Tag Archives: earnings-center

Buy The Winners

People come up with all kinds of reasons not to buy stocks with strong momentum. Some of the most common reasons that I hear are: Stocks with high momentum are risky. Stocks with high momentum are overvalued. Stocks with high momentum are susceptible to reversals. As for the first point, yes, buying stocks with high momentum is risky. So is buying stocks with weak momentum. As far as that goes, buying any stock is risky (stocks with good valuations, bad valuations, small cap, mid cap, large caps…) The stock market is a risky place. It can also be a very rewarding place. As for the second point, yes, sometimes high momentum stocks have higher valuations than low momentum stocks. But not always. Also, it is not uncommon for stocks with high price momentum to far exceed earnings expectations, and lo and behold, it often turns out that maybe they really weren’t overvalued after all. Finally, the concern about high momentum names being susceptible to reversals. There is truth to this. Momentum is a trend-following strategy, and all trends work great until they end. However, the key is whether or not enough money can be made while the trends are in place to make up for the amount of money that will be lost during changes in leadership. To the data. The Ken French Data Library is a fantastic resource for testing the merits of different strategies, as it includes performance for a variety of investment approaches (momentum, value, size, dividend yield…). One of the ways that the Ken French Data Library segments their universe of U.S. mid- and large-cap stocks is by size and momentum. The results below show performance of three different portfolios. All three are from a strategy that invests in stocks in the top half of market capitalization from their investment universe. The “High” momentum portfolio is an equally-weighted portfolio of the stocks from the universe, with the best momentum over the previous 12 months, the “Middle” momentum portfolio is an equally-weighted portfolio of stocks from the universe with moderate momentum (30-70th percentile) over the previous 12 months, and the “Bottom” momentum is an equally-weighted portfolio of stocks from the universe with the weakest momentum over the previous 12 months. All three portfolios were rebalanced monthly. Returns are inclusive of dividends, but do not include any fees or transaction costs. *12/31/1926 – 9/30/2015 Over this nearly 89-year period of time, the High momentum portfolio had an annualized return of 15.08%, the Middle momentum portfolio had an annualized return of 10.46%, and the Bottom momentum portfolio had an annualized return of 4.56%. Furthermore, the High momentum portfolio outperformed the Middle momentum portfolio in 86% of rolling 5-year periods, and outperformed the Bottom momentum portfolio in 94% of rolling 5-year periods over this period of time. Bottom line: Buy the winners (and continue to hold them as long as they remain strong). It doesn’t work all the time, but it works a high percentage of the time. When it comes to choosing long-term investment strategies that can be the cornerstone for an asset allocation, momentum makes a compelling argument to be in the mix. One final thought. I can’t tell you how often I see people make reference to the compelling returns of momentum over time and then say something like, “but whatever you do, never use it as a standalone factor!” Still baffled by that one. Seems that it works just fine as a single factor. To be clear, I am not arguing that momentum should be the only factor in an entire allocation. We have frequently made the argument, along with others, that momentum and value strategies tend to be good complements. However, I see no reason why a single-factor momentum strategy can’t make up a meaningful portion of a client’s overall asset allocation. The relative strength strategy is NOT a guarantee. There may be times where all investments and strategies are unfavorable and depreciate in value.

