In this course, you will start by reviewing the fundamentals of investments, including the trading off of return and risk when forming a portfolio, asset pricing models such as the Capital Asset Pricing Model (CAPM) and the 3-Factor Model, and the efficient market hypothesis. You will be introduced to the two components of stock returns – dividends and capital gains – and will learn how each are taxed and the incentives provided to investors from a realization-based capital gains tax. You will examine the investment decisions (and behavioral biases) of participants in defined-contribution (DC) pension plans like 401(k) plans in the U.S. and will learn about the evidence regarding the performance of individual investors in their stock portfolios. The course concludes by discussing the evidence regarding the performance of actively-managed mutual funds. You will learn about the fees charged to investors by mutual funds and the evidence regarding the relation between fees charged and fund performance. Segments of the portfolios of mutual funds that may be more likely to outperform and examples of strategies designed to “earn alpha” will also be introduced. Learners are welcome to take this course even if they have not completed "Investments I: Fundamentals of Performance Evaluation," as the first module contain a review of investment fundamentals and regression analysis to get everyone up to speed. Also, the course contains several innovative features, including creative out-of-the-studio introductions followed by quick-hitting "Module in 60" countdowns that highlight what will be covered in each module, four "Faculty Focus" interview episodes with leading professors in finance, and a summary of each module done with the help of animations! This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu.
1-2.3. Seasonality in Stock Returns
Loading...
En provenance du cours de University of Illinois at Urbana-Champaign
Investments II: Lessons and Applications for Investors
210 notes
University of Illinois at Urbana-Champaign
210 notes
Cours 4 sur 7 dans Specialization Financial Management
À partir de la leçon
Module 1: Fundamentals and Composition of Returns
In Module 1, we will briefly review the fundamentals of investments, including the trading off of return and risk when forming a portfolio, asset pricing models such as the Capital Asset Pricing Model (CAPM) and the 3-Factor Model, and the efficient market hypothesis. We will also discuss the two components of stock returns – dividends (cash received) and capital gains (changes in price since purchase).
Rencontrer les enseignants
Scott WeisbennerWilliam G. Karnes Professor of Finance
Department of Finance, College of Business
[MUSIC]
So is there a seasonal pattern in stock returns?
Given the incentives by the tax code to realize losses by the end of the year and
postpone gains, maybe does that trickle down to have effect on asset prices.
That's what we're going to look at in this video here.
So why don't we start out by just looking at is there a seasonal pattern in stock
returns by breaking out separately the returns of small stocks and
large stocks here.
So by small stocks, we're talking about stocks in the bottom 10%.
Based on market capitalization, their size of this 5,000 stocks,
let's say, in the US, this would be the bottom 500.
Large-cap stocks are the biggest, so like Apple,
Axon mobile would be on that group, the 10%.
So the light blue bars are the small stocks,
the dark blue bars are the large-cap stocks so very striking pattern.
Look, for example, at the light blue bars,
small stocks about two-fifths 40% of the return of small
stocks over the full year happens on average in the month of January.
We know the average small stock return over 1927 to 2014 was about 19%.
As you recall about 8%, it's just happening in the month of January alone.
Very striking.
When you look at the large cap stocks, you see that basically the returns say
fairly similar across the months here, you got.
Statistically reject that the average large-cap
stock return is actually the same across all the months.
So right off the bat we talked about this January effect in stock returns.
You may have heard that, we're talking about it here.
This is really what we're talking about,
this large return in small-cap stocks in the month of January.
Now, as you may recall, if you took the first course in investments,
we talked about there are some academic work by Bonds and Reinganum in 1981, when
they documented, hey, historically these small stock returns seem really high.
So do you see the same pattern in returns after 1981?
So let's look at 1982 to 2014, you see this January return for
small stocks is still higher than the other months,
about one-third now the average small stock return over the whole year,
seems to happen by the month of January.
Smaller than it was before, so it has come down, but still there,
you see the difference for small stocks, and again, you can't statistically reject
that you see kind of the same average
return across all the months for the dark blue bars are the large-cap stocks.
