April 18, 2013
Relative strength investors will be glad to know that James Picerno’s Capital Spectator blog has an article on the wonders of momentum. He discusses the momentum “anomaly” and its history briefly:
Momentum is one of the oldest and most persistent anomalies in the financial literature. The tendency of positive or negative returns to persist for a time seems like a ridiculously simple predictor, but it works. There’s an ongoing debate about why it works, but the results in numerous tests speak loud and clear. Unlike many (most?) reported sources of alpha, the market-beating and risk-lowering results linked to momentum strategies appear to be immune to arbitrage.
Informally, it’s fair to say that investors have been exploiting momentum in various forms for as long as humans have been trading assets. Formally, the concept dates to at least 1937, when Alfred Cowles and Herbert Jones reviewed momentum in their paper “Some A Priori Probabilities in Stock Market Action.” In the 21st century, an inquiring reader can easily find hundreds of papers on the subject, most of it published in the wake of Jegadeesh and Titman’s seminal 1993 work: “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” which marks the launch of the modern age of momentum research.
I think his observation that momentum (relative strength to us) has been around since humans have been trading assets is spot on. It’s important to keep that in mind when thinking about why relative strength works—and why it has been immune to arbitrage. He writes:
Momentum, it seems, is one of the rare risk factors with features that elude so many other strategies: It’s persistent, conceptually straightforward, robust across asset classes, and relatively easy to implement. It’s hardly a silver bullet, but nothing else is either.
The only mystery: Why are we still talking about this factor in glowing terms? We still don’t have a good answer to explain why this anomaly hasn’t been arbitraged away, or why it’s unlikely to meet an untimely demise anytime soon.
Mr. Picerno raises a couple of important points here. Relative strength does have a lot of attractive features. The reason it is not a silver bullet is that it underperforms severely from time to time. Although that is also true of other strategies, I think the periodic underperformance is one of the reasons why the excess returns have not been arbitraged away.
Although he suggests we don’t have a good answer about why momentum works, I’d like to offer my explanation. I don’t know if it’s a good answer or not, but it’s what I’ve arrived at after years of research and working with relative strength portfolios—not to mention a degree in psychology and a couple of decades of seeing real investors operate in the market laboratory.
- Relative strength straddles both fundamental analysis and behavioral finance.
- High relative strength securities or assets are generally strong because they are undergoing fundamental improvement or are in a sweet spot for fundamentals. In other words, if oil prices are trending strongly higher, it’s not surprising that certain energy stocks are strong. That’s to be expected from the fundamentals. Often there is improvement at the margin, perhaps in revenue growth or operating margin—and that improvement is often underestimated by analysts. (Research shows that investors are more responsive to changes at the margin than to the absolute level of fundamental factors. For example, while Apple’s operating margin grew from 2.2% in 2003 to 37.4% in 2012, the stock performed beautifully. Even though the operating margin is expected to be in the 35% range this year—which is an extremely high level—the stock is getting punished. Valero’s stock price plummeted when margins went from 10.0% in 2006 to 2.4% in 2009, but has doubled off the low as margins rebounded to 4.8% in 2012. Apple’s operating margin on an absolute basis is drastically higher than Valero’s, but the delta is going the wrong way.) High P/E multiples can often be maintained as long as margin improvement continues, and relative strength tends to take advantage of that trend. Often these trends persist much longer than investors expect.
- From the behavioral finance side, social proof helps reinforce relative strength. Investors herd and they gravitate toward what is already in motion, and that reinforces the price movement. They are attracted to the popular and repelled by the unpopular.
- Periodic bouts of underperformance help keep the excess returns of relative strength high. When momentum goes the wrong way it can be ugly. Perhaps margins begin to contract and financial results are worse than analysts expect. The security has been rewarded with a high P/E multiple, which now begins to unwind. The herd of investors begins to stampede away, just as they piled in when things were going well. Momentum can be volatile and investors hate volatility. Stretches of underperformance are psychologically painful and the unwillingness to bear pain (or appropriately manage risk) discourages investors from arbitraging the excess returns away.
In short, I think there are multiple reasons why relative strength works and why it is difficult to arbitrage away the excess returns. Those reasons are both fundamental and behavioral and I suspect will defy easy categorization. Judging from my morning newspaper, human nature doesn’t change much. Until it does, markets are likely to work the same way they always have—and relative strength is likely to continue to be a powerful return factor.
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Investor Behavior, Markets, Relative Strength Research, Thought Process | Tagged: behavioral finance, investor behavior, momentum, return factor, volatility | 
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Posted by:
Mike Moody
April 10, 2013
Morningstar does a pretty deep dive into momentum in their article Does Momentum Investing Work? I highly recommend reading the whole article as it covers some excellent long-term studies of momentum. It also has a nice profile of our PowerShares DWA Technical Leaders ETF (PDP).
While practitioners have been exploiting this relationship for decades, the idea has gained broad acceptance in the academic community only within the past 20 years. Momentum runs counter to the predictions of the efficient market hypothesis, but the evidence is too overwhelming to ignore.
