The Markets Had Been Calm Until Recently

Posted on October 16, 2014 | Investor Update

Investor-Update

If the volatility we’ve been experiencing as of late feels like a splash of cold water, it’s likely because it’s been a while since we’ve really experienced it. An extended stretch of calm waters preceded the U.S. market’s recent bout of volatility.

I’m going to share with you some updated numbers from what we crunched for last week’s AAII Dividend Investing update to put things in perspective. We use the iShares Dow Jones U.S. Index ETF (IYY) as the benchmark for both our DI and for our Stock Superstars Report portfolios. This ETF tracks the performance of the largest 1,260 U.S. stocks, giving it exposure to a combination of large-, mid- and small-cap stocks. This ETF incurred daily price changes of 1.5% or more 62 times in 2011 (29 days up by 1.5% or more and 32 days down by 2% or more.) For the entire period following 2011, meaning January 3, 2012, through yesterday, October 15, 2014, the ETF experienced a total of 39 days with a daily price change of 1.5% or more (20 down and 19 up). Again, 62 days in 2011 alone versus just 39 days for the nearly three-year period of 2012 through 2014.

Let’s look at the volatility another way. Wayne Thorp, who maintains a dashboard of market indicators for our Computerized Investing service, has been tracking the number of 1% down days for the Dow Jones U.S. ETF since 1999. Through Wednesday, he counted eight 1% down days over the last six months. This is below the median of 17 days and the average of 19 days with drops of 1% or more since 1999. (Wayne elaborates on this indicator in his Editor’s Outlook in the October Computerized Investing email newsletter that is being sent out this weekend.)

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Have Patience With Small-Cap Stocks

Posted on October 9, 2014 | Investor Update

Investor-Update

It has not been a good year for small-cap stocks. As of yesterday’s close, the Russell 2000 index was down 4.78% year-to-date. In contrast, the larger-cap Russell 1000 index was up 7.72%. We’re seeing similar comparisons with other indexes as well. For example, the S&P SmallCap 600 was down 4.99%, whereas the S&P 500 index was up 6.52%. (Obviously, these numbers will be lower once data reflecting today’s decline is published.)

Valuations have been blamed as the reason why. Small-cap stocks were expensive relative to large-cap stocks. They still are. S&P Capital IQ calculates the SmallCap 600 as trading at 22.1 times trailing 12-month (TTM) earnings, versus 26.3 at the end of 2013. In contrast, the S&P 500 is trading at 16.8 times TTM earnings, versus 16.9 at the end of 2013. Arguably, in the background, other concerns (e.g., the tapering of bond purchases by the Federal Reserve, geopolitics, the length of the bull market, etc.) are also playing a role in causing small caps to lag.

This is not the first time small-cap stocks have underperformed large-cap stocks, and it likely won’t be the last time either. As John McDermott and Dana D’Auria discussed a few months ago in the AAII Journal, small-cap stocks only beat large-cap stocks on an annual basis about 50% of the time between 1926 and December 2013. The size premium realized by small-cap stocks comes from their higher volatility. Small-company stocks experienced a standard deviation of 32.3% between 1926 and 2013. Large-company stocks had a lower standard deviation of 20.2%, according to the 2014 Ibbotson SBBI Classic Yearbook. (Standard deviation measures the range of values above and below average for a set of data. Larger values indicate greater variability.)

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The Investment Industry’s Response to Dementia

Posted on October 2, 2014 | Investor Update

Investor-Update

I had the opportunity to attend SIFMA’s Senior Investment Forum this week. It was an industry seminar focused on cognitive impairment (dementia, Alzheimer’s disease and related ailments). The timing was somewhat ironic given that on the same day of the conference, the family of Malcom Young—the founding member of Australian rock band AC/DC—confirmed the reason for the guitarist’s retirement: dementia. (I’m listening to some of his work as I write this.)

A positive takeaway from the conference is the investment industry’s awareness of the problem. Some firms have set up protocols, implemented training programs, or are otherwise are educating employees about identifying and working with clients showing signs of cognitive impairment. Wells Fargo Advisors distributes a pamphlet entitled “A Quick Reference Guide for Elder Financial Abuse.” Ameriprise Financial gives its financial advisers a “compliance snapshot,” which has guidance for working with clients believed to be “experiencing diminished mental capacity.” Bank of America Merrill Lynch has a director of financial gerontology. Cynthia Hutchins, who holds this role, believes this is the first such position of its kind.

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How to Invest Like a Quant Fund

Posted on September 25, 2014 | Investor Update

Investor-Update

Quant funds utilize computer algorithms to guide their investment strategies. These computerized methods pick securities based on quantitatively identifiable characteristics. Rather than selecting stocks with a good story (e.g., Alibaba (BABA)), they select stocks based on various fundamental or technical criteria.

