April 3, 2024 • 37 mins
Unlock the secret to smarter investment decisions as Steve Davenport and I celebrate the groundbreaking and Nobel-winning work of Daniel Kahneman, the father of behavioral investing.
We dissect the intricate dance of human biases and investment decision-making. We bring Kahneman's legacy vividly to life, as we delve into the ways in which his psychology-rooted insights—particularly regarding loss aversion—continue to mold our financial pursuits and quest for happiness.
Picture this: your ancestors, primed for survival, have passed down instincts that still dictate today's economic behaviors. We navigate through these prehistoric impulses and their impact on our responses to modern crises, such as the recent pandemic. We also consider how AI might play a future role in management of our economic behaviors.
This episode is a compelling narrative that stitches together the fabric of our decision-making processes, from the stock market to retirement planning, revealing the often overlooked influence of behavioral economics on professional and retail investors alike.
Ending on a note of self-reflection, we embrace the concept of a utility function for happiness.. This episode is not just a journey through the mechanics of wealth accumulation but a guide to aligning financial decisions with personal contentment.
Straight Talk for All - Nonsense for None
Please check out our other podcasts:
https://skepticsguidetoinvesting.buzzsprout.com
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Clem Miller (00:03):
Welcome everyone to Skeptic's Guide to Investing.
I'm Clem Miller and today we'regoing to talk about the recent
passing of behavioral economicslegend Daniel Kahneman.
Steve Davenport and I will diginto the research which Daniel
focused on and its ongoingeffects as investors.
Where do you start with?
(00:23):
Daniel Kahneman, Steve?
Well, I start at the beginningand as an Israeli born
psychology professor, he wasreally doing some interesting
work and he became friends withAmos Tversky, also a
psychologist, and it really is alittle bit unusual when you
(00:44):
talk about someone who wins aNobel Prize in economics because
he's never taken an economicsclass.
I think that his work tells mea lot about similar things that
we noticed when we discussed thelife of Charlie Munger.
I think that you know you startwith some of the accolades.
(01:05):
He won 23 honorary doctoratesin the US and around the world,
including one at your universityin DC, Clem.
He was the 2002 Nobel Prize inEconomics and his real
interesting part of what he didwas to just question some of the
(01:29):
underlying assumptions thatpeople make about behavior and
behavioral economics.
He's thought of as the father ofbehavioral economics.
He really was interested in,first started studying hedonism
and happiness and tried to thinkabout how these things could be
measured and how these thingscould be standardized, so that
(01:51):
you could then go around theworld and try to figure out how
to put the systems in place.
So first of all, I'd say hiscontribution and the way I look
at his life is, he wasunderstanding how decisions are
made by humans and it feels likea very simple concept.
But when you look at us, Ithink that I've always looked at
(02:19):
us as economic animals who willmake decisions that are good
for themselves, based on thefacts and information, but in
reality, humans make a lot ofdecisions that are more
instinctual, more like thecaveman.
So I think that understandingthat basic difference of humans
as unique decision makers reallywas the primary result of his
(02:43):
life's work.
I think, when you look at him,just like we looked at Charlie
Munger and Warren Buffett, heworked for a critical period
with fellow psychologist AmosTversky.
Kahneman and Tversky didseveral papers together on
several topics, and it remindsme of Charlie and Warren because
(03:03):
they both had their owncharacteristics, but they both
figured out how to mesh togetherand work together in a way that
makes the overall product andthe overall result that much
better.
And so, just like you and I,clem, you know, when you team
together two superstars, do youget an additive effect or do we
(03:26):
subtract from each other?
I like to think it's additive.
So I think that one thing thathe introduced is this concept of
bias and how it can lead usdown the wrong road.
When we think about biases, weusually think, well, those exist
for other people.
We're perfect decision makersand we don't make those same
(03:48):
human loyalty type of mistakes.
He then spent a lot of time onprospect theory, loss, aversion
and happiness.
I think that all three of thesethings have a great deal of
influence on what we talk aboutwhen we're talking about
investing.
What are we investing for?
What's the prospect of ourinvestments?
(04:08):
Results in 5, 10, 15 years?
And how does our approachtowards them lead us to better
results or worse results?
And I think the fact that heultimately sits and develops a
national or an internationalstandard for happiness.
Again, the question about moneyisn't should you be doing
(04:31):
something, it's how do you do itin a way that it aligned with
your life plan and help youfurther that happiness goal?
And then the last thing I thinkthat's most interesting about
Kahneman is that in the last sixmonths to a year, we've been
talking about AI and theimplications for investing, and
(04:53):
I look at what Kahneman wasdoing and saying and then I
wonder well, gee, are we correctin the assumption that a man or
human will make a betterdecision than AI will for
investing If we have all thesebiases, are these biases wrapped
up in our personal situationand therefore they're unique and
important, or are they justbiases that we have that really
(05:17):
don't add much value?
And therefore a moreindependent thinker and
programmed to give you optimalresults of the utility function
that is your life, maybe that'swhat we should be thinking.
So I think that his work andhis ideas are something that we
will be studying for the next 30to 40 years wow.
(05:39):
So there's really a lot to chew on there.
And you know what's what?
What I find interesting abouthim is that him and Tversky is
that they started off in onefield psychology and then he
moved into another fieldeconomics and I think some of
(06:00):
our most brilliant thinkers arethose who have are those who are
multidisciplinary.
They might start off in onediscipline and they move into
another discipline, andcertainly Daniel Kahneman was
one of those figures and I thinkas a result you know that's,
(06:22):
you know he ended up winning theNobel Prize right in 2002.
Steve Davenport (06:31):
I think it's a great lesson in terms of we
always think of ourselves asoutsiders.
I've always been an engineerwho was in finance and instead,
you know, you start to realize,hey, some of the fundamentals
and some of the disciplines ofscience, they can be helpful,
they can also be harmful,because the world doesn't always
(06:51):
work according to a set formula.
So I think it's interestingthat he was questioning,
questioning, questioning therelationship and the decision
making process, questioning therelationship and the
decision-making process.
And then we started to get intothe science of what part of the
brain are you using to thinkabout this decision?
And is that part of the braintypically associated with
(07:15):
reactionary decision-making oris it the thoughtful, decision
making part of your brain?
And I think that when wethought of what he started in
the 60s, you know, I don't thinkanybody imagined that we would
get to the level ofunderstanding of the human
genome and other things thatlead us to some of the
(07:35):
interesting work that's going ontoday.