Included in their article was the following study of momentum on U.S. and global stocks:
The tables below illustrate the momentum effect among large-cap U.S. and global stocks. Each column represents a fifth of the total number of stocks in the sample, which are ranked by their momentum. While there is not a linear relationship between the momentum quintiles, stocks with the highest momentum consistently outperform those in the lowest momentum quintile. Small-cap stocks tend to exhibit a stronger momentum effect. However, they can be more expensive to trade.
I also enjoyed this part about how the persistence of excess returns from momentum strategies continues to baffle people:
This evidence creates a puzzle. If the market were efficient, a simple trading rule should not produce superior returns. Arbitrage is a powerful force that should eliminate any excess profits, and yet, momentum has persisted 20 years after it was first widely published. Perhaps more troubling to disciples of Ben Graham and Warren Buffett, momentum appears to be at odds with decades of research, which suggest that stocks trading at low valuations tend to outperform.
The article also makes a strong case for why momentum makes a better companion for value than does growth:
In their paper, “Value and Momentum Everywhere,” Asness, Moskowitz, and Pedersen found that momentum worked well when value didn’t, and vice versa. Because they are two sides of the same coin, each with excess returns, combining value and momentum in a portfolio can offer powerful diversification benefits.
It’s not necessary, or advisable, to abandon value investing to benefit from momentum. Instead, momentum may be a good substitute for investors’ growth allocations. Momentum offers higher expected returns than growth and tends to be less correlated with value. The chart below compares the performance of a portfolio consisting equal weights in the Russell 1000 Value and Growth indexes, with a portfolio that replaces the growth allocation with the AQR Momentum Index. The two portfolios have similar volatility, but the value and momentum portfolio offers slightly better absolute and risk-adjusted returns.
Finally, I agree with Morningstar’s assessment of why the excess returns from momentum are likely to persist:
While a diversified and systematic momentum strategy can offer a powerful way to enhance returns, selecting a few stocks on the 52-week high list is a very bad idea. It is difficult to anticipate when a run will end and there may be no greater fool to bail you out. Although momentum is a short-term phenomenon, it is best suited for long-term investors. It won’t always work, but there’s a good chance that a disciplined momentum strategy will continue to outperform over the long term. After all, investor behavior won’t change overnight.
HT: Abnormal Returns
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Posted by:
Andy Hyer
March 21, 2013
Why relative strength?
Longboard Asset Management completed a study called The Capitalism Distribution that examined stock returns from the top 3000 stocks from 1983-2007. They found that:
-39% of stocks were unprofitable investments.
-19% of stocks lost at least 75% of their value.
-64% of stocks underperformed the index.
-25% of stocks were responsible for all the market’s gains.
Simply picking a stock out of a hat means you have a 64% chance of underperforming a basic index fund, and roughly a 40% chance of losing money!
Luckily, investors don’t need to picks stocks out of a hat and hope they get lucky in order to find the winners. Relative strength provides an effective framework for building a portfolio of winners and capitalizing on long term trends. Click here to read Relative Strength and Portfolio Management by John Lewis to see the results of relative strength tests on U.S. equities over a 16 year period. As summarized in the paper:
Relative strength and momentum strategies have delivered market-beating returns for many years. There has been a great deal of research in this area by both practitioners and academics. However, despite this public disclosure of information, these strategies continue to outperform over time. Many of the testing methodologies used over the years are not consistent with real-world portfolio construction and do not address the possible range of outcomes when implementing a relative strength strategy. Our continuous, Monte Carlo testing process corrects for both of these deficiencies. Similar to other research, our process shows simple relative strength factors to be extremely robust over intermediate horizon formation periods, and weak over very short-term and long-term horizons. We also find there can be great variation in portfolio returns over short time periods, but over long holding periods the portfolios perform exceptionally well.
HT: Mebane Faber Research
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Posted by:
Andy Hyer
March 21, 2013
Morningstar came out with a piece yesterday titled Are There Better Emerging-Markets ETF Choices? The article discussed the availability of alternative beta funds in the area, and had this to say, in part, about momentum:
While there has been relatively little academic research done on momentum in emerging-markets stocks, it has been observed in this asset class. There is currently one ETF that looks to capitalize on momentum in emerging-markets stocks–PowerShares DWA Emerging Markets (PIE), which was launched in December 2007. Over the five year period ending Feb. 28, 2013, this fund’s benchmark index produced annualized returns that outstripped the MSCI Emerging Markets Index by 155 basis points while exhibiting fairly similar levels of volatility.
Risk-tolerant investors looking for more growth-oriented exposure to emerging markets may want to consider PIE; it is currently the only emerging-markets ETF of reasonable size to provide a growth tilt.
The article also discusses some of the funds that offer low-volatility exposure, but did not mention that the low-vol and high relative strength return factors often complement one another nicely. In the domestic market, we’ve seen that these factors have excess returns that are negatively correlated. Although usage of low volatility in emerging markets has a much shorter history, it’s possible that we’ll see the same thing there over time.
It’s nice to see Morningstar give relative strength some attention!
Source: Yahoo! Finance
See www.powershares.com for more information. Past performance is no guarantee of future returns.
