Upon thinking about the differences between the highly successful traders I recently talked with and their less successful counterparts, five features stand out. Pretty much everything else follows from these five:
1) The less successful traders are anticipating market movement and trading accordingly. The highly successful traders are identifying asset class mispricings and trading off those.
2) The less successful traders are trading particular instruments and pretty much stick to those. The highly successful traders recognize that any combination of trading instruments can be considered an asset class and appropriately priced (and gauged for mispricing).
3) The less successful traders think of their market as *the* market. The highly successful traders focus on interrelationships among markets that cut across nationalities and asset classes.
4) The highly successful traders place just as much emphasis on understanding markets as predicting them. The less successful traders don't ask "why" questions.
5) The less successful traders are convinced they have proprietary information of value that they must not disclose to anyone. The highly successful traders use their proprietary information to selectively share with other highly successful participants, thereby gaining a large informational edge.
If I had to use one phrase to capture the essence of the highly successful traders, it would be analytical creativity. These traders are creative in their thinking about markets and rigorous in their pursuit of this creativity.
Sunday, April 30, 2006
Saturday, April 29, 2006
How Professional Traders Differ From Amateurs
I very recently had the pleasure of meeting with a group of professional traders who have been very successful, but who are also looking to maintain and extend their success. Many of these are traders who can make or lose a million dollars or more--in a single day. How do such traders differ from the average independent trader who is trying to make a living? Several differences between the professionals and amateurs struck me:
1) Resources - These professionals had a wealth of analytic resources at their fingertips--and they used these resources. They had a keen eye for how their market should be priced and took advantage of occasions when it moved from that benchmark.
2) Information Networks - The pros knew other pros and constantly talked with them to find out what was going on in the marketplace. This network was an important edge for many of the traders.
3) Strategy - Every trader I talked with could enunciate his or her specific edge in the marketplace and, in some fashion, could quantify that. I could not find a pure gut trader in the bunch.
4) Adaptation - Each of the pros knew details of his or her P/L, but also detailed trading statistics such as Sharpe ratios. When the stats veered off course, they were quick to make adjustments.
5) Complexity - The professional traders employed complex trading strategies that relied on trading different instruments and timeframes, all to exploit a single idea. Many of these strategies involved hedges that managed risk, even as they aggressively pursued their ideas. The idea of buying/selling a single thing and exiting it never arose in my conversations with them.
The most striking difference is that the professional traders viewed their work not only as a career, but as a profession. They were in this for the long haul, and many had long years of experience. They almost always had advanced (often graduate) education in finance or related fields and understood the complexity of markets. They also possessed tools to quantify risk and reward that extend far beyond the popular trading literature.
The bottom line? Knowledge matters. Whether you're a carpenter, artist, or trader, it is very difficult to obtain professional results without professional tools and training.
For more on the development of expertise, check out the articles on my personal site: How Expert Traders Make Decisions; Parts 1 and 2.
1) Resources - These professionals had a wealth of analytic resources at their fingertips--and they used these resources. They had a keen eye for how their market should be priced and took advantage of occasions when it moved from that benchmark.
2) Information Networks - The pros knew other pros and constantly talked with them to find out what was going on in the marketplace. This network was an important edge for many of the traders.
3) Strategy - Every trader I talked with could enunciate his or her specific edge in the marketplace and, in some fashion, could quantify that. I could not find a pure gut trader in the bunch.
4) Adaptation - Each of the pros knew details of his or her P/L, but also detailed trading statistics such as Sharpe ratios. When the stats veered off course, they were quick to make adjustments.
5) Complexity - The professional traders employed complex trading strategies that relied on trading different instruments and timeframes, all to exploit a single idea. Many of these strategies involved hedges that managed risk, even as they aggressively pursued their ideas. The idea of buying/selling a single thing and exiting it never arose in my conversations with them.
The most striking difference is that the professional traders viewed their work not only as a career, but as a profession. They were in this for the long haul, and many had long years of experience. They almost always had advanced (often graduate) education in finance or related fields and understood the complexity of markets. They also possessed tools to quantify risk and reward that extend far beyond the popular trading literature.
The bottom line? Knowledge matters. Whether you're a carpenter, artist, or trader, it is very difficult to obtain professional results without professional tools and training.