Also, one thing that's kind of an interesting difference to look across
the full sample of stock returns here versus the later samples.
When the small full sample, 1927 to 2014,
you see this gigantic January return for small stocks.
And this kind of more depressed December.
When you get to the later period, you see the January is coming down,
still high for small stocks, but less that was before, and
the higher return in December for the small stocks.
Maybe that could be consistent Distance, with people starting to realize like,
hey, stock prices seem to be going up for small firms in January,
maybe we should start to buy some of these in December anticipating that effect.
And we talked about one-thrid of the small stock return still after 1982 is
happening in January, but for large stocks we don't seem to see this difference.
So clearly, the return for small stocks are highest in the month of January.
That's a big chunk of their annual return as occurring in this month.
This is true even after the academic publications in the early 1980s.
Documenting a high return from small stocks.
This pronounced seasonal pattern is not present for large-cap stocks.
In fact, we can't statistically reject that the average monthly return for
the large-cap stocks Is the same across all the months of the year.
So let's consider a strategy, it's a long-short strategy where we're long small
stocks, and we're short large-cap stocks over this full sample period 1927 to 2014,
so we're just looking at the difference of small versus large.
So during the month of January,
when we look at this portfolio that's a difference of small minus large.
The CAPM alpha, or excess performance is six percentage points,
highly statistically significant.
So in the month of January, controlling for risk and
the CAPM beta is positive here.
This 0.46 says that in the month of January,
small stocks have a higher beta than small stocks by about 0.46 makes sense.
Small stocks, more sensitive to the state of the economy.
Controlling for that, small stocks still outperform by about six percentage points.
Look at all the other months, you still have this difference in risk.
Small stocks are riskier than large stocks.
That's why you have this differential beta of about 0.5,
but look at the alpha, it's basically 0, not statistically significant.
So the historic out performance of small stocks relative to large stocks we
talked about in several times, is really a January effect.
You look at the months outside January, small stocks
are riskier than large stocks higher in data but you don't see any alpha.
In terms of the differential performance after controlling for
their differences in price.
So why the high January returns?
We've identified this famous January effect.
But why?
Why is it there?
We see it's concentrated particularly in small firms,
particularly those that had losses during the prior year.
We haven't documented that yet, if you dig further into the data you see this.
The January return, it's in small firms that we show, and if you dig further it's
concentrated particularly in small stocks that have losses during the prior year.
So what responsible for this seasonal pattern?
There's two leading hypotheses.
One would be window dressing by institutional investors.
The second is tax loss trading by individual investors.
So is there any way we can disentangle which of these two is,
at least partially, explaining the seasonal phenomena?
So let's first talk about the various hypotheses and what's behind them.
Let's start with window-dressing.
So the idea is that institutions may want to avoid
reporting having held stocks that have fallen a lot in value.
No institution in their annual report
wants to be reporting that they held the stock that totally collapsed that year.
And institutional investors may then have an incentive to sell losing stocks right
before the end of the calendar quarter, or particularly the end of the year,
because they have to report their holdings on a quarterly basis to the SEC.
And you would think that this is done every quarter, but
maybe investors are really focusing at the end of the year, so let's sell this
stock that did really poorly, at the end of December, so we're not seen as holding
it when we give our account of what stocks are we holding at the end of the year.
So this could have the prediction, so losing stocks at the end of the year,
that leads to a rebound in prices in January.
Okay.
How about the tax-loss selling hypothesis?
Well this is focusing on individual investors and
this is related back to the realization-based capital gains tax.
So individual investors have an incentive through the tax code at least in the US
to sell stocks that have fallen in price to realize the capital loss and
get the tax deduction.
So this is particularly true for losses that have short term status,
and that's typically been either 6 or 12 months.
Currently it's 12 months in the US.
And this is particularly pronounced effect,
you would think at the end of the year.
Okay? Remember this,
if a loss is realized December 30th, we can use that to reduce our taxes one
year earlier than if we realize this loss in January, let's say January 2nd.
