Category Archives: etf

How Long Should I Give An Investment Plan?

Even the most brilliantly crafted investment plan has to be given time to work. The markets are inherently volatile but also inherently profitable. And when you start investing in the markets, you are very likely to see many highs and lows as the market gyrates before you see permanent gains. And since asset allocation involves crafting a portfolio out of many sectors which have low correlation, one component of your portfolio certainly will experience an early loss. Diversification means you will always have something to complain about. Perhaps the most important part of implementing an investment plan is the wisdom to know when one category doing poorly means you should do something and when it means nothing. We know from behavioral finance that many people give up on a brilliant investment philosophy too soon. They chase returns rather than rebalancing. And we know from studies on mutual fund flows that investors underperform the very mutual funds they are invested in because they buy funds after they have gone up and they sell funds after they have gone down. We don’t want to be the foolish investor who sells at the bottom only to reinvest at the top of the next bubble. Here is the primary question to help you discriminate between a brilliant investing strategy and a mistake: Do you have sufficient data to justify the long-term mean returns you want? It is a mistake to select an investment sector based on recent returns. In order to get meaningful statistics, you need to use the longest time horizon possible. Even 30 years is not long enough to judge which investment will have a higher mean return for the next 30 years. For example, we recently had a 30-year time period where long-term bond returns beat the return for stocks . Periodically, it is wise to reevaluate your investment selection to see if you made a mistake. You may have been enamored by the ability of a fund manager to select stocks . You may have thought a fund was worth higher fees and expenses. You may not even have understood what you were investing in. You may have invested in something that has a low or even negative mean return. Or you may have invested in an illiquid asset. If you do find a mistake, it is always a good time to sell a bad investment. There is no reason to “wait for a rebound,” because a better investment will on average rebound better for you. During the portfolio construction process, look for sectors with a high expected return, a low volatility, and a low correlation with other components of your portfolio. Then, when you experience the volatility, ask yourself if it behaved as you expected. Imagine that you have invested in a fund tracking the S&P 500 Index and it quickly experienced over two years a -19% annualized loss. Wondering if you made a mistake, you ask yourself, did your experience fit what your data expected? To answer this question, you look at the range of returns experienced by the S&P 500 Index since 1928 (all the data we have). The mean return (not including dividends) is about 7%. In the graph below, you can see this as the graph funnels around a 7% return the longer the number of years. The thick bars are 1-standard deviation from that mean; the thin bars are two standard deviations. Click to enlarge Returns within one or two standard deviations are commonplace returns. The data doesn’t just expect these, it predicts them. Within one standard deviation of the mean are approximately two out of every three returns experienced. Meanwhile, approximately 22 out of every 23 returns are within two standard deviations. As you can see, it depends on the number of years how wide the range of predicted annualized returns. Over a one-year time period, one standard deviation from the mean is from -13.00% to 28.07%. Meanwhile, over a thirty-year time period, one standard deviation from the mean is 5.45% to 8.53%. Two standard deviations for one-year time periods is -33.53% to 48.06%, and for thirty-year time periods, it is 3.91% to 10.08%. When you look at two-year time periods, the two-standard-deviation set of returns is from -21.81% to 34.56%. The return you experienced, -19%, falls in this time period, making it commonplace. Your data not only expected it, your data predicted it. Despite one-, two-, and three-year time periods all having moderate annualized losses within one-standard deviation, for the S&P 500 Index at a 7-year holding period, the bottom of the one-standard deviation range (2 out of every 3 returns experienced) rises above zero to a positive 0.02%. The bottom of the two-standard deviation range (22 out of every 23 returns) rises above zero after a 19-year period. Even good indexes which are part of a carefully crafted portfolio on the efficient frontier have a bad decade. Get rid of them at the low and you are liable to miss the recovery as the index returns revert to the mean and have some greater than average growth. And while individual stocks can go to zero, broad indexes cannot. To ensure this fact, your funds should be comprised of a large number of holdings. There is no such thing as over diversification. A large number of holdings helps ensure that the category is worth a place in your asset allocation for the long term even when returns are below average for a period of time. There are reasons to remove a sector from your asset allocation, but not simply for returns that are below average. The opposite is true, however. When a category experiences rapid appreciation, investors piling in may cause the price to rise faster than the expected earnings. A higher than normal forward P/E ratio can be an indicator of lower than expected future returns. Dynamic asset allocation would suggest trimming the allocation to sectors with a higher forward P/E ratio so that when the sector reverts to the mean, you have less experiencing the fall. Sometimes even a good investment can drop precipitously. Approximately 1 out of every 23 times the stock market will experience returns greater than two standard deviations from the mean. The markets are more abnormal than a normal Gaussian bell curve. This non-Gaussian mathematics is called Power Laws and forms the basis for fractals. Stock returns experience 4 or more standard deviations greater than normal statistics would predict. Gaussian statistics experience greater than 3 standard deviations approximately 0.2% of the time whereas the stock market experiences greater than 3 standard deviations approximately 0.56% of the time . When returns are outside of two standard deviations, the same analysis applies, but the hype from the financial news media is terrifying. The worst 12-month return for the S&P 500 was -70.13% (a 4-standard deviation loss) and ended June 30, 1932. The best 12-month return ended just 12 months later and was 146.28% (a 7-standard deviation gain). I take comfort in the fact that unusually large drops are often followed by unusually large gains. A similar pairing happened during the crash of 2008. The 12 months prior to 2/28/2009 experienced a -44.76% drop (a 3-standard deviation loss). The next 12 months appreciated 50.25% (a 3-standard deviation gain). For the most part, short-term returns should not ruin a brilliant long-term investment strategy. Normally, it is best to rebalance your portfolio selling what has gone up and buying what has gone down. If you can’t stomach rebalancing your portfolio, at least don’t lose heart and abandon the plan.

