Tuesday, June 23, 2015

Fad Investments (the Case of Good Harbor)

Investment News outlines an arbitration request by an investor seeking damages for being placed in two funds; one to F-Squared (an outright fraud) and another to Good Harbor's U.S. Tactical Core Fund (GHUIX).

The adviser placed approximately $900,000 of the investor's savings, which his lawyer said was the vast majority, in products managed by two so-called ETF strategists. More than half went into an F-Squared's AlphaSector Allocator Select, and the remainder went into Good Harbor Financial's U.S. Tactical Core product.
A quick look at the insanely good returns of the black box Good Harbor strategy prior to their fund launch (this was for Good Harbor's non-wrap and wrap accounts).

At roughly that time, a salesman at my former firm would rave about the returns of the strategy / drool at the commissions their quickly expanding distribution team was capturing (see fund flows below). I remember him sharing that flows were in the billion plus per quarter range (I can't verify that figure, but given the fund is only a fraction of firm's AUM that seems plausible).

To no surprise of anyone that knows me, I tried to figure out what they were actually doing, using the following Good Harbor objectives as my starting point.
  • Long-only stock exposure with reduced beta
  • Seeks to outperform the Standard & Poor's 500 Total Return Index by allocating investments tactically across various asset classes
  • Designed to align with US stocks during sustained bull markets
  • Designed to move defensively to US Treasuries during sustained bear markets
  • Use of leverage

Through a bit of trial and error, I backed into results that looked awfully similar using the following simplistic rules:
  • 3 and 6 month rolling returns (i.e. 2 paths)
  • If S&P 500 > Long Treasuries, allocate to the S&P 500
  • If S&P 500 < Long Treasuries, allocate to the Long Treasuries
  • 1.2x leverage

I hadn't thought about the above model (or Good Harbor for that measure) in more than 2 years, but when I came across the article I thought it would be interesting to dust off the model and compare the results of Good Harbor's strategy vs. my own (in the below, returns past January 2013 are the institutional fund). 

The results are pretty brutal; either their model's signal(s) were tied to momentum and that relationship broke down or... well, they simply changed how they followed the model (perhaps behavioral issues tied to managing billions vs millions). Either way, returns since January 2013 were 65% for the EconomPic replication model, 55% for the S&P 500, and -3% for the Good Harbor strategy.

As for the investors that piled in billions of dollars, this is seemingly yet another example of performance chasing. In this specific case by an advisor who should have known better than to chase returns with the majority of a client's portfolio (concentration that should not be done irrespective of past performance or future performance expectations). 

What's interesting to me is that performance chasing is especially prevalent for investments that are too good to be true, either with the potential of a new technology (biopharma comes to mind), the superiority of an investment manager (the case of Marketfield comes to mind), or (in this case) in the form of a black box that always beats the market (hedge funds also come to mind). 

In this specific case, you add in the 5.75% load of the A-share and this may be a situation where past performance is not the only issue:
The claim said that Wells Fargo earned about $19,000 in fees for recommending the products, eroding potential capital gains. According to a copy of the claim reviewed by InvestmentNews that created "a conflict in recommending such high commission investments.”
Source: S&P, Barclays

Monday, June 15, 2015

The Case for a Steady Volatility-State Managed Portfolio

The always interesting quant aggregator Quantocracy linked to an interesting post by John Orford (follow John on Twitter at @mmport80) outlining a 'Steady Volatility Strategy' that targets a constant volatility target based on the most recent VIX index as follows:

Stock weight = Target volatility / VIX 
For example, if an investor is targeting a portfolio volatility of 10% and the current VIX is 20, then the investor would weight stocks at x = 10 / 20 = 50% weight.
I've actually been working on something similar (actually... almost exactly the same thing), thus I thought it might be helpful to share some thoughts on why this strategy likely leads to a portfolio with an improved Sharpe ratio over time relative to the S&P 500.

Market Volatility is Sticky

High levels of market volatility tend to lead to continued high levels of market volatility (at least over short periods of time before mean-reversion does its magic). As the chart below highlights, higher levels of the VIX have largely been the result of high market volatility over the previous month, while high levels of VIX tend to lead to higher levels of market volatility over the next month. Putting the old A = B and B = C, so A = C thought process to work, we get to high levels of historical market volatility leading to high levels of future market volatility.