Leave a Comment » | Markets, Relative Strength Research | Tagged: alternative beta, emerging markets, low volatility, PIE, powershares, relative strength, return factor | Permalink
Posted by:
Andy Hyer
March 21, 2013
Our partners at Arrow Funds have recently published some relative strength research that should be essential reading for any advisor who is looking to provide value to their clients. Relative Strength Turns provides important insights into the cyclical nature of relative strength performance and makes a compelling case why now may be a great time to be allocating to relative strength strategies.
Historically, over very long periods of time, each of these relative strength models outperforms a buy-and-hold equity model. However, like many investment approaches, relative strength will sometimes underperform the market, and at other times it may outperform. This comparative performance, also known as RS Alpha, can be cyclical resulting in long-term trends with significant tops followed by underperformance and bottoms folloed by outperformance, as the chart below illustrates.
When the trend turns upward, it starts long periods of time when relative strength performance above the historical average.
The normal course of business in this industry is for fund companies to pound the table on a strategy or return factor that has already had an extended run of outperformance. Arrow Funds has taken a different approach with this research. Using historical data, they make a solid case for why relative strength is a winning long-term return factor and why the opportunity to enter relative strength strategies now may be particularly profitable.
Click below to read the entire piece.
Past performance is no guarantee of future returns. Click here for disclosures.
2 Comments | Relative Strength Research | Permalink
Posted by:
Andy Hyer
February 5, 2013
Ken French’s database is an unparalleled and *free* source of all types of stock market data. We’ve used this database to track high relative strength performance versus the broad market, other indices, against moving averages, and other return factors (like value).
Let’s dip back into the well for another go-round. Today, we updated our database to account for the full year of 2012. The chart below shows the 10-year rolling return numbers for the High RS portfolio on the Ken French website. Click here to read the description of how this portfolio is constructed. In layman’s terms, it’s the biggest stocks by market capitalization (top half), and the best performing stocks by price performance (top third). The results speak for themselves. Since 1927, the 10-year rolling return of the High RS portfolio has outperformed the S&P 500 Total Return index an astonishing 100% of the time.
“All I do is win”
Source: Ken French Database, Global Financial Data, Click to enlarge
Using that data, we constructed a linear graph of the spread between the two indexes. The spread was constructed by subtracting the 10-year rolling return of the S&P Total Return from the returns of the High RS portfolio.
Source: Ken French Database, Click to enlarge
The spread looks to be exiting a recent low. Over the last near-century, these types of lows in the High RS Spread have led to extreme outperformance in the 10-year rolling numbers. Of course, there is no way to tell what will happen in the future. However, using the past as our guide, we believe that going forward, the relative strength factor will continue to be a source for outperformance in a constantly changing market.
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Posted by:
JP Lee
January 28, 2013
We are fond of relative strength. It’s a solid investment method that have proven itself over a long period of time. Sure, it has its challenges and there are certainly periods of time during which it underperforms, but all-in-all it works and it’s been good to us. It’s always nice, though, when I run across another credible source that sings its praises. Consider the following excerpt from an article on the Optimal Momentum blog:
Momentum, on the other hand, has always made sense. It is based on the phrase “cut your losses; let your profits run on,” coined by the famed economist David Ricardo in the 1700s. Ricardo became wealthy following his own advice. [Editor's note: We wrote about this in David Ricardo's Golden Rules.] Many others, such as Livermore, Gartley, Wycoff, Darvas, and Driehaus, have done likewise over the following years. Behavioral finance has given solid reasons why momentum works. The case for momentum is now so strong that two of the fathers of modern finance, Fama and French, call momentum “the premier market anomaly” that is “above suspicion.”
Momentum, on the other hand, is pretty simple. Every approach, including momentum, must determine what assets to use and when to rebalance a portfolio. The single parameter unique to momentum is the look back period for determining an asset’s relative strength. In a 1937, using data from 1920 through 1935, Cowles and Jones found stocks that performed best over the past twelve months continued to perform best afterwards. In 1967, Bob Levy came to the same conclusion using a six-month look back window applied to stocks from 1960 through 1965. In 1993, using data from 1962 through 1989 and rigorous testing methods, Jegadeesh and Titman (J&T) reaffirmed the validity of momentum. They found the same six and twelve months look back periods to be best. Momentum is not only simple, but it has been remarkably consistent over the past seventy-five years.
Momentum, on the other hand, is one of the most robust approaches in terms of its applicability and reliability. Following the 1993 seminal study by J&T, there have been nearly 400 published momentum papers, making it one of the most heavily researched finance topics over the past twenty years. Extensive academic research has shown that price momentum works in virtually all markets and time periods, from Victorian ages up to the present.
Of course, momentum is just the academic term for relative strength. For more on the history of relative strength—and how it became known as momentum in academia—see CSI Pasadena: Relative Strength Identity Theft. The bigger point is that relative strength has a lot of backing from both academics and practitioners. There are more complicated investment methods, but not many that are better than relative strength.
