Journal of Financial Planning: September 2017
Harold Evensky, CFP®, AIF®, is chairman of Evensky & Katz/Foldes Financial. He frequently speaks on investment and financial planning issues, and is author of Wealth Management
and co-editor of The Investment Think Tank.
Tao Gou, Ph.D., CFP®, is an assistant professor at William Patterson University.
It is a pleasure to introduce my guest contributor, Tao Guo. Tao is a recent Ph.D. graduate in personal financial planning from Texas Tech and an assistant professor in finance and financial planning at William Patterson University. I know you’ll learn a lot from his column. Enjoy. – H.E.
“Evolution and Disruption in the Wealth Management Industry” by Charlotte Beyer (Journal of Wealth Management, Spring 2017). The long-time industry veteran Charlotte Beyer offers her insights on changes in the wealth management industry, including:
Today’s ultra-high net worth clients are much younger, more sophisticated, and have vastly different perspectives and preferences than their predecessors. They embrace a broader worldview and a “lean” lifestyle. They are interested in devoting their entire wealth to make a difference in the world while they are still alive. The late astronaut John Glenn referred to this as a goal of “live-acy” rather than the traditional legacy goal.
The female client base is growing quickly, but the female-friendly communication style and the number of women professionals has lagged. A 2012 study showed that women control about 33 percent of the wealth in U.S. and Canada, and this number is growing substantially. Another recent study has indicated that 52 percent of women out-earn their spouse, and 73 percent of women consider themselves to be the financial decision maker in the family.
The value proposition of advisers is changing. Clients are getting more sophisticated. They are more comfortable using technology for their finances; they are aware of the fiduciary duty and adviser compensation structures and have developed their own expectations. Many advisers don’t seem to keep up with these changes, but rather act like Luddites.
I recently had a chance to meet Beyer in person and asked her to say a few words to Journal readers. Her advice: “If you don’t adapt to change, you can’t survive. But if you adapt and stick to your conviction that financial planning is at the heart of wealth management, you will thrive.”
“Factors—Theory, Statistics, and Practice” by Stephen A. Ross (Journal of Portfolio Management, Special Issue 2017). Factor investing is a hot topic. New investment products that use factor investing strategies are offered on a daily basis, and new factors are proposed continuously. Ross suggests taking one step back and thinking about the theory and potential issues with factor investing:
The factor investing strategy is inspired by the arbitrage pricing theory (APT). If there are multiple factors that could explain the individual stock return, we can construct a portfolio that inherits the factor exposures from its constituent stocks and manage the risk and return. The factors are essentially the returns of a portfolio constructed in a certain way. However, APT does not identify any of these factors.
These factors are selected from a significant number of candidates through a statistical process. But the selection criteria are not stringent. Just like physicists need a five-sigma event to identify the Higgs boson, Ross suggests that maybe a higher standard needs to be established when selecting these factors.
Concerns are raised on the lack of strong theoretical foundations for these chosen factors. If one factor is statistically significant, and we have a hard time justifying it with a theory, maybe we are just data-mining the results.
“Inefficiencies in the Pricing of Exchange-Traded Funds” by Antti Petajisto (Financial Analysts Journal, First Quarter 2017). When we talk about ETFs, we lay our eyes on their advantages over mutual funds: transparency, tax efficiency, liquidity, intra-day trading, etc. This paper brings up the issue of pricing inefficiencies of ETFs.
ETFs with identical portfolios are supposed to have similar prices. However, Petajisto found that the average price deviation of ETFs with identical portfolios was about 100 bps. Larger deviations existed in asset classes such as some international funds and non-Treasury bond funds. The deviations were minor in asset classes such as diversified U.S. equity funds and nominal U.S. Treasury bonds. The paper provides price deviation estimations for a long list of asset classes. Petajisto explains that the arbitrage can be difficult and risky in some markets, which is consistent with the observed higher price deviation in some emerging market funds.