For more on the development of expertise, check out the articles on my personal site: How Expert Traders Make Decisions; Parts 1 and 2.
Friday, April 28, 2006
SPY Up, QQQQ Weak: What Next?
Friday we saw the S&P 500 (SPY) up on the day by over .40%, but the NASDAQ 100 Index (QQQQ) down by more than -.90%.
Since March, 2003 (N = 794), we've only had eight occasions in which QQQQ has been down more than -.75% but SPY has been up in a single day. Three days later, SPY was down by an average -.45% (3 up, 5 down). That is much weaker than the average three-day change of .18% for the sample overall. Conversely, when QQQQ is weak and SPY is also weak on the day, the next three day change in SPY is distinctly bullish. More to come this weekend...
Since March, 2003 (N = 794), we've only had eight occasions in which QQQQ has been down more than -.75% but SPY has been up in a single day. Three days later, SPY was down by an average -.45% (3 up, 5 down). That is much weaker than the average three-day change of .18% for the sample overall. Conversely, when QQQQ is weak and SPY is also weak on the day, the next three day change in SPY is distinctly bullish. More to come this weekend...
Wednesday, April 26, 2006
Three Day High and Low VIX: What It Means
We made a three day high on the Dow on Wednesday with a VIX reading below 12. So I decided to investigate what happens three days later.
Since March, 2003 (N = 792 trading days), when the Dow has made a three-day high and the VIX has been 12 or higher (N = 268), the next three days in the Dow have averaged a gain of .22% (163 up, 105 down).
When the Dow has made a three-day high and the VIX has been under 12 (N = 69), the next three days in the Dow have averaged a loss of -.03% (37 up, 32 down).
Once again, we see that a low VIX is associated with subnormal short-term returns.
Since March, 2003 (N = 792 trading days), when the Dow has made a three-day high and the VIX has been 12 or higher (N = 268), the next three days in the Dow have averaged a gain of .22% (163 up, 105 down).
When the Dow has made a three-day high and the VIX has been under 12 (N = 69), the next three days in the Dow have averaged a loss of -.03% (37 up, 32 down).
Once again, we see that a low VIX is associated with subnormal short-term returns.
The VIX is a Great Measure of Daytrading Opportunity
I want to thank Dave Mabe of Stock Tickr for taking the time to post an interview with me on his site. You'll notice Stock Tickr is one of the Trader Development resources that I list on my personal site. It's a unique concept, allowing users to scan other traders' watchlists and follow their performance.
Thanks also to Woodie of Woodie's CCI Club for posting my online session with club members.
It turns out the VIX is a pretty good measure of market opportunity for intraday traders. Since March, 2003 (N = 793), the average high/low range in SPY has been 1.06%, and the absolute value of the average move from open to close has been .54%.
When VIX has been below 12 (N = 132), the average high/low range has been .80% and the average move from open to close has been .38%. When VIX has been above 20 (N = 89), the average range has been 1.72% and the average open to close move has been .92%.
Here's another way of viewing the data: The odds of getting a 1% range in SPY are about 28% when VIX <> 20. Such information is helpful in gauging profit targets and might well prove helpful in forecasting the likelihood of trending or breakout moves.
Thanks also to Woodie of Woodie's CCI Club for posting my online session with club members.
It turns out the VIX is a pretty good measure of market opportunity for intraday traders. Since March, 2003 (N = 793), the average high/low range in SPY has been 1.06%, and the absolute value of the average move from open to close has been .54%.
When VIX has been below 12 (N = 132), the average high/low range has been .80% and the average move from open to close has been .38%. When VIX has been above 20 (N = 89), the average range has been 1.72% and the average open to close move has been .92%.
Here's another way of viewing the data: The odds of getting a 1% range in SPY are about 28% when VIX <> 20. Such information is helpful in gauging profit targets and might well prove helpful in forecasting the likelihood of trending or breakout moves.
Low VIX: What It Means for the Next Day(s)
A couple of VIX observations for today's market:
We were down about -.40% on SPY during Tuesday's session. Since March, 2003 (N = 791), when we've been down between -.20% and -.40% in a single session with a VIX below 12 (N = 14), the next day's change in SPY has averaged -.10% (7 up, 7 down). That's weaker than the average one-day change of .06% (441 up, 350 down) for the sample overall. Indeed, when SPY has been down between -.20% and -.40% in a session (N = 105), the next day's returns have been slightly bearish.