When Picking Mutual Funds, Don’t Be The Dumb Money

For the typical retail investor, mutual fund research reveals an uncanny ability to pick the worst fund categories at the worst possible times. The reason has to do with the tendency to base these types of decisions on “gut feeling” or emotion, rather than careful analysis. Investors feel most comfortable climbing aboard overvalued sectors of the fund universe towards the tail end of bull markets, only to flee to safety when stock prices are closer to their lowest. First identified by researchers Andrea Frazzini from NYU and Owen Lamont from Harvard, the poor timing ability of fund investors has come to be referred to as the “dumb money” effect. Emotion, limited attention, misguided perceptions and inexperience lead retail investors to make questionable decisions. This tendency to invest more in funds with high positive sentiment (for example tech stocks in the 1990s), and to pull out of funds with high negative sentiment (for example liquidating stock funds in 2008 and moving to bond funds), has led retail investors to lose on average about 1.5% annually, according to a 2007 analysis by Geoffrey Friesen of the University of Nebraska and Travis Sapp of Iowa State. Understanding investor behavior provides insight into why retail investors underperform the market. It also reveals how an investor, with a modest amount of additional effort, can improve their performance by avoiding common decision mistakes. Recent performance is the force that drives dumb money losses for many retail investors. This isn’t surprising since mutual fund advertisements and fund prospectuses tend to emphasize how well the mutual fund has performed in the past. Most investors shop for mutual funds the way they would for a toaster or microwave oven. Instead of researching the quality and durability of the product, they use shortcuts – cues of quality such as brand name recognition, an appealing marketing campaign, or a recommendation from a friend or family member. Yale researcher James Choi and his co-authors David Laibson and Brigitte Madrian of Harvard investigated how an average investor uses information on a mutual fund prospectus using identical S&P 500 index funds with different fund initiation dates. In addition to the prospectus, they gave respondents in different groups a “cheat sheet” that summarized differences in fund fees, and another that spelled out how the objective of all funds was to mimic the S&P 500. Samples of both employees and Wharton MBA students (with average SAT score at the 98th percentile) consistently focused on the obviously irrelevant fund performance rather than on fund fees even when presented with information that should have helped them make better choices. Brad Barber of UC Davis and Terrance Odean of Berkeley blame return chasing on the limited attention span of individual investors. According to their investor attention hypothesis, most of us have limited time to devote to researching mutual funds. We can either invest a huge amount of time and effort into learning how to evaluate and select funds, or we can simply invest in ones that capture our attention. The fact that mutual fund investors are attracted by the shiny funds does not serve them well in a market where sentiment can drive the value of securities too high or too low. A simple way to break the cycle of mutual fund underperformance is to develop an investment policy in which the investor maintains a diversified portfolio that reallocates periodically as market values change. This naturally works against investor sentiment by increasing investment in bonds when stock prices are rising and reducing one’s bond allocation when stock prices have fallen. Azi Ben-Rephael of Indiana University and his co-authors estimate monthly shifts between bond and stock mutual funds and find that investors consistently do the opposite-they shift to bond funds when equity values drop and back toward stock funds when equities rise in value. I use the monthly calculated shift in equity funds during the two significant equity bear markets of 2001-2002 and 2007-2009. In both cases, mutual fund investors move sharply toward bonds after stock prices have fallen. Investors appear to be unwilling to follow a disciplined long-run investment strategy by maintaining their portfolio risk exposure in a down market. Since poorly timed mutual fund sales are more harmful than poorly timed purchases, these flights to safety can have a significant impact on long-run portfolio performance. Including an investment policy statement inevitably leads to a discussion of the importance of rebalancing during good times and bad, allowing a client to anticipate portfolio volatility and follow a smart money strategy. Friesen and Sapp found that sentiment-driven underperformance on load funds was twice as large (1.92% per year) as the performance gap on no-load funds (0.96%). Incubated funds are also significantly more likely to be load funds. This is consistent with other studies that suggest that the mutual fund universe can be split between funds that are sold through the broker channel and funds that are bought through a direct channel. It is far easier to sell a privately incubated fund with significant recent excess performance, than it is to sell a fund with average performance. This is so even if neither fund is actually more likely to outperform in the future. It would be tempting to conclude that bad investor timing is primarily the result of inexperienced investors making bad choices, but a recent study by Ilia Dichev of Emory University and Gwen Yu of Harvard found that dollar-weighted returns on hedge funds are between 3% and 7% lower than time weighted returns. This is more than twice the dumb money difference observed in mutual fund investments. Since hedge fund investors are primarily institutions and extremely wealthy individuals, apparently even the professionals can get caught up in the excitement of investing in hot funds. Whether novice or professional, it is easy for an investor to fall into the trap of chasing returns of attention-grabbing funds. The good news is that investors who avoid relying on their emotions are much more likely to succeed in the long run. And a skilled investment advisor can help a client tune out the noise.

The Investment Landscape

As an addition to my Optimal Asset Allocation post on October 20 , I thought I’d share this graph which helps explain how I view the current investment landscape. Principle #1: The goal of investment is to beat inflation over the time period which the investment is held. To paraphrase a Warren Buffett article from 2012 – “investing is the transfer to others of purchasing power now with the reasoned expectation of receiving more purchasing power in the future. More succinctly, investing is forgoing consumption now in order to have the ability to consume more at a later date. From this definition there flows an important corollary: The riskiness of an investment should be measured by the probability – the reasoned probability – of that investment causing its owner a loss of purchasing power over his contemplated holding period. Assets can fluctuate greatly in price and not be risky as long as they are reasonably certain to deliver increased purchasing power over their holding period.” Principle #2: Again to paraphrase Buffett – investors should put more money into their best ideas – those which offer a higher risk-adjusted return. And the corollary to this principle is “Wait for the fat pitch”, i.e. be patient, ignore the daily market moves, and then load up when the market offers a bargain. With these two principles in mind, the graph below presents my projected asset class returns compared against the expected future inflation rate. Then I allocate among assets using 1) the Standard Deviation and Sharpe Ratio of returns – as risk measures, and 2) the Kelly Formula – to make sure the best ideas get more money applied to them. (click to enlarge) The results of my calculations are displayed in the chart on the Optimal Asset Allocation page.