So particularly at the end of the year,
we have a strong incentive to sell our losing investments,
particularly losing investments that would count as short term tax treatment.
Okay?
So, we have kind of a little problem here.
We have two hypothesis, both seem plausible.
They have very similar predictions.
Okay? Both window-dressing and
tax-loss-selling hypothesis have this prediction that you're going to
sell stocks with recent losses near the end of December.
When the selling pressure stops in early January that should lead to
a rebound in prices.
So there's kind of a liquidity effect.
Depressing prices for these past losers at the end of December
when that selling pressure stops, prices maybe then recover in January.
Okay, so can we distinguish between the two hypotheses?
We already kind of have a little hint.
Institutional ownership is typically higher in large-cap stocks than small-cap
stocks.
Okay?
We know the January effect is concentrated in small stocks, so
right off the bat that suggests that the individual tax motivated behavior,
that may be a larger part of the January Effect in institutional window dressing.
Just basically institutions are holding more large stocks.
So if they're doing window dressing it would probably be over large cap stocks.
Individuals are kind of relatively relative to institutions holding more
smaller stocks, and the January effect is in smaller stocks.
Okay?
But we can do maybe provide some more convincing evidence in some work I did
with Jim Poterba, actually exploits changes in capital gains tax
rules to really kind of pin down, can we attribute some of the January effect
in stock returns to individual tax rules?
Okay?
So let's actually look at how these tax rules have changed,
which really provides identification strategy to see, do tax rules
in the US actually affect asset prices and stock returns around the years?
So three tax regimes here.
And the key thing to focus on across these tax regimes is,
what is the holding period to classify for short term versus long term status here?
And both regime I and regime II, only a six month holding period for short term.
If you held the stock beyond six months, it classifies for long term tax treatment.
So the current rule in the US in which we had kind of in some years prior,
was a 12 month holding period.
So you could see there's variation over time, whether the holding period for
short term versus long term is six months versus 12 months.
Why does that matter?
Well we know if you realized a loss within the short term window
you're going to get a higher tax benefit.
Because short term gains and losses are at a higher rate than long term gains or
losses.
If you want to get a tax deduction you want the tax deduction
at a higher higher tax rate.
Okay?
So changes in this holding period of short term status are maybe potentially useful,
and maybe what suggest differences in
January returns associated with those changes in the tax rules.
Okay?
So what do we do in this paper?
We relate the January returns of stocks to the return over
the prior January to June and prior July to December.
And you can see this is getting at prior six months or prior 12 months here.
When the short-term holding period is defined as only 6 months,
returns over the prior July to December should matter
most in predicting December selling and the subsequent January return.
Right? Because that short term status gives you
a higher value for the tax deduction.
Higher value to realizing the loss.
When the short-term holding period is defined as 12 months,
returns over both the prior July to December and January to
June should matter in predicting December selling and the subsequent January return.
So just think simply if you bought an asset in February of 2014,
once you get to the end of 2014, if it's a one year holding period for
long-term status, it's still a short term asset, whether have that one year cutoff.
If it's a six month difference, short term versus long-term,
if you bought the asset in February of 2014,
by the time you get to the end of 2014 six months has already passed,
it's already a long-term asset, so there's less value to realizing the loss.
And that's what we're exploiting here in this empirical analysis.
So key is, under the window-dressing story, changes in tax rules for
individuals shouldn't matter in predicting the January return.
Okay? Because institutional investors is just
like we want to sell stocks that have prior losses, because
you don't want to be seen as holding them when we file our annual report.
So let's relate January returns to past performance.
And we're going to do a simple regression where we look at what's the January return
during the first week in January,
and we'll also throw in this kind of last day in December as well.
Because there's some evidence of like, hey, the kind of January rebound
seems to start the last day of December but that's a kind of minor point.
Same results will hold if we just look at the first five days in January.
So look at this first week in January return and relate it to,
what was the performance of the stock in the past January to June period?
As well as the past July to December period?
And when we're looking at these kind of losses, that is just giving us,
what was the magnitude of the loss?