Many hedge funds follow quantitative strategies. Smart beta funds also follow these strategies. Last week, Morningstar announced that it is now designating quant exchange-traded funds (ETFs) as strategic beta funds. The investment research company described these funds as those that try to improve returns or isolate a specific return relative to a benchmark, increase or decrease the level of risk relative to a benchmark, or follow non-return or risk-oriented strategies, such as equal-weight strategies.

The basic idea behind quant funds is to identify anomalies or return factors that lead to higher returns or less volatility. By giving a preference to investments with these characteristics, higher returns, less volatility or both are sought. It can be an unemotional way to invest as long as personal biases are not allowed to interfere with either the creation or the execution of the model. The better you are able to stick to the model, the more you will be able to invest like a quant fund.

Creating your own model does require a level of comfort with a good screening program such as our Stock Investor Pro and, depending on the model used, a spreadsheet. If you are unwilling or unable to do the mathematical and computer work, following a quantitatively oriented screen or buying a strategic beta fund may be the better option.

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Be Careful Not to Let Biases Impact Your Decisions

Posted on September 18, 2014 | Investor Update

Investor-Update

There is a new study about superstitions and portfolio returns. It should not surprise you to hear that superstitious individual investors have worse performance than those who are not superstitious. Any time biases are introduced into financial decision making, returns will be affected.

The study looked specifically at Taiwanese traders. The researchers found a far higher ratio of orders placed at prices ending in the number eight than they did for orders ending in the number four. This was attributed to the fact that Chinese culture views the number “8” as lucky and the number “4” as unlucky. The researchers noted that in Mandarin, “four” is pronounced similar to “death,” whereas “eight” is pronounced similar to “good fortune.”

Traders who were the most superstitious trailed investors who were the least superstitious on an intraday, one-day and five-day basis. The reason is simple. The superstitious traders let their biases toward certain numbers govern their investing decisions, rather than making purely objective choices.

The study’s authors pulled no punches when discussing the results. They called superstitions “a separate dimension of an investor’s cognitive disability in making financial decisions.”

It’s not fair to solely call out Taiwanese traders for being superstitious. A bias toward or against certain numbers exists in many cultures and religions. Here, in the United States, 13 is viewed as an unlucky number. Some buildings go so far as to rename their 13th floors to avoid having it as an option on elevators, including our own office building. Conversely, 13 is a lucky number in many other countries, as is three. It is not uncommon for a Jewish person to give monetary gifts or make donations in multiples of 18. Based on anecdotal evidence, it seems fairly common for people to use birthdates when choosing lottery ticket numbers.

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In Investing, Simpler Can Often Be Better

Posted on September 11, 2014 | Investor Update

Investor-Update

The financial industry loves complexity. There is an ever-growing number of computerized models designed to maximize the returns from securities and optimize portfolio allocations, among other things (including executing trades faster). This complexity has led to new research, new strategies and new products.

Complexity can lead to unintended consequences, however. We saw this in 1998, when hedge fund Long-Term Capital Management imploded. We saw it again during the last financial crisis. Wall Street’s process of stripping and repackaging mortgage loans resulted in securities that looked good on a spreadsheet, but were disastrous in a portfolio.

Complexity also exists at the individual investor level. The investment industry is currently pitching alternative funds designed to follow hedge fund-like strategies. The strategies used by these funds often are not easy to understand (even by the advisers selling them). Complexity even exists at the stock selection level, where it is very possible for a strategy to be misunderstood by all but a small group of investors.

What is complex to one person may seem simple to another. Answering three questions can determine whether a strategy is too complex for you: Do you understand what the strategy is designed to look for? Can you easily follow the strategy? Do you understand what its potential risks are? If you cannot answer yes to these questions, then the strategy may not be right for you. At the very least, you need to learn more about the strategy before proceeding.

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In Investing, Simpler Can Often Be Better

Posted on September 4, 2014 | Investor Update

Investor-Update
The financial industry loves complexity. There is an ever-growing number of computerized models designed to maximize the returns from securities and optimize portfolio allocations, among other things (including executing trades faster). This complexity has led to new research, new strategies and new products.

Complexity can lead to unintended consequences, however. We saw this in 1998, when hedge fund Long-Term Capital Management imploded. We saw it again during the last financial crisis. Wall Street’s process of stripping and repackaging mortgage loans resulted in securities that looked good on a spreadsheet, but were disastrous in a portfolio.

