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Monday, June 13, 2016

The Brutal Math of a 60/40 Portfolio

Think only a bear market can keep returns of a 60/40 near 0%... think again.

Given the huge opportunity cost of allocating to cash or bonds at current yield levels, even generally optimistic return assumptions for stocks are enough to keep portfolio level returns near 0% real. The goal of this post is to set the stage for a future post where I hope to share potential solutions that may improve potential returns with a similar risk profile as a traditional 60/40 and to set proper expectations of what a 60/40 allocation dragged down by low yields may provide.

After-tax real return forecasts (see below for the formula used in the calculation)

  • Let's say you assume stocks will return 6% nominal going forward. 
  • After tax returns (assuming gains are taxed at the more favorable 20% capital gains tax rate) = 4.8% (6% x [1 - 20%]) 
  • After tax after inflation returns assuming a forecasted 2% inflation rate = ~2.8% (4.8% - 2.0%) 

  • Bonds will generally (best case scenario) return their yield (current yield to worst of the Barclays Aggregate Bond index = 2.0%) 
  • After tax returns assuming the less favorable rate applied to coupons (and a 35% tax rate) = 1.4% (2% x [1 - 35%]) 
  • After tax after inflation returns assuming the forecasted 2% inflation rate = ~-0.6% (1.4% - 2.0%) 

  • 60% Stocks = 2.8% x 60% = 1.68% contribution 
  • 40% Bonds = -0.6% x 40% = -0.24% contribution 
  • Total return = 1.45% real 
Throw on the ~1% fees many financial advisors charge and/or the lower yields many investors are accepting by taking less duration risk / diversifying U.S. bond exposure to even lower yields abroad and an investor may break through the 0% threshold even with a 6% stock forecast. This coming from an allocation that has a historical standard deviation of roughly 10% over time.

Initial takeaways 

The math above outlines the importance of:
  • Shielding returns from taxes whenever possible 
  • Keeping fees as low as possible (or ensuring you get something for your fees)
  • Seeking alternative sources of return (whether through allocation or alternative asset classes that now have a very low hurdle rate relative to bonds to be included)
  • Minimizing an allocation to negative real return asset classes

Tuesday, May 17, 2016

Can We Predict Forward Alternative Investment Performance?

My friend Ben from A Wealth of Common Sense poses the interesting question, How Should Alternative Investments Be Benchmarked? Please go read his post for a number of interesting thoughts on that topic. In this post, rather than rehash his arguments, I'll go a different direction and articulate what drives the performance of alternatives (i.e. hedge funds / liquid alts) to see if we can predict forward performance (which in a backwards way, may provide some insight into how an investor might think about benchmarking performance).

Low Interest Rates = A Headwind for Absolute Hedge Fund Performance

What's interesting to me is that one of the main reasons I regularly hear why investors are allocating to hedge funds, is actually a reason why hedge performance has been so disappointing. Back to Ben's post for a specific example in the form of a comment from his reader (bold mine).

Interest rates are too low and stock market volatility is too high so we have to hold some alternatives in our client portfolios. 
Low interest rates are actually a reason not to own alternatives. People seem to forget that alpha is a "cash plus" return stream. The excess performance of a hedge fund (with 100% of returns driven by alpha) will be a certain %, which added to the cash rate gets to the total return generated by the hedge fund. The same skill that generated a 10% hedge fund return when cash rates were 5% (5% alpha + 5% cash), only generates 5% when cash rates are 0%. As a result, all else equal, the lower the cash rate, the lower the relative performance of hedge funds.

Predicting Alternative Investment Performance

While interest rates are an important consideration when making an allocation to an alternative manager, they are not enough to predict future relative performance vs a traditional stock / bond allocation. One key is to look at the level of risk premia (both stock and bond risk premia).

Risk premia is:
The difference between the expected return on a security or portfolio and the "riskless rate of interest".

In my analysis I calculate the expected return on stocks and bonds as follows:
  • Stocks: CAPE yield (1/CAPE) - Source
  • Bonds: Long Term Bond Yields - Source
I then subtract out the riskless rate of interest (which I define as the average 7 year forward t-bill yield) to get the premia, while the 40/60 blend is a 40% equity risk premium / 60% bond term premium blend (given the average hedge fund beta is ~0.40). In this analysis, I forecast future cash rates moving up 50 bps / year to 2% and staying there (more on this later) to get the stock and bond term premia for forward years that have not yet occurred.

In terms of predicting alternative fund vs. stock / bond performance, the opportunity cost of allocating to a hedge fund is largest when these premia are high and lowest when they are low (or negative). As you can clearly see from the chart above, stock and bond risk premia were very low in the late 1970's / early 1980's when cash rates were elevated, high in the mid 1980's when Volcker was able to control inflation pushing down cash rates, subdued in the 1990's when stock valuations got extended, then huge in the mid to late 2000's after the financial crisis that pushed stock valuations lower and cash rates to 0%.

Given the above framework, you can see how the mid 1990's were a great time to be in hedge funds from both an absolute perspective (cash rates were high) and relative perspective (the equity risk premium was low), while the exact opposite situation has been true for the last 7+ years. The chart below takes the above starting risk premia levels since 1994 and plots them against the relative forward performance of the Credit Suisse Hedge Fund Index (I can only get returns starting in 1994) vs. a 40% stock / 60% allocation.

What Can We Predict from Here?

Given this analysis, it appears the opportunity cost of hedge funds is once again approaching "fair value" given the much lower bond term premium, BUT an allocation will be largely dependent on an investors view of the direction of cash rates. It is less important to relative performance whether cash rates are currently low, but whether they will stay low. Should they move much higher than the 2% modeled in my analysis, then now may actually be a good time think about alternatives.

Sunday, May 15, 2016

The Smoother "PATH": PutWriting At The High

The analysis presented below combines two separate frameworks that were previously outlined:

The first post outlined how avoiding bear markets (by only holding equities when they were near an all-time high) has lead to very strong risk adjusted returns, going so far to show the great performance of a strategy that only allocated to stocks when they were at an all-time high. The second post outlined what an investment in put writing provided and pointed out the surprising fact that selling puts on the S&P 500 has actually resulted in better risk-adjusted returns when markets were calm than when volatility was heightened (and premiums were higher). I recommend reading either / both if interested in more detail.