Sharpe Ratios are Higher During Low Volatility Environments

While returns have in fact been a bit higher when volatility is elevated, the relationship has been much weaker than the relationship between historical and forward volatility. As a result, the S&P 500 has had a Sharpe ratio almost 2x higher when the VIX was less than 20 than when it was above 20. As a reminder, Sharpe ratio is excess performance to cash over standard deviation. The lower denominator when volatility is low more than offsets the impact of slightly lower returns on the Sharpe ratio calculation.

Allocating More to Equities when the Sharpe Ratio is Higher = Improved Return Profile

As a result of a higher Sharpe ratio when the VIX is less than 20, an investor could produce higher risk-adjusted returns by allocating more to stocks when the VIX is less than 20 and less when the VIX is above 20. In the example below, stock weights were increased 50% to 150% when the VIX was less than 20 and decreased 50% to 67% when the VIX was above 20 (financed by 3-month t-bills when levered / allocated to 3-month t-bills when unlevered).

While the introduction of leverage brings in a whole assortment of other risks I'll ignore here, the result of the steady volatility allocation over the above time frame is a portfolio with:
  • More consistent year-to-year performance: 12-month standard deviation ranged from 11% to 31% for steady volatility vs. 8% to 45% for the S&P 500
  • Lower drawdown: -47% for steady volatility vs. -55% for the S&P 500
  • Lower overall volatility and higher returns: see above

Source: CBOE, S&P, Federal Reserve

Wednesday, June 10, 2015

The Relationship Between TIPS, Treasuries, and Inflation

TIPS "treasury inflation protected securities" currently provide very little upside (return), but that exact statement can be made about just about any area of the fixed income market. Where they do present a potential opportunity is in relative terms against traditional Treasury bonds. Regardless, this post is less about the opportunity within TIPS and more about the return profile they provide. For a deeper dive into how TIPS function, I recommend this Vanguard piece.

What are TIPS?

TIPS provide an investor with real (i.e. after inflation) returns guaranteed by the U.S. government. You buy TIPS at a real rate, which is lower than traditional Treasuries by a 'break-even' inflation rate determined by the marketplace. For example, in the below post I will assume the nominal rate on a Treasury bond of 2.5% and a break-even inflation rate of 2.0%, resulting in a TIPS real yield of 0.50% (all relatively close to current levels for bonds with a 10 year maturity).

Return Profile of Treasuries vs. TIPS

The below chart is without a doubt an oversimplification, but the most important aspect is that nominal bonds (i.e. Treasuries) provide a nominal return (over a time frame equal to their duration) that is extraordinarily close to their yield to maturity. For this exercise we will ignore the path of returns (i.e. how they got there... which is important), so that we can focus solely on the relationship between inflation and returns (nominal and real).

Treasury Bonds

At the current yield of 2.5% and an 8-year duration, a 10-year maturity Treasury bond WILL provide an investor a nominal return very close to 2.5% over the next 8 years regardless of inflation. As Treasuries do not adjust for inflation, assuming an inflation rate at a constant level over the life of the Treasury bond, the real return of a Treasury bond is simply the nominal rate less the inflation rate. For example, if inflation is 3% and the Treasury bonds only return 2.5%, then real returns are negative -0.5%. On the other hand, if there is deflation, then the real return moves higher. For example, if deflation is -1% and the nominal yield is 2.5%, then the real return is 3.5%.


Inflationary Environment
At a real yield of 0.5%, TIPS provide an investor with a real return equal to 0.5% if there is inflation, while the nominal return will increase by the rate of inflation. For example, if the inflation rate is a constant 2%, then TIPS provide the same nominal return as Treasuries (the fact they are the same, means the break-even is 2%). If inflation is above 2%, then TIPS provide a greater nominal return than Treasuries... if less, they provide a smaller nominal return than Treasuries. 

Deflationary Environment
A TIPS investor is guaranteed to receive PAR at maturity, thus is given an embedded "deflation floor" option. As outlined in this Vanguard piece:
TIPS also provide some deflation protection to the principal (but not to the coupon payments). At maturity, if consumer prices have fallen so much that the inflation-adjusted principal would be below par, the Treasury will repay the principal at par value. In this manner, TIPS provide a “deflation floor.”
As a result, while nominal bond real returns move in a linear fashion to changes in inflation rates, TIPS cannot move negative (unless the real yield at purchase was negative) in nominal terms, thus the real return also increases in a deflationary environment (a ~0% nominal return when deflation is 3% = to a 3% real return). 


