hello I'm Andrew low and welcome to the project on the pursuit of the perfect portfolio today I have the pleasure and the honor of speaking with Bill Sharp the originator of the capital asset pricing model and the person who many believe to be the founder of passive investing and what many of us now engage in on a daily basis with our own portfolios Bill thank you very much for joining us today my great pleasure Andy to be with you so I would like to start by uh getting your thoughts on where passive investing is today
and how far it's come because uh uh back in the 1960s uh we saw the beginning of passive investing with uh John Bogle of course but actually Bogle gives credit to you and Bill fa and John mcquown so can you tell us a little bit about that time and uh how it really came about from the conception of your ideas of passive investing to actual implementation well I my recollection is that there was uh Roger ibbitson and Rex singfield had a a venture going with a bank in Chicago I can't remember the name of the
bank uh which was more or less at about the same time as the Wells Fargo Venture I actually started with another group that was going to do an index fund um but the business side didn't work out uh and that would have I think preceded the Wells Fargo um the um Wells Fargo Venture uh I had a little role in that uh other than from my academic work I had a call from a chap who was the son I believe of the head of Samsonite luggage company who had just finished an MBA at Chicago and
had been studying the academic literature and he said uh really like to get something for the I think it was for the pension fund for the company uh that was more consistent with you know equilibrium ideas Etc and um so I put him in touch with Bill fa whom I knew personally and the original design I believe for that fund was to be an equal weighted Market portfolio but cooler heads prevailed and I think uh and it became a cap weighted let's call it well in fact I think that according to uh Bill fa uh
it was 100 uh nysse stocks initially that was equal weighted and was rebalanced once a month and apparently it was a a nightmare to administer because of that Trading uh yeah that's correct I think they they realized this this was difficult to implement and of course it was inconsistent with the theory MH and then M mown uh had been was at that time still I think the head of sort of an operations research group at Wells and so he and Bill in various combinations brought about the uh the first you know serious major Index Fund
I guess you'd say now this was 1969 71 around I have to trust your memory cuz I don't remember the exact date so what strikes me well no it happened to no it must have been a little later because I was at Stanford at the time it was possibly in the SE 70 maybe 71 time perod but what's amazing to me is that your thesis was in 1961 so this was just a few years after your thesis that these ideas were implemented a really fascinating read because the first few chapters uh were applications of portfolio
optimization and you give a lot of credit to Harry marowitz for uh working with you he was at the Rand Corporation at the time but the last chapter of your thesis uh chapter five was on a positive theory of security Market behavior and that's when you decided to take all of the portfolio optimization and ask the simple question uh not so simple back then but certainly simple in retrospect what would happen if everybody behaved this way and of course we've got the capital asset pricing model to thank for the outcome of that uh thought process
um how did you come upon that I I mean that just seemed like something that was really quite a remarkable set of insights that came out of nowhere well um let me back up a little I had actually started a dissertation on uh internal transfer pricing using all kinds of operations research tools which I thought was really quite good and um building on the work of Jack klier it turned out Jack came to UCLA about the time I was I thought halfway through my dissertation and so Arman Alin my adviser said well why don't you
go talk to Jack klier and I did and I gave him the chapters that IID finished and went back in a week and he said I don't think there's a dissertation here so I went to Fred Weston who was also my adviser in uh big influence on me and said what am I going to do Fred and Fred said well remember in the seminar you really like the work of the sky marcoz and I think he's just come to Rand where I was at the time let's go to talk to him so I introduced myself
to Harry and we chatted for an extended period of time and basically Fred Weston Arman Alin on the faculty at UCLA made a deal that Harry would in effect be my dissertation adviser although he was not on the faculty so Harry was very much a big influence and to your question um there were three basic pieces to that dissertation it was all predicated on uh what I like to call the single index model of security return formation uh which was in Harry's book uh or I sometimes call it the diagonal model first one in any