Clem Miller (07:39):
So, Steve, I thought that economic animals,
to use your term, were efficientin their decision making.
My understanding of an economicanimal is that it was more into
(08:06):
thinking that human beings weremore concerned about loss
aversion than about sort ofoptimizing returns, which is, or
optimizing risk, adjustedreturns, to use an expression
often used in finance, a lossaversion.
And also, I've read that youknow, I've certainly read that
(08:33):
people are, you know, asdecision makers, much more
investment.
Decision makers have roughly atwo to one ratio of being
concerned about loss aversionversus u pside return.
So, yeah, that I mean two toone is a big ratio.
So , Steve, once again you knowwhy aren't economic animals
(08:57):
efficient in their decisionmaking?
Steve Davenport (09:01):
Yes, I think we like to tell ourselves that we
are right.
We like to think of ourselvesas having optimized every aspect
of our life, but, as you cantell from my hair the fact I
haven't shaved it's not reallytrue.
Right, if I was alwaysoptimized, I would look, start
(09:25):
to look at things and say we'resurrounded by unique
characteristics that makeoptimization according to some
standard function almostimpossible to apply across
economics, across countries,across different geographies.
Geographies because, you know,an economy that's based on
(09:48):
agriculture is very differentthan an economy based on
technology versus an economythat's, you know, based on oil.
These things all influence whattype of people and what type of
things are going to happen.
I still think of us Clem, andthis is maybe because I've been
watching too many Geico ads, butI'm like a caveman trying to
(10:08):
stay alive.
Food, heat, water those are thethings that matter to me.
We are loss adverse and we goback to that idea that we
survived thousands of yearsbecause we were able to use
(10:30):
rocks, use fire, use wheels, to,make our lives more consistent
and provide that water and foodand and be able to survive in
the environments where, wildanimals would come and take our
food and potentially rip us toshreds.
(10:51):
I think that today we're in avery different environment, but
genetically we have that code inour DNA that's telling us hey,
I don't know where my next mealis coming from, where do I go?
And if it's raining, I get outof the rain.
The rain's not going to hurt me, but I just still get out of it
(11:11):
because I've had thousandsprogramming of years of program.
So I think understanding wherewe came from is really important
, so that when we think aboutwhat we're trying through our
loss aversion technique, we needto sometimes take a step back,
and I personally feel like Imight focus too much on loss
(11:35):
aversion and maybe my ratio ishigher, but I think it really
needs to think about and measureyour internal utility function,
and we are seeking risk forgrowth, and the reason we do
that is that we understand thatinflation and other things can
(11:56):
eat away at the assets we have.
And so I believe that when welook at ourselves as economic
animals, I think we're probablytaking a leap forward, that
maybe we shouldn't all.
We should realize first that weare going to try to survive as
a civilization and thenafterwards we're into some of
(12:19):
the other things in the pyramidof needs and wants.
So I think of myself still as acaveman.
Clem Miller (12:31):
So, Steve, that leads to an interesting question
, which is you know, if you lookback at our recent experience
with the pandemic, you know I'msure somebody you know, some
future Daniel Kahneman, is goingto look back and say and do
(12:52):
some research as to you knowwhether we were approaching the
pandemic as cavemen, trying tobe loss averse, or whether we
were really trying to optimize.
You know my guess whether wewere really trying to optimize.
My guess is not being apsychologist, but my guess is
(13:12):
that we were certainly morethinking about loss aversion
than we were about, you know,optimizing.
You know which would have takenmore more of an economic
standpoint in terms of how wemanage the pandemic.
Steve Davenport (13:28):
Correct.
I felt that we should havelooked around and said what
other countries in the worldhave had these and how have they
handled them?
We should have becomeresearchers on Korea and Japan,
because those two Asiancountries, when they said, hey,
we've got a pandemic, they allput their masks on.
(13:50):
They all, you know, did thesocial distancing.
They did these things that theyhad done before and they were
familiar with.
In the United States we neverhad a pandemic till, you know,
since the Spanish flu in theearly 1900s.
So we just didn't know how toreact and I think, as cavemen,
we said, okay, let's preserveourselves first.
(14:13):
Should we have said, hey, thisis really important to preserve
yourself.
If you're one of thesecharacteristics, I have diabetes
, I'm overweight, I have thesefive health issues those would
have been the people that youshould have taken care of first.
But instead we said everybodyneeds to stay away, everybody
(14:34):
needs to close down.
And I think it was a little bitof our democratic process,
right where we say, look, we'regoing to treat everyone equally,
where we say, look, we've gotto treat everyone equally.
Everyone's the same.
If we disallow freedom for some, we can't disallow it for just
(14:56):
a specific group, and that'swhat makes this whole discussion
about how good are humans atmaking decisions and will AI be
better at the heuristic decisionprocess.
I think it leads to some veryinteresting chat GPT type
discussions where we think wecan put a question in and we
will get an answer that isrelevant.
Where are we making the worstdecisions in our lives?
(15:19):
Is it in health?
Is it in money?
Is it in health?
Is it in money?
Is it in relationships?
I would like to say let'sfigure out what things are going
poorly and then try to figureout how we optimize and minimize
those things.
What things do people do welland how do we maximize those
(15:48):
properties?
I think that what Kahneman doesis he looks at things and says,
hey, you need to watch out forthis, this and this, and I think
that using chat, gpt or AI, itmay be like it's a pardon, you
(16:10):
know, it's a part.
So, since we're out of thecaves, I have to believe that
our loss aversion hurts us andtherefore it's something that we
should all watch out for.
I'm trying to change and tryingto be more patient with my
investing and I hope it.
You know, I hope it has relatedto better results the last few
years, and I hope it continuesto.
I also believe we're a littlebetter at collaboration versus
(16:33):
singular research on an idea.
I believe that there is abenefit from two people sharing
an idea, and I think that when Ilook at condominium diversity
and I look at Charlie and Warren, I kind of believe that there's
something there for everyone.
When you think about ideas, wethink I'm going to go down this
(16:53):
path and I journey down the pathand maybe I go too far before I
ask somebody else what theythink, you know of the journey
I'm going on, and I think itshould be a way for us to put
some guardrails on ideas thatallow them to travel on the
right road towards the rightdestination by having others
(17:17):
collaborate, and I thinkcollaboration is something that
we need to investigate with AI.