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Posted by:
Mike Moody
December 27, 2012
Very interesting data published by Mark Hanna that explains much of the challenges that trend followers have had over the past couple of years:
Historically the idea with basic technical analysis is to be very cautious when the market breaks key technical moving averages – especially the longer term ones i.e. 200 day moving average; and conversely be aggressive when above said averages. Since 1940 you’d get an outperformance of some 10% on the S&P 500 by following that simple rule. However in his weekly letter John Hussman points out that policy makers have created a “new normal” with their interventionist policies since 2009. It helps explain why things have been quite backwards for much of the past few years and certainly had me a bit shocked at the data. But it makes sense when you think of all the “V shaped” moves off of broken charts when an explicit intervention was announced by this central bank or that one, or one government body or another. That said the incredible lack of progress when markets are over their 200 day MA and their incredible bounces when below since 2009 (or even 2010) are quite eye opening.
To put some numbers on this, it’s worth noting that since 1940, the S&P 500 has achieved an average annual total return of 14.5% in weeks where it was above its 200-day moving average as of the prior week’s close, and just 4.4% when it was below its 200-day moving average.
By contrast, since 2009, the S&P 500 has achieved an average total return of just 5.4% annually when it has been above its 200-day average, versus 36.7% when it has been below. Put another way, advancing trends above the 200-day average have repeatedly failed, making limited net progress overall, but declines have been halted and often breathtakingly reversed with each intervention. This pattern also reflects an unfinished cycle, the completion of which is likely to significantly damage the appeal of reflexively “buying the dip.”
The recent pattern isn’t just an artifact of the rebound from the 2009 low. Even since 2010, the S&P 500 has gained just 1.5% annually when it has been above its 200-day moving average, versus a striking 46.3% annual return when it has been below. Needless to say, this pattern is not necessarily indicative of how the S&P 500 will behave in the future, and is in fact contrary to the historical pattern.
It is common to hear explanations for why the interventionist tendencies of policy makers are here to stay. However, I think it much more likely that “this too shall pass.” After all, this is surely not the first time in our history where interventionist policies have been elevated for periods of time.
HT: Abnormal Returns
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Posted by:
Andy Hyer
December 17, 2012
Although relative strength investors are not always happy about having their return factor co-opted by academics (who re-named it “momentum”), it’s always nice to see that academics love the power of momentum. In their 2007 paper, Dissecting Anomalies, Eugene Fama and Ken French cover the waterfront on return anomalies, examining them both through style sorts and regression analysis. CXO Advisory put together a very convenient summary of their findings, reproduced below.
Source: CXO Advisory (click to enlarge)
CXO’s conclusion is especially succinct: In summary, some anomalies are stronger and more consistent than others. Momentum appears to be the strongest and most consistent.
We couldn’t have said it better ourselves.
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Posted by:
Mike Moody
December 14, 2012
Eric Falkenstein has an interesting argument in his paper Risk and Return in General: Theory and Evidence. He proposes what is essentially a relative strength argument about risk and return. He contends that investors care only about relative wealth and that risk is really about deviating from the social norm. Here is the summary of his draft from the excellent CXO Advisory:
Directly measured risk seldom relates positively to average returns. In fact, there is no measure of risk that produces a consistently linear scatter plot with returns across a variety of investments (stocks, banks, stock options, yield spread, corporate bonds, mutual funds, commodities, small businesses, movies, lottery tickets and bets on horse races).
- Humans are social animals, and processing of social information (status within group) is built into our brains. People care only about relative wealth.
- Risk is a deviation from what everyone else is doing (the market portfolio) and is therefore avoidable and unpriced. There is no risk premium.
The whole paper is a 150-page deconstruction of the flaws in the standard model of risk and return as promulgated by academics. The two startling conclusions are that 1) people care only about relative wealth and that 2) risk is simply a deviation from what everyone else is doing.
This is a much more behavioral interpretation of how markets operate than the standard risk-and-return tradeoff assumptions. After many years in the investment management industry dealing with real clients, I’ve got to say that Mr. Falkenstein re-interpretation has a lot going for it. It explains many of the anomalies that the standard model cannot, and it comports well with how real clients often act in relation to the market.
In terms of practical implications for client management, a few things occur to me.
- Psychologists will tell you that clients respond more visually and emotionally than mathematically. Therefore, it may be more useful to motivate clients emotionally by showing them how saving money and managing their portfolio intelligently is allowing them to climb in wealth and status relative to their peers, especially if this information is presented visually.
- Eliminating market-related benchmarks from client reports (i.e., the reference to what everyone else is doing) might allow the client to focus just on the growth of their relative wealth, rather than worrying about risk in Falkenstein’s sense of deviation from the norm. (In fact, the further one gets from the market benchmark, the better performance is likely to be, according to studies on active share.) If any benchmark is used at all, maybe it should be related to the wealth levels of the peer group to motivate the client to strive for higher status and greater wealth.
I’m sure there is a lot more to be gleaned from this paper and I’m looking forward to having time to read it again.
1 Comment | Markets, Portfolio Theory, Relative Strength Research, Thought Process | Tagged: active share, portfolio theory, relative strength, return, risk | Permalink
Posted by:
Mike Moody
October 26, 2012
Martjin Cremers, a professor at Yale, and his colleague, Antti Petajisto, authored a paper on the concept of active share. Advisor Perspectives recently interviewed Mr. Cremers to ask about his research. (This link is worth checking out, as it has links to additional articles such as From Yale University: New Research Confirms the Value of Active Management and Compelling Evidence That Active Management Really Works.)