When Does Put Writing Make Money?
Selling puts make money when the premium collected is greater than the decline in the market (relative to the strike price) from the time the puts were sold to the time the puts expire (i.e. ignoring financing costs if you sold an at-the-money put, collected a premium worth ~5% of the notional value of the S&P 500, and the S&P 500 went down less than 5%, the trade was profitable). Thus, despite the lower premiums collected, selling puts more consistently make money when market volatility is low because the market is much less likely to decline (i.e. selling insurance to safe drivers is more lucrative even if you charge a lower premium).

Going one step further, the chart below shows all forward one month returns for the CBOE PutWrite Index and the S&P 500 Index only for periods when the S&P 500 reached an all-time high the previous month-end going back 25 years.

Highlighting the consistency of returns for both the CBOE PutWrite Index and S&P 500 when the previous month-end value of the S&P 500 was at an all-time high:

CBOE PutWrite
  • 11.1% annualized geometric returns
  • 4.6% annualized standard deviation
  • 2.9% annualized downside deviation
  • Positive 79% of the time
S&P 500
  • 8.5% annualized geometric returns
  • 10.3% annualized standard deviation
  • 4.8% annualized downside deviation
  • positive 60% of the time

The PATH Model
The model below is a simplified / lower risk version of one I've kicked around for a while, but it has resulted in an interesting historical path of returns.

The rules:
  • If the S&P 500 ended the previous month at an all-time high, allocate to the CBOE PutWrite Index (PATH = Putwrite At The High)
  • Otherwise, allocate to Aggregate Bonds
  • Levered version = 2x levered allocation to the CBOE PutWrite Index at-the-high financed at the applicable cash rate

The caveats of how this will perform going forward should be pretty obvious, namely that the path of the S&P 500 is hugely important.
  • If there is no new S&P 500 high, the strategy will simply sit in bonds (and yields are much lower)
  • If there is a huge market downturn in the period that puts were sold, that loss may take a LONG time to make up (especially at low yields)
Caveats aside, the relative historical returns of the non-levered model were ~2% higher annualized than bonds with an almost identical risk to the index, while the 2x levered version provided returns that were "stock-like" (~4% higher than bonds), but with a 60% lower standard deviation and a 90% lower max drawdown than the S&P 500.

At some point in the likely distant future, I hope to put out a white paper with a much more in-depth background and details of the broader model. For now, please feel free to reach out to me with any thoughts on Twitter @econompic.

Wednesday, May 4, 2016

Growth or Value in a Low Growth Environment?

Financial Advisor Magazine recently published an article by the CIO of LPL titled 'Value Comeback' making the case for Value. There were some interesting points in the article connecting the recent growth outperformance with lower interest rates and/or oil, but the following point on low growth being a driver of the growth outperformance did not make much sense to me.

One of the main arguments against value (and in favor of growth) in recent years has been the slow global growth environment. When there is not a lot of growth in the economy or corporate profits, then it logically follows that the market would pay a premium for the companies that are generating growth (what we have referred to as motorboats, which can grow without a macro tailwind, as opposed to sailboats, which need economic growth to grow). 
The data support this. Over the past 25 years, when economic growth is slow (real gross domestic product [GDP] below 2.5%), growth outperforms value by an average of 4.1%, and beats value two-thirds of the time.
This caught my eye because in a previous post I noted that despite the outperformance of growth over the past 3, 5, and 10 years, it wasn't multiple related (i.e. investors have not paid a larger premium for growth stocks). In fact, growth stocks have gotten relatively cheap by the measure of forward P/E (the current premium is about 20% for growth vs. the 30 year average of ~40%). In addition, I always assumed that growth did better during strong periods of high growth because that's when optimism tends to be highest and growth stocks become bid up during that exuberance (i.e. the roaring 90's).

So I ran the numbers for the same period that was reflected in the article, looking at Russell 3000 Growth and Russell 3000 Value (all cap indices) as my growth and value proxies. I then annualized the performance for each quarter when real GDP was < 0%, between 0% and 2.5%, between 2.5% and 5.0%, and 5%+. The results show value has historically done better in all environments EXCEPT when growth was quite high (above 5%).

Much of the historical outperformance of value did coincide with much higher valuations for growth stocks, so past outperformance of value vs growth may not happen even if growth remains sluggish going forward. In addition, the depressed price of commodities (due to the global slowdown) may make value (where most energy companies are classified) as the place to be if the economy expands quickly, However, it does clearly show that economic growth has been good for stocks in general and high levels of economic growth have historically been especially good for growth stocks.

Friday, April 29, 2016

Know What You Own: Alternative Funds Edition (Streamlined)

For the full wonky version of the below, please go here.

Below are the objectives / investment strategies of two different “alternative” funds pulled from the prospectus and/or annual report for each, along with high level details of how they were actually positioned as of their most recent semi-annual reports on 12/31/15. In this post I'll leave historical performance out of it (one has been horrific, one has been solid - which makes sense when you realize they are opposing strategies), as this post is meant to highlight the importance of looking under the hood, only allocating to strategies that you understand, and ensuring that the manager follows what has been outlined in their prospectus. This is especially important when it comes to alternative funds with less defined limitations (though in the case of Fund A... they seem to simply ignore these limitations).


Fund A: 
  • The Fund seeks to achieve long-term capital appreciation, with added emphasis on the protection of capital during unfavorable market conditions (page 1).  
  • The total notional value of the Fund’s hedge positions is not expected to exceed the value of stocks owned by the Fund (page 3).
Fund B: 
  • "Always hedged, all the time, using put options" (source)
  • "With no reliance on market timing or stock selection" (source)
To summarize, Fund A states it it can not have negative market exposure, while Fund B is described as always being hedged to the market (i.e. implies a 0% market exposure).


The chart below is my attempt to simplify the payoff structure of each Fund inclusive of all the options they have bought or written (go here for a full breakdown of the fund positions). Fund A sold deep-in-the-money calls that effectively neutralized the stocks held, leaving only the puts (meaning it is short the market). Fund B is a bit more complex, but is long the market on the way up (though less than 100%) and exposed to the market (though less than 100%) on the way down (with a relatively neutral position when the market is down ~5-10%).

