publish target share prices, although they are ot geerally available from data vedors. These are ofte set i relatio to the aalyst s valuatio rolled forward 12 moths, but may also capture other factors i the share prices such as takeover premiums ad optioality (eg. ew projects, upside from acquisitios, ability to reivest at high margial retur o capital etc) ot captured i the base valuatio. A estimate of itrisic value could be derived from the 12-moth forward target share price by dividig this figure by the equity cost of capital ad addig the et preset value of divideds expected to be paid over the 12 moth period. The lack of cosistecy of assumptios betwee broker aalysts is likely to be the mai disadvatage of this idicator of itrisic value. EPS times a multiple as a proxy measure of itrisic value Earigs per share (EPS) multiples (ie. PE multiples) are a crude but commo valuatio method. The multiple essetially captures the discout rate ad perpetuity earigs growth rate ito oe figure. To avoid capitalisatio of cyclically low / high earigs, the EPS multiple should be applied as close as possible to mid cycle earigs. 1
Cosesus earigs per share forecasts are geerally oly available o at most a 2 year forward basis, so some cyclical compoet i EPS is uavoidable. The multiple is essetially 1 / [r-g] where r is the discout rate ad g is the growth rate (with the earigs growth rate g based o the assumptio of a 1% payout ratio, to exclude the double coutig of earigs growth from retaied earigs). The followig chart shows the T, T+1, ad T+2 PE multiples for the Australia share market (S&P ASX 2 idex) sice March 23. S&P ASX 2 Idex PE 19. 18. 17. 16. 15. 14. 13. 12. 11. 1. Mar-3 Ju-3 Data Source: Credit Suisse mths 12 mths 24 mths Sep-3 Dec-3 Mar-4 Ju-4 Sep-4 Dec-4 Mar-5 Ju-5 Sep-5 Dec-5 Mar-6 Ju-6 Sep-6 Dec-6 Mar-7 Ju-7 Sep-7 Dec-7 Mar-8 Usig the above PE data ad applyig it to the S&P ASX 2 Accumulatio idex, eables estimates of T, T+1 ad T+2 EPS (accumulated for divideds) to be calculated. This is show i the chart below. 11
S&P ASX 2 Accumulatio Idex EPS 35 3 25 2 15 1 mths 12 mths 24 mths Data source: Credit Suisse Mar-3 Ju-3 Sep-3 Dec-3 Mar-4 Ju-4 Sep-4 Dec-4 Mar-5 Ju-5 Sep-5 Dec-5 Mar-6 Ju-6 Sep-6 Dec-6 Mar-7 Ju-7 Sep-7 Dec-7 Mar-8 By applyig a multiple to T+2 EPS (accumulated for divideds) forecasts, we get a estimate of BIV. The multiple used should be cosistet with the approach used to assess PIV. Amogst other assumptios, the use of a costat multiple implies a costat discout rate ad a costat termial growth rate. This may ot be reasoable, especially whe T+2 EPS has a elemet of cyclicality. As ca be see from the above chart, cosesus aalyst earigs forecasts ted to be achored to curret year EPS, but typically aroud 2% higher. As such, estimates of BIV usig curret year EPS may be as good as those usig T+2 EPS. T, T+1 or T+2 EPS times a multiple could provide a exterally assessable, fudametally based assessmet of BIV ad PIV where other more direct measures are ot available. Price to book value as a proxy measure of itrisic value Price to book valuatios are most commoly used i idustries which are capital itesive ad commodity i ature. For example, aalyst valuatios of the US property & casualty sector rely heavily o price to book multiples. Price to book valuatios ted to be less reliable for compaies that operate i idustries that are o capital itesive ad frachise or brad based. 12
The variace of the price to book ratio betwee compaies is sigificatly greater tha that of the variace of price earigs multiples betwee compaies. As such, price to book is less likely to form a good proxy for itrisic value at a idividual stock level. Eterprise valuatios (usig EBIT, EBITDA ad et debt) as a proxy measure of itrisic value Eterprise valuatios are similar i ature to EPS multiple based valuatios. Cosesus data from data vedors may be available for idividual compaies, however esurig veracity of the calculatios of eterprise value usig the raw data may be difficult for a exteral party. I particular, the treatmet of ay value accruig to miority iterests (which are icluded i eterprise value) ad o-ordiary equity holders eeds to be determied o a compay by compay basis whe calculatig the itrisic value of a portfolio or the market bechmark. Quatitative factors as a proxy measure of itrisic value: Quatitative factors that have log-term predictive power could also be used a proxy measures of itrisic value. The followig chart shows the 1, 3 ad 5 year iformatio ratios for a rage of commo quatitative factors based o aalysis performed by Credit Suisse. Most of the factors are self explaatory. Size relates to the performace of large compaies (ie. a positive iformatio ratio shows that large compaies have bee outperformig smaller compaies). 