I hear about writers who giveAI a topic and then they take
the output and then add theirown special flair to it.
Maybe, that's the way we shouldbe using AI, instead of looking
at the results and say look atus.
(17:39):
We use AI for our summationsand our capsules and our titles,
and we know it's not perfect,so we try to collaborate with it
to come up with some of theadjectives and some of the
common phrases, but we want itto be unique to us and I think
that's the future.
It's collaboration.
(17:59):
It's not just I accept theoutput from chat GPT, I accept
the output from chat GPT.
And then the last item I thinkabout when I think about AI and
(18:21):
this idea of behavioraleconomics is that we need to
start to at least put down onpaper what is the utility
function for happiness.
I believe that everybody youknow when you think about you
know I used a lot of utilityfunctions in my optimizations
for quantitative management andyou know you have alpha, you
have tracking risk, you havetaxes, and you combine that with
any other frictions, liketrading costs, and that's how
(18:43):
you try to optimize yourportfolio, like trading costs,
and that's how you try tooptimize your portfolio.
And I believe that when wethink about happiness, we've got
relationships, we've got peoplewe care about, we've got health
, both mental and physical, andthen I think that all of our
efforts should really be on.
(19:03):
Am I doing enough for myself ina way that's going to give me
the economic, health andrelationship benefits to
optimize who I am and how I doon this journey?
So the longest journey startswith a step and I agree you
should still make that step, butI'm thinking about
(19:23):
collaboration, and avoidinglosses helps you to focus on a
measurable result.
Clem Miller (19:31):
So, Steve, what would be your biggest bias?
And then I'll tell you mine.
You go first.
Steve Davenport (19:41):
I think that we are all products of a very
imperfect education system andan imperfect support system in
the classroom and at home.
And I think your IQ, yourintellectual quotient, your EQ,
(20:02):
your emotional quotient and yourphysical quotient all are
unique parts of who you are, sothey lead you towards biases
when we needed biases to help usevolve, and I think that today
we still need biases to help usevolve, because I believe that
what will come out of COVID willbe this realization that
interaction and socializationare a bigger part of our life
(20:25):
than we ever realized and thatby isolating we created more
depression and more instability.
But it's hard to look atbecause it doesn't show up on a
list of diseases or a list ofyou know, ailments.
But I think loneliness will bethe thing that will come back as
one of the biggest byproductsof COVID.
(20:48):
And for your original question,my answer would be loss
aversion.
I think that I tend to lookminimize, minimize, minimize
that loss aversion, and I needto probably be a little more
thinking about my returnoptimization.
Clem Miller (21:04):
Yeah, I guess my biggest bias would be I look
around and I get excited aboutnew themes, new opportunities,
and I purposefully try my verybest to stay rational when there
(21:28):
seems to be excitingopportunities out there.
And so you know, you've noticed, you know, my skepticism about
things like, you know, bitcoinor AI or renewable energy or ESG
.
You know these things, you know, have some excitement for me,
but I think that you know, someof that excitement is really
(21:49):
irrational and I have to pullmyself back and restrain myself
and, you know, stay true to somedegree of uh, of process, uh,
you know, using quantitative andto some degree qualitative, but
not, you know, not get myselfuh over my skis and thinking
(22:10):
about, you know, and getting tooexcited about themes.
Steve Davenport (22:14):
Yeah, I think that we talked about sector
neutrality and we try to besector neutral for that very
reason.
If the S&P is, you know, 30%,25% in technology, and you look
at it and you say I got two anda half percent positions, that's
10 to 12 positions, okay, youhave to make some.
(22:37):
You know you can fill in thefirst five or six probably
pretty easily.
Seven, eight, nine, get alittle tougher and then you look
at who you're leaving off thelist when you're talking about
10, 11, 12.
And that's why I think itcreates that little bit of
discipline for you that youdon't say I want to own all 20
of these tech names.
(22:57):
And you know you say I feelreally good and, yes, you will
feel good when the growth isthere and the tech does well,
but you will, you will feel painwhen it doesn't.
And that's where I think youknow I come at it from the
standpoint of avoiding the pain.
That's where I think I come atit from the standpoint of
(23:22):
avoiding the pain.
But then I also get I probablyget a little less joy when the
returns are really strong fortech.
But I'm willing to live withthat because I believe that
balance is the key.
Clem Miller (23:29):
So, basically, this loss aversion shows up to a
large degree in your assetallocation.
Steve Davenport (23:38):
Yes, and I think it's.
When I think about it, clem,I'm usually seeing clouds on the
horizon and I think aboutmanaging risk from avoiding
negative returns.
I look at it relative to thebenchmark and I look at it as
how am I doing?
(23:58):
Versus inflation and noinflation plus rate.
I think that all three are goodbenchmarks, but they can't
always be the one that drivesyour decision.
We are going to lose money,sometimes because the economy is
going to go negative duringrecessions.
Therefore, companies are goingto earn less and the multiple
(24:18):
you apply to those earnings isgoing to have to bring it down.
So I think there's you knowthere's a lot of good reasons
why you know the caveman helps,but there are also reasons why,
as Conum approved, you need tokeep them under control a little
(24:39):
bit.
Asset allocation is a majordecision for most advisors and
clients and I think that when welook at it, we say this client
should probably be in 80-20.
But the client has lived theirwhole life living in a 60-40
world.
So how do you get that clientto either accept more risk or
(25:04):
understand the risk he's taking,or try to minimize his regret
if the returns go up too much?
So I believe that's the realarea where, as advisors, we need
to step forward, understand theclient's biases where they came
from, where they're going, whatthey have in terms of their
(25:25):
wants and needs and then we usenew research and information to
try to make better decisions,like the 401k decision.
When you let employers put a401k in place and the employee
needs to take an active momentto do something about it,
meaning to get rid of it, moreand more people sign up for
(25:48):
401ks and their overallretirement results are better.
That's a case where we had abehavior people weren't signing
up because it just involved alittle bit of work.
We do the work for them, wepre-sign them up.
When they join a company, allof a sudden, their results are
immediately better because theykind of know inherently that
it's good for them, but theyjust weren't willing to do the
(26:10):
work to set it up.
So I think that when I look atallocation, first you need to
make, do the work to set it up.
So I think that when I look atallocation, first you need to be
in the game, and then it's aquestion of how you play the
game.
So I think that there's.
You know, as an industrialengineer, you think about two
things effectiveness andefficiency.
Effectiveness is choosing theright things.