  • Fund A states it can not have market exposure of less than 0%, yet was materially short the market 
  • Fund B implies it is has 0% market exposure, yet was materially long the market
So the two funds basically have:
  • The exact opposite stated investment strategies as one another
  • The exact opposite positioning as one another
  • The exact opposite positioning as their own stated investment strategy
And we wonder why there is investor confusion / disappointment?

As an aside... I find Fund B's strategy interesting.

Know What You Own: Alternative Funds Edition

Warning... I got way too wonky in this post. If you want a streamlined version of the below, go here.

Below are the objectives / investment strategies of two different “alternative” funds pulled from the prospectus and/or annual report of each, along with detailed analysis of how they were actually positioned as of their most recent semi-annual reports on 12/31/15. In this post I'll leave their actual performance out of it (one has been horrific, one has been solid - which makes sense when you realize they are opposing strategies), as this post is meant to highlight the importance of looking under the hood, only allocating to strategies that you understand, and ensuring that the manager follows what has been outlined in their prospectus, This is especially important when it comes to alternative funds with less defined limitations (though in the case of Fund A... they seem to simply ignore these limitations).


Fund A: 
Objective: The Fund seeks to achieve long-term capital appreciation, with added emphasis on the protection of capital during unfavorable market conditions. It pursues this objective by investing primarily in common stocks, and uses hedging strategies to vary the exposure of the Fund to general market fluctuations (page 1).  
Investment strategy: The investment manager expects to intentionally “leverage” or increase the stock market exposure of the Fund in environments where the expected returns from market risk is believed to be high, and may reduce or “hedge” the exposure of the Fund to market fluctuations in environments where the expected return from market risk is believed to be unfavorable (page 3). 
To make it abundantly clear how this fund defines leverage and hedging, the prospectus states.
Leverage: "The maximum exposure of the Fund to stocks, either directly through purchases of stock or indirectly through option positions is not expected to exceed 150% of its net assets" (page 3). 
Hedging: "The total notional value of the Fund’s hedge positions is not expected to exceed the value of stocks owned by the Fund, so that the most defensive position expected by the Fund will be a “fully hedged” position in which the notional values of long and short exposures are of equal size" (page 3).

Fund B: 
Objective: The Fund seeks income and growth of capital (page 1).  
Investment strategy: "The Fund's core strategy has been and will always be to purchase an underlying hedge at 100% of the notional value of the underlying through corresponding LEAPS put options and proportionally write shorter-term options against the long underlying equity ETFs and LEAPS puts. Premiums received from writing options represent income-type positions that are designed to take advantage of time decay and help pay for the cost of the hedge"(page 2). 
Elsewhere, Fund B is described as:
  • "Always hedged, all the time, using put options" (source)
  • "With no reliance on market timing or stock selection" (source)

To summarize... fund A states the fund can have exposure ranging from 0% to 150% (i.e. cannot go short), while Fund B is described as always being hedged the the market (i.e. implies a 0% market exposure) and uses the time decay (i.e. they are long theta) to pay for the hedge.


While I hoped to stay out of the weeds with regards to option pricing, the tables below break down the fund exposures inclusive of the options bought or written as of 12/31/15. While funds often mark options at market value (i.e. how much you can buy or sell them at that day's close), economic exposure is what matters to an investor (i.e. if the market moves up or down, what is the impact to the portfolio). As an example, stock futures are marked-to-market every day, meaning they have a market value of ~$0 at the end of the day. Yet I think we can all agree that a fund with 3x notional exposure to stocks (i.e. triple levered ETFs) have 300% exposure to the stock market, not 0%.

To calculate the real exposure, you first need to calculate the notional exposure of the options and delta adjust them to account for how in or out of the money the options are (delta is the degree to which an option is exposed to shifts in the price of the underlying asset). Walking through the table columns from left to right...
  • Contracts: # held or written as of 12/31/15
  • Expiry: when the option contracts expire
  • Index Value: the value as of 12/31/15
  • Strike: the level at which the stock is in- or out-of-the money; puts are in-the-money when they are below the strike, calls when they are above
  • Notional: contracts x 100 (notional value of $100 times the index value per the terms of these option contracts)
  • Delta: the degree to which an option is exposed to shifts in the price of the underlying asset (a deep in the money call option has a delta of 1 meaning it provides the same exposure as the underlying stock market, while a negative sign indicates it is short that exposure which results from buying puts or selling calls); note I assumed an 18% volatility figure to calculate the options for all periods, which is right around where the VIX was as of 12/31/15 as is close enough for this.
  • Delta Adjusted Exposure: this is the economic exposure that investors are actually exposed to

Now let's take a look at what exposure the two funds had as of 12/31/15 (if anyone sees an issue with any of my calculations, please let me know).

Fund A (source)

Delta adjusted option exposure of -$900 million relative to the $600 million market value of the fund's stocks as of 12/31/15 = net -$300 million market exposure (i.e. it was 50% short the market as fund AUM was ~$600 million).

Fund B (source)

Delta adjusted option exposure of around -$500 million relative to the ~$1.27 billion market value of the fund's stocks as of 12/31/15 = net $777 million market exposure (i.e. it was ~60% long the market as fund AUM was ~$1.3 billion).

Long Option Exposure

Short Option Exposure / Net Fund Exposure

The chart below is my attempt to simplify the payoff structure of each, ignoring the time decay of options held (time decay is a huge drag on Fund A and a substantial tailwind for Fund B). Fund A sold deep-in-the-money calls that effectively neutralized the stocks held, leaving only the puts and a net short position. Fund B is a bit more complex, but is long the market on the way up (though less than 100%) and exposed to the market (though less than 100%) on the way down (with a relatively neutral position when the market is down ~5-10%).


  • Fund A, which states it can have market exposure between 0% to 150%, was materially short the market 
  • Fund B, which implies it is has 0% market exposure, was materially long the market
So the two funds basically have:
  • The exact opposite stated investment strategies as one another
  • The exact opposite positioning as one another
  • The exact opposite positioning as their own stated investment strategy
And we wonder why there is investor confusion / disappointment?