event I I developed an algorithm that could very efficiently solve a problem in that special case a general portfolio Theory portfolio optimization problem and second chapter at Fred's urging I worked with an actual human financial advisor try to capture his predictions probabilistically and then do the efficient portfolio thing and we could talk about that separately but then in the third and uh so the first was pretty much Harry's idea that I should try to do something in terms of efficient algorithms second was Fred's idea I should try this with a human being and the third
was just it it wasn't really armen's idea I don't believe but it was just what he had taught me to do uh as you know microeconomics is you make a model of say how firms behave and how individual consumers behave and then you build a a theory or a model of what would happen to prices in a marketplace where you have these actors doing their thing so I thought well you know that's what a microeconomist would do and and here we have a theory about people dealing with probabilistic outcomes uh ala maritz and let's let
me just think about what if everybody did what Harry said um what would happen to the prices of Securities and what would that imply for expected returns and risks but in the dissertation it was all predicated on this single model one factor if you will a return generating process and then to to finish that story um I went I finished the dissertation in June started the University of Washington in September and thought this is a really great result I wonder if I can generalize it and so I spent several months trying to figure out how
to do it without sort of putting the rabbit in the Hat was there a way to pull the rabbit out of the Hat without putting it in to begin withh and I figured out yes there was so you know your thesis was interesting in a number of respects one because it was actually working on a topic that wasn't particularly popular in economics at the time isn't that the case it really wasn't in economics uh well Fred Weston had been trained as an economist and then had taken a position in basically Corporate Finance um at in
the business school at UCLA I took a field with him although my my work was in economics and I was his research assistant one of many as well and he had been bringing and and others were just beginning to bring economics into uh Finance but it certainly was n there wasn't much economics in finance and there wasn't much uncertainty right in economics at that point arrow and de Bru's work came later MH and your thesis was interesting in that it took Theory and actually applied it as well so uh I noticed that in the appendix
you actually have Fortran code I do I do which I can understand actually I'm one of the few uh but uh it was actually I think it was for too at the time and and it was it was very applied at at the same time it was also extraordinarily theoretical it was really the the both extremes were represented that must have been unusual as well wasn't it at the time well I think that probably reflected the fact that I was at the Rand corporation uh at Rand although I was not a programmer MH uh we
were all the people doing the basic the research were encouraged to learn programming and in order to be able to better work with the real programmers right and so I took internal classes on programming and uh absolutely loved it and uh so and I I loved algorithms uh as well and so and that was the era in which operations research we thought was going to save the world so brand was just a hot bed of operations resarch and computer science and um we had some very powerful for the day equipment and um so I became
hooked on programming I even created a programming language and wrote a compiler and you know you know we can talk that's the dark side of my life I suppose I still program almost every day so you know we noticed that in your thesis uh you mentioned that the analysis was for 96 stocks uh and that it cost $300 of programming time on the Mainframe computer at the time to run that analysis to be perfectly Frank I ran it at Ram so it was free I see for me but it was an an IBM 709 I
believe it was or it could have been a 704 um and uh but that's what it would have cost commercially right um and yes I mean my algorithm which today you know yawn but uh it would have saved an awful lot of money at the time yes it was it was a totally different world and you had to do key punch cards I was so good because I did all my own key punching and all my data I was so good at Key punching I figured if things didn't go well in the economics business uh
or Finance business I could always a progam no a key punch Operator Operator really good so the the capital asset pricing model has as one of its main features the importance of the market portfolio the tangency portfolio um and again that's one of these ideas where after the fact after you understand it it seems so simple and obvious but beforehand nobody really understood any of it and the role of systematic versus educ syncratic risk so to me that really is the heart of passive investing it's the fact that you've got this passive portfolio that actually
provides some really incredible opportunities for investors to set their portfolios on automatic pilot um what's your sense of how quickly that idea was adopted because while Wells Fargo and the Samsonite Corporation were you know leaders and Pioneers it took a while before John Bogle was able to take that idea and turn it into the Behemoth that we now know as Vanguard well um I guess there are two two sides of that one is how long did it take the Prof the economics and finance profession to sort of become interested in the theory MH and then
