The Capital Spectator

Research Review | 5.21.13 | Risk Management & Asset Allocation

Advances in Portfolio Risk Control: Risk! Parity?
Winfried G. Hallerbach (Robeco) | May 1, 2013
Spurred by the increased interest in applying “risk control” techniques in an asset allocation context, we offer a practitioner’s review of techniques that have been newly proposed or revived from academic history. We discuss minimum variance, “1/N” or equal-weighting, maximum diversification, volatility weighting and volatility targeting – and especially “risk parity”, a concept that has become a real buzz word. We provide a taxonomy of risk control techniques. We discuss their main characteristics and their pluses and minuses and we compare them against each other and against the maximum Sharpe Ratio criterion. We illustrate their implications by means of an empirical example. We also highlight some important papers from the vast and still growing literature in this field. All in all, this note serves as a practical and critical guide to risk control strategies. It may help you to demystify risk control techniques, to appreciate both the “forest” and the “trees”, and to judge these techniques on their potential merits in practical investment applications.

]]> Tail Hedging Strategies
Issam Strubn (The Cambridge Strategy) | May 7, 2013
This article introduces an algorithm for tail risk hedging and compares it to other existing methods. This algorithm adjusts the exposure level based on a measure of tail risk obtained by applying Extreme Value Theory (EVT) to estimate Conditional Value at Risk (CVaR). This method is applied to the S&P 500 and MSCI Emerging Markets equity indexes between 2000 and 2012 and its performance is compared to cash and options based tail hedging strategies. The cash based methods are shown to significantly increase risk adjusted returns and reduce drawdowns, while the options based strategy suffers a decrease in performance from 2003 on due to the increase in cost of puts with respect to calls after that date. The tail hedging technique presented in the article is fully investable as its turnover is limited; additionally it can replace long/short equity hedge funds for investors who do not have access to alternative investments.

Macro-Based Parametric Asset Allocation
Richard Franz (WU Vienna University) | May 3, 2013
This paper presents a novel approach to asset allocation which builds up on macroeconomic factors. Without doubt the financial return of asset classes are interlinked with the economy. However, it is not that clear how to bring the finance and economy world together within a portfolio’s asset allocation. I propose a direct modeling of the weights with global macroeconomic risk factors. These risk factors are not asset class specific but potentially related to the return of all asset classes. In this paper I focus on three asset classes: stocks, bonds and the risk free asset. The approach is robust, links macroeconomic factors to financial returns intuitively and outperforms a standard 60/40 portfolio almost twice in terms of the Sharpe Ratio - in sample and out of sample. This outperformance even remains to a large extent when considering transaction or leverage costs.

Stochastic Portfolio Theory Optimization and the Origin of Alternative Asset Allocation Strategies
Gianluca Oderda (Ersel Asset Management) | .May 7, 2013
What is the theoretical reason why a particular alternative allocation strategy, or a combination thereof, should offer a superior return vs. risk tradeoff? Can we derive an optimal alternative allocation strategy from first principles, both from an absolute return perspective, to identify the most appropriate long-term strategic benchmark, and from a relative return perspective, to identify the alternative allocation strategy with the highest expected information ratio relative to a market-cap weighted index? We attempt to answer these questions, by building on the stochastic portfolio theory framework of Fernholz, to study the evolution of portfolio wealth, both in absolute terms and relative to a market index. We prove that the portfolio maximizing the expected value of logarithmic portfolio wealth at a fixed level of volatility differs from the traditional mean-variance portfolio solution by the linear combination of three further terms: an equally weighted portfolio, a risk parity portfolio, and a high cash flow rate of return portfolio. Most importantly, we prove that, given any market capitalization weighted index, the portfolio maximizing relative logarithmic growth with respect to this index deviates from the market benchmark by the linear combination of four subportfolios: an equally weighted portfolio, a risk parity portfolio, a high cash flow rate of return portfolio, and a global minimum variance portfolio. Consistent with previous empirical research, we prove that an investor can profit from diversification effects when spreading his investment across different alternative asset allocation methods, and we show the four alternative asset allocation building blocks which constitute the optimal portfolio.

Strategic Allocation to Commodity Factor Premiums
D. Blitz & W. De Groot (Robeco) | May 16, 2013
Investors may wonder whether the traditional arguments for investing in commodities still apply, as the return, diversification and inflation-hedging potential of commodities appear to have declined. In this study, we take a fresh look at the strategic allocation to commodities, considering not only the commodity market portfolio, but also various other factor premiums documented to exist in the commodities market. We find that a commodity factor portfolio consisting of the momentum, carry and low-volatility factor premiums exhibits a significantly better risk-adjusted performance than a conventional commodity portfolio. We also find that only such a commodity multi-factor portfolio adds value in the strategic asset allocation. As the traditional commodity market portfolio appears to deserve little or no role at all in the strategic asset allocation, we argue that investors should not postpone the consideration of alternative commodity factor premiums to a later stage of the investment process.