As an aside... I find Fund B's strategy interesting.

Tuesday, April 12, 2016

What You Pay Matters Less than What You're Paying For

Patrick O’Shaughnessy has a great post, The More Unique Your Portfolio, The Greater Its Potential, outlining how active share is what drives the level of potential before fee excess return for an active manager. If you allocate to active managers... go through it twice. As Patrick notes:

If there is a lot of overlap between your portfolio and the market, there is only so much alpha you can earn. This is obvious. Still, when you visualize this potential it sends a powerful message. Active share—the preferred measure of how different a portfolio is from its benchmark—is not a predictor of future performance, but it is a good indicator of any strategy’s potential excess return.
In other words, active share is an important metric as it shows what an investor is actually paying for (especially true now that the cost of beta is essentially zero). So, while an investor still needs to fully understand and believe in an active manager's philosophy, process, and discipline, the cost paid may be less important in isolation. What may be more important is the cost paid relative to what you are paying for.

You don't always get what you pay for

Using Morningstar Large Blend category data (the most plain vanilla of the plain vanilla), the below charts look at the relationship between fund expenses and active share for funds with active share > 20 to see what an investor is actually paying for. I narrowed the universe down further to funds benchmarked against the S&P 500 and then I did my best to strip out funds with style tilts (i.e. there were some growth, value, and dividend funds that fell in the category). One issue that remains is the below is screened by oldest share class to exclude duplicates, so there is some apples to oranges comparisons going on in terms of share class (though almost all of the funds are A share).

The first chart highlights the weak relationship between expenses charged and active share provided. An extreme example that was stripped out of the analysis that I came across was an S&P 500 index fund charging 1.60% with a 4.75% load.

The second chart compares the expense ratio against expenses normalized for active share (i.e. expenses charged divided by active share). Given the weak relationship between expenses and active share from the first chart, it should be no surprise that higher expenses generally mean higher normalized expenses too. This is a reason why funds with higher fees are less likely to outperform than funds with lower fees... investors are generally not getting a higher active share product for those higher costs.

Things get more interesting when you compare normalized expenses against active share. Here you can clearly see that the normalized expense ratio generally moves lower as active share increases. In fact, some of the cheapest normalized funds are those that have a much higher active share and may charge a slight premium.

Taking advantage of the "fungibility" of funds

While active share is a good indicator of a strategy's potential excess return gross of fees, an investor may not want to take as much relative risk or pay the fees embedded in the highest active share products. The good news is an investor can create a lower cost / lower active share solution through an allocation to higher active share managers and index funds... even if the cost may initially appear slightly higher in absolute terms.

For example... assuming an investor believes the capabilities of manager A and B are identical and has a 20% active share target. Yet:
  • Manager A costs 50 bps for 20% active share = 50/20 = 2.5 bp normalized expense ratio
  • Manager B costs 100 bps for 50% active share = 100/50 = 2.0 bp normalized expense ratio
While manger A is cheaper in terms of the absolute expense charged, manager B is clearly cheaper it terms of the expense per unit of active share. As a result, an investor can allocate 40% to manager B and 60% to a ~0 bps passive ETF, The result is the same 20% active share (40% allocation x 50% active share = 20% active share) at a lower cost (100 bps x 40% + 0 bps x 60% = 40 bps vs. the 50 bps for manager A).


When choosing an active manager, confidence in the team, the process, and the discipline the team has in following that process through various market cycles continues to be of obvious importance. As important is not the cost you pay in absolute terms, but rather what you pay for each unit of the skill they are selling.

Thursday, April 7, 2016

Active Management is Far From Dead

Eric Balchunas has an article on Bloomberg titled The Financial Industry Is Having Its Napster Moment asking "Has the music stopped for the financial industry?", sharing the following chart of flows since 2007.

He forecasts ~$1 trillion in outflows from higher fee active management every 4 to 5 years from here, which he believes will cause a material decline in revenue for investment management firms.
In other words, about $2.5 trillion in assets could migrate out of active mutual funds over the next decade. That money will shift from producing $18 billion in revenue to producing just $5 billion. That’s $13 billion less in revenue in the next decade and upward of $30 billion over the next 20 years. All this could be expedited by the new fiduciary standard—as well as a parallel trend that sees institutional funds moving toward passively managed investments, too.
As I'll outline below, while this is true in a vacuum... it misses an important aspect of what really drives asset growth (hint... for established players, it's not flows).

Flows Do Not Equal Asset Growth = The Industry is Still Thriving

Given this level of flows to passive from active, you would likely guess that the level of AUM for passive solutions would have grown by a much greater amount than active mutual funds, especially following the failure of active managers to protect investors during the financial crisis... right?


Given the huge AUM "advantage" of the much more mature mutual fund business, market appreciation has allowed domestic equity active managers to grow AUM by exactly the same amount within the domestic equity category, almost $1.8 trillion each since March 2009 market lows (data from Morningstar).

And while the Bloomberg article focused on domestic equities, let's take a look at the whole mutual fund / ETF complex..

That's a HUGE jump in AUM (and revenues) for investment management firms and given the huge operating leverage these managers employ (i.e. scale is huge for the bottom line) they are printing money.

So... unlike the music industry that has seen revenues slump as the preference for a high fee record slice has shifted to low fee digital, all while the overall music pie remains small (or has gotten smaller), the preference for a passive slice of the investment pie has occurred while that pizza has grown from a small to a large one.

If you believe capitalism isn't dead (I don't), then overall AUM in domestic equities (and especially across all global assets) will continue to expand... likely faster pace than active will be replaced.

Long live active management!

Monday, March 21, 2016

Buyback Performance Demystified

Earlier this month, in my post Stock Buybacks Demystified I attempted to remove some of the mystery surrounding buybacks, showing they are no different from an economic perspective (if you ignore the impact of taxes and the effects of signaling) than dividends. Given the recent outperformance of dividend paying stocks (as defined by those in the S&P 500 Dividend Aristocrat index) vs. stocks engaged in buybacks (as defined by those in the S&P 500 Buyback index) over the last year, I thought it might be helpful to demystify what has driven the recent outperformance of dividend stocks, share the historical performance of each, and outline some forward expectations for relative performance given where we currently sit.