The Psychology Of Investing

The longer that I’ve been at this investing thing, the more convinced I am that the difference between an average investor and a good investor is all in the mind. I’ve been investing for over 15 years now and I’ve learned a lot along the way. I think it took me the better part of a decade to work out what makes a good business and a quality investment. The much harder aspect of investing is to summon the courage to commit your capital in the face of hundreds of other people telling you otherwise. These people can be respected investment analysts, talking heads on TV, and even your own friends and family. I now have a pretty good idea of what makes my cut as a high-quality business. That tends to be a business that produces high returns on equity in excess of 20%, strong free cash flow generation and conversion of revenue to free cash flow, all combined with a strong market opportunity and rapidly growing topline growth. Now these businesses aren’t necessarily easy to find; however, when you do identify them they are easy to spot. The harder aspect of investing is to commit your capital to these high-quality opportunities that you’ve identified in the face of 101 reasons not to do so. I’ll give you an example. Celgene (NASDAQ: CELG ) is an exceptionally high-quality business with strong rates of revenue growth and good cash flow generation. However, when you look at the stock, it’s had a rough go of things over the last three months. My own purchase is down a good 10% from where I made it. There are all manner of concerns with the stock, most of which I believe will prove to be relatively immaterial over the next five years. The biggest threat is the regulation of drug pricing under the Democrats. There is also the threat that Celgene may be unsuccessful in diversifying its revenue base away from Revlimid, its chief moneymaker. All those things are likely to be unfounded. It’s not in the Democrats’ best interest to make drug discovery unattractive to commercial interests. That will just dry up funding and investment into areas of medicine that have a real human need. Celgene also managed to negotiate a deal with the generic drug manufacturer that will effectively push out its window of exclusivity to almost 2025. That’s almost 9 years for the company to explore new partnerships, invest in new R&D and acquire potential companies that can diversify its revenue base. Yet, despite of this, the company’s stock price remains stubbornly near one-year lows while other companies are now routinely making 52-week highs. I’ve committed capital to Celgene; however, I feel I twang of remorse whenever I check my trading account and see this position solidly in the red while most of my other recent growth investments are now well in the green. I was thinking further about exactly why that is in my case. I don’t think it’s an aversion to losses. Rather I believe that in general we all have a desire for positive affirmation. That’s true for us with our friends with family and even in the workplace. We all want validation that we’ve made the right choices in all aspects of my life. Unfortunately in investing, things don’t this work that way unless you happen to ride a solid growth stock that just consistently appreciates month after month and year after year. You’re not going to get positive reinforcement of your investment decision continually. If you’re looking at taking deep value positions where you have the potential for the greatest upside, you need to lose the desire for positive affirmation and that’s not easy. In fact, it’s really hard because when you see that position continuously in the red, it makes you think that others in the market know something that you don’t or that you have missed something in your analysis. Deep value investing is a pretty lonely game. Invariably it means going against the crowd in almost every bet that you make. And this is where Buffett really stands out for me . More than any other investor, he has shown a unique ability to shut out external influences on his thinking and just go with his gut conviction in purchases of American Express (NYSE: AXP ), Solomon Brothers and to a lesser extent Coca-Cola (NYSE: KO ). These investments were all done at times when those companies were on the nose. American Express suffered from the effects of a salad oil scandal which effectively cut the company’s share price in half. Solomon Brothers suffered from a devastating bond trading scandal which at one point threatened it with bankruptcy. Even Coca-Cola ( KO ) looked like a business that was heading for a sustained slowdown at the point when Buffett invested, with annual revenue growth declining from 17.1% the decade earlier to just 5.2%. I look at my own current list of holdings, and there are more than a few that have suffered or are suffering through crises where investors doubt their ability to make a comeback. CochLear ( OTC:CHEOF ) was the most recent example of a situation where a devastating company event was successfully overcome by the company. Before 2011, CochLear was a high-quality, high-growth business delivering cochlear implants across the world. In fact, the business was the market leader for implants. Unfortunately in 2011, the company suffered from a product recall that sent the company’s share price down by almost 40%. When you are a healthcare company with a reputation for high quality, a product recall event could potentially be a devastating reputational blow. I recognized the opportunity and went in guns blazing . CochLear subsequently recovered lost market share and continues to grow strongly. The net result is that the share price has more than doubled from the lows that it reached during this period of crisis. However, it wasn’t smooth sailing. In fact, the company’s share price was depressed for a period of six months after I made my investment and there was more than an occasion there where I had to reflect and think about whether I’d made the right move. In more recent times, investors have been making assumptions that Chinese economic growth is going to slide to a standstill, and with that, the prospects of Baidu (NASDAQ: BIDU ) and Alibaba (NYSE: BABA ), two of China’s great growth stories will be heading down the toilet. However, both these companies have such strong competitive advantages that I took the view that they will likely prosper for a long time and proceeded to buy. In less than a month, the market subsequently reassessed its view of the Chinese recession and, more importantly, the long-term prospects of Baidu and Alibaba, and I find both positions up more than 17% from where I made my initial investment. The one remaining position that I have which is a real test of my conviction in the company and its ability to overcome adversity is my investment in Chipotle (NYSE: CMG ) that I’ve written about here extensively. The company has significant problems in regaining customer confidence in relation to its E. coli and norovirus scandals. This is a play where you have to believe that customers will ultimately forget these incidents over time, and the company can bring back customer trust and reestablish its position as a provider of high-quality food. However, it’s hard to see this as a long-term outcome when you’re bombarded with images of empty stores and constant analyst downgrades and reminders of incidents on social media of customers getting ill. I look at this investment as a test of my long-term ability to pick a company that has the potential to rebound after significant negative company events, and also as a test of my ability to stick with a position whose outcome is uncertain but which has the potential for significant upside. Investing is as much a test of your character as anything else. It tests the level of conviction that you have in your research and your ideas, and it’s the ultimate test because you literally have to put your money where your mouth is and be prepared to wait a long time to see if your conviction was correctly placed. Those that have the ability to master their emotions and drown out the noise truly have the qualities to be successful long-term investors. Given his track record of making many such successful contrarian plays in the presence of significant negative events and placing large amounts of capital in these plays, I place Warren Buffett at the very top of investors with the greatest mastery of their psychology. Editor’s Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks.