In normal market environments when inflation is relatively stable, long-term returns tend to be similar for both Treasuries and TIPS. However, TIPS materially outperform in an inflationary environment, while Treasury outperformance is capped by a rate roughly equal to the break-even inflation rate in a deflationary environment. Thus, assuming a view that an inflationary and deflationary scenario are equally likely, the unlimited potential outperformance of TIPS vs. Treasuries in an inflationary environment and limited upside of Treasuries vs. TIPS in a deflation environment would sway an investor towards TIPS.

Wednesday, June 3, 2015

An Improved High Yield Alternative

I really don't like the high yield asset class. Not just in the current environment with near-low historical yields and the potential for material liquidity issues, but in general. As an asset class, I think high yield:

  1. Often caters to unsophisticated investors that only look at the yield
  2. Is riskier than its returns suggest due to an opaque credit market that doesn't as regularly reprice bonds (as they do within equities)
  3. Has unfavorable tax consequences relative to stocks as coupons are taxed at a much higher rate than the capital appreciation of stocks

Historical Performance Comparison to Stocks

One draw of high yield is the view that its performance is from a known yield (vs. the less guaranteed market appreciation of equities). In addition, the Sharpe ratio of the asset class has historically been superior to stocks (i.e. more return per unit of risk). The counter points to that argument is that the Sharpe ratio is overstated as volatility of high yield is under-reported (see point 2 above), as well as the fact that high yield returns are the result of two factors (credit and rates) that can be replicated with an allocation to stocks and bonds (thus a high yield vs. stocks comparison is apples to oranges). Case in point being that a 54% S&P 500 / 46% treasury portfolio since the Barclays High Yield 1983 inception has the same standard deviation and higher returns vs high yield... thus a higher Sharpe ratio. 

Decomposing High Yield Returns

Before getting into details of a high yield alternative, let's decompose historical high yield returns to get a better sense of what an investment in high yield actually provides. 

High yield benefits from the return of two main factors, credit and rates (actually as we'll see it mainly benefits from rates). As the chart outlines below, the credit (spread) component of high yield and the rates component are often well balanced, making high yield a "risk-parity" like allocation between the two factors. As a result, comparing high yield to a blended stock/bond allocation rather than a stand-alone stock or bond allocation makes sense. Or as we'll outline below, there may be an opportunity to replace one of the factors with a more efficient / more liquid component. The below charts break down the returns into these two factors over the past 25 years (as far back as Barclays reports them separately).

Despite a higher contribution to portfolio level risk from the credit (spread) component...

Credit (spread) has provided a materially smaller contribution to the long-term performance of high yield

Swapping in Credit Risk via Equities vs. Bonds

If high yield is a sub-optimal way to access credit risk an investor utilizing leverage can replicate high yield via treasuries for the rate factor and the S&P 500 for the credit / spread factor.

The below chart shows the equity curve of two such options going back to 1983...
  • High Yield Alternative A: scale stocks to provide similar return as high yield: 100% treasuries, 24% S&P 500 financed at 3-month t-bills 
  • High Yield Alternative B: scale stocks to provide similar risk as high yield: 100% treasuries, 46% S&P 500 financed at 3-month t-bills

The Results

Historical results are certainly promising on an absolute and relative basis. Not only were Sharpe ratios improved, drawdowns were materially reduced. In addition, a portfolio consisting of treasuries and the S&P 500 will likely be MUCH more liquid than high yield during periods of turmoil.

Sources: S&P, Barclays, Federal Reserve

Monday, June 1, 2015

Ignore the Margin Debt Alarm

The margin debt alarm has seemingly been sounded every few months when investors realize absolute levels of margin debt have reached new all-time highs (inferring that risk taking has too reached all-time high levels). This brief post highlights why any such alarm (and any future margin debt alarm) should likely be ignored.

Oversimplified Analogy

Absolute levels of debt simply don't matter. As anyone who took an accounting or corporate finance course in high school or college understands, what is relevant are levels of debt relative to asset and equity levels. Taken to the extreme... does someone worth $2000 with $5000 of credit card debt have the same debt problems as someone worth $2 million with $5000 of credit card debt? Of course not. What matters is the level of debt to the assets that debt is supporting.

Relative Margin Debt is the More Appropriate Calculation

Doug Short put together the below chart outlining NYSE debt and S&P 500 equity levels going back 20 years. When viewed in isolation, NYSE Margin Debt levels (red) have risen sharply since 2009 lows. What has also risen sharply since 2009 are equity valuations.

