Tag Archives: stocks

Dumb Alpha: The Ignoramus’s Guide To Asset Allocation

By Joachim Klement, CFA Modern finance constantly busies itself with the development of new, more sophisticated ways to manage risk and generate returns. These efforts, however, generate their own risks – for example, overspecifying a model or falling prey to data mining. On the opposite end of the spectrum are simple ways to invest that have a proven track record of providing superior investment outcomes. This article focuses on investment techniques that are so simple it is surprising how well they work, a phenomenon that Brett Arends of MarketWatch has called “dumb alpha.” The Dumb-Smart Way to Think about the Future Assume you are a middle-aged man with a receding hairline and an expanding waistline. In short, you don’t look like George Clooney – you look like me. Moreover, you need to finance your retirement with your savings. Creating a portfolio to build retirement wealth is no easy feat given the fact that retirement may be 20 to 40 years in the future. A lot can happen in that time: 30 years ago, Japan was on its way to overtaking the United States, China was a closed-up Communist country, Europe and North America had broken the spell of runaway inflation, and Brazil was a basket case. Who can say what the next 30 years will bring? Luckily, you are well aware that it is nigh impossible to predict which investments will do well during the next three decades. And assuming this is true, there are only two logical ways to invest. One possibility is to hold all your savings in cash or the safest short-term bills and bonds. The problem with this approach is that you will have a hard time keeping pace with inflation once taxes and other expenses are taken into account. And in some countries, like Germany and Switzerland, you even face what my colleague Will Ortel calls ” unterest rates .” The other possibility is to invest the same amount of your money in every asset class. This makes sense because you don’t know how stocks will do compared with bonds or real estate investments, or how Apple stock will do compared with Barry Callebaut. The simplest example of this naive equal-weighted approach would be a portfolio split 50/50 between stocks and bonds. Another approach would be to invest one-quarter of your assets in cash, one-quarter in bonds, one-quarter in equities, and one-quarter in precious metals. Similarly, instead of investing in a common stock index such as the cap-weighted S&P 500 Index, you could evenly spread your precious funds across all 500 stocks of the index. The Advantages of a Naive Asset Allocation As it turns out, this way of investing tends to work extremely well in practice. In their 2009 article ” Optimal versus Naive Diversification: How Inefficient Is the 1/N Portfolio Strategy? ,” Victor DeMiguel, Lorenzo Garappi, and Raman Uppal tested this naive asset allocation technique in 14 different cases across seven different asset classes and found that it consistently outperformed the traditional mean-variance optimization technique. None of the more sophisticated asset allocation techniques they used, including minimum-variance portfolios and Bayesian estimators, could systematically outperform naive diversification in terms of returns, risk-adjusted returns, or drawdown risks. Unfortunately, naive asset allocation does not work all the time. Over the last several years, only one asset class generated high returns: stocks. So, a naive asset allocation will not keep up with the more equity-concentrated portfolios during such periods. But it is interesting to note how well a naive approach works over an entire business cycle. Practitioners should compare their portfolios with a naive asset allocation to check whether they really have a portfolio that delivers more than an equal-weighted portfolio. You can create a better (“more sophisticated”) portfolio than the equal-weighted (“dumb”) one, but it is surprisingly hard to do. As a check, you can create an equal-weighted portfolio from the assets or asset classes used in your current portfolio. Then test whether the current portfolio is superior to this equal-weighted benchmark over time in terms of returns, risks, and risk-adjusted returns. If that is the case, congratulations: You have a good portfolio. If not, you should think of ways to improve the performance of your existing portfolio. It is also pretty clear why this dumb alpha works. Within stock markets, putting the same amount of money in every stock systematically prefers value and small-cap stocks over growth and large-cap stocks. These two effects conspire to create outperformance. There is a second effect at play, however. After all, the value and small-cap effect cannot explain why a naive asset allocation also works in a multi-asset-class portfolio. The key reason for its strong showing is its robustness to forecasting errors. Most asset allocation models, like mean-variance optimization, are very sensitive to prediction errors. Unfortunately, even financial experts are terrible at forecasting, and one follows forecasts at one’s peril. By explicitly assuming that you cannot predict future returns at all, an equal-weighted asset allocation is well suited for unexpected surprises in asset class returns – both positive and negative. Since unexpected events happen time and again in financial markets, in the long run an equal-weighted asset allocation tends to catch up with more “sophisticated” asset allocation models whenever an event happens that the latter are unable to reflect. In other words, if the naive asset allocation outperforms a more sophisticated portfolio, it might provide a hint as to why this is the case. Are there too many risky assets in the sophisticated portfolio that directly or indirectly create increased stock market exposure? What are the implicit or explicit assumptions that led to the more sophisticated portfolio that have not materialized and have led to an underperformance relative to a less sophisticated naive asset allocation? In this sense, the naive asset allocation can act as a check to an existing sophisticated portfolio and as a risk management tool. Disclaimer: All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Does This New Consumer Discretionary ETF Look Promising?