The Wisdom Of Twitter Crowds: Tweet-Based Asset-Allocation Strategy Outperforms Several Benchmarks

By Jacob Wolinsky Interesting study and finding from Andrew Lo re Twitter and FOMC: “The Wisdom of Twitter Crowds: Predicting Stock Market Reactions to FOMC Meetings via Twitter Feeds” Pablo D. Azar is a PhD student in the Department of Economics and Laboratory for Financial Engineering, Sloan School of Management, MIT. Email: pazar@mit.edu Andrew W. Lo is Charles E. and Susan T. Harris Professor and the Director of the Laboratory for Financial Engineering, Sloan School of Management, MIT. Email: alo-admin@mit.edu Abstract With the rise of social media, investors have a new tool to measure sentiment in real time. However, the nature of these sources of data raises serious questions about its quality. Since anyone on social media can participate in a conversation about markets—whether they are informed or not—it is possible that this data may have very little information about future asset prices. In this paper, we show that this is not the case by analyzing a recurring event that has a high impact on asset prices: Federal Open Market Committee (FOMC) meetings. We exploit a new dataset of tweets referencing the Federal Reserve and show that the content of tweets can be used to predict future returns, even after controlling for common asset pricing factors. To gauge the economic magnitude of these predictions, the authors construct a simple hypothetical trading strategy based on this data. They find that a tweet based asset-allocation strategy outperforms several benchmarks, including a strategy that buys and holds a market index as well as a comparable dynamic asset allocation strategy that does not use Twitter information. Investor sentiment has frequently been considered an important factor in determining asset prices. Traditionally, sentiment is measured by observing analyst estimates, survey data, news stories, and technical indicators such as put/call ratios and relative strength indicators. Two drawbacks of these indicators are that they are based on a relatively sparse subset of the population of investors and, except for technical indicators, are not measured in real time. The rise of social media allows us to overcome these drawbacks and measure the sentiment of a large number of individuals in real time. These data sources give the quantitative investor a new tool with which to construct portfolios and manage risk. However, because social media data is generated by individual users and not investment professionals, the following questions arise about the quality of this data: • Do user messages contain relevant information for asset pricing? • Can this information be inferred from more traditional sources, or is it truly new information? • Can social media data help predict future asset returns and shifts in volatility? To answer these questions, we focus on a single recurring event that reveals previously unknown information to the market: Federal Open Market Committee (FOMC) meetings. Eight times a year, the FOMC meets to determine monetary policy. The decisions made by the FOMC are highly watched by all market participants, and often have a significant impact on asset prices.1 To understand how investors on social media behave around FOMC meeting dates, we create a new dataset of tweets that cite the Federal Reserve. Using natural language processing techniques, we can assign a polarity score to each Twitter message, identifying the emotion in the text. We show that this polarity score can be used to predict the returns of the CRSP Value-Weighted Index, even when limiting ourselves to articles and tweets that are published at least 24 hours before the FOMC meeting. We use these results to construct trading strategies that bet more or less aggressively in a market index depending on Twitter sentiment. We find that portfolios using Twitter data can significantly outperform a passive buy-and-hold strategy. Click to enlarge Click to enlarge Full study below SSRN-id2756815