Chicago Fed: Slower Slow Growth In April… Again

The US economy slowed in April for the second time in as many months, “led by declines in production-related indicators, according to today’s release of the Chicago Fed National Activity Index, a weighted average of 85 economic data sets. But the deterioration has yet to make a conspicuous dent in the three-month moving average (CFNAI-MA3), which remained virtually unchanged at -0.04 last month vs. a revised -0.05 for March. The three-month average offers "a more consistent picture of national economic growth," the Chicago Fed advises. By that standard, the US economy is still expanding at a pace that’s only slightly below its historical trend as of last month.

]]> Based on the guidelines published for this index, today’s update also shows that recession risk was low in April. A CFNAI-MA3 value below -0.70 after a period of economic expansion "indicates an increasing likelihood that a recession has begun," according to the Chicago Fed. By that measure, last month remained convincingly in the growth camp. A similar analysis was dispatched in last week’s update of The Capital Spectator Economic Trend & Momentum indices.

For the moment, the expansion stumbles on, although It’s been clear for weeks that the manufacturing sector has wavered recently and that the blowback. It’s still unclear if these headwinds will persist. If they do, the question is whether the broader economy is headed for darker days in the near term? That’s an open debate, as always, but for now it appears that the economy remains on a path of modest growth, albeit at a reduced pace vs. the first quarter.

The next round of updates may tell us if the malaise is spreading and deepening, starting with tomorrow’s report on existing home sales, followed by Thursday’s releases: weekly jobless claims and an early look at the trend in May via the flash estimate of the Markit PMI manufacturing index.

The Lesson From Japan

Japan's stock market is on a roll, largely because expectations have dramatically changed this year about the underlying state of macro for the planet's third-largest economy. The iShares MSCI Japan Index ETF (EWJ) is up a potent 24% year-to-date. That's a substantial premium over the 18% gain for US stocks (SPDR S&P 500 (SPY)), for instance. An aggressive new round of monetary and fiscal stimulus that's weakened the yen and revived animal spirits explains most of the rally. So-called Abenomics seems to be working. Is Japan's two-decade stretch of disappointing economic performance finally at an end? Possibly, although a few months of improvement vs. 20 years of stagnation is hardly definitive proof. But let's leave all that aside and consider the larger point of relevance for investing, namely: the surprise factor.

]]> How many investors anticipated Japan's return to glory? Surely there are a few brilliant (lucky?) ones out there. But most of us were clueless, as implied by the long-running habit of underweighting Japanese equities in asset allocation strategies. Japan, it was widely assumed, was destined to remain a moribund economy, suffering a nearly perfect volte-face from a generation ago, when the Land of the Rising Sun was generally hailed as the exemplar of a new economic order. But a funny thing happened on the way to a sure thing: the forecast fell apart.

Japan's gradual but persistent fall from macroeconomic grace over the last 20 years convinced almost everyone that there was little point to investing in the country's stock market in anything more than a token allocation. The wary outlook was certainly understandable, perhaps even rationale. Nobody likes to stick their hand out when knives are falling form the sky, year after year.

It's still unclear if the recent turnaround in the market's outlook for Japan is a reliable reflection of what's coming, or one more head fake on the road to disappointment. But it's interesting to note that few if any of the usual suspects were talking about the great rebound in Japan late last year. That's no mystery, since predicting the future is still a mug's game as a general rule. Japan offers a rather conspicuous example, but it's hardly an exception. Everywhere you look, there are monuments to failure in the dark art of looking ahead. A few quick examples:

• The US bond market, we've repeatedly been told by "experts", is in imminent danger of collapse. The problem, of course, is that this advice is several years old and so far it's notable only for being wrong.
• Gold is destined to rise to $5,000 an ounce or higher in something akin to a straight line because hyperinflation is just around the corner. Gold has surged over the last decade, although the bloom has come off the rose in 2013. Why? The fact that hyperinflation is still nowhere in sight may be part of the answer.
• The US dollar is destined to collapse amid "reckless" Fed policies. The reality is far less exciting: a trade-weighted index of the dollar is more or less flat these days relative to the period leading up to the Great Recession.
• The US economy is headed into another recession. That's true, of course, in the sense that that there's always another downturn in the business cycle lurking in the future. But for several years now we've been told that a new recession is imminent, and so far these forecasts have been perfect… perfectly wrong.

There are many more instances of forecasts that crashed and burned. No wonder that broadly diversifying across the major asset classes (aka keeping radical bets to a minimum) has a habit of routinely generating competitive results vs. the majority of "expertly" managed portfolios that end up charging more and delivering less vs. Mr. Market's asset allocation. The surprising surge in Japan's stock market is merely the latest headline-grabbing example of why it's so hard to beat an expansively defined investment strategy.