Background: Buybacks have consistently outperformed since inception 

The first chart shows the growth of $1 invested in dividend stocks vs $1 invested in buyback stocks going back to the inception of the S&P 500 buyback index in early 1994. What we see is pretty consistent underperformance of dividend paying stocks over time that has compounded to 2% / year outperformance of the buyback stocks since inception (note both have outperformed the S&P 500). 

Background: Relative performance is highly mean-reverting
The second chart shows the relative performance of dividend stocks less buyback stocks over 12-month rolling periods going back to the inception of the S&P 500 buyback index. What we see is:
  • Pretty consistent underperformance of dividend paying stocks (most of the relative return series is negative) 
  • Mean-reversion characteristics (when one outperforms the other materially, it tends to bounce the other direction pretty quickly)
  • Dividend outperformance during periods of market stress 

Why have dividend stocks outperformed recently? Valuation differences
In addition to market stress that favors dividend stocks, the change in relative valuations have driven dividend stocks (i.e. it's been seemingly more technical than fundamental). The chart below shows valuations (i.e. P/E) of the dividend and buyback indices as of month-end February and as of a year ago. While dividend stocks were richer by this measure even a year ago, valuations among dividend stocks have held up pretty well. On the other hand, valuations among buyback stocks have gotten materially cheaper, driving the relative underperformance of buyback stocks and creating a huge valuation gap between the two. 

What now? 
The final chart shows the impact of shorter-term (12-month) relative performance between dividend and buyback indices on longer (3-year) forward relative performance. We can see:
  • Pretty consistent underperformance of dividend paying stocks over most three year periods 
  • Mean-reversion characteristics kicking in when dividend stocks have outperformed by the 10% level they have over the last 12-months (when dividend stocks have outperformed by 10% or more over a 12-month time frame, they have underperformed by an average of 6.4% / year for the next three years)

Neither dividend stocks or buyback stocks outperform in all periods or market environments, but under the view that the underlying economy appears to be holding up, current valuations, the historical outperformance of buyback stocks, the mean-reversion characteristics of buybacks (following recent dividend outperformance), and certainly the tax efficiency of buybacks all seem to support a tilt toward buybacks. 

Wednesday, March 9, 2016

Stock Buybacks Demystified

Based on my Twitter feed, stock buybacks seem broadly misunderstood in terms of what they are meant to accomplish (to redistribute excess capital back to shareholders) and the impact they have relative to dividends. As an aside, I also don't understand the following typical complaints:
  1. Buybacks are done when stocks are rich: if the stock of a company performing buybacks is "rich", then why are you owning it to begin with?
  2. Buybacks are often done during bull markets and stop during bear markets: that is due to the fact companies often have higher earnings and more excess cash available to distribute during bull markets

As a result, I wasn't too surprised when the below chart made the rounds yesterday, along with the following implications:
  • Stock performance is higher only because of financial engineering
  • Households are scared of equities and are poor market timers

In this post I'll provide the case for why (ignoring taxes and the effects of signaling):
  • Buybacks and dividends are economically identical
  • Buybacks are an incremental driver of the outflows we've seen from households
  • Why flows (both inflows and outflows) do not relate to demand / why households almost always have outflows

Buybacks and Dividends are Economically Identical

Excluding the potential signaling or tax effects of buybacks vs dividends, buybacks and dividends are identical in terms of overall economic impact. For example, assuming the following:
  • Corporation X has $2.5 billion in excess cash to distribute back to shareholders
  • Corporation X has a market cap of $5 billion ($2.5 billion enterprise value + $2.5 billion cash)
  • Corporation X has 100 million shares outstanding, priced at $50 / share (100 million shares x $50 / share = $5 billion market cap)
  • Corporation X will earn $1 billion ($10 / share) the following year
  • Shareholder X owns 100 shares and has spending needs of $1000
  • 100% of Shareholder X's wealth and income comes from their stock ownership

Situation 1: Corporation X distributes the excess cash to their shareholders via a $2.5 billion buyback
  • Corporation X buys back $2.5 billion of their shares at $50 (i.e. they retire 50 million shares)
  • Corporation X now has 50 million shares outstanding at $50 = $2.5 billion market value (all made up of their enterprise value)
  • With no dividend payment, shareholder X will need to sell 20 shares (x $50) to meet their $1000 spending need, meaning they will have 80 shares x $50 = $4000 in Company X stock
  • Corporation X will earn $1 billion next year or $20 / share given their 50 million shares
  • So... next year Shareholder X will be entitled to a $20 x 80 = $1600 of those earnings

Situation 2: Corporation X distributes the excess cash to their shareholders via a $2.5 billion dividend
  • Corporation X distributes $2.5 billion via dividend ($25 / share)
  • Corporation X still has 100 million shares outstanding, but at an enterprise value of $2.5 billion each share is now worth $25 / share
  • Shareholder X can meet all of their spending needs through the dividend distribution (1000 x $25 = $2500 dividends) and after spending $1000 still has $1500 cash remaining
  • Shareholder X can use the excess $1500 to buy 60 more shares at $25 share, meaning they now own 160 shares at $25 = $4000 in Company X stock
  • Corporation X will earn $1 billion next year, which is $10 / share given 100 million shares
  • year Shareholder X will be entitled to $10 x 160 shares = $1600 of those earnings

A table summarizing the above example (click for larger image)

What has changed? 
  • # of shares outstanding
  • Price of shares outstanding
  • Earnings per share
  • Shareholder X becomes a net seller of shares in the buyback scenario

What has stayed the same?
  • Enterprise value of the firm ($2.5 billion)
  • The overall level of earnings ($0.5 billion)
  • Earnings Shareholder X is entitled to next year ($1600)
  • Overall market value / demand for Company X stock from Shareholder X ($4000)
  • Overall net purchases of the stocks ($1.5 billion)*
* In the buyback scenario, $2.5 billion is bought back by Company X, but if all shareholders acted like Shareholder X, they would sell $1 billion for their spending needs ($1.5 billion net purchases); in the case of dividends, of the $2.5 billion distributed, $1 billion is spent, and the same $1.5 billion is used to buy back shares with the excess cash.