there was how long did it take the industry to become interested in in the Practical implications um I remember the uh capm article which went around through a refereeing editorial process for 3 years uh finally was published in ' 64 and I knew at the time and I'm sure I was right that was going to be the best paper I ever wrote and U you nothing is has convinced me of that that I wasn't right about that and so the question was how good was it and so I sat by the phone we didn't have
email then waiting uh for the phone to ring or people to send letters and nothing zero notada uh finally after about a year people started paying some attention to it um and I was focused more than on the adoption by of the ideas by the the profession academic profession um but that took a while but once that got started you know there was a lot of lot of activity for and against and um but the U the implementation was just glacial it just took forever um because you know it sort of went against everything people
in the investment industry did um there was even an ad taken out by somebody a full page ad in one of the Investment Bank trade magazines uh professional magazines with an Uncle Sam uh saying indexed investing is unamerican really yes yes indeed oh yeah uh may I tell one other anecdote please because there was sort of two aspects of this uh there was also the idea that um that you know it was really dumb to just buy everything in Market proportions that you needed intelligent people doing research Etc and so there was the whole random
walk movement out of MIT mainly Paul 's book with that name Paul who uh was at one point addressing 500 Securities people in New York after the random walk book had come out and the person who introduced him was a leading person from the industry and he said uh as he finished the in I have one question for you Professor cner if you're so smart why aren't you rich and of course I got a big Applause so Paul went to the podium and said said well I have one question for you whatever his name was
if you're so rich why aren't you smart thereby setting back the academic professional interaction by at least a decade but but there was there was huge resistance in the industry to the idea that it could possibly be that simple and and and and a lack of understanding that that was an implication of of people in the industry being really smart at least enough of it being smart but it went against all the commercial interests of almost everybody sure well the 1960s and70s in in the uh investment industry was the era of the Gunslinger you know
the the the Meltdown right yeah and it seems like your work has really 5050 they were the Nifty nifty50 yes that's right and your work H has really uh in my view democratized investing in the sense that you've taken investing out of the hands of the so-called experts or Gunslingers and you put it into the hands of individual investors people who don't know a lot about investing but can still get a decent rate of return invest for their retirement by investing in this passive portfolio uh I would say yes that's true and that's a good
thing uh it's a very good thing um on the other hand I think it's important to understand that all index funds are not equally socially responsible so as we know a lot of the narrower let me call them index funds uh are being used egregiously for first of all they tend to be expensive and they're being used for day trading and Lord knows what and all kinds of gambling and and bding activity and the other thing I think that that we should always remember is there's a kind of an irony the market portfolio passive highly
Diversified portfolio makes sense only to the extent that there are people trying to beat the market keeping prices of individual Securities and sectors reasonably in line with probabilistic forecast let me say it so so there is this this concern we used to be worried a lot I and many others what if there were too many dollars in index you know broad index funds uh I think at this point you know we don't have to worry about that much um the intent to bet and gamble you know and the and the desire uh seems to be
alive and well so so people are still doing some kind of research fundamental research but but it really is important that there be fundamental research and there has to be some sort of reward for at least the people who do the research so hedge fund manager managers do play a role in this ecosystem well I mean it could also be people who build portfolios of industry stocks uh sure I'm not Shing it has sure it has to be hedge fund managers right so um Your Love of software is something that has never left you as
you point out you still program today um I I want to turn out of financial engines because that's an instantiation of Your Love of software and Technology as well as your interest in helping investors so can you tell us a little bit about that and how that came about sure let me give you a little bit of a backstory in the uh prior period uh my wife and I actually uh had a research and consulting firm um working with institutional investors Pension funds endowments um um helping them with what they did and uh for whatever