3. Quatitiative Factors - recet periods 2. Iformatio ratio 1.. -1. -2. -3. -4. Price to CF Div Yield ROE Price to Book Forward PE 12M Prc Mom 3M EPS Rev 3M Mometum 1YR EPS Growth 2YR EPS Growth 2YR PEG Size 5 Years 1 Year 3 Years Source: Credit Suisse Basic measures of value such as cashflow yield [Price to CF], divided yield [Div Yield], book yield [Price to Book], ad earigs yield [Forward PE] seem to have ot bee successful 13
quatitative factors over the past 1 ad 3 years. This may reflect the stage of the curret market cycle (eg. the bull ru i commodities ad resources), ad / or it may reflect the icreased cocetratio of use of quatitative fuds which have arbitraged away this value compoet of historic excess returs. The poor performace of fiacials i the past year has egatively impacted may of the value based measures. For quatitative factors with log-term predictive power, it could be argued that those factors are essetially idetifyig stocks that are tradig above / below their itrisic value. However, somewhat couter ituitively price mometum (over 3 moths ad 12 moths) is oe of the most positive quatitative factors over each period. This suggests that share prices cotiue to rise despite gettig more expesive ad cotiue to fall despite gettig cheaper. There may be some elemet of fudametals for example share price falls from EPS dowgrades ted to cotiue due to the persistet ature of EPS revisios. Ivestmet aalysts ad compaies ted to uder estimate the persistece of EPS revisios. The success of mometum factors i recet years may have bee exaggerated by the cotiued rise i commodity prices which has cotiued to boost profitability of resource compaies. There may also be some elemet of herdig that reiforces the share price mometum for periods of time. Share price mometum (outside that compoet related to improved fudametals) may exaggerate movemets away from itrisic value, but over loger time periods the share price is likely to be attracted back to the itrisic value of the compay. A alterate view may be that the stregth of the share price mometum factors may just reflect that share prices take a period of time to move towards itrisic value. The followig chart shows how the quatitative factors have performed over the past 5 ad 1 years. It shows that most of the value factors have performed well over this loger time horizo, although divided yield ad price to book factors have bee poor performers over the past 5 years. 1.4 1.2 1..8.6.4.2. -.2 -.4 -.6 -.8 Quatitative Factors - loger term periods Price to CF Div Yield ROE Price to Book Forward PE 12M Prc Mom 3M EPS Rev 3M Mometum 1YR EPS Growth 2YR EPS Growth 2YR PEG Size Iformatio ratio 1 Years 5 Years Source: Credit Suisse 14
The itrisic value of ivestmet portfolios with a bias to log-term positive predictive quatitative factors would the eed to be calculated allowig for these factors i some maer as the factors o their ow do ot provide a valuatio of the portfolio. Accuracy of estimatig itrisic value from exteral data sources The degree of accuracy i estimatig itrisic value from exteral data sources is a key issue. If, for example, a portfolio maager chages his ivestmet mix from lower growth to higher growth compaies, the the short dated EPS of the fud would most likely fall sigificatly. Applyig a costat valuatio multiple to this would idicate that the Portfolio Maager had destroyed itrisic value, however the icreased earigs growth of the fud may have justified the decisio ad the itrisic value of the fud may have actually icreased. It could be argued that cosesus data is what is reflected i the market price of securities ad therefore market prices are the best estimate of BIV. Applyig cosistet macro criteria (eg. bod yields, discout rates, ecoomic outlook) betwee the calculatios of PIV ad BIV is also a importat cosideratio. 