Context matters... while debt levels did rise more quickly than equity valuations from 2001 through 2007, since 2007 margin debt has moved in complete unison with stock valuations; margin debt has consistently stayed between 2.0% and 2.5% of the value of the S&P 500 index. This means margin debt has not increased at all when you account for assets that margin debt is supporting.

Do Absolute or Relative Margin Debt Levels Even Matter?

The only thing an increase / decrease in absolute margin levels tells you is how the stock market has done in the past. As markets rise, margin levels rise. As markets fall, margin levels fall.  This can be seen in the bottom left chart (red), where 46% of the relationship over the past 20 years (the time frame in Doug's chart) has been driven by market movements.

As all the other R-square levels attest, there has been very limited relationship with changes in margin levels and future market movements over the last 20 years and absolutely no relationship between historical or future market movements with the very small changes that have occurred in the relative levels of margin debt to S&P 500 valuations.

Returns vs. Margin Debt (1995-2015)

So next time you hear anything about absolute levels of margin debt... ignore it.

Sources: NYSE Data / Yahoo Finance

Tuesday, May 12, 2015

The Case Against High Yield

Following up on my post The Relationship Between Stocks and Bonds, which outlined why it is probable that stocks will outperform Treasury Bonds over the next 10 years, let's take a look at another expensive area of the bond universe... high yield U.S. corporate bonds.

High yield bonds: Where's the high yield?

As the right-hand chart below highlights, the 5.95% yield to worst of the Barclays U.S. High Yield Index (as of 4/30/15) is near its all-time low. Due to defaults, this yield should be thought of as the best case return that can be expected over a 5-10 year period, rather than the likely forward return.

Why? Over ten year periods since 1986 (the furthest back I could gather yield to worst data):

  • The forward ten-year return of the Barclays U.S. High Yield Index has under-performed its yield 93% of the time
  • The forward ten-year return of the Barclays U.S. High Yield Index has under-performed its yield by an average of 3.5% / year (with a 3.5% standard deviation) 

While there are certainly no guarantees, given the 5.95% yield, history "implies" a ten year forward annualized return of 2.5% with a one-standard deviation range of -1% to 6%.

High yield vs. stocks: The story gets worse

While U.S. stocks appear expensive by most measures, they have nothing on high yield. Using the same format as above, the below compares the excess yield of high yield relative to stocks vs. the excess return of high yield relative to stocks.

The first thing you may notice in the right-hand chart below is that high yield's excess yield vs. stocks is only slightly above 2%, well shy of the 7% average from 1987 through 2005 and not even in the same ball park as the 15% level reached during the early 1990's and financial crisis. Note... the below uses the CAPE yield (more details here); using the S&P 500's current earnings yield gets you to a sub 1% figure, slightly above the negative level that occurred in 2013.

Relative performance results look even worse than high yield in isolation:
  • High yield's forward ten-year relative performance vs. stocks has under-performed its excess yield 100% of the time
  • High yield's forward ten-year relative performance vs. stocks has under-performed its excess yield by an average of 8.3% / year, with a 5.2% standard deviation 

Given the current 2.2% excess yield of high yield bonds vs. stocks (as of 4/30/15), history "implies" a -6% ten-year annualized underperformance vs. stocks with a one-standard deviation range of annualized underperformance of -11% to -1%.

"History doesn't repeat itself, but it does rhyme" - Mark Twain

Looking back at the performance of high yield corporate bonds since the crisis, we see remarkably strong performance among the lowest credit quality segments of the market. It wasn't long ago that we found ourselves in a similar situation of lower quality outperformance; the chart below highlights the almost five year run from late 2002 through mid-2007 that looks awfully similar to the returns we've experienced since the end of 2008. In between these two time frames was a massive flight to quality / junk sell-off that took place during the financial crisis, which created the opportunity for the most recent period of junk outperformance (and NOBODY wanted to allocate to high yield in early 2009).

There are times when high yield bonds present an attractive opportunity in absolute or relative terms. Today does not appear to be one of them.

Thursday, May 7, 2015

A Guide to Creating Your Own Hedge Fund

As a follow-up to A Guide to Creating Your Own Smart Beta Fund, let's dive into the high flying paying world of hedge fund management.