The Standard Advice (That's Often Ignored)

Greg Mankiw has a talent for cutting to the chase when it comes to observations of macro and finance and he doesn't disappoint in his latest NY Times column, which summarizes his view on how to answer the question: What stocks should I buy? The Harvard professor explains that the best response is not to answer at all, at least not directly. An "evasive" explanation, however, is worth a lot in this case. He advises that "the market processes information quickly", "price moves are often inexplicable", and "diversification is essential". Agreed. Mankiw's writing about stocks, but his succinct guidelines on equities apply to asset allocation too. For all the reasons that holding a low-cost basket of stocks (i.e., an index fund) is appealing from empirical and theoretical perspectives, the same is true for a multi-asset class portfolio. This is old news, of course, but Mankiw's column reminds that it's also forever new in the otherwise hazardous business of dispensing investment advice.

Book Bits | 5.18.13

● From a Market Economy to a Finance Economy: The Most Dangerous American Journey
By A. Coskun Samli
Summary via publisher, Palgrave Macmillan
Dwindling innovation and deteriorating economic conditions are caused by a major force, a systemic shift in the American economy. In this gripping book, Dr. Samli makes the case that the US economy is shifting for the worse, tilting towards a finance-driven economy, and argues that investing in innovation will bring us out of the recession and back to a successful, market-driven economy.

]]> ● The Federal Reserve: What Everyone Needs to Know
By Stephen H. Axilrod
Summary via publisher, Oxford University Press
The Federal Reserve System--the central bank of the United States, better known as The Fed--has never been more controversial. Criticism has reached such levels that Congressman Ron Paul, contender for the Republican presidential nomination in 2012, published End the Fed, with blurbs from musician Arlo Guthrie and actor Vince Vaughn. And yet, amid a slow economy and partisan gridlock, the Fed has never been more important.... Drawing on years of experience inside the Federal Reserve System, Axilrod shows how these tools actually work, and answers a series of increasingly detailed questions in the series format.

● The Alternative Answer: The Nontraditional Investments That Drive the World's Best-Performing Portfolios
By Bob Rice
Summary via publisher, HarperCollins
The first book to explain the new world of alternative investing, showing how anyone can use nontraditional options to significantly increase returns and lower risks. The world's elite investors have long relied on alternative investments to produce superior returns. Until now, these strategies were the exclusive purview of institutions and the superwealthy, but today any informed investor can play the same game.

● Berkshire Hathaway Letters to Shareholders: 1965-2012
By Warren Buffett (Max Olson, Editor)
Recommendation via Value Investing World
The absolute best compilation of Warren Buffett’s letters if you are looking to read them all from start to finish, edited wonderfully by my friend Max Olson. Whether you are an investor, businessman, or just interested in business and investments in any way, I can’t think of anything better to sit down and read from start to finish.

● Who Owns the Future?
By Jaron Lanier
Review via The Plain Dealer
For Lanier, the system is not working well. Long a believer that the Internet has "killed more jobs than it has created," he is concerned about its potential to deepen inequality: "The wide adoption of transformative connecting technology should create a middle-class wealth boom, as happened when the Interstate Highway System gave rise to a world of new jobs in transportation and tourism, for instance, and generally widened commercial prospects. Instead we've seen recession, unemployment, and austerity."

● I Invented the Modern Age: The Rise of Henry Ford
By Richard Snow
Review via The Wall Street Journal
As it happens, Ford didn't have shareholders for most of the time he ran the Ford Motor Co., and he didn't want them. The man who founded one of America's iconic companies hated investors, as well as accountants and bankers—anybody implicated in the financial arts. Just as paradoxically, the industrialist who, as he himself said, invented the modern age despised modernity and built a museum village to commemorate the past. He was oddly oblivious to style—cars, to Ford, were all about the engine. And though his opinions could be noxious and retrograde, he was often ahead of his time. He made a point of hiring thousands of African-Americans, and he had surprisingly 21st-century notions of health, frowning on tobacco and meat and favoring fruit and legumes. He was also a mechanical genius.

● $10,000 Gold: Why Gold's Inevitable Rise Is the Investor's Safe Haven
By Nick Barisheff
Summary via publisher, Wiley
As paper currency continues to lose its purchasing power and global markets struggle in the face of economic turmoil, investors are turning to gold to stabilize their portfolios. $10,000 Gold explains why this is a smart move, arguing that the price of gold will continue climbing to $10,000/ounce and beyond in the years to come. Looking at the underlying causes of gold's rising value, the book contends that intelligent investors have no choice but to invest in this precious metal. Written by one of the world's leading authorities on gold, the book teaches readers to think independently about gold, money, and the geopolitics that affect its price.