Active share is a holdings-based measure of how different the holdings in an active portfolio are from the benchmark portfolio. As an example, an S&P 500 index fund would have an active share of 0%, since the holdings would be identical to the benchmark. Portfolios with low active shares around 20-60% are still so close to the benchmark that they are considered closet indexers.
Where Cremers and Petajisto differ from the establishment is that by segmenting managers in this way, they believe they are able to identify a subset of managers–those with high active share–who can outperform the benchmark over time.
That result is probably the most controversial. We find significant evidence, in our view, that a lot of managers actually do have some skill.
What I find refreshing about their approach is their willingness to examine aggregate data more thoroughly. In aggregate, their data also shows that fund managers do not outperform the benchmark. Most studies stop there, pretend not to notice that numerous tested factors show evidence of long-term outperformance, and then advise investors to buy index funds and to forget about active management.
Cremers and Petajisto were not content to take the lazy road. And, in fact, when looked at in more granular fashion, the data tells a different story. Closet indexers do worse than the market, but many managers with high active share show evidence of skill. This is much more in accord with other academic research that shows that broad, robust factors like relative strength and deep value can outperform over time. A manager that pursued such a strategy would have high active share and would have a good chance of long-term outperformance. That’s exactly what our systematic relative strength strategies are designed to do.
—-this article originally appeared 2/10/2010. Last week, another well-known pundit was advancing the results of their study, which showed that managers do not outperform the market. They also took the lazy road, claiming that investors should just buy index funds. The truth is more nuanced, as Cremers and Petajisto show. There are several tested return factors that show long-term outperformance, such as value and relative strength. Managers pursuing a factor-based strategy would be likely to have high active share, and according to Cremers and Petajisto, might be just the type of manager that shows evidence of significant skill.
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Posted by:
Mike Moody
September 19, 2012
The chart below measures the percentage of high relative strength stocks that are trading above their 50-day moving average (universe of mid and large cap stocks.) As of 9/18/12.
The 10-day moving average of this indicator is 87% and the one-day reading is 88%.
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Posted by:
JP Lee
September 4, 2012
This just in from Institutional Investor: many backtests fail in real life. They write:
Makers of indexes often fill in the blanks with historic data on the components to produce hypothetical index performance. But a recent Vanguard study found that a large percentage of these hypothetical, back-filled indexes that had outperformed the U.S. stock market didn’t keep up after they went live as the index returns subsequently fell. What may be happening, says senior Vanguard ETF strategist Joel Dickson, is that indexes are being developed by “rearview mirror investing,” that is, through selection bias of what worked well in the past. The result can mean a nasty surprise for investors.
Duh.
Pretty much anyone can do data mining with the computing power available on a desktop computer. And index providers will continue to do data mining as long as investors ram money into products with lousy backtests.
Back-filled index funds attract on average twice the cash flow in the initial launch phase than funds with new indexes that don’t have such data, indicating that the availability of a track record makes the fund more attractive — even if it probably won’t last.
Good backtesting can be very useful and can give investors a good idea of what to expect in the future. But how can an investor tell if the backtest is any good or not?
One thing to examine is how robust the index methodology is. For example, when we built our Systematic Relative Strength products, we subjected them to Monte Carlo testing for robustness. That made it apparent that the systematic investment method itself was sound, even though the range of outcomes on a quarterly or annual basis can be significant.
With the proliferation of indexes for ETFs, it’s becoming important to be able to evaluate how robust the backtesting was. Probably partly because of a robust backtesting process, our Technical Leaders Index has outperformed the market since inception. I’m sure many other indexes are thoughtfully constructed—but I’m just as sure that there are some that are not.
Do your homework before you put client money at risk.
See www.powershares.com for more information. Past performance is no guarantee of future returns. A list of all holding for the previous 12 months is available upon request.
Leave a Comment » | Investor Behavior, Markets, Relative Strength Research | Tagged: backtesting, data mining, etf, monte carlo testing, PDP, relative strength, systematic investment process | Permalink
Posted by:
Mike Moody
August 15, 2012
How do you judge the merits of momentum? Gary Antonacci says there are three ways to evaluate any investment opportunity:
- The first is to require that the method make sense. Is it in tune with the nature of the markets?
- The second criterion for accepting a new investment approach is robustness.
- The final way of judging robustness is by seeing how well an approach holds up in multiple markets and time periods, as well as with different parameter values.
The whole article is worth the read, but on the subject of robustness, Antonacci states the following:
Momentum is one of the most robust approaches ever explored in terms of its applicability and reliability. Following the 1993 seminal study by Jegadeesh and Titman, there have been nearly 400 published momentum papers, making it one of the most heavily researched finance topics over the past twenty years. Extensive research has shown that price momentum works in virtually all markets and all times periods from Victorian ages up to the present. It also has performed well using a wide range of look back periods.
There will always be doubters and those too impatient to capitalize, but the data supporting momentum is pretty hard to refute.
Note: Longtime readers will recognize that relative strength is known as “momentum” in the academic community.