(26:31):
Efficiency is doing thosethings well.
Effectiveness is choosing theright things.
Efficiency is doing thosethings well.
And so, when you look at thegeneral decision making, I think
it's effective to have 60% to80% in what I would call risky
assets equities, and it's veryefficient to do that with a four
(26:55):
or five basis point index fund,because you're not paying a lot
and you get a lot of exposure.
Can you do better and try to dobetter Absolutely?
And that's why we try, withindividual management, to create
what I'll call core portfolios,portfolios that are containing
the best names.
So I understand why people havebiases and why people are in
the wrong allocations, and Ithink it's really about trying
(27:22):
to get people to understandthose frictions and those biases
and then come up with maybesomething that's a little bit
better decision not an optimaldecision, because I think
optimal is so relative that it'sreally hard to come up with the
best one for everyone.
What's?
your feeling about behavioraleconomics and its influence.
Clem Miller (27:51):
Well, I think you know certainly it has managers.
Many of them think aboutbehavioral economics as one
aspect of their philosophy andprocess.
Many of them do especially onthe value side of the equation
not necessarily so much on thegrowth side and they're always
(28:14):
looking.
Those who are applyingbehavioral economics are always
thinking in terms of the marketmispricing stocks, overvaluing
stocks, undervaluing stocks andthey try to exploit these
mispricings.
(28:34):
So, yeah, I think behavioraleconomics has had considerable
influence over the investmentcommunity, that is, the
professional investmentcommunity.
I think that retail investorsreally don't understand too well
how they're being affected bybehavioral economics and I think
(28:58):
that this whole mean stockthing as well as crypto.
There's a lot of behavioraleconomics involved in driving
those retail decisions and Ijust don't think retail
investors know that they'rebeing subject to this behavioral
exploitation.
(29:18):
To look at it from thatstandpoint, I think you're right
.
Steve Davenport (29:27):
It's hard to look at Charlie Munger and have
him say staying away from yourportfolio, trading less, is the
right decision, but you canprove through time that less
turnover leads to usually betterresults.
And I think that less lossaversion will lead to higher
returns, especially for women,who tend to be more conservative
(29:48):
and as women investors, theyhave a longer lifespan.
They have the likelihood thattheir wages are going to be
lower than a similar man.
Therefore, if you get a longerlifestyle life and you have less
earnings and you havedisruption for children or
family members, those things allmean that you have to make a
(30:11):
little bit better decision onterms of loss aversion and how
much exposure you have to riskanything in the mailbag so, um,
hmm, are there, um so, steve,are there any books on this
process, uh, on this topic,which we should read to maybe
understand it better?
(30:32):
well daniel condom.
His most famous book isThinking Fast and Slow, and it's
definitely a great read foranybody in this topic because I
think it allows you to realizehow instinctual some decisions
and reactions are versus acting.
So you want to be acting versusreacting.
You don't want to have thesestimuli kind of push you towards
(30:56):
a decision as a chess playerwith a clock in a game you
constantly battle.
Is your decision good versus isit perfect?
And then you try to weigh howmuch they strengthen your
position and how much theybenefit you for the long term
(31:17):
and I'll tell you.
You can sit there for a whileand go through the permutations
of five moves ahead, 10 movesahead, and then you realize I
don't know what his responsecould be completely different
and not one of the choices Ihave.
So, yes, I think that when weanalyze our own thinking,
(31:41):
no-transcript.
Clem Miller (31:43):
Okay, so you know thanks.
I would just say well, I wouldjust say, as far as I'm
concerned, you know, I've read anumber of things about
behavioral economics.
I don't think there's a singleand I've read that book,
thinking Fast and Slow, but youknow, I don't think there's any
single book that I wouldrecommend on the topic, any
(32:11):
single book that I wouldrecommend on a topic.
Rather, what I do is I look ata number of books about value
investing, about growthinvesting, about quality
investing, and you know thereare some books you know I can
recommend and maybe we'll dothis on a future podcast books
about, you know, sort of, youknow, interviewing particular
managers and getting someinsights from them, and I
(32:33):
certainly would want to do thaton a future podcast, and
mispricing of securities iscertainly something that is
discussed in those books.
So, yeah, so I would say, youknow, let's stay tuned for a
future podcast discussing howdifferent managers look at.
I'll give you a pass.
Steve Davenport (32:54):
I'll give you a pass for today, but your
homework, should you choose toaccept it as to come back.
Maybe when we're talking toFraser next week we'll we'll go
around the room and say what'sour best investment book of all
time.
Clem Miller (33:07):
Right?
Which which leads me to to toask you around the room and say
what's our best investment bookof all time?
Right?
Which leads me to ask you Steve, we do have Fraser Rice on next
week.
Can you tell us a little bitabout Fraser?
Steve Davenport (33:19):
Fraser is an expert on all things planning
and taxation for clients.
Long-term and understanding howfamilies can control and manage
their assets betweengenerations is a huge step in
the next level of investing.
Once you understand you haveassets and then you satisfy your
(33:39):
needs with those assets, thenyou take the next step in terms
of how should I involve mychildren, how should I be
involved in my grandchildren'slives, and ultimately you want
to try to make those decisionsand structures, put them in
place so that you're oneminimizing that taxation but
(33:59):
also doing something to improvethe utility of happiness for a
family.
I think Fraser is very good atlooking at complex families and
in situations and providinginsights that makes the overall
plan match what the overallneeds and wants are for a family
(34:20):
, so I think it'll be great tohave him, yeah.
Clem Miller (34:23):
So, steve, why don't you quickly summarize what
we discussed today?
Sure.
Steve Davenport (34:30):
Like Charlie Munger, there is much to learn
from Daniel Kahneman's life andhis leadership.
One challenge ideas.
He challenged the ideas ofbiases and thinking and thought.
These animals are not economicanimals, they're not as
efficient as we originallythought.
Humanity is, by definition, notperfect.
(34:50):
Therefore, I think that we haveto take that viewpoint when we
start looking at individuals andsay we know they're going to
make an imperfect decision, buthow do we minimize the level of
imperfection?
We prioritize strengths andmistakes, but not necessarily
that we probably focus too muchon the mistakes, and maybe
(35:13):
that's what we take from DanielKahn.
Understand your utilityfunction.
There's a utility for happinessthat would equal your safety
plus your economics, plus youreconomics, plus your health,
physical and mental plusfriendships, family and friends.