 Per Investopedia:

Hedge funds are alternative investments using pooled funds that may use a number of different strategies in order to earn active return, or alpha, for their investors. Hedge funds may be aggressively managed or make use of derivatives and leverage in both domestic and international markets with the goal of generating high returns (either in an absolute sense or over a specified market benchmark). Because hedge funds may have low correlations with a traditional portfolio of stocks and bonds, allocating an exposure to hedge funds can be a good diversifier. 
Hedge funds shouldn't be thought of as an asset class, rather (in aggregate) they are simply go anywhere investment vehicles that attempt to provide absolute returns with low correlation to traditional asset classes. As an investment vehicle, they just happen to charge an absurdly high fee (a 2% management fee + 20% of excess returns above some threshold is generally accepted as a reasonable starting point).

As an aside, there is a case for managers that can produce consistent, excess returns (i.e. high Sharpe ratios) that are uncorrelated to traditional asset classes to be paid at least 2% / 20%, but there are far and few managers that come close to producing these type of returns legally. For those managers that can, access is limited to the brightest and/or best connected capital allocators. In other words, if you are a retail investor or financial advisor with assets less than $10 billion without a Rolodex that needs its own warehouse... don't bother. 

What is an investor to do? I'll show you.

In this case I'll create a "solution" using funds from the world of liquid alternatives. Actually... I'll go one step further and use the two worst performing funds from Morningstar's multialternative category for the ten years ending 3/31/15.

Turning Lemons into Lemonade

I won't pick on the Dunham Distribution Fund or Hatteras Alpha Hedged Strategies Fund too much... I'll simply show the objectives and present the ten-year equity curve for each fund before outlining how we'll use these funds to create an improved risk-adjusted, uncorrelated, return stream.

Fund Objectives:
  • Dunham Monthly Distribution: Seeks to provide positive returns in rising and falling market environments.
  • Hatteras Alpha Hedged Strategies: Seeks to achieve consistent returns with low correlation to traditional financial market indices while maintaining a high correlation to the Hedge Fund Research, Inc.(“HFRI”) Fund of Funds Composite Index.

Performance Results (3/31/2005-3/31/2015)

Okay, I need to pick on them a bit more as expenses for both funds were higher than their ten year annualized returns by a significant margin, meaning the investment manager received more money than any buy and hold investor (and this ignores the 5.75% front-end load on the Dunham fund). In addition to producing a negative Sharpe over this time frame with returns that had a very high correlation to equities (go here for details outlining the importance of a high Sharpe ratio and/or low correlation within a broader asset allocation), they have experienced material drawdowns. Despite these returns, the Dunham Fund has grown their asset base to almost $300 million (from less than $100 million in 2010), while the Hatteras fund is slightly above $500 million in assets. If you're one of those investors... would love to know why.

Momentum... Momentum... Momentum... Momentum...

As outlined in my post The Case for Hussman Strategic Growth, a dual momentum approach as introduced in Gary Antonacci's white paper Risk Premia Harvesting Through Dual Momentum (follow Gary at Optimal Momentum), provides the possibility of capturing the absolute performance of an asset (or fund), while avoiding extended periods of underperformance. In this instance, I allocated to either the Dunham Distribution Fund, Hatteras Alpha Hedged Strategies Fund, or short-term bond (ETF IEI) based on whichever was the most above it's 9-month moving average. The resulting time series is then compared with the Barclay Hedge Fund Index, which shows 'the average return of all hedge funds (excepting Funds of Funds) in the Barclay database'.

The result... a dual momentum approach to the two worst performing funds in the multialternative universe has provided all of the absolute return of the average hedge fund, with lower standard deviation, and materially lower drawdown / correlation / beta, all with better liquidity.

What's next? Applying the same framework on a segment of the market that is likely to lead to similar levels of correlation, but with materially higher levels of performance.

Monday, May 4, 2015

No... Investors Haven't Underperformed Every Asset Class

The following chart has been floating around for more than a year, supposedly showing investors have not only performed poorly, but even worse than almost any asset class. As Richard Bernstein stated:
The average investor underperformed nearly every asset class. They could have improved performance by simply buying and holding any asset class other than Asian emerging market or Japanese equities.

Let's start with my conclusion. This chart is highly misleading in that it compares apples (geometric time-weighted returns of assets classes) to an orange (dollar weighted returns of the average investor) since 1993, resulting in asset class performance that is materially higher than any investor buying into the market would have received.