7. Profile of a skilled Portfolio Maager As defied earlier, a skilled Portfolio Maager greater rate tha the rate of growth i BIV. is essetially oe who ca grow PIV at a Let us say a skilled Portfolio Maager may be able to grow PIV > BIV at aroud 4% per aum over a log period of time. However, over shorter periods the Portfolio Maager is i some years likely to add more tha 4%, some years add modest amouts, but i other years grow PIV below that of BIV as eve a skilled Portfolio Maager will make some mistakes. Effectively a skilled Portfolio Maager has a expected ability to grow PIV > BIV, with a volatility aroud its delivery. The charts below show the 5%-95% probability bad (assumig a ormal distributio) for the growth i a Portfolio Maager fud s itrisic value over the growth i itrisic value of a market bechmark assumig a 4% expected growth of PIV > BIV with a 4% stadard deviatio. This first chart shows the bad over a 5 year period ad the secod chart shows the bad over a 3 year period. The chart below shows that usig the above criteria, there is aroud a 5% probability that it may take at least 3 years for a skilled Portfolio Maager to grow PIV i excess of BIV. After 5 years a skilled Portfolio Maager should have grow PIV i excess of BIV by at least 5% (ie. aroud 1% pa) with a 95% cofidece iterval. There is also a 9% probability that after 5 years the Portfolio Maager has grow PIV i excess of BIV by betwee aroud 5% ad aroud 4% (ie. betwee 1% ad 7% pa). 15
% total excess retur 45.% 4.% 35.% 3.% 25.% 2.% 15.% 1.% 5.%.% -5.% PIV i excess of BIV assumig 4% pa expected ad 4% stadard deviatio over 5 years 5% probability bad Expected 95% probability bad 1 2 3 4 5 Years The 3 year chart shows that over log periods of time if a maager is skilled it should be clearly evidet. % total excess retur 4.% 35.% 3.% 25.% 2.% 15.% 1.% 5.%.% -5.% PIV i excess of BIV assumig 4% pa expected ad 4% stadard deviatio over 3 years 5% probability bad Expected 95% probability bad 5 1 15 2 25 3 Years 16
Share price volatility ad the skilled Portfolio Maager A skilled Portfolio Maager may be growig PIV at a greater rate tha the growth i BIV, but i the short-term to medium term this may be hidde to exteral parties due to the volatility ad vagaries of share price movemets that do t relate to chages i PIV ad BIV. PM t should be attracted to PIV t, but may be dislocated for a period of time. Similarly, BM t should be attracted to BIV t, but agai may be dislocated for a period of time. It could be expected that PIV t PM t (ie. the cheapess of the portfolio) would be correlated to BIV t BM t (ie. the cheapess of the bechmark) whe broader market moves are drive more by setimet tha by fudametals. It is the ratio [PIV t PM t ] / [BIV t BM t ] (ie. the relative cheapess of the portfolio versus the bechmark) which would create the mai oise i measurig relative performace based o market prices. The amout of volatility i the ratio [PIV t PM t ] / [BIV t BM t ] will likely deped o the market coditios ad o the Portfolio Maager s ivestmet style. Skilled Portfolio Maagers who have a deep value style may ted to have loger periods i which the itrisic value of their ivestmets is ot recogised by the broader ivestmet commuity. This would most likely partly relate to the cocetratio of their portfolio to certai factors (eg. low PE, out of favour compaies). Skilled Portfolio Maagers who have a broader based ivestmet style may fid that the itrisic value of their ivestmets is more quickly recogised by the broader ivestmet commuity ad they therefore are likely to have shorter periods i which the relative cheapess of their portfolio versus the bechmark is at extreme levels. The followig charts show the 5 ad 3 year profiles of a perfectly skilled Portfolio Maager (ie. oe that ca grow PIV at 4% pa above the growth i BIV with zero stadard deviatio) with 5% to 95% probability rage of outcomes for PM compared to BM. The data assumes that the ratio of PIV / PM to BIV / BM has a mea of 1.15 ad a stadard deviatio of.85. It is likely that the ratio would remai above 1. (ie. the Portfolio Maager would be expected to maage the portfolio so that the securities were relatively cheaper tha the market). I this example the 5% probability is 1.1x ad the 95% probability is 1.29x. Give a iitial startig poit it would take a period of time for this volatility to emerge. For simplicity of calculatio it is assumed to apply for all periods after Year 1. 17