Household Flows Don't Matter / Should be Negative

As highlighted above under 'what has changed', household outflows are in fact impacted on the margin by the form of capital distribution (i.e. whether it is received via buyback or dividend). In the case of a buyback, households are simply creating their own dividend through the sale of shares. Given the two situations are identical in terms of overall demand for Company X stock (demand at time 0 was $5000 worth of stock, post spending it was $4000), we can see why flows really don't matter.

In fact, while the initial chart circulating through Twitter highlights the negative flows from the household sector for stocks from 2008-2015, what may be a surprise is that the overall level of stocks held by the household sector (i.e. a better measure of demand) jumped from $5.4 trillion at the end of 2008 to more than $12.7 trillion over that same time frame (as of 9/30/15  - the latest z.1 report), a normalized increase of 37% of GDP to 70% of GDP.

But a key point is that household net flows for a mature / functioning economy should be negative... when markets have positive returns, investors put in less money today than what that investment should compound to when they make withdrawals in the future. Thus, it should be no surprise that net flows from the household sector have historically been negative over all longer periods of time going back 60 years, while the amount of stock held by the household sector has continued to move higher.

To summarize... the form of distribution really does not matter and buybacks are not evil... the next time you hear someone state buybacks are the cause of the run up in stocks, try replacing the word buyback with dividend.

"Stocks are up because of a huge increase in dividends" sounds a lot less controversial than "stocks are up because of a huge increase in buybacks", though they are both identical signs that the performance has been driven by an improvement in fundamentals and an increase in cash flows.

Wednesday, February 17, 2016

Combining Momentum and Dollar Cost Averaging for Smoother Results

Josh Brown (i.e. The Reformed Broker) recently shared the aptly titled post How to Make Volatility Your Bitch highlighting how dollar cost averaging into a volatile market can lead to higher overall returns:

Door number one – you spend 15 years putting $1000 into an investment every month for 15 years, with the possibility of seeing that investment get cut in half twice.
Door number two – you spend 15 years putting $1000 into an investment every month for 15 years, with the same annual performance of what’s behind door number one, but no drawdowns.
Which would you choose? 
On the surface, you’d choose door number two. Of course, who wouldn’t? 
But it’s the wrong choice. The trick here is to remember that you’re adding to the investment at a rate of $1000 per month. That’s when you realize that door number one, with it’s twin 50% crashes, is the better option.
His point is an important one for long-term investors... you would rather pay less (than more) for a security today if it is worth more in the future and for long investment horizons that has typically been true. So in general, regularly contributing to your retirement (or other long-term goals) is good practice.

The Caveat

BUT there is a caveat... dollar weighted returns are only better than time weighted returns if the dollar weighted price you paid was lower than the price at the ending date. As dailyVest outlines (bold mine):
In contrast with a time-weighted approach, the dollar-weighted rate of return calculation method does measure the size and timing of cash flows, as well as the investment performance. Thus,
  1. Periods in which more monies are invested contribute more heavily to the overall return – hence the term “dollar-weighted” 
  2. In this case, investors are rewarded more for larger investments made during periods of greater price appreciation 
Given we are so close to the all-time high in the S&P 500, chances are each dollar invested over the last 15 years was below (or well below) the current price, resulting in more investments having greater price appreciation and dollar weighted returns > time weighted returns. So... rather than looking at just the current 15 year period, let's go back and look at 15 year periods ending 5 and 10 years back (which end at less of a peak) to see how well the same door number one vs door number two worked out.

Note: the analysis below shows $1000 invested each month in the S&P 500 and in a return stream with identical 15 year time weighted returns, but with 0% volatility.

Dollar weighted returns > Time Weighted Returns over Most Recent 15 Years

Dollar weighted returns < Time Weighted Returns over 15 Years Ending 2010

Dollar weighted returns < Time Weighted Returns over 15 Years Ending 2005

In these examples we see just how important the ending point is in determining which return stream "wins", as well as how important the end date is in the overall growth of the $180,000 contributed (which is a reason why investors generally should derisk as they approach retirement). It also outlines why dollar cost averaging into a solution that can protect against the downside may be beneficial relative to a buy and hold strategy by limiting the amount of dollar weighted contributions made at poor entry points.

Dollar Cost Averaging in a Capital Preservation Strategy: The Case for Momentum

Because I have the urge to compare all buy and hold strategies with momentum, the below replicates the above charts and adds a momentum equity curve with this simple rule at month-end:
  • If S&P 500 > 10-Month Moving Average, then S&P 500
  • Otherwise, Aggregate Bonds
Similar to what is shown in the charts above, the charts below outline the growth of $1000 a month into the S&P 500, an identical time weighted return series with zero volatility, and the above momentum strategy.

The momentum strategy provided much more consistent dollar growth in all three time frames and in these specific windows materially outperformed both a buy and hold and 0% volatility iteration (this will not necessarily be the case in all periods - especially in up and to the right equity markets). So... perhaps it's the combination of consistent contributions and a strategy more focused on capital preservation that can more easily make volatility your bitch (without the volatility).

Wednesday, February 10, 2016

Avoiding Bear Markets to Improve Risk-Adjusted Returns

Ben Carlson of A Wealth of Common Sense has a recent post, When Global Stocks Go On Sale, outlining that it is typically a pretty good time to be buying when the MSCI World stock index is in a 20% or greater drawdown.

His insightful takeaway and chart outlining the historical drawdowns and forward performance of the index is below:

There were only two times out of the ten bear markets where stocks weren’t higher one year later. Only once were stocks down three years later. And there was never a period where stocks weren’t higher five years after initially falling 20%. The paradox of investing is that the best times to put your money to work are often when things seem like they’re never going to get better.

While I in no way disagree with his insight, especially for a buy and hold investor thinking of selling, I thought it would be fun to share the completely opposing strategy that avoids these periods of distress, as well as one that avoids stock exposure after even one month of negative performance.

Avoiding Extended Drawdowns May Improve Risk Adjusted Returns

As I outlined in a previous post, Using "Normal" Drawdowns as a Timing Signal, an investor who sold their S&P 500 allocation whenever the S&P 500 index was in a drawdown of 10% or more, and instead held bonds, had similar long-term returns as a buy and hold investor, but with materially less risk and drawdowns.