Leave a Comment » | Relative Strength Research | Tagged: momentum, relative strength, robust investment approaches | Permalink
Posted by:
Andy Hyer
July 25, 2012
We’ve just released a small-cap ETF with PowerShares (DWAS), which is the first U.S. relative strength small-cap ETF. We’ve done our own testing, of course, but it might also be instructive to take a look at other small-cap relative strength returns. Once again, we used the Ken French data library to calculate annualized returns and standard deviation. The construction of their relative strength index is explained here. The difference this time around is that we used small-cap stocks instead of large-cap stocks. Generally speaking, a small-cap stock is one whose price times number of outstanding shares (market capitalization) is between $300 million and $2 billion. However, the Ken French data used also includes micro-cap stocks which have an even smaller market capitalization (typically between $50-$300 million). Market cap is above $10 billion for large-cap stocks.
In the past, small-cap stocks have yielded high returns. They often perform well because companies in early stages of development have large growth potential. However, the potential of high earnings also comes with high risk. Small-cap companies face limited reserves, which make them more vulnerable than larger ones. Furthermore, in order to grow, they need to be able to replicate their business model on a bigger scale.
This is the sort of tradeoff investors must think about when choosing how to structure their portfolio. Typical factor models suggest that there are excess returns to be had in areas like value, relative strength, and small-cap, often at the cost of a little extra volatility. If you’re willing to take on more risk for the chance of higher returns, a portfolio that combines relative strength with small-cap stocks might be a good place to look!
Leave a Comment » | Relative Strength Research | Tagged: cap, capitalization, etf, large, large cap, market, relative strength, small | Permalink
Posted by:
Amanda Schaible
July 25, 2012
The chart below is the spread between the relative strength leaders and relative strength laggards (universe of mid and large cap stocks). When the chart is rising, relative strength leaders are performing better than relative strength laggards. As of 7/24/2012:
The index has taken a hit over the last few weeks. The one day reading is 66% and the 10-day reading is 77%.
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Posted by:
JP Lee
July 24, 2012
The chart below is the spread between the relative strength leaders and relative strength laggards (universe of mid and large cap stocks). When the chart is rising, relative strength leaders are performing better than relative strength laggards. As of 7/23/2012:
The RS Spread continues to trade above its 50 day moving average.
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Posted by:
Amanda Schaible
July 3, 2012
In this post, I’ll be looking at another market indicator, the VIX, which is otherwise known as the fear index. The Chicago Board Options Exchange Market Volatility Index measures the expected market volatility over the next 30 days. When VIX is low, there is a low expectation of volatility; and when high, the opposite is true. The VIX is quoted in percentage points, and roughly correlates with the expected annualized percentage change of the S&P 500.
Looking at monthly data starting in 1990, the VIX has ranged from about 10 at the end of January 2007 to about 60 at the end of October 2008. The highest reading ever was an intra-day high 89.53 on October, 24th 2008. In fact, 7 of the highest 10 readings have occurred since the financial crisis started in 2008.
To find returns, we’ve sorted the VIX into deciles, from lowest to highest. We then used Ken French’s high relative strength database (explained here) to determine the average percentage of growth 3, 6, and 12 months out.
Chart 1: Average Relative Strength Returns by VIX Decile.
The returns tend to have a U shape, with high returns at both extremes of the VIX. This is true when looking at all three periods (3, 6, and 12 months). Furthermore, average returns have been best when the VIX is extremely high rather than extremely low. To get some perspective, the bottom 20% of month-end readings range from 10 to 13, and the top 20% range from 25 to 60.
Even though some of the largest growth rates have occurred when the VIX is high, we must remember that most investors are risk averse and prefer low volatility. Therefore, convincing clients to invest when the VIX is high may be a daunting task. If you’d like to read more, both the VIX index and the preference for low volatility are discussed in this previous blog post.
There have been consistent relative strength return trends when looking at VIX readings over the past 22 years. If these trends continue, there may be high future returns next time the VIX hits an extreme level.
1 Comment | Investor Behavior, Relative Strength Research | Tagged: fear index, indicator, relative strength, returns, vix | Permalink
Posted by:
Amanda Schaible
June 27, 2012
The chart below measures the percentage of high relative strength stocks that are trading above their 50-day moving average (universe of mid and large cap stocks.) As of 6/26/12.
The 10-day moving average of this indicator is 59% and the one-day reading is 52%.
Leave a Comment » | Relative Strength Research | Permalink
Posted by:
JP Lee
June 22, 2012
Did you know that modern portfolio theory has been incorrectly applied by the industry for the past 60 years?
The foundation of investment education for CFP certificants is modern portfolio theory, which gives us tools to craft portfolios that effectively balance risk and return and reach the efficient frontier. Yet in his original paper, Markowitz himself acknowledged that the modern portfolio theory tool was simply designed to determine how to allocate a portfolio, given the expected returns, volatilities, and correlations of the available investments. Determining what those inputs should be, however, was left up to the person using the model. As a result, the risk of using modern portfolio theory – like any model – is that if poor inputs go into the model, poor results come out. Yet what happens when the inputs to modern portfolio theory are determined more proactively in response to an ever-changing investment environment? The asset allocation of the portfolio tactically shifts in response to varying inputs!