And that is something that's going to be negative, so if the loss was,
it fell 10% then this is going to be minus point one.
If the stock went up then the loss is 0.
Okay?
So let's look at the results over these three tax regimes.
And if you see these three stars,
it indicates statistical significance at the 1% level.
So what do we see for both tax regime I and tax regime II?
We see if you have losses during the past July to December,
you see those losses predict a higher January return.
So the way to think about this is if you have a loss through the prior July to
December of ten percentage points, that predicts a higher January return of 1.4 or
1.5 percentage points across these two regimes.
What's interesting is the effect of a loss in July to December
is higher than the effect of a loss from January to June.
You look at the coefficient loss July to December, it's always higher and
statistically higher in magnitude then the coefficient on the loss January to June.
Both in regime I.
And in Regime II.
Why is that the case?
Short-term losses are more valuable in terms of reducing taxes.
Over Tax Regime I and Regime II, it's only a six month holding period for short-term.
After six months, it becomes long term.
So losses that would've happened at the beginning of the year, January to June by
the time you get to the end of the year, those holding would've been long term.
So, they should matter less in December selling and thus, a January rebound.
So, the kind of key prediction here for Tax Regime I and
Tax Regime II losses at the end of the year.
Remember, a losses are negative.
Negative times a negative is a positive should lead to higher January returns
than losses that happened at the first part of the year.
Exactly what we find, but
what happens when you go to Tax Regime III when it's a 12-month holding period?
So, then losses in the first half of the year and
the second half of the year should matter in predicting the January return.
If I bought the stock in February, once I get to December,
that would still be a short-term holding, because a full year hasn't passed.
What do you see for these coefficients here?
They're basically statistically the same.
So when the tax regime is 12 months, losses during the first half of the year,
January through June losses during the second half of the year.
July through December both matter in the same way in predicting
the subsequent January affect.
So I think this is quite compelling evidence that the changes in the tax rule
seem to affect the January returns and
that suggests that the individual tax laws actually affect asset prices,
and returns around the end of the year.
So now, it's time to bring out for our pause, think and answer segment here.
So, two questions.
Why has the small-firm January effect declined over time?
We saw relative to the full sample since the early 80s,
the small-firm effect has declined over time and second question here.
Assuming the January effect persists,
what type of investor should be buying loser small stocks in December?
So, let's think about each of these two questions and then we'll come back for
my take on them.
Why has the small-firm effect declined over time?
Well, one, there could be the publicity, right?
We talked about those early academic papers in the 1980s.
Also, as we'll talk about later in this course, direct, individual ownership
of stock has fallen fairly dramatically from the early 1980s till now.
So if less individuals are directly trading stocks and taxable accounts,
that would suggest less tax-motivated trading, less potential for
these end-of-the-year patterns.
For the second question, assuming this effect persists,
if there is this January effect, Due to this tax motivated trading.
What type of investor should be buying this loser small-cap stocks in December?
Well untaxed institutions.
So if a taxable person is selling stocks that have gone down at the end of
December to get the deduction.
And temporarily the price is low because of the liquidity effect,
all this selling pressure.
And then there's a recovery in January when the selling pressure stops,
If I'm an untaxed pension fund or an untaxed individual,
why don't I buy this stock that the other person is selling in December and
then I get that January return?
Now, of course, if that happens a lot the prices in December, you know,
kind of go up so there no longer is that January return.
So, key takeaways There is a January effect in the return of small stocks,
but not in large stocks.
Indeed, this historical higher return of small stocks relative to large
stock that we've talked about before is concentrated in the month of January and
isn't present February to December.
The January effect is larger for stocks that have experienced losses
in the prior year and varies with changes in the capital gains tax rules.
So evidence again of taxes mattering.
Explorer notre catalogue
Rejoignez-nous gratuitement et obtenez des recommendations, des mises à jour et des offres personnalisées.
Coursera propose un accès universel à la meilleure formation au monde,
en partenariat avec des universités et des organisations du plus haut niveau, pour proposer des cours en ligne.
© 2018 Coursera Inc. Tous droits réservés.