I think that if you think aboutthat utility function, you
(35:38):
don't have to have thecoefficients exactly right and
the magnitudes may be off fordifferent people, but thinking
about happiness first will startyou on a path towards
ultimately leading you to morehappiness.
So, Steve I know.
Clem Miller (35:51):
I would just say I totally agree with your, your
second, your last point aboutyou know the happiness function,
so I totally agree with that.
So, Steve, thank you very muchfor all of your insights today.
Very much for all of yourinsights today, and we hope
everybody enjoyed this episodeof Skeptic's Guide to Investing.
(36:13):
Thanks everybody for listening,Thanks everyone.
Welcome everyone to Skeptic's Guide to Investing.
I'm Clem Miller and today we'regoing to talk about the recent
passing of behavioral economicslegend Daniel Kahneman.
Steve Davenport and I will diginto the research which Daniel
focused on and its ongoingeffects as investors.
Where do you start with?
(00:23):
Daniel Kahneman, Steve?
Well, I start at the beginningand as an Israeli born
psychology professor, he wasreally doing some interesting
work and he became friends withAmos Tversky, also a
psychologist, and it really is alittle bit unusual when you
(00:44):
talk about someone who wins aNobel Prize in economics because
he's never taken an economicsclass.
I think that his work tells mea lot about similar things that
we noticed when we discussed thelife of Charlie Munger.
I think that you know you startwith some of the accolades.
(01:05):
He won 23 honorary doctoratesin the US and around the world,
including one at your universityin DC, Clem.
He was the 2002 Nobel Prize inEconomics and his real
interesting part of what he didwas to just question some of the
(01:29):
underlying assumptions thatpeople make about behavior and
behavioral economics.
He's thought of as the father ofbehavioral economics.
He really was interested in,first started studying hedonism
and happiness and tried to thinkabout how these things could be
measured and how these thingscould be standardized, so that
(01:51):
you could then go around theworld and try to figure out how
to put the systems in place.
So first of all, I'd say hiscontribution and the way I look
at his life is, he wasunderstanding how decisions are
made by humans and it feels likea very simple concept.
But when you look at us, Ithink that I've always looked at
(02:19):
us as economic animals who willmake decisions that are good
for themselves, based on thefacts and information, but in
reality, humans make a lot ofdecisions that are more
instinctual, more like thecaveman.
So I think that understandingthat basic difference of humans
as unique decision makers reallywas the primary result of his
(02:43):
life's work.
I think, when you look at him,just like we looked at Charlie
Munger and Warren Buffett, heworked for a critical period
with fellow psychologist AmosTversky.
Kahneman and Tversky didseveral papers together on
several topics, and it remindsme of Charlie and Warren because
(03:03):
they both had their owncharacteristics, but they both
figured out how to mesh togetherand work together in a way that
makes the overall product andthe overall result that much
better.
And so, just like you and I,clem, you know, when you team
together two superstars, do youget an additive effect or do we
(03:26):
subtract from each other?
I like to think it's additive.
So I think that one thing thathe introduced is this concept of
bias and how it can lead usdown the wrong road.
When we think about biases, weusually think, well, those exist
for other people.
We're perfect decision makersand we don't make those same
(03:48):
human loyalty type of mistakes.
He then spent a lot of time onprospect theory, loss, aversion
and happiness.
I think that all three of thesethings have a great deal of
influence on what we talk aboutwhen we're talking about
investing.
What are we investing for?
What's the prospect of ourinvestments?
(04:08):
Results in 5, 10, 15 years?
And how does our approachtowards them lead us to better
results or worse results?
And I think the fact that heultimately sits and develops a
national or an internationalstandard for happiness.
Again, the question about moneyisn't should you be doing
(04:31):
something, it's how do you do itin a way that it aligned with
your life plan and help youfurther that happiness goal?
And then the last thing I thinkthat's most interesting about
Kahneman is that in the last sixmonths to a year, we've been
talking about AI and theimplications for investing, and
(04:53):
I look at what Kahneman wasdoing and saying and then I
wonder well, gee, are we correctin the assumption that a man or
human will make a betterdecision than AI will for
investing If we have all thesebiases, are these biases wrapped
up in our personal situationand therefore they're unique and
important, or are they justbiases that we have that really
(05:17):
don't add much value?
And therefore a moreindependent thinker and
programmed to give you optimalresults of the utility function
that is your life, maybe that'swhat we should be thinking.
So I think that his work andhis ideas are something that we
will be studying for the next 30to 40 years wow.
(05:39):
So there's really a lot to chew on there.
And you know what's what?
What I find interesting abouthim is that him and Tversky is
that they started off in onefield psychology and then he
moved into another fieldeconomics and I think some of
(06:00):
our most brilliant thinkers arethose who have are those who are
multidisciplinary.
They might start off in onediscipline and they move into
another discipline, andcertainly Daniel Kahneman was
one of those figures and I thinkas a result you know that's,
(06:22):
you know he ended up winning theNobel Prize right in 2002.
Steve Davenport (06:31):
I think it's a great lesson in terms of we
always think of ourselves asoutsiders.
I've always been an engineerwho was in finance and instead,
you know, you start to realize,hey, some of the fundamentals
and some of the disciplines ofscience, they can be helpful,
they can also be harmful,because the world doesn't always
(06:51):
work according to a set formula.
So I think it's interestingthat he was questioning,
questioning, questioning therelationship and the decision
making process, questioning therelationship and the
decision-making process.
And then we started to get intothe science of what part of the
brain are you using to thinkabout this decision?
And is that part of the braintypically associated with
(07:15):
reactionary decision-making oris it the thoughtful, decision
making part of your brain?
And I think that when wethought of what he started in
the 60s, you know, I don't thinkanybody imagined that we would
get to the level ofunderstanding of the human
genome and other things thatlead us to some of the
(07:35):
interesting work that's going ontoday.
Clem Miller (07:39):
So, Steve, I thought that economic animals,
to use your term, were efficientin their decision making.
My understanding of an economicanimal is that it was more into
(08:06):
thinking that human beings weremore concerned about loss
aversion than about sort ofoptimizing returns, which is, or
optimizing risk, adjustedreturns, to use an expression
often used in finance, a lossaversion.
And also, I've read that youknow, I've certainly read that
(08:33):
people are, you know, asdecision makers, much more
investment.
Decision makers have roughly atwo to one ratio of being
concerned about loss aversionversus u pside return.