Chicago Fed Nat'l Activity Index: Apr 2013 Preview

The three-month average of the Chicago Fed National Activity Index (CFNAI) is expected to rebound moderately to +0.20 in the April report, according to The Capital Spectator's average econometric forecast. That compares with CFNAI's -0.01 three-month average for March. A value below -0.70 indicates an "increasing likelihood" that a recession has started, according to guidelines from the Chicago Fed. Based on today's estimates, CFNAI's three-month average is projected to remain at levels that historically are associated with growth in the update for April, which is scheduled for release on Monday, May 20.

]]> Here's a closer look at the numbers, followed by brief definitions of the methodologies behind The Capital Spectator's projections:

VAR-4A: A vector autoregression model that analyzes four economic time series to project the Chicago Fed National Activity Index: the Capital Spectator's Economic Trend & Momentum Indexes, the the Philadelphia Fed US Leading Indicator, and the Philadelphia Fed US Coincident Economic Activity Indicator. VAR analyzes the interdependent relationships of these series with CFNAI through history. The forecasts are run in R with the "vars" package.

VAR-4B: A vector autoregression model that analyzes four economic time series to project the Chicago Fed National Activity Index: US private payrolls, real personal income less current transfer receipts, real personal consumption expenditures, and industrial production. VAR analyzes the interdependent relationships of these series with CFNAI through history. The forecasts are run in R with the "vars" package.

ARIMA: An autoregressive integrated moving average model that analyzes the historical record of the Chicago Fed National Activity Index in R via the "forecast" package.

ES: An exponential smoothing model that analyzes the historical record of the Chicago Fed National Activity Index in R via the "forecast" package.

US Economic Profile | 5.17.13

Economic updates in recent weeks suggest that the economy is facing new headwinds. Notably, Industrial production and housing starts slumped in April. The latest data points may imply trouble down the road, but the case is still weak for arguing that the economy's suffering in the here and now. Indeed, a big picture review of the business cycle betrays few signs of stress, based on today’s update of The Capital Spectator's Economic Trend Index (ETI) and Economic Momentum Index (EMI). In other words, the odds are low that the NBER will eventually declare April as the start of a new recession, based on the current data sets available.

]]> For a closer look at the numbers, let’s start with a recap of all the indicators in ETI and EMI. Although the degree of positive momentum is slowing for some indicators in the April column—the ISM Manufacturing Index and industrial production—the downshifting is hardly universal. What's more, it's notable that negative comparisons are MIA for all the numbers in the March to April period. The closest that the numbers come to red ink is in the April entry for the Consumer Sentiment Index, which is unchanged as of last month vs. its year-earlier level.

Looking at ETI and EMI in historical context shows that both measures continue remain well above their respective danger zones: 50% for ETI and 0% for EMI.

Translating ETI's historical values into recession-risk probabilities via a probit model also suggests that the odds are low for thinking that April marks the start of a recession.

Finally, let's consider the near-term outlook for ETI and EMI by predicting future values with an econometric technique known as an autoregressive integrated moving average (ARIMA) model. The ARIMA model estimates the missing data points for each month through June. Although ETI is projected to decline modestly in the near term, the retreat is expected to keep the index well above its danger zone. Forecasts are always suspect, of course, but recent projections of ETI have proven to be relatively reliable guesstimates vs. the full set of monthly reported numbers that followed. As such, the latest projections (the four light blue bars on the right) offer some support for cautious optimism. For comparison, the chart below also includes ARIMA projections published on these pages in previous months, which you can compare with the actual data, as currently known (red squares). The assumption here is that while any one forecast is likely to be wrong, the errors may cancel one another out to some degree by aggregating the estimates.

For additional, context, here are the last three monthly ETI and EMI updates:

18 April 2013
18 Mar 2013
18 Feb 2013

April's Pinch Gets A Bit Tighter

It’s a rough morning for US economic news. Initial jobless claims jumped sharply last week and housing starts in April suffered the biggest monthly decline in six years. Overall, it’s pretty ugly, but it’s not yet fatal for the business cycle, or so a broad review of indicators still suggests. We could be slipping over the edge, but we could just as easily be stuck in another one of the temporary slow patches that’s plagued the recovery from time to time since the Great Recession ended. Clarity is coming, even if it’s tempting to assume the worst in the wake of today’s updates. But before we do anything, let’s take a closer look at the data.

]]> Jobless claims rose last week by a hefty 32,000 to a seasonally adjusted 360,000. The five-year lows of the past few weeks suddenly look like ancient history. But if it’s easy to over-dramatize last week’s pop, putting the numbers in context suggests that nothing much has changed. Indeed, despite the latest increase, the four-week moving average has barely nudged higher.

Somewhat more troubling is the year-over-year trend in the unadjusted claims data. As the next chart shows, new filings for unemployment benefits slid by a thin 2% last week vs. the year-earlier total. That’s the smallest pace of decline in six weeks.