Complexity also exists at the individual investor level. The investment industry is currently pitching alternative funds designed to follow hedge fund-like strategies. The strategies used by these funds often are not easy to understand (even by the advisers selling them). Complexity even exists at the stock selection level, where it is very possible for a strategy to be misunderstood by all but a small group of investors.

What is complex to one person may seem simple to another. Answering three questions can determine whether a strategy is too complex for you: Do you understand what the strategy is designed to look for? Can you easily follow the strategy? Do you understand what its potential risks are? If you cannot answer yes to these questions, then the strategy may not be right for you. At the very least, you need to learn more about the strategy before proceeding.

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Seven Rules for Beating the Market

Posted on August 29, 2014 | Investor Update

Investor-Update
Last week, I discussed how beating the market is hard to do. I wrote the commentary to provoke an awareness of the challenge that faces anyone pursuing an active strategy. Bluntly put, if you try to handpick investments without a disciplined, rational, well-thought-out plan for doing so, (barring really good luck) you will underperform.

A task that is hard is not one that is impossible. Individual investors can do better than the S&P 500. Today, I’m going to give guidance on how. It will be guidance that applies to a wide variety of specific approaches, including value, growth and technical analysis. I’m going to intentionally keep the guidance broad for an important reason: Regardless of the investing style you like to follow, the overarching rules for success don’t change.

Rule 1: The optimal strategy is not one that maximizes return, but rather one that helps you stick to your long-term investing plan and achieve your goals. Big returns always sound enticing. Pitched by someone with a charismatic personality, a high-return strategy sounds even better. But if you can’t stick to the strategy because of its complexity, the volatility it incurs, the time commitment it requires, the number of transactions associated with it, your interest level or any other reason, then it’s not an optimal strategy for you. If you are unwilling to or can’t stick with a strategy, don’t use it.

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Don’t Assume Beating the Market Is Easy

Posted on August 22, 2014 | Investor Update

Investor-Update
The majority of investors use active strategies for a single reason: to beat the market. There are other reasons, of course, to handpick securities (or pay a fund manager to do so), such as realizing a higher stream of portfolio income or reducing volatility. Today, though, I want to focus on what you should consider when trying to beat the market.

The financial industry has done a great job making beating the market seem easy. Go to just about any financial media outlet (traditional or social) and you’ll find plenty of chatter claiming index funds are for suckers. What you often won’t find is a frank discussion about the long-term results actually realized by a large group of investors or fund managers.

There is a good reason for this: The numbers aren’t good. Consider the performance data published in our 2014 Guide to the Top Mutual Funds. Just 35% of funds with 10-year track records beat the S&P 500 index on a 10-year annualized basis. In other words, you had nearly a two-thirds chance of trailing the S&P 500 over the past 10 years if you bought an actively managed fund. The actual odds are worse because funds that folded over the last 10 years are excluded (“survivorship bias”) from the current guide and taxes are excluded from the return calculations.

The performance hurdle is not just limited to mutual funds. Barry Ritholtz, who writes The Big Picture Blog, says an active trader has to beat the S&P 500 by 25% annually to come out ahead. The large margin primarily reflects the impact of taxes. The active trader pays short-term taxes, and these costs add up. The long-term passive investor, conversely, pays little in taxes until he or she retires and makes withdrawals at a potentially lower tax rate.

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Are Smart Beta ETFs Smart Investments?

Posted on August 15, 2014 | Investor Update

Investor-Update
The concept of smart beta funds has intrigued me. Smart beta funds use quantitative rankings to determine what stocks to hold and how to weight them. I agree with the general concept, but I wondered if smart beta exchange-traded funds (ETFs) actually delivered better performance. So I used the data in our ETF Guide to conduct an analysis.

This would seem to be an easy task: just line up the funds and compare the returns. After all, most funds, be they mutual funds or ETFs, can be quickly categorized as passive or active, small cap or large cap, domestic or international, etc. With smart beta ETFs, things weren’t so simple. In fact, I quickly found myself facing a quandary: What actually counts as a smart beta fund?

Morningstar does not designate funds as being smart beta in the data it supplies. (We use Morningstar’s data for our mutual fund guide, our ETF guide and our Quarterly Mutual Fund Update.) A search on Google for a list of smart beta ETFs didn’t turn up much either. This meant my first step was to create a list of smart beta ETFs.

The first few choices were easy. I knew there are ETFs based on Research Affiliates smart beta indexes, such as the PowerShares FTSE RAFI US 1000 (PRF). I included ETFs based on equal-weight market capitalization indexes, such as Guggenheim S&P 500 Equal Weight (RSP), even though equal-weight indexes were in existence before the term “smart beta” became popular.

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