Consumer discretionary is one of the sectors that have delivered commendable performance so far this year. The credit goes to the recovering U.S. economy, cheap gas prices, subdued inflation and prolonged ultra-low interest rates. The recent Fed minutes revealing its reluctance to raise interest rates in the near term should bode well for the sector, at least for the rest of the year. Notably, the most popular consumer discretionary ETF, Consumer Discret Sel Sect SPDR ETF (NYSEARCA: XLY ), returned 7.7% in the year-to-date time frame, while S&P 500 Index lost 2.1% in the same period. Manulife Financial Corp’s (NYSE: MFC ) insurance and investment manager John Hancock has forayed into the ETF world with six multi-factor smart beta offerings. One of them is JHancock Multifactor Cnsmr Discret ETF , trading under the symbol JHMC . The launch of this consumer-discretionary-focused ETF looks to be timely. Smart beta ETFs aim to obtain a return that’s higher than the return of the benchmark index, which is the fund’s alpha. Apart from higher returns, the fund seeks to reduce costs and enhance diversification. They follow a passive management strategy with a tweak in the component weightings unlike traditional, market-cap-weighted index funds. JHMC in Details Like other ETFs of John Hancock, JHMC is also based on the index that is developed by Dimensional Fund Advisors, which will also act as the sub-advisor to the fund. Dimensional is one of the first managers to work on multi-factor and rules-based investing. The index comprises securities in the consumer discretionary sector within the U.S. universe whose market capitalizations are larger than that of the 1001st largest U.S. company. The ETF comprises 154 holdings with Comcast Corporation (NASDAQ: CMCSA ) occupying the top position with 3.52% share, followed by Amazon.com, Inc. (NASDAQ: AMZN ) with 3.45% share and Home Depot, Inc. (NYSE: HD ) with 3.22% share. The top 10 holdings constitute around 23.96% of the fund. As far as sector allocation is concerned, media takes the top spot with 22.38% allocation, followed by specialty retail, and hotels, restaurants and leisure with 22.32% and 14.66% shares, respectively. The fund is moderately expensive as it charges 50 bps in fees from investors per year. How Does it Fit in a Portfolio? The upbeat September auto sales data triggered optimism in the consumer discretionary sector. U.S. light-vehicle sales increased 15.7% year over year to 1.44 million units in September. Sales on a seasonally adjusted annualized rate (“SAAR”) basis surged to 18.17 million units in the month from 16.53 million units in September 2014. It was the highest SAAR since July 2005. Further, retail sales spending indicates positive consumer sentiment for the sector. Consumer spending accounts for roughly 70% of the economic activity in the U.S. In August, personal spending edged up 0.4% from the prior month, as per the U.S. consumer department. For September, consumer spending is expected to rise as well given higher auto sales and, with the holiday season around the corner, it would likely remain bullish this year. The National Retail Federation predicted that U.S. holiday sales for the last two months of the year will grow 3.7%, higher than the 10-year average of 2.5%. Finally, rising consumer confidence bodes well for the sector. According to the business research group, Conference Board, the consumer confidence index increased to 103 in September after rising to 101.3 in August. The monthly reading was the highest since this January. The bullish trend in consumer spending is not only a positive for the consumer discretionary sector but also for investors interested in this new ETF. ETF Competition Being a smart-beta ETF, JHMC definitely deserves attention. However, there are a number of popular consumer discretionary ETFs that are already on the investors’ tracking list. Among them, the most popular are above mentioned XLY and First Trust Cnsmr Discret AlphaDEX ETF (NYSEARCA: FXD ). XLY tracks the S&P Consumer Discretionary Select Sector Index focusing on companies defined by the S&P 500 Composite Stock Index. The fund’s top ten holdings comprise nearly the same stocks as that of JHMC. It has an impressive asset base of $10.7 billion. On the other hand, FXD follows the StrataQuant Consumer Discretionary Index selecting stocks from the Russell 1000 Index that may generate positive alpha relative to traditional passive style indices. It manages an asset base of $2.4 billion. Both XLY and FXD stand nearly at the same level in terms of yield, with XLY offering 1.4% and FXD offering 0.86%. However, on the cost front, XLY looks very attractive with only 15 bps in fees compared with a much higher annual fee of 70 bps for FXD. Original Post