The big loser in today’s news, however, is new housing starts, which slumped to the lowest level since last November. The good news is that newly issued building permits jumped last month, topping the 1 million mark for the first time since 2008. That’s a sign that housing starts may rebound in the months ahead. It doesn't hurt that builder optimism rebounded a bit in yesterday's update of the the National Association of Home Builders/Wells Fargo Housing Market Index for May.

On a year-over-year basis, both starts and permits continue to post healthy gains, although new residential construction’s annual pace fell to +13% last month—the slowest since October 2012.

Yes, we’re all on high alert once again about the possibility for deeper troubles in the economy. But we’ll need to see the warning signs stretch out well beyond a few dark data points, which is all we have now.

Now It's Really Time For A Flat Tax

If the scandal over monitoring political groups that forced the acting commissioner of the IRS to resign this week doesn't inspire dismantling the tax-collecting agency and introducing a flat tax, nothing will. It won't happen, of course. But it should. There are easier, more efficient ways to collect taxes than allowing bloated bureaucracies to act with near impunity as a quasi-government within a government. If that's not painfully clear at this stage, if it's not obvious that the IRS is too big, too powerful, and oversees an impossibly convoluted set of tax laws, it's hard to imagine that we'll ever engage in meaningful reform of the US tax system, which is in dire need of reforming.

]]> Instead, the only consolation is a symbolic resignation from the head of the IRS and a lengthy report (pdf) from the Treasury Inspector General for Tax Administration that refers to “inappropriate criteria” for the agency's targeting of conservative groups. Perhaps a few people may go to jail when the dust clears. And we'll have Congressional hearings too. But the IRS will survive, on that point you can be sure.

And therein lies the problem. The Byzantine empire that the IRS oversees is a net drag on the US economy. The fact that we, as a country, move heaven and earth to collect 15%-20% of GDP as taxes through time by way of 72,000 pages of tax code is, well, ludicrous. Some form of the flat tax would do the same thing without the brain damage. Indeed, the current system incurs enormous costs in time and money, as anyone with a fairly complicated tax situation will tell you. Actually, it's the height of arrogance on the government's part that it imposes a tax system on its citizens that they have little hope of understanding or even complying with.

As one quick example: What's the rule on wash sales when it comes to swapping one broad US equity ETF for another--an S&P 500 fund for a Russell 3000 fund, for instance? The advice varies, depending on who you talk to. This type of trade runs afoul of the wash sale rule, some CPAs tell me. Others say it's fine. This debate has been going on for a number of years, but the IRS has yet to clarify.

The bottom line: there is no rationale for the incredibly complex and often ambiguous rules that govern our tax system. Beyond the obvious economic inefficiencies this insanity imposes, it also fuels a giant bureaucracy that wields enormous power that apparently extends to political affairs. To what end? To collect a relatively stable share of revenues as a percentage of the economy? That's like calling out the Marines to issue traffic tickets.

The real IRS scandal is that this agency has grown to proportions that were never intended. Absolute power corrupts absolutely, Lord Acton warned. The only question is whether we, as a nation, will fix what's in desperate need of fixing? Don't hold your breath.

Why doesn't Congress want to reform the tax system? A recent essay by a pair of professors have a reasonable if cynical answer:

The more complex the tax code is, the more politicians can use budget gimmicks to hide the benefits they give to their cronies and traditional voting blocs as they position themselves for the next election. At the heart lies the politician's election-year mantra: I'll hand out more governmental largesse and lower your taxes. Only we can't have it all.

Industrial Output In April Slumps The Most In Eight Months

Industrial production fell more than expected last month, sliding 0.5% in April. That’s a bit deeper than economists projected, and it's an even bigger drop relative to the modest gain that my econometric modeling suggested. But based on today's release, it's obvious that April was a rough month for the industrial sector. The worst, in fact, since last August. The manufacturing component of industrial activity didn’t fare much better, slipping 0.4% last month. That’s the second consecutive monthly retreat for manufacturing, according to this series. It’s also the first time that manufacturing in this data set slumped for two months running since 2009.

]]> The slowdown in industrial output is visible in other indicators, including the survey data via the ISM Manufacturing Index. But the weakness in the industrial/manufacturing slice of the economy would be all the more troubling if the labor market was exhibiting equally dark signs of stress. For the moment, that’s not the case. Jobless claims have been plumbing new five-year lows recently and the decent if unspectacular April report on private payrolls suggests that the economy will continue to post modest growth for the near term.

Nonetheless, today’s news on industrial production leaves more room for doubt about what comes next. The year-over-year percentage change in industrial activity, while still positive, dipped to +1.9% last month, a rate that shares the dubious distinction of matching January’s pace and reflecting the slowest annual gain in three years.

It’s still premature to expect the worst for the business cycle, although we’re again at the anxious stage of analysis that emphasizes each new data point as a potential smoking gun in the search for additional signs of weakness. Next up: tomorrow’s updates on housing starts and jobless claims. Thursday's consumer price inflation release is also worth watching for any signs that disinflation/deflation risk is escalating.