This post walks through the error and shows how to get to returns that are a more appropriate comparison. The conclusion is that the discrepancy between the geometric time-weighted asset class returns and investor dollar-weighted returns has not been driven by poor investor behavior, but rather by the path of asset class returns. A huge and important distinction.

Starting Point: What are Geometric Returns?

The blue bars shown in the Richard Bernstein chart are geometric weighted returns (i.e. time weighted returns), which unlike average returns take into account the effects of compounding (a good thing), but do not account for dollar flows.

A quick example....

Let's assume an investor returns 100% in year 1 and is down 50% in year 2. While the average return is 25% / year = (100% - 50%) / 2 = 25%, geometric returns were 0% (as follows):
  • Year 1: the $1 turns into $2 (100% return)
  • Year 2: the $2 turns into $1 (50% loss)
  • The $1 invested at time 0 = $1 at time 2 = 0% geometric return
As Investopedia points out
Investment returns are not independent of each other, so they require a geometric average to represent their mean.
As an aside... beware any manager only showing average returns. At a minimum they are reporting returns too high (average returns are always > geometric returns).

THE ISSUE: Geometric Returns vs. Dollar Weighted Return: Comparing Apples to an Orange

Now to the major issue with Richard Bernstein's chart... it contains two different types of return calculations; (1) time weighted geometric average returns for the various asset classes and (2) dollar weighted for investor returns (these two should NEVER be compared).

dailyVest explains dollar-weighted returns (bold and bullet format 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 
To reiterate... dollar weighted returns put more emphasis on recent performance than time weighted returns when market flows are positive. For example, going back to the investor with a 100% return in year 1 and a -50% return in year 2, but this time showing dollar-weighted returns for an investor that dollar cost averages $1 each year:
  • Year 1: the $1 turns into $2 (100% return); the investor then adds another $1 to their $2 investment, so they have $3 total investments heading into year 2
  • Year 2: the $3 turns into $1.50 (50% loss)
  • The $2 total investment is now worth only $1.50 
A -13.3% annualized dollar-weighted loss, despite the same 0% geometric return.

The Path of Returns Over the 20-year Period Mattered

Returns were MUCH higher at the beginning of the 20-year period ending 12/31/2013 than the end due to (1) the 1990's equity bubble and (2) two material drawdowns that took place between 2000 and 2009. The chart below shows annualized geometric returns of the S&P 500 at various points in time using 12/31/1993 as the starting point for all those periods. For example, as of 1998, the annualized geometric returns of the S&P 500 from 12/31/1993 through 1998 was almost 25% annualized. By comparison, by the end of 2013 the S&P 500 returned ~9% annualized from 12/31/1993 - 12/31/2013 (as shown in Richard Bernstein's chart and below).

Dollar-Weighted Returns Have Been Similar to Investor Returns

Since dollar weighted returns put more emphasis on recent performance, we would EXPECT dollar-weighted returns to be lower. For the 20-year period ending 12/31/2013, the S&P 500's geometric returns were 9% annualized, while dollar weighted returns (assuming the same amount investment each month from 1993-2013) were a full 4% lower. Again, this 4% discrepancy assumes completely unemotional dollar cost averaging and is another 1% lower if you assume the contribution rate grew by the rate of inflation over that time frame. Performance dispersion for asset classes where recent performance has been relatively worse (think developed international and emerging markets), was further amplified by the time-weighted / dollar-weighted comparison.

This does work both ways; the chart above was recreated below using data from June 2007 through April 2015, a period when equity returns were much HIGHER in the more recent portion of that time frame.

As a result, dollar-weighted equity returns have actually been higher than geometric returns and my guess is that investor performance would appear "much improved" vs the original Richard Bernstein piece. This, despite what has likely been a period highlighted by poor investment behavior through and since the crisis.

Thursday, April 30, 2015

Implications from the Rise of Passive Investing

ThinkAdvisor shares Jeff Gundlach's (DoubleLine) thoughts from the Milken Institute Global Conference, outlining the potential impact of the shift towards passive investing within Robo Advisors.

The financial planner industry has very wide range of delivery. A lot of … asset gathers do nothing; others are very creative. With robo-advisors, the costs are low. So the draw is the lack of overall success by human advisors at three or four times the cost of an algorithm, or spreadsheet advisor. 
The impact being...
One-size-fits-all solutions channel people into the same investments, which then introduces systemic risk.
In a conversation I had with Ben Carlson (of the must read A Wealth of Common Sense), I shared that while it is odd he focused on robo-advisors given they are such a small percent of the market, his point is relevant in terms of the huge shift we've seen over the last 20+ years towards indexing. While I won't get into the details of my own view on passive vs. active investing (high level... in my view there are parallels to the prisoner's dilemma in that it is a rational choice for most individual taxable investors, but poor for investment returns / the economy as a whole), I do think it increases systematic risk due to the concentration of assets into so few products.