for personal reasons and and other reasons it seemed I did go back to academics and it seemed to me that we were beginning this shift from institutional investing for retirement in particular uh to find benefit plans where the investment was done by professionals if you will at at the corporations and employers to um individuals being responsible for their own investment 401K plans Etc and uh so I decided to shift my research in that direction uh sort of declare a victory the other front where I've been working for a long time and um work on the
problems of the individual choosing Vehicles offered by the employer Etc and I was doing that uh in straight academic mode I was writing programs putting them on the nent then nent web Etc and um colleague of mine uh in the law school um it was Securities Joe gruntfest been on the SEC and I were having coffee and and he gave me a long song and dance about how if I really wanted to impact real people making these decisions we needed to form a firm Etc so that was sort of how Financial engines began and so
he introduced me to a fellow who was a lawyer who also could start help start firms and um Craig Johnson so the three of us basically created Financial engines and the goal was to help individual employees better use the 401K plans that were available to them for retirement savings and and that and and of course the idea was to apply all the work that had been done in the academic Finance field um which we set about doing so that uh company's quite successful today but it it was a slowo at the first wasn't it it
was of a challenge to get people to understand how to use the system uh oh yes um there's a case that was written uh by I think someone at Harvard um about that and and uh it was really very simple you just have four different business completely different business plans and then on the fifth it clicks so we tried retail we tried online we tried this we tried that until um we finally hit on what at least at that time was the um the appropriate venue which was to provide all the software online and offline
as needed to all the employees of a large employer um and then uh make individual accounts with individual management available to any of those employees who wanted to go beyond what was provided by the employer to to all the employees and and so so the sort of like textbooks uh they're used by students but you sell to the professor and our service was used by the employees right but we sold to the employer yeah and it's been quite successful I understand it's it has it's uh I'm I'm long since retired from the company so so
I don't have any insight as to details now other than what's publicly available but um yes it's it's depending on the day of the week it's a one and a half or A2 billion do public company it's fantastic and so and I think they have under management if something like you know well it's it's it's very large it's the largest registered investment advisor in the US right so it's been very gratifying and you've been thinking about how investors look at their Investments for quite some time in fact in your thesis you actually had some work
on subjective probabilities and preferences and uh your Princeton lectures were focused on looking at U ways of modeling preferences and uh what do you think the biggest challenges are for a typical investor uh because you've spent a lot of time thinking about the the ordinary individual not the finance Professor but uh people who don't have any Finance background what are they up against well the um it's you know perhaps jump ahead it's it I and many others focused for many years on what we call the accumulation phase M you're saving for your retirement and and
while that was difficult because it was a multi-period problem on Route we could sort of take a shortcut and say well what you care about is the probability distribution of your wealth on the day you retire M and and we could sort of stop at that point so at least you know there were m multiple periods getting there but at least there was one distribution that was the U object of choice uh or of analysis and um and and of course if you leave aside issues like human capital and some other things you could argue
and we'll talk later about perhaps about the perfect portfolio that the investment decision was really pretty simple if you had access to a truly Diversified true broad Market portfolio you just divide your money between that and something low or very low risk either low real you know low real risk or possibly low nominal risk now in a 401k plan you don't have that luxury you have to work with whatever the investment vehicles are that the employer makes available so that's a more difficult problem um but you know you could say well we could characterize your
preferences by some measure of risk aversion Vis the money you have the day you retire MH and that's a one parameter kind of thing and that's that's that's helpful I'm now devoting my effort to the decumulation phase what do you do after you retire or on the day you retire how do you allocate money and investment Etc uh over the years you have left with whatever they may be that's a much much much harder problem why is that oh well let me count the ways first of all you don't know how long you're going to