But before we pull the plug on optimism, keep in mind that industrial production has stumbled several times in recent years—stumbles that proved to be false alarms in terms of the big picture. It’s too early to say if that’s true again, or if we’re on the cusp of something more ominous. The truth will out fairly soon, although the usual suspects will no doubt rush to judgment today. But until (or if) we see convincing signs of deterioration in other indicators, it’s still unclear if today’s weak industrial production report is noise or an early signal of approaching darkness. Based on my recent update on a broad review of financial and economic data, the aggregate trend still implies that modest growth will prevail (I'll have an update soon). Rest assured that when the broad trend takes a decisive turn for the worse, you’ll read about it here.

Meantime, it’s still wise to avoid the trap of letting the number du jour dictate your outlook. The economy’s always in a constant state of flux, as is the projected macro trend. But this ongoing state of change is usually a gradual evolution, even if the talking heads and the latest headline would have you believe otherwise.

US Housing Starts: April 2013 Preview

Housing starts are expected to total 1.013 million in April in tomorrow’s update, based on The Capital Spectator's average econometric forecast (seasonally adjusted annual rate). That’s a modest decline vs. the previously reported total of 1.036 million for March. Meanwhile, The Capital Spectator's projected gain for April is well above the numbers in several consensus forecasts drawn from surveys of economists.

]]> Here's a closer look at the numbers, followed by brief definitions of the methodologies behind The Capital Spectator's projections:

VAR-3: A vector autoregression model that analyzes three economic series to project housing starts: new home sales, newly issued permits for residential construction, and the monthly supply of homes for sale. VAR analyzes the interdependent relationships of these series with housing starts through history. The forecasts are run in R using the "vars" package.

ARIMA: An autoregressive integrated moving average model that analyzes the historical record of housing starts in R via the "forecast" package.

ES: An exponential smoothing model that analyzes the historical record of housing starts in R via the "forecast" package.

R-1: A linear regression model that analyzes the NAHB Housing Market Index in context with housing starts. The historical relationship between the data sets is applied to the more recently updated NAHB Housing Market Index to project housing starts. The computations are run in R.

Surprising Asset Allocation Results That Really Aren't Surprising

Monday's article on the average to above-average results that usually describe a passive allocation to all the major asset classes brought charges of foul play from some quarters. A few critics said I was cherry picking the data; one claimed that I was intentionally manipulating the numbers so as to engineer a favorable result for a benchmark of broad asset allocation vs. the universe of its actively managed equivalent. How, they wondered, could a passive strategy that holds everything compare so favorably on a regular basis? In fact, it would be surprising—impossible, in fact—if the results were otherwise.

]]> Professor Bill Sharpe made this point more than two decades ago in his short essay "The Arithmetic of Active Management," which observes:

Properly measured, the average actively managed dollar must underperform the average passively managed dollar, net of costs. Empirical analyses that appear to refute this principle are guilty of improper measurement.

This doesn't mean that passive management wins the horse race. That's impossible too. The extremes always go to the actively managed accounts. As Sharpe notes:

It is perfectly possible for some active managers to beat their passive brethren, even after costs. Such managers must, of course, manage a minority share of the actively managed dollars within the market in question. It is also possible for an investor (such as a pension fund) to choose a set of active managers that, collectively, provides a total return better than that of a passive alternative, even after costs. Not all the managers in the set have to beat their passive counterparts, only those managing a majority of the investor's actively managed funds.

Nonetheless, when you take a pool of assets, simple mathematics demonstrates that there can only be a small share of portfolio combinations that rise to the top of portfolio results for any given time period. This outcome, which is persistent through time, is obvious once you consider that there are two main strategies for engineering above-average results (for simplicity, let's ignore leveraging and short sales, which can be thought of as two additional strategy choices). You can select a subset of assets and/or you can pick different weights for some or all the assets, relative to an appropriate benchmark for the asset pool under scrutiny. The investors who choose wisely on those fronts will always constitute a minority. The problem is that it's really hard to choose wisely month after month, year after year.

In fact, the pool of active managers is actually smaller than simple math implies. After adjusting for trading costs, taxes and other real world frictions, the mistakes of active management further pares the pool of above average results, as Charlie Ellis has pointed out many times over the years.

Across relatively short time spans, the results can and do vary by a wider range, giving the impression at times that the analysis above is misguided. But performance eventually drifts back to the results implied by "The Arithmetic of Active Management."

One way to think about why broad diversification generally leads competitive results is by looking at a performance chart of all the major asset classes for the past 250 trading days through yesterday's close (May 14), based on ETF proxies. Note the wide array of price changes in the chart below, which sets all the funds to initial values of 100 as of May 14, 2012.