How much has passive taken over?

The shift to passive has been monumental; 20 years ago passive investments made up a bit more than 20% of all assets within small, mid, and large core / blend Morningstar categories, the majority of which was allocated by institutional investors with long-term investment horizons. Now, we're looking at a passive market share of 50-70% within core U.S. equities, with the bulk of net flows coming from retail investors with much shorter investment horizons.

As Ben pointed out:
performance chase by weak hands will probably always cause more volatility in any product type.
I agree and in the case of indexing, the product is the entire market. My hypothesis that systematic risk has increased due to the concentration of assets is supported by the strong historical relationship between market performance, market volatility, and passive outperformance. Money has piled into indexing (a product that is composed of the entire market) when markets have performed well, periods when active managers have underperformed and volatility has been low. Passive market shares gains have slowed when markets have underperformed, periods when active managers have had much stronger relative performance and market volatility has been amplified.

Relative performance of active vs passive (in this case the percent of managers outperforming on the y-axis and market performance on the x-axis)

This raises the question of whether the relative performance of the average active manager is due to stock selection or is instead a function of flows into the market that have been allocated irrespective of underlying fundamentals. If the latter, when flows leave the market (as they always do at some point), it won't be individual stocks that underperform, it will likely be the entire market.

Tuesday, April 28, 2015

The Uncertain Future of Robo-Advice

I had a Twitter back and forth with the founder of Wealthfront regarding the tax efficiency of their platform vs. using the same asset allocation model within an ETF (see here). I thought it might be of interest to provide additional details, as well as some thoughts on robo-advice more broadly.

Investopedia defines a robo-advisor as:

A robo-advisor is an online wealth management service that provides automated, algorithm-based portfolio management advice without the use human financial planners. Robo-advisors (or robo-advisers) use the same software as traditional advisors, but usually only offer portfolio management and do not get involved in more personal aspects of wealth management, such as taxes and retirement or estate planning.  
Let me be clear... I am absolutely THRILLED that robo-advisors exist. If nothing else, they pressure fees traditional advisors and ETFs charge, while an allocation made to a robo-advisor (by a hands-off investor) is likely to result in materially better performance than could be expected from many brokers that charge exorbitant fees. In addition, I've seen first hand from a "techie" brother in-law that a small, (but real and growing) community in the Silicon Valley has been drawn to the automation robo-advisors provide, which hopefully leads to a better financially educated community for all involved. BUT... I really don't understand where the 'actual' service they provide sits on the advice / allocation spectrum that consists of a traditional advisors that act as fiduciary on one side (higher fee, higher interaction, higher education benefits to their clients) and the multi-asset / target date ETFs on the other (lower fee, lower interaction, lower education).

Where's the Advice?

While I think robo-advisors can create a decent portfolio based on an initial survey and may be able to provide decent adjustments over time (none of this is all that difficult... most robo-advisors and ETFs get to the same place), over the years I've realized that 90%+ of the value a traditional advisor provides is the “advice”. Advice does not only consist of the beginning "how much risk are you comfortable with" phase or the year-to-year "has anything changed" phase, but a real thorough understanding of changes that have taken place in their client's life. As important is the "advisor as therapist", talking their clients down from the ledge when investment behaviors ebb and flow with the market.

I question whether robo-advisors can manage investor emotion. Investors generally ignore advice when it goes against their view and/or when they have real fear (of missing out or of losing money). There are times when an investor benefits immensely from a simple "slap across the face" from their advisor (i.e. when markets are off 50% and they want to sell). What will happen to allocations on robo-platforms when markets (eventually) turn lower? Wealthfront has already outlined that their investor base has changed their risk tolerance as markets have moved and this took place in what has generally been an up-and-to-the-right market.

Tax Efficiency: Self-Contained ETFs Rule the Land

Ignoring investor behavior for a moment, robo-advisors platforms are simply inferior to an existing alternative option available to all retail investors in an area they claim superiority... tax efficiency. Without getting into how ETF sausages are made, target-date and multi-asset ETFs can avoid capital gains most of the time (high level details here) even when the ETF rebalances within the wrapper from an outperforming holding to an underperforming holding. This is HUGE for tax efficiency, as an investor may not have to pay capital gains taxes from the day they buy into the ETF, until the day they eventually sell, allowing returns to compound to a greater extent over time.