The evolution of the industry for much of the past 60 years since Markowitz’ seminal paper has been to assume that markets are at least “relatively” efficient and will follow their long-term trends, and as a result have used historical averages of return (mean), volatility (standard deviation), and correlation as inputs to determination an appropriate asset allocation. Yet the striking reality is that this methodology was never intended by the designer of the system itself; indeed, even in his original paper, Markowitz provided his own suggestions about how to apply his model, as follows:
To use [modern portfolio theory] in the selection of securities we must have procedures for finding reasonable [estimates of expected return and volatility]. These procedures, I believe, should combined statistical techniques and the judgment of practical men. My feeling is that the statistical computations should be used to arrive at a tentative set of [mean and volatility]. Judgment should then be used in increasing or decreasing some of these [mean and volatility inputs] on the basis of factors or nuances not taken into account by the formal computations…
…One suggestion as to tentative [mean and volatility] is to use the observed [mean and volatility] for some period of the past. I believe that better methods, which take into account more information, can be found.”
- Harry Markowitz, “Portfolio Selection”, The Journal of Finance, March 1952.
The whole article, The Rise of Tactical Asset Allocation, by Michael Kitces is a great summary of the problems with the way that modern portfolio has been applied. Of course, even if the industry had taken Markowitz’ advice and tried to forecast the inputs of standard deviation, covariance, and expected return they would have run into an entirely different problem—without a crystal ball, trying to forecast those inputs is no better than simply taking the historical means!
As Kitces correctly points out, there continues to be rising demand for an alternative approach to asset allocation. At Dorsey Wright, we espouse a trend following approach to asset allocation. Specifically, we allow relative strength to determine how a multi-asset class portfolio will be allocated. It is flexible, pragmatic, and it works. Try talking to your clients about it and don’t be surprised if they agree that it makes a lot of sense.
HT: Abnormal Returns
1 Comment | Relative Strength Research, Tactical Asset Alloc | Permalink
Posted by:
Andy Hyer
June 22, 2012
Investors frequently rely on market indicators, such as moving averages, to decide when to buy, sell, or hold a stock. In fact we hear all the time of the magical powers of the moving average indicator, which has the mystical capabilities of keeping you out of trouble during market downturns, while making sure you are along for the ride on any rallies.
Therefore, we decided to test performance of Ken French’s High Relative Strength Index (an explanation of this index can be found here) against 50 and 200 day moving averages. We’ve calculated returns based on the assumption that the investor buys or holds when the price of the RS stock is above the moving average, and sells when the price drops below the moving average. So when the index is above its 50-, or 200-day moving average, we are fully invested, and when it’s below, we are out of the index.
Chart 1: Returns from 1963-2012. During this time period, basing buy and sell decisions off of the 50 day moving average is more successful than being fully invested. It is important to keep in mind that this data includes the bear markets of the 1970s and 2000s.
Chart 2: Returns from 1975-2007. When we start at a different point in time, the 50 day moving average performs much more poorly. In this dataset, we’ve cut out two large bear markets, and the effect on returns is drastic. In this case, it would have been better to just buy and hold.
Table 1: Annualized Returns by Time Periods. The average annualized returns also vary based on the period of time measured. At certain times, following moving averages outperforms being fully invested; but in other periods the opposite is true. Check out the difference between the two periods of ’83-’00 and ’66-’82. Using a moving average can either make or break your returns.
Charts 3 and 4: Fully Invested Ken French – Use of 50 Day MA (5 and 10 Year Performance). Investment performance based on moving averages varies greatly over time. In some periods, it performs incredibly, while in others it does terribly.
The performance of moving average based investment is directly related to the time period in which it is measured. As shown in Table 1, the returns can be completely different even in periods that partially overlap. The question then becomes not whether or not to use a moving average, but when! If you can predict the future, you’ll easily be able to decide whether or not to use a moving average when holding an index.
4 Comments | Relative Strength Research | Tagged: 200 day, 50 day, buy-and-hold, moving average, performance, relative strength, s&p500, stock market | Permalink
Posted by:
Amanda Schaible
June 20, 2012
The Journal of Indexes has the entire current issue devoted to articles on this topic, along with the best magazine cover ever. (Since it is, after all, the Journal of Indexes, you can probably guess how they came out on the active versus passive debate!)
One article by Craig Israelson, a finance professor at Brigham Young University, stood out. He discussed what he called “actively passive” portfolios, where a number of passive indexes are managed in an active way. (Both of the mutual funds that we sub-advise and our Global Macro separate account are essentially done this way, as we are using ETFs as the investment vehicles.) With a mix of seven asset classes, he looks at a variety of scenarios for being actively passive: perfectly good timing, perfectly poor timing, average timing, random timing, momentum, mean reversion, buying laggards, and annual rebalancing with various portfolio blends. I’ve clipped one of the tables from the paper below so that you can see the various outcomes:
Click to enlarge
Although there is only a slight mention of it in the article, the momentum portfolio (you would know it as relative strength) swamps everything but perfect market timing, with a terminal value more than 3X the next best strategy. Obviously, when it is well-executed, a relative strength strategy can add a lot of return. (The rebalancing also seemed to help a little bit over time and reduced the volatility.)