In general, when VIX has been below 12 (N = 129), SPY has averaged a loss of -.12% (60 up, 69 down) over the next three days. That is much weaker than the average three-day gain of .18% (462 up, 329 down) for the sample overall. Similar results are found when we isolate VIX readings between 11 and 12.
It appears that a low VIX has been bringing subnormal near term returns. Worth keeping in mind the rest of this week.
We were down about -.40% on SPY during Tuesday's session. Since March, 2003 (N = 791), when we've been down between -.20% and -.40% in a single session with a VIX below 12 (N = 14), the next day's change in SPY has averaged -.10% (7 up, 7 down). That's weaker than the average one-day change of .06% (441 up, 350 down) for the sample overall. Indeed, when SPY has been down between -.20% and -.40% in a session (N = 105), the next day's returns have been slightly bearish.
In general, when VIX has been below 12 (N = 129), SPY has averaged a loss of -.12% (60 up, 69 down) over the next three days. That is much weaker than the average three-day gain of .18% (462 up, 329 down) for the sample overall. Similar results are found when we isolate VIX readings between 11 and 12.
It appears that a low VIX has been bringing subnormal near term returns. Worth keeping in mind the rest of this week.
Tuesday, April 25, 2006
Breadth of Market Moves: Creating a New Indicator
I'm at work creating an indicator that tracks upside and downside momentum within a basket of large cap issues as a way of gauging overall market strength. The basket contains 17 stocks that are highly weighted within the S&P 500 average and/or that represent key sectors of the S&P 500. These include consumer stocks, cyclical issues, financial companies, and technology shares. I have found in the past that tracking the number of stocks within the basket that make new highs or new lows in a given intraday time period (e.g., the past 2 hours) is very useful in detecting valid breakouts vs. false ones. The total number of stocks making new short-term highs minus new short-term lows, plotted as a cumulative total, also works well as an intraday trend measure.
My new project takes the methodology from the Demand/Supply Index (summarized each day on the Trading Psychology Weblog) and applies it to the basket of 17 issues. Thus, at the end of each day, I count the number of stocks in the basket displaying positive vs. negative short-term price momentum. At the end of Monday's trade, for instance, we had 8 stocks with positive momentum and 9 with negative. I will begin reporting this statistic on the Weblog as well, with the idea of eventually testing it for historical patterns here on this blog.
While the specific composition and sector weighting of my basket remains proprietary, my hope is that this work encourages readers to monitor more than the individual stocks or indices that they are trading. The breadth of market moves plays an important role in their continuation or reversal. An alternative to my basket would be a close monitoring of sector ETFs, their new highs/lows, momentum, etc.
My new project takes the methodology from the Demand/Supply Index (summarized each day on the Trading Psychology Weblog) and applies it to the basket of 17 issues. Thus, at the end of each day, I count the number of stocks in the basket displaying positive vs. negative short-term price momentum. At the end of Monday's trade, for instance, we had 8 stocks with positive momentum and 9 with negative. I will begin reporting this statistic on the Weblog as well, with the idea of eventually testing it for historical patterns here on this blog.
While the specific composition and sector weighting of my basket remains proprietary, my hope is that this work encourages readers to monitor more than the individual stocks or indices that they are trading. The breadth of market moves plays an important role in their continuation or reversal. An alternative to my basket would be a close monitoring of sector ETFs, their new highs/lows, momentum, etc.
Monday, April 24, 2006
Profiting From Historical Studies of Individual Stocks
Most of my posts on this blog have focused on the S&P 500 Index, which is what I predominantly trade. There is no reason, however, why historical studies can't be applied to individual equities. Indeed, such research might have even greater promise than modeling the indices, since stocks can be chosen according to their volatility and trending properties.
Today's trade offered a perfect opportunity in Google (GOOG). The stock rose over 5% on Friday on volume that was 1.83 times its 20-day average. Stocks that have made large moves are especially good candidates for study, because volatility tends to carry over from day to day. On average, a stock that has moved well on strong volume will offer good movement the next day. If there is also a directional bias to this movement, a good trade idea is born!