The Paradox Of Risk: Central Planning Is Linear, Reality Is Non-Linear

You thought it was safe to drive 90 miles an hour on a rain-slicked narrow road while you were tipsy because the airbag would save you, but it still hurts when you crash. I first discussed the Paradox of Risk in August 2008, just before the stock market melted down : The Unintended (Risky) Consequences of “Backstopping” Risk (August 12, 2008). This is the Paradox of Risk: the more risk is apparently lowered, the higher the risk we are willing to accept. I recently covered a related topic, The Dangerous Illusion That Risk Can Be Offloaded Onto Others (October 2, 2015). The paradox is that believing risk has been eliminated leads us to take on insane levels of risk – levels that we would never have accepted before, levels that essentially guarantee our financial destruction. I recently had the opportunity to discuss these topics with Max Keiser: Keiser Report: Global Paradox of Risk (25:40 – I join Max and Stacy in the 2nd half) 1. The Fed Put, the belief that the Federal Reserve will never let stocks decline by more than a few percentage points before it steps in and saves the market from any further decline. 2. The belief that hedges dependent on counterparties paying off when the market craters have effectively transferred risk to others. 3. The belief in Modern Portfolio Management, i.e. that risk can be hedged or reduced to near-zero by diversifying one’s portfolio, investing in assets with low correlation, etc. All of this is nice, but fatally flawed. Max and I discuss the reality that markets are not linear, they are fractal. Central planning is linear, but reality is non-linear. The net result is the Fed can do whatever it wants, whenever it wants, and markets will still crash from time to time. That markets crash is predictable, but not when they crash. I’ve prepared a chart that depicts the downside of the Paradox of Risk: everyone who believes in the Fed Put, hedges or Modern Portfolio Management will view any decline in stocks as temporary. As a result, they won’t sell as markets plummet. When markets finally hit bottom, believers will assure themselves that the Fed is going to push stocks higher any day now, because they have always done so in the past. When central planning efforts to push stocks back up falter, the believers that risk has been banished grow frustrated; come on, Fed, do whatever it takes! Alas, the Fed has done whatever it takes but it has failed to produce the desired effect. Now the market starts another slide to fresh lows, and the believers finally start recognizing that risk has not been disappeared: counterparties start failing, hedges don’t get paid off, and a sense that events are spiraling beyond the control of central planning is spreading. Sorry, believers that risk has been banished: it’s too late, you’re wiped out. You thought it was safe to drive 90 miles an hour on a rain-slicked narrow road while you were tipsy because the airbag would save you, but it still hurts when you crash: Keiser Report: Global Paradox of Risk (video).