Maybe for Joe Retail Investor, who can’t control his emotions and/or his impulsive trading, asset allocation and rebalancing is the way to go, but if you have any kind of reasonable systematic process and you are after returns, the data show pretty clearly that relative strength should be the preferred strategy.
—-this article originally appeared 1/8/2010. Relative strength rocks.
Leave a Comment » | From the Archives, From the MM, Markets, Relative Strength Research, Tactical Asset Alloc, Thought Process | Tagged: asset allocation, buy-and-hold, momentum, rebalancing, relative strength, systematic investment process, Tactical Asset Allocation | Permalink
Posted by:
Mike Moody
June 12, 2012
In past posts (“Relative Strength vs. Value-Performance over Time” and “Relative Strength, Decade by Decade”), I’ve used the Ken French database’s relative strength portfolio. While this is useful in concept, what solidifies the findings in my previous posts is the similarity between Ken French’s High RS data and one of our ETFs, PDP.
PDP is a PowerShares ETF based on the Dorsey Wright Technical Leaders Index. It has its own proprietary calculation method, which is different than that of the Ken French database. Yet, over the past five years, both have performed very similarly.
Table 1:
PDP has only been on the market since March of 2007. Yet, over those five years, the two indexes have performed almost exactly the same…no small feat considering the stock market over the last few years. Imagine, then, using the Ken French data as a “loose proxy” for PDP going back decades. We’re not saying the two will always perform the same—we’re just pointing out that it’s clear both indexes are exploiting the same factor (RS) in a practical way.
Currently, relative strength growth rates (10-year rolling returns) are at some of the lowest levels since the 1930s; and historically we can see that growth rates often increase once they hit rock bottom. That may bode well for relative strength returns going forward.
Chart 1:
See www.powershares.com for more information about PDP. Past performance is no guarantee of future returns. A list of all holdings for the trailing 12 months is available upon request.
Leave a Comment » | Markets, Relative Strength Research | Tagged: index, PDP, relative strength, return factors, stock market | Permalink
Posted by:
Amanda Schaible
June 5, 2012
This post explores relative strength success by decade, dating back to the 1930s. Once again, we’ve used the Ken French data library and CRSP database data. You can click here for a more complete explanation of this data.
Chart 1: Percent Outperformance by Decade. This chart shows the number of years in which relative strength has outperformed the CRSP universe each decade. RS outperformance has occurred in at least half of all years each decade.
Chart 2: Average 1-Year Performance by Decade. This chart shows the average yearly growth by decade of a relative strength portfolio and of the CRSP universe. Each decade, the average performance of relative strength has been greater than the average performance of the CRSP universe. Generally speaking, when the market’s average performance is increasing, RS outperforms CRSP by a greater percentage than it does when the market is doing poorly.
In short, relative strength has been a durable return factor for a very long time.
1 Comment | Relative Strength Research | Tagged: decade, historical, investment, momentum, over time, performance, relative strength | Permalink
Posted by:
Amanda Schaible
May 31, 2012
Thanks to the large amount of stock data available nowadays, we are able to compare the success of different strategies over very long time periods. The table below shows the performance of two investment strategies, relative strength (RS) and value, in relation to the performance of the market as a whole (CRSP) as well as to one another. It is organized in rolling return periods, showing the annualized average return for periods ranging from 1-10 years, using data all the way back to 1927.
The relative strength and value data came from the Ken French data library. The relative strength index is constructed monthly; it includes the top one-third of the universe in terms of relative strength. (Ken French uses the standard academic definition of price momentum, which is 12-month trailing return minus the front-month return.) The value index is constructed annually at the end of June. This time, the top one-third of stocks are chosen based on book value divided by market cap. In both cases, the universes were composed of stocks with market capitalizations above the market median.
Lastly, the CRSP database includes the total universe of stocks in the database as well as the risk-free rate, which is essentially the 3-month Treasury bill yield. The CRSP data serves as a benchmark representing the generic market return. It is also worthwhile to know that the S&P 500 and DJIA typically do worse than the CRSP total-market data, which makes CRSP a harder benchmark to beat.
Source:Dorsey Wright Money Management
The data supports our belief that relative strength is an extremely effective strategy. In rolling 10-year periods since 1927, relative strength outperforms the CRSP universe 100% of the time. Even in 1-year periods it outperforms 78.6% of the time. As can be seen here, relative strength typically does better in longer periods. While it is obviously possible do poorly in an individual year, by continuing to implement a winning strategy time and time again, the more frequent and/or larger successful years outweigh the bad ones.
Even more importantly, relative strength typically outperforms value investment. Relative strength defeats value in over 57% of periods of all sizes, doing the best in 10-year periods with 69.3% of trials outperforming. While relative strength and value investment strategies have historically both generally beat the market, relative strength has been more consistent in doing so.
10 Comments | Relative Strength and Value, Relative Strength Research | Tagged: historical, investment, over time, performance, relative strength, strategies, value | Permalink
Posted by:
Amanda Schaible