In order to deliver impressive above-average performance over the past year (roughly the trailing 250 trading days), it was necessary to favor the best performers. The top-three in our example above: foreign REITs (VNQI), foreign developed-market stocks (VEA), and US stocks (VTI). The challenge is that this type of ranking is an ever-evolving list. Today's winners end up as tomorrow's losers, which eventually rise to the top in the next period. In order to maintain an above-average record for any length of time, you'd have to identify the winners and losers in advance more often than not. History suggests this is devilishly difficult, which is why it's so hard to outperform a relevant benchmark of the targeted asset pool for anything more than a short period of time. Yes, some talented (lucky?) managers beat the odds, but good luck deciding in advance who's destined for that exclusive club. Anyone want to take a guess which asset allocation funds will be in the top 10% for the trailing 10-year period through May 2023? I didn't think so.

Even during periods of extreme negative results, the persistence of average performance via broadly defined asset allocation persists. In October 2008, for instance, when red ink was everywhere, I pointed out that a portfolio of all the major asset classes remained near the middle of results. Granted, those results were negative, but the fact that they were also average is simply the flip side of the average to above-average results that accompany this strategy in the good times, which thankfully is the dominant state of affairs across time.

This hard rule applies within a given asset class and for multi-asset class strategies too. Does that mean you should slavishly hold a passive mix of all the asset classes? No, not really. But history does suggest that you should think twice before going off the deep end with second guessing Mr. Market's asset allocation.

Rather, you should focus most of your attention on rebalancing the asset classes. It's pretty clear that broad diversification across markets is essential. The question, then, is how to optimize the rebalancing process? The default strategy is simply rebalancing periodically—once a year, for instance. This basic methodology has done quite well, although it's worth considering how to enhance the process further. But that's a topic for another day.

For now, the lesson is clear: Diversification across asset classes is the foundation for reliably capturing the lion's share of the global market's beta. If that beta comes with a positive expected return, as it usually does, we have ia powerful bit of advice for considering how to customize Mr. Market's allocation to match specific needs and goals. This is old news, of course, even if comes as a shock to some observers of the financial scene.

US Industrial Production: April 2013 Preview

Tomorrow's report on industrial production for April is projected to post a 0.2% gain, based on The Capital Spectator's average econometric forecast (seasonally adjusted). The expected increase represents a modest slowdown vs. March’s 0.4% rise. Meanwhile, the Capital Spectator’s average projection for April contrasts with expectations for a drop in industrial production via consensus forecasts from economists.

]]> Here's how the numbers stack up, followed by brief definitions of the methodologies behind The Capital Spectator's projections:

R-1: A linear regression model using the ISM Manufacturing Index to predict industrial production. The historical relationship between the variables is applied to the more recently updated ISM data to project industrial production. The computations are run in R.

R-4: A linear regression model using four variables to project industrial production: US private payrolls, an index of weekly hours worked for production/nonsupervisory employees in private industries, the ISM Manufacturing Index, and the stock market (S&P 500). The historical relationships between the variables are applied to the more recently updated data to project industrial production. The computations are run in R.

VAR-1: A vector autoregression model using the ISM Manufacturing Index to predict industrial production. VAR analyzes the interdependent relationships of the variables through history. The forecasts are run in R using the "vars" package.

VAR-7: A vector autoregression model using seven variables to project industrial production: US private payrolls, an index of weekly hours worked for production/nonsupervisory employees in private industries, the ISM Manufacturing Index, the stock market (S&P 500), real personal income less current transfer receipts, real personal consumption expenditures, and oil prices. VAR analyzes the interdependent relationships through history. The forecasts are run in R using the "vars" package.

ARIMA: An autoregressive integrated moving average model that analyzes the historical record of industrial production in R via the "forecast" package to project future values of the data set.

ES: An exponential smoothing model that analyzes the historical record of industrial production in R via the "forecast" package to project future values of the data set.

Retail Sales: Slow Growth In April

Whenever a key economic indicator shows weakness in the latest monthly update, the usual worries arise. No explanation required in the current environment and so today’s retail sales report for April will draw a fresh round of dark predictions from the usual suspects. And perhaps they’ll be right this time. But for now, it’s still premature to argue that the modest growth train has derailed, even if it looks that way by focusing on the latest data point.

]]> Consumer spending increased a weak 0.1% in April, although that compares favorably to March’s 0.5% decline, the biggest monthly slide since last June. No one will mistake the latest numbers as anything other than a sign that retail consumption has turned sluggish again. But for those who are quick to jump on the listless number du jour as a sign of macro apocalypse, a bit of perspective may inspire a less-strident view.

Let’s start by considering retail sales ex-gasoline, a rough proxy for measuring appetite for what consumers are willing and able to buy vs. what they’re effectively forced to purchase for such things as driving to work. By that standard, retail spending climbed a healthy 0.7% in April, the most since last November.