It turns out that, since April 2005 (N = 254 trading days), we've had 14 instances of a one-day rise in GOOG that exceeds 3% on relative volume of 1.5 times average or greater. The next day, GOOG was up by an average 1.6% (11 up, 3 down). That's much more bullish than the average one-day gain in GOOG of .34% (149 up, 106 down).
Sure enough, when we got selling in GOOG during the morning--but could not make new lows vis a vis Friday--the trade idea paid off well. I'll have an article in Trading Markets shortly outlining the trade and some lessons from it.
The moral of the story, however, is that it pays to be flexible in what one trades. Even in a low volatility S&P market, there can be excellent trading opportunities in individual stocks and, of course, outside the equity universe.
Today's trade offered a perfect opportunity in Google (GOOG). The stock rose over 5% on Friday on volume that was 1.83 times its 20-day average. Stocks that have made large moves are especially good candidates for study, because volatility tends to carry over from day to day. On average, a stock that has moved well on strong volume will offer good movement the next day. If there is also a directional bias to this movement, a good trade idea is born!
It turns out that, since April 2005 (N = 254 trading days), we've had 14 instances of a one-day rise in GOOG that exceeds 3% on relative volume of 1.5 times average or greater. The next day, GOOG was up by an average 1.6% (11 up, 3 down). That's much more bullish than the average one-day gain in GOOG of .34% (149 up, 106 down).
Sure enough, when we got selling in GOOG during the morning--but could not make new lows vis a vis Friday--the trade idea paid off well. I'll have an article in Trading Markets shortly outlining the trade and some lessons from it.
The moral of the story, however, is that it pays to be flexible in what one trades. Even in a low volatility S&P market, there can be excellent trading opportunities in individual stocks and, of course, outside the equity universe.
Sunday, April 23, 2006
Trader Development
I've updated my Trader Development page, adding quite a few new links to worthwhile blogs, services, and websites. Also included are links to two of my audio sessions for Woodie's CCI Club. My goal is to make this a central repository for services that educate and train traders. If you have suggestions for further links, don't hesitate to let me know either through the comment feature on the blog or through the email address on my bio page. Thanks!
The Major Movement Below the S&P 500 Surface
Here is what has happened over the past 25 trading sessions:
S&P 500 (SPY): Up .09%
Long Bond (TLT): Down -4.85%
Real Estate Stocks (IYR): Down -3.72%
Financial Stocks (XLF): Down -.18%
Consumer Staples Stocks (XLP): Down -2.82%
Retail Stocks (RTH): Down -2.80%
Energy Stocks (XLE): Up 9.62%
Gold (GLD): Up 14.20%
You get the idea. The S&P has gone nowhere, but this masks considerable movement beneath the surface. Energy stocks and precious metals are soaring, while bonds fall (interest rates rise). This is taking a toll on consumer and retail stocks, as well as real estate issues. Financial stocks are not feeling a similar pinch at this juncture. Because they are the most highly weighted group within the S&P 500 Index, they are a major prop for the bull market. It is difficult for me to see how sustained energy price increases, coupled with rising interest rates--a continuation of the weak dollar vs. commodities phenomenon--will not, over time, so weigh on consumers that an economic slowdown, if not a recession, becomes a reality.
S&P 500 (SPY): Up .09%
Long Bond (TLT): Down -4.85%
Real Estate Stocks (IYR): Down -3.72%
Financial Stocks (XLF): Down -.18%
Consumer Staples Stocks (XLP): Down -2.82%
Retail Stocks (RTH): Down -2.80%
Energy Stocks (XLE): Up 9.62%
Gold (GLD): Up 14.20%
You get the idea. The S&P has gone nowhere, but this masks considerable movement beneath the surface. Energy stocks and precious metals are soaring, while bonds fall (interest rates rise). This is taking a toll on consumer and retail stocks, as well as real estate issues. Financial stocks are not feeling a similar pinch at this juncture. Because they are the most highly weighted group within the S&P 500 Index, they are a major prop for the bull market. It is difficult for me to see how sustained energy price increases, coupled with rising interest rates--a continuation of the weak dollar vs. commodities phenomenon--will not, over time, so weigh on consumers that an economic slowdown, if not a recession, becomes a reality.