So, yeah, that I mean two toone is a big ratio.
So , Steve, once again you knowwhy aren't economic animals
(08:57):
efficient in their decisionmaking?
Steve Davenport (09:01):
Yes, I think we like to tell ourselves that we
are right.
We like to think of ourselvesas having optimized every aspect
of our life, but, as you cantell from my hair the fact I
haven't shaved it's not reallytrue.
Right, if I was alwaysoptimized, I would look, start
(09:25):
to look at things and say we'resurrounded by unique
characteristics that makeoptimization according to some
standard function almostimpossible to apply across
economics, across countries,across different geographies.
Geographies because, you know,an economy that's based on
(09:48):
agriculture is very differentthan an economy based on
technology versus an economythat's, you know, based on oil.
These things all influence whattype of people and what type of
things are going to happen.
I still think of us Clem, andthis is maybe because I've been
watching too many Geico ads, butI'm like a caveman trying to
(10:08):
stay alive.
Food, heat, water those are thethings that matter to me.
We are loss adverse and we goback to that idea that we
survived thousands of yearsbecause we were able to use
(10:30):
rocks, use fire, use wheels, to,make our lives more consistent
and provide that water and foodand and be able to survive in
the environments where, wildanimals would come and take our
food and potentially rip us toshreds.
(10:51):
I think that today we're in avery different environment, but
genetically we have that code inour DNA that's telling us hey,
I don't know where my next mealis coming from, where do I go?
And if it's raining, I get outof the rain.
The rain's not going to hurt me, but I just still get out of it
(11:11):
because I've had thousandsprogramming of years of program.
So I think understanding wherewe came from is really important
, so that when we think aboutwhat we're trying through our
loss aversion technique, we needto sometimes take a step back,
and I personally feel like Imight focus too much on loss
(11:35):
aversion and maybe my ratio ishigher, but I think it really
needs to think about and measureyour internal utility function,
and we are seeking risk forgrowth, and the reason we do
that is that we understand thatinflation and other things can
(11:56):
eat away at the assets we have.
And so I believe that when welook at ourselves as economic
animals, I think we're probablytaking a leap forward, that
maybe we shouldn't all.
We should realize first that weare going to try to survive as
a civilization and thenafterwards we're into some of
(12:19):
the other things in the pyramidof needs and wants.
So I think of myself still as acaveman.
Clem Miller (12:31):
So, Steve, that leads to an interesting question
, which is you know, if you lookback at our recent experience
with the pandemic, you know I'msure somebody you know, some
future Daniel Kahneman, is goingto look back and say and do
(12:52):
some research as to you knowwhether we were approaching the
pandemic as cavemen, trying tobe loss averse, or whether we
were really trying to optimize.
You know my guess whether wewere really trying to optimize.
My guess is not being apsychologist, but my guess is
(13:12):
that we were certainly morethinking about loss aversion
than we were about, you know,optimizing.
You know which would have takenmore more of an economic
standpoint in terms of how wemanage the pandemic.
Steve Davenport (13:28):
Correct.
I felt that we should havelooked around and said what
other countries in the worldhave had these and how have they
handled them?
We should have becomeresearchers on Korea and Japan,
because those two Asiancountries, when they said, hey,
we've got a pandemic, they allput their masks on.
(13:50):
They all, you know, did thesocial distancing.
They did these things that theyhad done before and they were
familiar with.
In the United States we neverhad a pandemic till, you know,
since the Spanish flu in theearly 1900s.
So we just didn't know how toreact and I think, as cavemen,
we said, okay, let's preserveourselves first.
(14:13):
Should we have said, hey, thisis really important to preserve
yourself.
If you're one of thesecharacteristics, I have diabetes
, I'm overweight, I have thesefive health issues those would
have been the people that youshould have taken care of first.
But instead we said everybodyneeds to stay away, everybody
(14:34):
needs to close down.
And I think it was a little bitof our democratic process,
right where we say, look, we'regoing to treat everyone equally,
where we say, look, we've gotto treat everyone equally.
Everyone's the same.
If we disallow freedom for some, we can't disallow it for just
(14:56):
a specific group, and that'swhat makes this whole discussion
about how good are humans atmaking decisions and will AI be
better at the heuristic decisionprocess.
I think it leads to some veryinteresting chat GPT type
discussions where we think wecan put a question in and we
will get an answer that isrelevant.
Where are we making the worstdecisions in our lives?
(15:19):
Is it in health?
Is it in money?
Is it in health?
Is it in money?
Is it in relationships?
I would like to say let'sfigure out what things are going
poorly and then try to figureout how we optimize and minimize
those things.
What things do people do welland how do we maximize those
(15:48):
properties?
I think that what Kahneman doesis he looks at things and says,
hey, you need to watch out forthis, this and this, and I think
that using chat, gpt or AI, itmay be like it's a pardon, you
(16:10):
know, it's a part.
So, since we're out of thecaves, I have to believe that
our loss aversion hurts us andtherefore it's something that we
should all watch out for.
I'm trying to change and tryingto be more patient with my
investing and I hope it.
You know, I hope it has relatedto better results the last few
years, and I hope it continuesto.
I also believe we're a littlebetter at collaboration versus
(16:33):
singular research on an idea.
I believe that there is abenefit from two people sharing
an idea, and I think that when Ilook at condominium diversity
and I look at Charlie and Warren, I kind of believe that there's
something there for everyone.
When you think about ideas, wethink I'm going to go down this
(16:53):
path and I journey down the pathand maybe I go too far before I
ask somebody else what theythink, you know of the journey
I'm going on, and I think itshould be a way for us to put
some guardrails on ideas thatallow them to travel on the
right road towards the rightdestination by having others
(17:17):
collaborate, and I thinkcollaboration is something that
we need to investigate with AI.
I hear about writers who giveAI a topic and then they take
the output and then add theirown special flair to it.
Maybe, that's the way we shouldbe using AI, instead of looking
at the results and say look atus.
(17:39):
We use AI for our summationsand our capsules and our titles,
and we know it's not perfect,so we try to collaborate with it
to come up with some of theadjectives and some of the
common phrases, but we want itto be unique to us and I think
that's the future.
It's collaboration.
(17:59):
It's not just I accept theoutput from chat GPT, I accept
the output from chat GPT.
And then the last item I thinkabout when I think about AI and
(18:21):
this idea of behavioraleconomics is that we need to
start to at least put down onpaper what is the utility
function for happiness.