$ Fud size 23 21 19 17 15 13 PIV / PM to BIV / BM ratio of 1.15 ad a.85 stadard deviatio for a perfectly skilled maager over 5 years PM high value (95% probability bad) PM low value (5% probability bad) BM expected value 11 9 1 2 3 4 5 Years $ Fud size 7 6 5 4 3 2 PIV / PM to BIV / BM ratio of 1.15 ad a.85 stadard deviatio for a perfectly skilled maager over 3 years PM high value (95% probability bad) PM low value (5% probability bad) BM expected value 1 5 1 15 2 25 3 Years The charts suggest that it would take 3 to 4 years of market price based ivestmet performace to idetify a perfectly skilled maager at the 95% cofidece level. The charts, however, do t allow for the volatility of a o-perfect skilled Portfolio Maager. I this case it would take loger for the skill of the Portfolio Maager to be idetified by market price based ivestmet performace at the 95% cofidece level. 18
As a skilled Portfolio Maager (expected growth i PIV > BIV of 4% per aum with a 4% stadard deviatio) at the 95% cofidece level will have grow PIV i excess of BIV by at least 1.7% pa after 8 years, we ca approximate the combiatio of volatility i skill ad volatiliy i PIV / PM to BIV / BM, by lookig at the 1 year profile of a perfect moderately skilled Portfolio Maager, usig a 1.7% per aum skill level with o volatility ad the previous assumptios of PIV / PM to BIV / BM with a mea of 1.15 ad a stadard deviatio of.85. This combiatio is show i the chart below. 39 PIV / PM to BIV / BM ratio of 1.15 ad.85 std dev for a perfect moderately skilled maager 1.7% alpha, % std dev $ Fud size 34 29 24 19 PM high value (95% probability bad) PM low value (5% probability bad) BM expected value 14 9 2 4 6 8 1 Years The charts suggest that it would take aroud 8 years of market price based ivestmet performace to idetify a skilled maager at the 95% cofidece level. Mote Carlo Simulatios Sta Beckers paper Maager Skill ad Ivestmet Performace: How Strog is the Lik?, performed 1 simulatios usig a Mote Carlo simulatio of skilled fud maagers with coceptually idetical data with othig but luck separatig the best from the worst results. He performed the results for a log/short hedge fud maager (with a target aual stadard deviatio of 3.2%); a coservative log-oly maager (with a target aual stadard deviatio of 13.%); a moderately coservative log-oly maager (with a target aual stadard deviatio of 14.5%); ad a aggressive log-oly maager (with a target aual stadard deviatio of 17.25%); His aalysis showed that skill will show through for a hedge fud ivestor ad a coservative traditioal maager, with eve the most ulucky amog them havig positive iformatio ratios after five years. Coversely for a log-oly aggressive fud maager he said a five year period is ot log eough to do justice, as 2% of them eded up with egative iformatio ratios through bad luck oly. The simulatios suggested some aggressive log-oly fud 19
maagers may still have egative iformatio ratios after twety years despite havig uderlyig skill. Beckers the ra the simulatios assumig maagers had o skill. O average, the maagers had a zero iformatio ratio, but after three years the luckiest maagers eded up with a iformatio ratio of 1.7 or higher. After 3 years at least 15% of maagers had a iformatio ratio of.7 or higher. After 5 years the simulatio showed at least 1% of maagers had a iformatio ratio of.7 or higher. Beckers cocluded We kow that skilful maagers may be forced out of busiess through bad luck. Eve more worrisome is that a respectable proportio of maagers without a clue could easily stay i busiess for five years or loger. He added The atural coclusio therefore is that maager selectio o the basis of returs data (ad league rakigs) is extremely hazardous..this has very soberig cosequeces for the mutual fud idustry, where typically the oly iformatio i the public domai i the returs data track record. The aalysis from this paper provides coclusios that are cosistet with those arisig from Becker s simulatios, i that they show performace figures over shorter periods of time ca be poor idicators of uderlyig Portfolio Maager skill. 