live or how long your wife or partner is going to live and um second uh you know there are many alternative investment strategies even though they may ideally all have some Market base but they don't have to be just the market and something riskless and and third we really don't know what people's preferences are you know we have ways of of modeling that um that make some assumptions that are pretty much inconsistent with a lot of the behavioral literature even more so than the ones we've been doing on the accumulation phase so it's a very
very difficult problem M um you still I think can structure it so you choose what I call a riskless asset and a market-based portfolio which is something that has only Market risk but not necessarily the broad Market portfolio um and so so it's a very difficult problem and um but you can certainly you if you're so inclined cut the investment Alternatives down to reasonably small number uh by assuming some kind of an equilibrium model MH in the the accumulation problem and the accumulation problem really you kind of need a multi-period equilibrium model not the one
period kind of capm but that's not horribly hard to get given the popularity of apps and Robo advisors do you think there's a possibility that we'll actually be able to automate some of these decisions because uh uh the first phase of the democratization of investing is what you and other Pioneers did uh in the 70s and 80s uh but now is there a second stage where we can take what you did at Financial engines and really uh scale it so that uh we put these uh kinds of autom ated tools in the hands of typical
individuals well I'm not sure I was at a conference and somebody asked me about Robo advisors it was the day that Schwab announced they were going to do it something in the area and uh and somebody mentioned you know said well Financial engines is a robo advisor to which I said I'm I'm not sure that they want to be considered such and fortunately the one of the officers was in the audience so I asked him and he wasn't quite sure at that point although right I there's a tendency in the trade literature to refer to
financial engin as a robo advisor um and certainly they use a lot of Technology right in the advice but they have human beings too um but yes I I certainly think much more can be done although I'm a little Disturbed I I I haven't looked at many of them but I looked at one which would be NE remain nameless where I happen to know a lot of the principles of the new retail let's call them Robo advisors M and they they have all of their um methodology online so you can see absolutely everything and they
use lowcost index funds I mean it's it's you go right down the line yes yes yes yes that's that's that's what we all have advocated but then if you dig deeply you find and they even use what I used to call reverse optimization where they they get a covariance matrix and they get expected returns by assuming the market is portfol portfolio is efficient so you back out expected returns which would be consistent with equilibrium so sort of a capm thing sure and thus far you know yes yes you know good for them uh and then
it turns out they put in some quote views and use a procedure build on reverse optimization that fiser black and Bob litterman developed to mix views of sectors in their case like value stocks small stocks sectors that they think are better than they should be or worse than they should be as an investment and then they back out adjusted expected returns and then their advice is predicated on those yeah um and so uh I was with them until they did that you know and I don't know if if there are some of the others that
that that just do everything they do and stop before that that latter stage but but it's it's so again the issue is do you really want to you know make bets according to somebody's beliefs about markets being out of whack and in the old days it was on individual stocks and bonds and now it tends to be on sectors or you know value stocks or grow stocks or big stocks or small stocks or you know chemistry stocks versus whatever and um there been what I consider a perversion of the index philosophy with all these narrow
ETFs with Incredible turnover MH um so I don't know whether it's better to do a high turn over betting on sectors hedge funds of course are the extreme case um or in the old days where you bet on you know this utility versus that utility and you sat on them but but I don't Advocate either and and I think you said expenses really matter uh I think it's it's it's really important to understand that an absolutely abhorent amount of money is being transferred from all ordinary individuals trying to save and finance their retirement in particular
to the financial industry I mean there's just so much needless expense uh for which they're getting nothing uh of any real value and uh if you look at the retirement income area now as increasing numbers of people are coming to their retirement was serious amounts of money to invest didn't used to happen because we had didn't have toine contribution savings plans um every part of the industry and parts that you wouldn't even think of as being in the finance industry are trying to get a piece of that that pie and they're offering uh they're very