Monthly numbers are noisy, however, and so it’s always wise to take the latest update with a grain of salt. For a clearer look at the trend, the year-over-year change is somewhat more reliable if we’re trying to get a handle on the business cycle. On that front, today’s release suggests that nothing much has changed vs. recent history. Retail sales advanced 3.7% last month vs. the comparable year-ago figure. That’s up, by the way, from March’s 2.9% annual pace.

Consumer spending, in other words, reveals no clear and present danger signs of rolling off the edge. Yes, it may all come crashing down tomorrow, and we’ll no doubt be advised of that risk in the coming days, when the dark princes of macro roll out a new wave of warnings. But if you’re looking for unambiguous threats to the slow-to-moderate growth narrative that’s prevailed for some time, you won’t find it in today’s retail sales update.

Well, perhaps you can, if you look real hard. But your challenge is tougher if you’re also searching for confirming signs of darkness from other indicators. No dice when it comes to payrolls in April, which continued to advance at a modest pace while last week’s update on initial jobless claims slipped to another five-year low. In fact, a broad review of economic and financial indicators still suggest that slow growth remains the path of least resistance until further notice, a trend that drew support in last week’s update of the Macro-Markets Risk Index.

The first lesson in business cycle analysis is rather obvious: the economy is growing most of the time. As it happens, the current expansion is weak and vulnerable to any number of hazards that lurk here and abroad, but it’s growth nonetheless. A couple of centuries of history tell us that we should only assume otherwise upon a persuasive set of statistical smoking guns. Those guns have been MIA for some time, even if a few numbers have turned wobbly at times.

One day the tide will turn, a fate that happens to be another striking empirical fact in the historical record. But unless you’re trying to draw attention in a TV interview, you should wait for the numbers to tell us to press the panic button. That’s a boring way to practical macro analysis, but it redeems itself by minimizing the number of false warnings that tend to accompany a more media-friendly approach for looking ahead. Yes, we'd all like to be early when it comes to calling major turning points in the business cycle, but there's something to be said for being right too. The question is how do you blend a practical mix of the two? We can start by avoiding the usual approach of jumping off the deep end every time we see a new number.

Boring, Diversified, And (Still) Tough To Beat

Most investors suffer high fees and earn low returns. There are no sure-fire solutions, at least for the second problem, although playing defense by way of investing in a broadly diversified portfolio across the major asset classes with low-cost index products is a good start. This isn't a silver bullet, but history suggests you can do quite well with this simple strategy. And if you add in a bit of rebalancing, you'll probably do moderately better still. Not tomorrow, necessarily, but through time the odds usually stack up in your favor with this strategy. This basic advice drives the financial industry crazy because it sounds incredibly easy and doesn't cost much. It's hard to charge a lot for a strategy that requires no skill or forecasting prowess. But the results speak for themselves.

]]> Several times a year I like to check in on how passive allocation compares with a broad spectrum of multi-asset-class mutual funds and ETFs, most of which are actively managed and charge a comparatively high fee. As usual, a majority of this group trails the Global Market Index (GMI), an unmanaged value-weighted mix of the major asset classes that's the standard benchmark on these pages. Reviewing results for the 10 years through the end of April 2013, GMI ended up at the 70th percentile of performance vs. 1,100-plus funds.

Here's a closer look at how the numbers stack up:

Running the data on a risk-adjusted basis offers similar results, courtesy of my own proprietary database and numbers from Morningstar's Principia software. The familiar message is that you can do quite well by holding a broad basket of asset classes. The absolute return number is always in doubt of course. But what's fairly consistent is the relative performance ranking of GMI vs. a broad pool of funds navigating the realm of asset allocation. Indeed, the history above is similar to the rankings posted in January 2013 or a year ago, for instance.

After crunching the numbers several times a year for nearly a decade on this front, the result is usually the same. It's hard to beat asset allocation when defined across a wide array of asset classes. It's even harder if the benchmark rebalances the mix on a periodic basis. The historical record is a reminder that we should think twice about second-guessing Mr. Market's portfolio choices. This sounds like a dumb idea, until you look at the results for a majority of "smart" money managers.

Another dumb idea that ends up looking rather savvy is keeping expenses low, which is quite easy to do with index mutual funds and ETFs. Replicating GMI with ETFs, for instance, can be done for less than 50 basis points, perhaps a lot less, depending on the products you choose. Many of the active funds in the chart above charge two to three times as much.

The power of broad diversification across asset classes, favoring low-cost index funds, and simple rebalancing is a no-brainer that serves as a robust, investable benchmark. Yet relatively few investors take full advantage of this strategy. That's probably why GMI's competitive results persist: most investors are doing something else. But innovation seems to come at a steep price in relative and perhaps absolute terms.

Why should we expect GMI and related strategies to remain competitive? For a familiar reason: the future's uncertain, and that's not likely to change. If you have a high-confidence forecast on one or more asset classes, you can dispense with broad diversification. That's standard practice in the financial industry. Unfortunately for investors, the standard practice has an annoying habit of delivering the standard result.