8. Fudametal idexes Somewhat surprisigly fudametal idices are a relatively ew cocept. The 24 paper Fudametal Idexatio by Rob Arott, Jaso Hsu ad Philip Moore itroduced the cocept of o-capitalisatio weighted idices. The paper says The geesis of our o-capitalizatio weighted market idexes stems from a cocer that market capitalizatio is a particularly volatile way to measure a compay s size or its true fair value. If so, capitalizatio weightig may lead to sub-optimal portfolio retur characteristics because prices are too oisy relative to fudametals. The paper by Arott, Hsu ad Moore measures a firm s size by: Book value Trailig 5-year average cashflow Trailig 5-year average reveues Trailig 5-year average sales Trailig 5-year average gross divided; ad Total employmet. The aalysis also icluded a composite measure, equally weightig book value, cashflow, sales ad gross divided. No divided payers were treated differetly to low divided payers. 2
The followig table shows that the aual returs of the fudametal idexes were o average 215 basis poits higher tha the equivalet capitalisatio-weighted idexes. The results were over the 43 year period 1962 to 24. The followig table shows the performace of the Fudametal idexes as at February 28. Source: http://www.researchaffiliates.com/rafi/performace.htm It seems that the costructio of fudametal idexes based o idicators of value may lead to out performace whe measured agaist market capitalisatio weighted idices. This may reflect the disciplie of measurig ad maagig the fudametal idex based o itrisic value criteria. A compoet of this out performace may be a liquidity premium where stock prices are impacted by large buy or sell orders i the market which ca be captured by approaches focused o value based measures rather tha market capitalisatio based measures. The factors used i the costructio of these fudametal idexes are relatively crude. For example, they do t explicitly take ito accout a compay s competitive positioig or expected log-term profit margis. Solid ivestmet aalysis should allow a ivestor to 21
improve o the assessmet of true fair value used i these fudametal idexes. If so, out performace should be eve further ehaced by fudametal aalysis ad portfolio costructio adoptig the disciplies ivolved i the costructio of fudametal idexes. 9. Coclusio Whe a ivestor is faced with the results of a uderperformig Portfolio Maager based o share price movemets, the ivestor eeds to decide if the uderperformace relates to bad luck by a skilled Portfolio Maager, bad luck from a uskilled Portfolio Maager or just share price volatility which has created a buyig opportuity for a skilled Portfolio Maager. The ivestor should have a differet reactio to each of these reasos for uderperformace. If it is bad luck from a skilled Portfolio Maager the the ivestor should stick by the Portfolio Maager; if it is bad luck from a uskilled Portfolio Maager the the ivestor should exit (subject to caveats such as tax); ad if it is due to share price volatility with a skilled Portfolio Maager the the ivestor should add to their holdig as the Portfolio Maager s fud is ow cheaper. Similarly, whe a ivestor is faced with the results of a outperformig Portfolio Maager based o share price movemets, the ivestor eeds to decide if the outperformace relates to good performace by a skilled Portfolio Maager, good luck from a uskilled Portfolio Maager or just share price volatility which has boosted the performace of a skilled Portfolio Maager more tha justified by their skill. Agai, the ivestor should have a differet reactio to each of these reasos for outperformace. The outperformace of a uskilled Portfolio Maager provides a great opportuity to exit (agai subject to caveats such as tax). The reactio to the outperformace of the skilled Portfolio Maager is more difficult ad would deped upo the situatio. If all skilled Portfolio Maagers were equally skilled the the ivestor should reallocate fuds from the skilled Portfolio Maager