good many of them are very good behavioral analysts they know how to create a product or a service that sounds just great right but ends up sucking a huge amount of the value out of these retirement savings and and I find that you know absolutely scandalous and I think it's the finance industry in the academic part of the finance field we've got to somehow or other educate people so they're not suckered into these uh systems that play to people behavioral Tendencies need some anti marketing market and give them give them something that is just not
appropriate that's my crusade well so we're getting closer to the uh the the bottom line question for all of these considerations which is uh what you consider to to be the perfect portfolio uh the $64 trillion doll question I guess um in preparation for that um let me get a sense uh from you as to whether or not uh the financial crisis of a few years ago has changed your thinking at all about how people go out investing uh has the uh has the crisis really caused you to rethink any of the basic principles of
uh financial management um probably far less than it should have um I mean all of the theory is predicated on best estimates of probability distributions of future outcomes MH uh not frequency distributions of things that happened in the past M and uh so you know uh who knows what the best probability distribution was just before the Meltdown MH and whether that was a two Sigma or three sigma or five Sigma event um and so you know I don't I do um I think it's important that people understand that really bad things can happen you know
that it uh I think perhaps we were being some were being led into a sense of well we've got all these wonderful things in place we couldn't have a replay of the Great Depression MH uh or at at least the stock market side of it um but no I I don't think so I mean I I uh I think you might worry about what probability distributions you use but sort of the theories have always said you know given a consensus view of the probabilities of different things happening in the real economy prices will be set
thus and so and this will there will be this relationship um and um all the tests of course most of the empirical tests have implicitly or explicitly assumed that at each point in time people assume the future would be like it was over whatever historic period you're using for your empirical analysis um that's a very very large assumption and and you know if I can say we theoreticians never assume that you know many of us including my limited empirical work said well let's kind of see if that if historic outcomes are a reasonable proxy for
what people thought at each point in time during the historic period uh and and see if there's any consistency with our theories but um that's a big assumption sure and if if if you don't pass that test then some would say we haven't I'm not sure that means you throw out the theory right okay so with that in mind uh what would you consider to be the perfect portfolio well strange you should ask because uh I'm I'm now working on a book in this retirement income area MH and uh so there came a point at
which I had to I had to answer the question um and so I went I've said this in print for many many many many years decades um ideally it would be a combination of a riskless real portfolio something like tips or something where index to inflation right yeah uh and all the tradable bonds and stocks in the world in Market proportions MH and um what I calling at least at the moment the world bond stock fund let's call it mhm and so the question was then all right if and I sort of maybe invest in
something like it but not very much like it probably certainly passive but um so uh and I certainly have the tips but so then the question was all right if you really wanted to invest in this thing today given what's available what would you do so I looked at various uh index funds ETFs with a very very careful eye on expense ratios because expense ratios as you know they can add up can add up hugely and um so I ended up with and I actually in July I invested in this I I put a some
of my money uh in this exact portfolio um and what is it well it it has four component and this is partly it would have three or two or one ideally M if the index fund industry would give us the vehicles M and I have been badgering my Joel Dixon and others at Vanguard for many many years to actually create this fund uh for us uh and um but they haven't yet nor has any as far as I know anyone else so it has four components and the reason it's four is the fees are lower
if you use these four than than some mother and they all they all happen to be Vanguard M um you could come close with Schwab or Fidelity MH um and uh they are a US total stock market fund a non- us what amounts to axy for total stock market fund mhm um a US Bond Total Bond market fund and then a non us total bond market fund now I should say the uh the non- US bond fund is currency hedged and I'm I'm not sure how I feel about that but it is that's what it
is and there aren't many that fit that that are not currency HED and I'm not sure that may not be a good idea but I I don't have a full I think I could build an equilibrium model where that would work if everybody held currency held portfolios um but I haven't thought that through um and um so those are the funds and then the question is how much do you puts and how do you keep them up to date as it were uh it turns out that the two stock funds have indices you know they're