I believe that everybody youknow when you think about you
know I used a lot of utilityfunctions in my optimizations
for quantitative management andyou know you have alpha, you
have tracking risk, you havetaxes, and you combine that with
any other frictions, liketrading costs, and that's how
(18:43):
you try to optimize yourportfolio, like trading costs,
and that's how you try tooptimize your portfolio.
And I believe that when wethink about happiness, we've got
relationships, we've got peoplewe care about, we've got health
, both mental and physical, andthen I think that all of our
efforts should really be on.
(19:03):
Am I doing enough for myself ina way that's going to give me
the economic, health andrelationship benefits to
optimize who I am and how I doon this journey?
So the longest journey startswith a step and I agree you
should still make that step, butI'm thinking about
(19:23):
collaboration, and avoidinglosses helps you to focus on a
measurable result.
Clem Miller (19:31):
So, Steve, what would be your biggest bias?
And then I'll tell you mine.
You go first.
Steve Davenport (19:41):
I think that we are all products of a very
imperfect education system andan imperfect support system in
the classroom and at home.
And I think your IQ, yourintellectual quotient, your EQ,
(20:02):
your emotional quotient and yourphysical quotient all are
unique parts of who you are, sothey lead you towards biases
when we needed biases to help usevolve, and I think that today
we still need biases to help usevolve, because I believe that
what will come out of COVID willbe this realization that
interaction and socializationare a bigger part of our life
(20:25):
than we ever realized and thatby isolating we created more
depression and more instability.
But it's hard to look atbecause it doesn't show up on a
list of diseases or a list ofyou know, ailments.
But I think loneliness will bethe thing that will come back as
one of the biggest byproductsof COVID.
(20:48):
And for your original question,my answer would be loss
aversion.
I think that I tend to lookminimize, minimize, minimize
that loss aversion, and I needto probably be a little more
thinking about my returnoptimization.
Clem Miller (21:04):
Yeah, I guess my biggest bias would be I look
around and I get excited aboutnew themes, new opportunities,
and I purposefully try my verybest to stay rational when there
(21:28):
seems to be excitingopportunities out there.
And so you know, you've noticed, you know, my skepticism about
things like, you know, bitcoinor AI or renewable energy or ESG
.
You know these things, you know, have some excitement for me,
but I think that you know, someof that excitement is really
(21:49):
irrational and I have to pullmyself back and restrain myself
and, you know, stay true to somedegree of uh, of process, uh,
you know, using quantitative andto some degree qualitative, but
not, you know, not get myselfuh over my skis and thinking
(22:10):
about, you know, and getting tooexcited about themes.
Steve Davenport (22:14):
Yeah, I think that we talked about sector
neutrality and we try to besector neutral for that very
reason.
If the S&P is, you know, 30%,25% in technology, and you look
at it and you say I got two anda half percent positions, that's
10 to 12 positions, okay, youhave to make some.
(22:37):
You know you can fill in thefirst five or six probably
pretty easily.
Seven, eight, nine, get alittle tougher and then you look
at who you're leaving off thelist when you're talking about
10, 11, 12.
And that's why I think itcreates that little bit of
discipline for you that youdon't say I want to own all 20
of these tech names.
(22:57):
And you know you say I feelreally good and, yes, you will
feel good when the growth isthere and the tech does well,
but you will, you will feel painwhen it doesn't.
And that's where I think youknow I come at it from the
standpoint of avoiding the pain.
That's where I think I come atit from the standpoint of
(23:22):
avoiding the pain.
But then I also get I probablyget a little less joy when the
returns are really strong fortech.
But I'm willing to live withthat because I believe that
balance is the key.
Clem Miller (23:29):
So, basically, this loss aversion shows up to a
large degree in your assetallocation.
Steve Davenport (23:38):
Yes, and I think it's.
When I think about it, clem,I'm usually seeing clouds on the
horizon and I think aboutmanaging risk from avoiding
negative returns.
I look at it relative to thebenchmark and I look at it as
how am I doing?
(23:58):
Versus inflation and noinflation plus rate.
I think that all three are goodbenchmarks, but they can't
always be the one that drivesyour decision.
We are going to lose money,sometimes because the economy is
going to go negative duringrecessions.
Therefore, companies are goingto earn less and the multiple
(24:18):
you apply to those earnings isgoing to have to bring it down.
So I think there's you knowthere's a lot of good reasons
why you know the caveman helps,but there are also reasons why,
as Conum approved, you need tokeep them under control a little
(24:39):
bit.
Asset allocation is a majordecision for most advisors and
clients and I think that when welook at it, we say this client
should probably be in 80-20.
But the client has lived theirwhole life living in a 60-40
world.
So how do you get that clientto either accept more risk or
(25:04):
understand the risk he's taking,or try to minimize his regret
if the returns go up too much?
So I believe that's the realarea where, as advisors, we need
to step forward, understand theclient's biases where they came
from, where they're going, whatthey have in terms of their
(25:25):
wants and needs and then we usenew research and information to
try to make better decisions,like the 401k decision.
When you let employers put a401k in place and the employee
needs to take an active momentto do something about it,
meaning to get rid of it, moreand more people sign up for
(25:48):
401ks and their overallretirement results are better.
That's a case where we had abehavior people weren't signing
up because it just involved alittle bit of work.
We do the work for them, wepre-sign them up.
When they join a company, allof a sudden, their results are
immediately better because theykind of know inherently that
it's good for them, but theyjust weren't willing to do the
(26:10):
work to set it up.
So I think that when I look atallocation, first you need to
make, do the work to set it up.
So I think that when I look atallocation, first you need to be
in the game, and then it's aquestion of how you play the
game.
So I think that there's.
You know, as an industrialengineer, you think about two
things effectiveness andefficiency.
Effectiveness is choosing theright things.
(26:31):
Efficiency is doing thosethings well.
Effectiveness is choosing theright things.
Efficiency is doing thosethings well.
And so, when you look at thegeneral decision making, I think
it's effective to have 60% to80% in what I would call risky
assets equities, and it's veryefficient to do that with a four
(26:55):
or five basis point index fund,because you're not paying a lot
and you get a lot of exposure.
Can you do better and try to dobetter Absolutely?
And that's why we try, withindividual management, to create
what I'll call core portfolios,portfolios that are containing
the best names.