with the lowest ratio of PIV / PM to BIV / BM to the skilled Portfolio Maager with the highest ratio of PIV / PM to BIV / BM. If the skilled Portfolio Maagers have differet levels of skill that also eeds to be take ito accout. For the ivestor to make these importat decisios they will eed to be able to differetiate the reasos for the uder or outperformace. This requires a aalysis of the Portfolio Maager s ability to grow PIV i excess of the growth i BIV. It may be possible to assess this qualitatively (eg. askig the Portfolio Maager to explai their ivestmet decisios ad assessig if the explaatios are well fouded ad logical). I additio, as this paper has discussed, Portfolio Maager skill could be assessed quatitatively by measurig idicators of the growth i itrisic value of a portfolio versus that of the bechmark. Ivestors commoly measure the key fudametals (ie. PE, divided yield, ROE, price to book) of ivestmet portfolios, but there seems to be a lack of fudametal aalysis of Portfolio Maager s skill as defied i this paper. This may partly be due to the relative ivisibility ad difficulty i calculatig PIV ad BIV - but that does t mea that it is ot worthwhile tryig to estimate these factors. This is especially the case for Portfolio Maagers themselves, as it is their role to maage the growth i PIV for their ivestors. The disclosure of performace attributio ito its three compoets would assist cliets of Portfolio Maagers i better uderstadig the level of skill of that portfolio maager. That said, Portfolio Maagers may be reluctat to publicly disclose potetially competitive 22
iformatio such as the assessed itrisic value of their ivestmet holdigs. Udue emphasis o public disclosure may also chage ivestig behaviour ad may lead to over estimatios of itrisic value by Portfolio Maagers i attempts to justify poor ivestmet decisios. That said, measurig is a first step i maagig ad I hope this paper is a step alog that road of ecouragig a greater focus o the key compoets of Portfolio Maager skill. Refereces Arott R, Hsu J, Moore P, 24, Fudametal Idexatio, Fiacial Aalysts Joural, 61, 2, 83-99; http://www.researchaffiliates.com/ideas/pdf/fudametalidexatio.pdf ASIC, September 22 (revised Jue 23). A review of the research o the past performace of maaged fuds http://www.asic.gov.au/asic/pdflib.sf/lookupbyfilename/fmrc_report.pdf/$file/fmrc_ Report.pdf ASIC, July 23, ASIC guidelies: usig past performace figures i ivestmet ads ASIC, August 26, ASIC cocered over misleadig use of past performace iformatio i ads, Beckers S, 1997, Maager Skill ad Ivestmet Performace: How Strog is the Lik?, The Joural of Portfolio Maagemet, Volume 23 Number 4, Summer 1997 Berstei W, 26, Efficiet Frotier, Fudametal Idexig ad the Three-Factor Model http://www.efficietfrotier.com/ef/adhoc/fi.htm Buffett W, Jue 1996 (updated), Berkshire Hathaway, Ower Related Busiess Priciples http://www.berkshirehathaway.com/owma.pdf CFA Istitute, February 25, Global Ivestmet Performace Stadards (GIPS) http://www.cfapubs.org/doi/pdf/1.2469/ccb.v25.5.42 Fama E, 1965, Radom Walks i Stock Market Prices, Fiacial Aalysts Joural, September/October 1965 (reprited Jauary-February 1995) Fog K, Gallagher D, Garder P, Swa P, April 24, A closer examiatio of ivestmet maager herdig behaviour http://wwwdocs.fce.usw.edu.au/bakig/semiar/24/peter%2garder%23.pdf IdexIvestor, Will Fudametal ad Divided Weightig Deliver What They Promise? http://www.idexivestor.com/free/fudametaldivided.php Idex Uiverse, 27, Fudametal Idexig Smackdow, Rob Arott, Gus Sauter, Jeremy Seigel, August 27 http://idexuiverse.com/compoet/cotet/article/6/2995.html?issue=117&magazieid=2 &Itemid=11 Margolis D, New York Uiversity Leoard Ster School of Busiess, Market Efficiecy Defiitios ad Tests http://pages.ster.yu.edu/~adamodar/new_home_page/ivemgmt/effdef.htm 23
PIMCO, Jue 25, Rob Arott Discusses the Fudametal Approach to Stock Market Idexig, http://www.pimco.com/leftnav/product+focus/25/arott+fudametal+idexig+itervi ew.htm Research Associates Fudametal Idexatio; http://www.researchaffiliates.com/rafi/rafi.htm Warig M.B, Ramkumar S, 28, Forecastig Fud Maager Alphas: The Impossible Just Takes Loger, Fiacial Aalysts Joural Vol 64, Number 2, March / April 28 24