These pricing inefficiencies seem to be persistent with periodical spikes. The price deviation was the widest in late 2008. An active trading strategy built to exploit these pricing inefficiencies could generate a Carhart alpha of up to 16 percent annually using asset classes that have higher price deviations.
What can the planners or investors do? (1) Recognize that certain share classes have larger price deviations and remember to compare the ETF price with its intrinsic value before trading; (2) The intraday indicative value (IIV), which is updated by the exchange every 15 seconds, can be a better measure of intrinsic value than the net asset value; but be cautious, the IIV also has its own limitations; and (3) look at the official price premiums and trade when the premium is flat in the past few days.
“A Review of Fixed-Income Indexing and Index Investing” by Hongfei Tang and Xiaoqing Eleanor Xu (The Journal of Wealth Management, Spring 2017). This article is extremely informative for two reasons: (1) I believe many practitioners are much more familiar with equity indices than bond indices, even though we all believe that bond portfolios deserve equal attention; and (2) bond indices by nature are much more complicated than equity indices. Some highlights of this paper include:
Bond indices have experienced four major changes in the past decades. The indices have changed significantly due to: bank mergers, acquisitions, and bank failures; the emergence of global multi-class and multi-currency bond indices; the introduction of fundamental weighted indices; and the emergence of ETF products that track certain bond indices.
Bond indices traditionally are weighted based on market value, which could result in the greater weight for more leveraged sectors/countries and less weight for emerging markets (due to their less-developed bond markets). The consequence is greater credit risk and/or interest rate risk exposure. Fundamental-weighted indices started to debut in 2009 and have become a popular alternative. These indices weight investments based on fundamental factors such as country GDP, fiscal sustainability, corporate cash flow, etc. However, fundamental investing needs active management, which leads to higher transaction cost and frequent portfolio rebalance. Tang and Xu show that a traditional bond index outperformed a fundamental index by 0.12 percent per month when the stock market return was positive, but underperformed by the same 0.12 percent per month when the stock market return was negative.
The majority of top 20 U.S.-listed bond ETFs have an expense ratio of 0.2 percent or lower and an average price premium of under 0.1 percent over their net asset value. This suggests that bond ETFs are very efficient investment vehicles. However, bond ETFs in general suffer from higher tracking error (relative to their benchmark index) mostly due to lower liquidity, larger amounts of underlying bond components, and the need for frequent rebalancing.
“Neural Evidence of Regret and Its Implications for Investor Behavior” by Cary Frydman and Colin Camerer (The Review of Financial Studies, November 2016). Behavioral finance studies are often built on field experiments in an effort to isolate as many affecting factors as possible to identify the causal relation between one factor and the investor behavior. Yet these experiments still cannot avoid biases, measuring errors, etc. The use of functional magnetic resonance imaging (fMRI) in behavioral finance studies make it possible to perform biologically direct tests on the relation between emotion and investor behavior.
Previous neuroscience literature identified the brain area that is closely related to regret. Frydman and Camerer conducted an asset market experiment and tracked participants’ brain activities. The neural data showed that participants experienced regret right after they observed the price of their recently sold stock go up. Participants with higher levels of regret were more likely to not repurchase the stock even when it was optimal to do so. Having this stock in your portfolio could constantly remind you that you made a mistake selling it, and that doesn’t feel good. This behavior is called the repurchase effect.
“Peer Pressure: Social Interaction and the Disposition Effect” by Rawley Z. Heimer (The Review of Financial Studies, November 2016). How would you behave in an online social network dedicated to stock trading? Would you do anything to impress others? Using a unique dataset, Heimer found that interaction on stock trading social networks increased the chances of disposition effect. The author proposed that it might be because the investor wants to create a positive self-image, but ends up making more suboptimal investment decisions.
Befriended traders in the network developed correlated levels of disposition effect. Heimer explains that traders may have been concerned about their performance benchmarked on their “friends’” performance, which led to more investment mistakes. Additionally, inexperienced traders, who could gain the most from the social network interactions, were found to be the ones most likely to display disposition effect.