So I understand why people havebiases and why people are in
the wrong allocations, and Ithink it's really about trying
(27:22):
to get people to understandthose frictions and those biases
and then come up with maybesomething that's a little bit
better decision not an optimaldecision, because I think
optimal is so relative that it'sreally hard to come up with the
best one for everyone.
What's?
your feeling about behavioraleconomics and its influence.
Clem Miller (27:51):
Well, I think you know certainly it has managers.
Many of them think aboutbehavioral economics as one
aspect of their philosophy andprocess.
Many of them do especially onthe value side of the equation
not necessarily so much on thegrowth side and they're always
(28:14):
looking.
Those who are applyingbehavioral economics are always
thinking in terms of the marketmispricing stocks, overvaluing
stocks, undervaluing stocks andthey try to exploit these
mispricings.
(28:34):
So, yeah, I think behavioraleconomics has had considerable
influence over the investmentcommunity, that is, the
professional investmentcommunity.
I think that retail investorsreally don't understand too well
how they're being affected bybehavioral economics and I think
(28:58):
that this whole mean stockthing as well as crypto.
There's a lot of behavioraleconomics involved in driving
those retail decisions and Ijust don't think retail
investors know that they'rebeing subject to this behavioral
exploitation.
(29:18):
To look at it from thatstandpoint, I think you're right
.
Steve Davenport (29:27):
It's hard to look at Charlie Munger and have
him say staying away from yourportfolio, trading less, is the
right decision, but you canprove through time that less
turnover leads to usually betterresults.
And I think that less lossaversion will lead to higher
returns, especially for women,who tend to be more conservative
(29:48):
and as women investors, theyhave a longer lifespan.
They have the likelihood thattheir wages are going to be
lower than a similar man.
Therefore, if you get a longerlifestyle life and you have less
earnings and you havedisruption for children or
family members, those things allmean that you have to make a
(30:11):
little bit better decision onterms of loss aversion and how
much exposure you have to riskanything in the mailbag so, um,
hmm, are there, um so, steve,are there any books on this
process, uh, on this topic,which we should read to maybe
understand it better?
(30:32):
well daniel condom.
His most famous book isThinking Fast and Slow, and it's
definitely a great read foranybody in this topic because I
think it allows you to realizehow instinctual some decisions
and reactions are versus acting.
So you want to be acting versusreacting.
You don't want to have thesestimuli kind of push you towards
(30:56):
a decision as a chess playerwith a clock in a game you
constantly battle.
Is your decision good versus isit perfect?
And then you try to weigh howmuch they strengthen your
position and how much theybenefit you for the long term
(31:17):
and I'll tell you.
You can sit there for a whileand go through the permutations
of five moves ahead, 10 movesahead, and then you realize I
don't know what his responsecould be completely different
and not one of the choices Ihave.
So, yes, I think that when weanalyze our own thinking,
(31:41):
no-transcript.
Clem Miller (31:43):
Okay, so you know thanks.
I would just say well, I wouldjust say, as far as I'm
concerned, you know, I've read anumber of things about
behavioral economics.
I don't think there's a singleand I've read that book,
thinking Fast and Slow, but youknow, I don't think there's any
single book that I wouldrecommend on the topic, any
(32:11):
single book that I wouldrecommend on a topic.
Rather, what I do is I look ata number of books about value
investing, about growthinvesting, about quality
investing, and you know thereare some books you know I can
recommend and maybe we'll dothis on a future podcast books
about, you know, sort of, youknow, interviewing particular
managers and getting someinsights from them, and I
(32:33):
certainly would want to do thaton a future podcast, and
mispricing of securities iscertainly something that is
discussed in those books.
So, yeah, so I would say, youknow, let's stay tuned for a
future podcast discussing howdifferent managers look at.
I'll give you a pass.
Steve Davenport (32:54):
I'll give you a pass for today, but your
homework, should you choose toaccept it as to come back.
Maybe when we're talking toFraser next week we'll we'll go
around the room and say what'sour best investment book of all
time.
Clem Miller (33:07):
Right?
Which which leads me to to toask you around the room and say
what's our best investment bookof all time?
Right?
Which leads me to ask you Steve, we do have Fraser Rice on next
week.
Can you tell us a little bitabout Fraser?
Steve Davenport (33:19):
Fraser is an expert on all things planning
and taxation for clients.
Long-term and understanding howfamilies can control and manage
their assets betweengenerations is a huge step in
the next level of investing.
Once you understand you haveassets and then you satisfy your
(33:39):
needs with those assets, thenyou take the next step in terms
of how should I involve mychildren, how should I be
involved in my grandchildren'slives, and ultimately you want
to try to make those decisionsand structures, put them in
place so that you're oneminimizing that taxation but
(33:59):
also doing something to improvethe utility of happiness for a
family.
I think Fraser is very good atlooking at complex families and
in situations and providinginsights that makes the overall
plan match what the overallneeds and wants are for a family
(34:20):
, so I think it'll be great tohave him, yeah.
Clem Miller (34:23):
So, steve, why don't you quickly summarize what
we discussed today?
Sure.
Steve Davenport (34:30):
Like Charlie Munger, there is much to learn
from Daniel Kahneman's life andhis leadership.
One challenge ideas.
He challenged the ideas ofbiases and thinking and thought.
These animals are not economicanimals, they're not as
efficient as we originallythought.
Humanity is, by definition, notperfect.
(34:50):
Therefore, I think that we haveto take that viewpoint when we
start looking at individuals andsay we know they're going to
make an imperfect decision, buthow do we minimize the level of
imperfection?
We prioritize strengths andmistakes, but not necessarily
that we probably focus too muchon the mistakes, and maybe
(35:13):
that's what we take from DanielKahn.
Understand your utilityfunction.
There's a utility for happinessthat would equal your safety
plus your economics, plus youreconomics, plus your health,
physical and mental plusfriendships, family and friends.
I think that if you think aboutthat utility function, you
(35:38):
don't have to have thecoefficients exactly right and
the magnitudes may be off fordifferent people, but thinking
about happiness first will startyou on a path towards
ultimately leading you to morehappiness.
So, Steve I know.
Clem Miller (35:51):
I would just say I totally agree with your, your
second, your last point aboutyou know the happiness function,
so I totally agree with that.
So, Steve, thank you very muchfor all of your insights today.
Very much for all of yourinsights today, and we hope
everybody enjoyed this episodeof Skeptic's Guide to Investing.
(36:13):
Thanks everybody for listening,Thanks everyone.
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