A similar situation has played out for investors allocated to stocks within the MSCI World index when drawdowns were less than 10% or U.S. treasuries when the MSCI World was in a drawdown greater than 10%, while a 20% threshold wouldn't have held up quite as well as the 10%, but would have provided roughly similar returns with less risk than a buy and hold investment.

What gives?

The reason for the improved risk-adjusted performance has been the power of momentum within the MSCI World index during drawdowns. When the MSCI World index ended a month at a roughly 10% drawdown, it often moved lower... sometimes much lower. At a 20% drawdown, only 2 of the 5 times was this in itself a decent short-term buying opportunity (highlighted in green). The other 3 times presented a better opportunity further down the road.

Buying Only at the Peak

Taking this "drawdown avoidance" to the extreme, let's see how an investor in the MSCI World index would have performed if they only bought when it was making new end-of-month highs. In this example, an investor is only holding the MSCI World index if the previous month was at an all-time high, otherwise U.S. Treasuries.

While there were long periods of relative underperformance (and this is an extremely high turnover strategy), the resulting performance and lower risk offers some insight into how a strategy that is less exposed to risk, yet can avoid loss of capital, may actually be able to improve absolute and relative performance.

Wednesday, January 27, 2016

The Case For High Volatility Strategies

Which investment would you prefer to invest in to diversify your existing stock allocation? 

Asset A with an expected:
  • 3% annualized return
  • 3.5% annualized standard deviation
  • 0.00 correlation with your existing investment
Asset B with an expected:
  • -5% annualized return
  • > 50% annualized standard deviation
  • 0.00 correlation with your existing investment

Easy question right? Perhaps not.

Asset B may actually improve long-term returns and reduce risk at the portfolio level, whereas an investment in Asset A may just be a drag on performance. This post will walk through an example, outline the math behind the results, and hypothesize how an investor may want to think about this phenomenon. Going one step further, I will outline how this may, in part, explain the low volatility anomaly (one example being that low-volatility stocks have produced higher risk-adjusted returns than high-beta stocks in most markets studied).


The chart below outlines the performance of an investment in the S&P 500 (using actual monthly S&P 500 returns) going back to the SPY ETF inception (I was being lazy), as well as a monthly rebalanced allocation consisting of a 90% weight to the S&P 500 and a 10% weight to:: 
  • Asset A: which reverts monthly from negative to positive performance (-0.75%, +1.26%, -0.75%, +1.26%), compounding to a 3% annualized return at a 3.5% standard deviation; in the chart below this assumes price action of $100 to $99 to $100 to $99... but with an incremental 3% return built in.
  • Asset B: which reverts monthly from negative to positive performance (-15.4%, +17.2%, -15.4%, +17.2%), compounding to a -5% annualized return at a 56.5% standard deviation; in the chart below this assumes price action of $100 to $85 to $100 to $85... but with an incremental -5% negative return built in.

Despite the 8% annualized outperformance of asset class A vs B that compounded to a 100% gain in asset A and a 70% decline in asset B, the 90% stock / 10% allocation to asset B results in a combined portfolio with higher returns, a higher sharpe ratio, and a lower drawdown relative to an allocation to the positive returning asset A (the benefit of the allocation to asset A was the reduced standard deviation as that allocation reduced risk asset exposure by 10%).

We see below how much asset B benefits the portfolio when both both asset A and B are on equal return footing.

What gives?

William Bernstein wrote a great piece on the topic back in 1997 titled The Rebalancing Bonus. The whole article is worth a read, but he shares the following formula that calculates the "bonus" received by rebalancing across asset classes.

RB1,2 = X1X2 {SD1SD2 (1 - CC) + (SD1 – SD2)/ 2}

RB = rebalancing bonus
X1 = allocation weight to asset 1
X2 = allocation weight to asset 2
SD1 = standard deviation to asset 1
SD2 = standard deviation to asset 2
CC = correlation coefficient

Before you complain too much about the math, I'll walk through the equation from left to right (assuming "all else equal") with the applicable points to the example above in bold:
  1. A more balanced blend (i.e. a closer to 50/50 weighting) will provide a greater rebalancing bonus
  2. A higher standard deviation of either asset class will result in a greater rebalancing bonus as an investment gets "more bang for your buck" 
  3. A smaller correlation (or negative correlation) will result in a greater rebalancing bonus 
  4. A larger difference in the standard deviation of the two asset classes will result in a greater rebalancing bonus
In the case of a higher volatility solution, bullets #2 and #4 both result in a higher rebalancing bonus and higher return (all else equal). In my example, the rebalancing bonus went from roughly 10 bps given a 10% allocation to asset A to 150 bps given a similar 10% allocation to asset B.
Asset A: RB = 90% x 10% [~15% x 3% (1-0) + (~15% - 3%)^2/2] = ~10 bps
Asset B: RB = 90% x 10% [~15% x 56% (1-0) + (~15% - 56%)^2/2] = ~150 bps
Given the 10% allocation, the return differential of 8% (the 3% return for asset A less the -5% return for asset B) x the 10% weight is only 80 bps, significantly lower than the benefit of the rebalancing bonus. In this example, in order for the two blended portfolios to have a similar return, the return gap between asset A and B must be closer to 14%.


From an asset allocation perspective, the above has a number of implications.

For one, it certainly makes the case for an allocation to strategies uncorrelated to an existing portfolio that have higher levels of expected volatility. In my opinion, the most obvious strategy that is largely under-allocated to is managed futures and to a lesser extent certain hedge fund styles and (until the last 10 years when everyone piled in)... commodities. I would also note that return expectations for the traditional diversifier, core bonds, are quite low and volatility of those returns are anticipated to remain low (thus a rebalancing bonus near 0), thus an allocation to a high volatility diversifier only needs low (or potentially negative expected) returns to make sense.

Another potential implication of the positive impact higher volatility strategies have on the rebalancing bonus is that this may partially explain the low volatility anomaly seen within asset classes, such as within stocks and bonds. When viewed in isolation, the outperformance of less volatile asset classes seems like an anomaly, but when viewed within a broader portfolio construct it makes sense that these lower volatility investments may need a higher expected return to draw in investors.