On the other hand, a robo-advisor can do everything right to optimize tax efficiency (tax loss harvesting / use dividend payments and contributions to limit the capital gains associated with rebalancing), but may still force an investor to realize capital gains as there is a limit to how much they can offset as the asset base grows relative to the contributions made by the investor.

For example... the charts below outline the level of rebalancing (as a percent) that can be supported by flows and dividend / interest payments for a portfolio over time assuming a $10,000 annual contribution, 8% annual returns, and a 3% dividend + interest income (slightly higher than the current "yield" of a 60/40 portfolio). The left hand chart shows the level as a percent over time, while the right hand chart shows the level as a percent in dollar terms using the same assumptions.

Using this simply for illustrative purposes, the key is that over time, the level of rebalancing that can be supported by contributions and distributions narrows materially towards the 3% distribution rate as contributions become smaller relative to the asset base. This also ignores the fact the contributions eventually turn to withdrawals, thus the level of rebalancing supported by flows will turn negative.

Compare the above 3-4% figure to the rebalancing required to maintain a simple 60/40 portfolio over time. The chart below outlines the shift from stocks to bonds (or bonds to stocks) required over rolling 12-month periods to maintain the 60/40 weights. Note the levels are materially higher when rebalancing is needed most (i.e. after sharp moves in stocks) and completely ignores the rebalancing associated with an asset allocation “glidepath” towards more bonds as an investor approaches retirement; rebalancing that is typically made when an investors has an asset base materially higher. This level only goes higher if an investor delays the rebalancing process (the benefit of doing so outlined here).

In my opinion, robo-advice is more of a feature than a solution. Robo-advisors lack the advice / hand-holding of a traditional advisor and the tax efficiency of ETFs.  If you desire the latter, why not just allocate to a multi-asset ETF and have some sort of "lock box" feature that requires a 30 minute conversation with a financial advisor, a full week to think, then another 30 minute conversation if you ever want to trade / sell the ETF? To me, that may result in all the behavior correction investors need at a reduced cost.

Friday, April 24, 2015

The Case for Hussman Strategic Growth

Well... maybe not the "case for". Rather, a "kinda / sorta case". If you're contemplating making a long-term allocation to the fund (you're not)... don't.

While John Hussman is without question a remarkable writer (and in my view a remarkable analyst - just too smart for his own good when it comes to allocating capital), the Hussman Strategic Growth Fund has produced some pretty horrific performance.


  • Performance percentile ranks of 97th, 100th, 100th, and 100th over 1, 3, 5, and 10 years
  • Negative absolute performance over 3 months, 1 year, 3 years, 5 years, and 10 years
  • A current drawdown of 36% since the 9/15/08 Lehman Brothers collapse 

Worse... the first page of the prospectus outlines:
The Fund seeks to achieve long-term capital appreciation, with added emphasis on the protection of capital during unfavorable market conditions.

While I won't remotely defend that performance, especially given its objective, I will point to its history of outperforming during the two market downturns since the fund's inception. This provides a potential opportunity for an investor willing to look past recent performance.

Potential ways to utilize the fund...

Absolute Momentum
Applying a very simple momentum model as introduced in Meb Faber's A Quantitative Approach to Tactical Asset Allocation (follow Meb on his blog mebfaber.com) would have provided an investor with the majority of excess performance, without the subsequent 6 1/2 year downturn. In this case we are simply allocating to the Hussman Strategic Growth Fund when the fund is > 9-month moving average, otherwise allocating to cash.

Dual Momentum
Rather than sit in cash if there are better opportunities, another way to utilize the Hussman Strategic Growth Fund is through a dual momentum approach as introduced in Gary Antonacci's white paper Risk Premia Harvesting Through Dual Momentum (follow Gary at optimalmomentum.com). In this instance, I tweaked his formula slightly and allocated to Hussman Strategic Growth, the S&P 500, or cash based on whichever is the most above it's 9-month moving average.

The results...

So, if/when markets eventually roll over and you think Hussman is capable of outperforming in a bear market environment (he certainly has spent much of the last 15 years contemplating how to structure a bearish portfolio), the strategy might actually make for an interesting allocation.

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