they track indices for which the providers publish market caps and these are all float adjusted by the way so they don't include bonds held by the fed or the European Bank CCB etc etc um and uh so so in the case of of the non us it's a footsie index footsie publishes market caps for their indices every month in about 7 to 10 days after the month end uh for the US it's a crisp index and that's public they publish quarterly few days week or two 10 days after the end of the quarter and uh
but fortunately the bond funds are indices they're Barkley's indices Barkley does not publish market caps right uh if you want to spend $2,000 and get a license you can probably get them but but ordinary people can't so for those I use other indices um I think one's the City Bank index and can't remember what the other one is maybe they both are I think they both are where you can get market caps and so the idea is that as soon you after the end of the quarter you start looking at these sites until you get
all your market caps for the four and then what you do is you look at last night's value of the funds and compare them with the value at the end of the quarter if 10 days ago let's say and then you sort of do an adjustment okay and then you rebalance I've only rebalanced this once uh and uh I only had to move about was about a third of 1% of my money oh uh to rebalance it but that's on a quarter that's one quarter but hopefully it'll be a low turnover okay there're also you
can also get a feel for this um footsy has um a tool that's available publicly for playing with quote adaptive asset allocation which is a procedure which I wrote about in an article 3 or four years ago MH and you can play around with that using some of their data right so that's something that a robo adviser might be able to do is to help adjust the we if I can do it a robo advisor can do it oh yeah but I mean but but but hopefully Vanguard will or Fidelity or somebody or Schwab will
put them out of business on that that part of it by just doing it sure exactly I mean I mean it would be so easy you know for anybody to create a fund of funds out of those funds right um and adjust the weights for you MH and um and then you mix that with tips MH no you know and and yeah voila you got it you're done terrific that sounds and it's just a matter of how you wait it with the tips now uh your equilibrium theorist will tell you now wait a minute if
a bunch of people are going to hold that plus tips how are the markets going to clear MH um and uh you you can you can build a story in which you know and there are also government bonds you have to worry about that but in some sense young people you know young people um are on the other side of that right they're the issuers of those government bonds they're going to have to pay up right so so you can argue that that old people are on one side of that deal and young people are
on the other and then you get a market equilibrium okay so you really are a little that's very casual Theory think about the big picture yeah I try to I try to try not to be demonstrably inconsistent with a a larger worldwide market equilibrium story right so stocks and bonds seem to be really part of your overall portfolio what about other asset classes like uh real estate or natural resources um well first I I would point out that in in that stock and bond portfolio you've got a lot of exposure to real estate you've got
REITs right you know for the real estate you've got the real estate held by insurance companies you've got the real EST of you know every Retailer's you know store uh and possibly land so there's a lot of lot of real estate in there um and private Equity yes uh it would be nice to have sort of a way to get a piece of that um unicorn startups and Silicon Valley yes we're beginning to see a little bit of those private shares sort of held by by uh mutual funds although they tend not to be in
the indices um but uh individuals have their own Holdings of real estate if you own your house of your human capital in your job if you're in the tech industry you've got some human capital in the tech industry so yes it would be nice to have broader exposure uh to some things that are not on public markets but some other that doesn't keep me up at night maybe it should right well on behalf of all investors around the world I want to thank you for your incredible theories uh and the implementation you've really transformed financial
markets uh and you've helped investors secure their financial Futures and uh really appreciate your spending time with us they did tell us about the perfect portfolio I would thank you and just say one more thing to the individual investors who might be watching that's how you invest but you got to save enough first and most people many people are not right that's actually a very important Point any ideas about how to go about doing that that sacrifice um I mean the numbers are staggering when you look at longevity uh and just do simple calculations yeah
you just got to save an awful lot um because nobody else is going to do it for you except Social Security right and um while some of us might wish to have more generous Social Security especially for at least for lower income that's probably not going to happen right another challenge well hopefully you're continuing to work on that for the rest of us I am I'm writing programs okay great thank you very much Bill we appreciate pleasure thank youen