Using the rebalancing bonus formula and the following inputs which go back to the December 1990 inception of the S&P 500 High Beta and S&P 500 Low Volatility indices, we get the following rebalancing bonuses despite the higher correlation of the S&P 500 High Beta index with the S&P 500 index:
High Beta: RB = 50% x 10% [14.4% x 28.2% (1-0.89)) + (14.4% - 28.2%)^2/2] = 35 bps
Low Volatility: RB = 50% x 10% [14.4% x 11.0% (1-0.75)) + (14.4% - 11.0%)^2/2] = 11 bps
Pretty close to the 38 bps and 12 bp rebalancing bonus they provided in reality. In this instance, that 26 bp differential makes up ~25% of the excess performance a 50/50 S&P 500 / low volatility blend over that time frame.

Monday, January 25, 2016

Are Stocks Cheap? Checking in on Current Valuations

I'll leave it to others to chime in whether forward P/E's are useful or not given the fact they typically overstate earnings and I'll ignore that earnings may be at a cyclical peak (more on the latter here). As an aside, technicals in the market are filthy, as most short-term signals I look at are providing caution (example here). BUT, based purely on current forward P/E's relative to their own history, both large growth and large value stocks look awfully attractive if you are of the belief that the recent market noise is just noise vs. a sign of recession.

How attractive?

The below chart plots all quarterly forward P/Es against the forward 5-year annualized returns of both indices going back to the 1979 Russell inception of each. As of January 15th, the forward P/E of large value breached 14x while large growth went sub 17x, both historically great valuations to be buying at for the longer-term.

Highlights include that the average forward 5-year annualized returns of large value / growth were 13.9% / 16.1% when the P/E was below current levels and only 7.6% and 5.5% when above (and growth has never had a negative 5-year return when the forward P/E was this low).

Monday, December 14, 2015

Tweeting High Yield: A Round Trip in Investor Sentiment

With high yield all the rage these days, I thought it might be worthwhile aggregating tweets / posts going back to the beginning of this credit cycle to outline where we've come from and to share some thoughts on where we might be going. Curious if this format is helpful or too disjointed.

Backdrop... how did we get from the distressed 2008 (a 20%+ index yield), to sub-10% yields and a risk on mentality?

In March 2009, corporate bonds appeared to be a screaming buy and the Fed had an outsized impact getting spreads (and yields) much lower - much quicker than I thought was possible.

Once things calmed, why was there a reach for yield? Because it was the only place where yields were high.
Why are Investors are Reaching for Yield?: Because high yield is just about the only place you can get yield...
Despite the reach, I didn't mind high yield back in 2012 when rates backed up to 8% given where we seemed to be in the credit cycle (i.e. early).

When did things get frothy? I'd say early 2013 when Yields went sub-5%

Yields went from over 8% to under 5% within 6 months. At that point (and since), I could not get my head around high yield valuations.
Especially when viewed relative to stocks, once the yield on high yield bonds < earnings yield on stocks.
I was far from the only person who saw the froth in high yield
High yield sentiment seemed formed by the strong 5 year performance of the asset class. But perspective on how that return was achieved appeared missing:
Interesting back and forth in comments of this tweet. Some very smart people couldn't see a situation I thought / think has a decent probability. High yield underperformance even without stock underperformance given extreme valuations of high yield.

High Yield Sentiment Flashed Warning Signs in 2014 - Very Briefly

The sentiment shift and my view that high yield investors could be well over their ski's became very apparent when high yield "sold off" just 2% in fall 2014 and investors viewed that as abrupt:
Despite that "sell-off", yields in the lowest quality segment were still absurdly rich, but investors calmed their fears and dove back in, despite crazy yields.

Recent Views: The Sell-off was Expected - It Doesn't Seem to Be the Crisis Others Want to Make It

Which gets us caught up to this year when I brought my blog back after a three year hiatus and I jumped right into an area of the market I felt was misunderstood:
Yet, DESPITE my views of how mispriced things were, until financials within high yield become more stressed, I am less concerned about the recent sell-off's impact on the overall market (though things can / do change quickly):
This is supported by the perspective on where current yields are (yields still aren't all that high) and relatively contained within energy:
In times like this, perspective is much needed (i.e. things haven't been bad by historical standards):
If an allocation to high yield is to be made, note that lower quality high yield has not led to historical outperformance:

Wednesday, December 9, 2015

It's Generally Smart to Avoid Credit Risk

I've previously outlined that high yield credit risk is typically less ideal than simply gaining credit exposure through stocks and rate exposure through bonds. Now Larry Swedroe outlines the case for avoiding investment grade credit risk altogether.

There are many well-documented anomalies in finance. Among them is the surprisingly small return that investors historically have earned for taking credit risk in fixed-income markets—the default premium, as measured by the difference in returns between long-term Treasurys and long-term corporate bonds, has been only about 0.3%—and that stocks with a higher risk of defaulting on debt have produced lower returns.
Going back to 1988, which is as far back as Barclays breaks down the returns of the Long Corporate Bond index into the contribution from credit and rates ex the spread, the return from the credit component has actually been slightly negative at -0.09% annualized vs the 8.12% return for a like duration Treasury bond. A similar story plays out in intermediate corporate bond space, where the credit spread contributes only 0.37% of the 7.24% return for the Barclays Corporate Bond Index since 1988.

The story is more nuanced than "credit always underperforms the yield" as yield is generally a great predictor of future returns, but yield should generally be viewed more as the ceiling for future returns than actual future returns. The issue is when there is stress in the market, such as during the financial crisis when 13 year cumulative performance (the rough duration of the index) of long corporate bonds underperformed the yield's "predicted" return by almost 80% (the 13 year forward performance starting in 1995 ended during the 2008 meltdown).

My general view of credit is to avoid it unless you feel you are being more than fairly compensated. Even if you miss shorter periods of relative outperformance (vs treasuries), allocating only when credit looks like a screaming buy will likely result in a much better long term return profile. In the case of long corporate bonds, allocating only when the spread of long corporate bonds to treasuries was greater than 200 bps (something that occured just 20% of the time), returned 1.1% annualized more since that same 1988 start.