Saturday, April 22, 2006
Sector Correlations You Should Know About
With the big moves in oil and gold and crosscurrents in the stock indices, it's worth taking a look at how sectors move relative to one another. We can do this by measuring the correlations of their daily changes. From November, 2004 to the present (N = 358 trading days), here are some correlations of daily price changes:
S&P 500 Index and Energy Stocks (SPY/XLE): .52
S&P 500 Index and Consumer Stocks: .84
S&P 500 Index and Gold (SPY/GLD): .08
Energy Stocks and Gold (XLE/GLD): .29
Energy Stocks and Consumer Stocks (XLE/CMR): .24
Gold and Consumer Stocks (GLD/CMR): -.03
Since the start of 2006, we've seen two interesting developments in the correlations:
Energy Stocks and Gold (XLE/GLD): .54
Energy Stocks and Consumer Stocks: .15
What this may be telling us is the following:
1) Consumer stocks are very weakly correlated with movements in energy and gold--much less so than other components of the S&P 500 Index.
2) Energy stocks and gold have increased their correlation with each other, in what I view as a "weak dollar vs. commodities" phenomenon.
3) Fully 25% of the variation in the S&P 500 Index (the square of the correlation) is attributable to moves in energy issues. Over two-thirds of the variation in the S&P 500 Index is attributable to moves in consumer stocks.
4) Sectors that benefit from the growing "weak dollar vs. commodities" phenomenon are more likely to outperform sectors that rely on consumer purchasing power, which may be doubly taxed by higher interest rates/mortgage payments and higher energy prices--at least until fiscal and monetary policy addresses dollar weakness. Such crosscurrents make it difficult to sustain overall strength in the S&P 500 Index, which is a hybrid of companies that benefit from and are hurt by high commodity prices.
5) My personal conjecture is that we won't see an outright bear market until higher interest rates--needed to attract capital to dollar denominated assets--weigh on a majority of stock sectors.
S&P 500 Index and Energy Stocks (SPY/XLE): .52
S&P 500 Index and Consumer Stocks: .84
S&P 500 Index and Gold (SPY/GLD): .08
Energy Stocks and Gold (XLE/GLD): .29
Energy Stocks and Consumer Stocks (XLE/CMR): .24
Gold and Consumer Stocks (GLD/CMR): -.03
Since the start of 2006, we've seen two interesting developments in the correlations:
Energy Stocks and Gold (XLE/GLD): .54
Energy Stocks and Consumer Stocks: .15
What this may be telling us is the following:
1) Consumer stocks are very weakly correlated with movements in energy and gold--much less so than other components of the S&P 500 Index.
2) Energy stocks and gold have increased their correlation with each other, in what I view as a "weak dollar vs. commodities" phenomenon.
3) Fully 25% of the variation in the S&P 500 Index (the square of the correlation) is attributable to moves in energy issues. Over two-thirds of the variation in the S&P 500 Index is attributable to moves in consumer stocks.
4) Sectors that benefit from the growing "weak dollar vs. commodities" phenomenon are more likely to outperform sectors that rely on consumer purchasing power, which may be doubly taxed by higher interest rates/mortgage payments and higher energy prices--at least until fiscal and monetary policy addresses dollar weakness. Such crosscurrents make it difficult to sustain overall strength in the S&P 500 Index, which is a hybrid of companies that benefit from and are hurt by high commodity prices.
5) My personal conjecture is that we won't see an outright bear market until higher interest rates--needed to attract capital to dollar denominated assets--weigh on a majority of stock sectors.
Friday, April 21, 2006
Strong Dow, Weak Russell: What Next?
Yesterday's market was unusual in that the Dow (DIA) was up more than half a percent, but the Russell 2000 (IWM) was down more than half a percent. Since March, 2003 (N = 788), that has only occurred once. In fact, we've only had six occasions in which the Dow has been up more than .30% in a single day when the Russell has been down by -.30 or more on that same day. FWIW with such a small sample, the Dow was down the next day on four of those six occasions, but by three days out was up on five of the occasions.
When we widen out the parameters and look at occasions when the Dow was up by more than .10%, but the Russell down by more than -.10% (N = 45), the next day in the Dow is also bearish, with an average loss of -.19% (18 up, 27 down). That is much weaker than the average Dow daily gain of .05% (429 up, 359 down).
When we widen out the parameters and look at occasions when the Dow was up by more than .10%, but the Russell down by more than -.10% (N = 45), the next day in the Dow is also bearish, with an average loss of -.19% (18 up, 27 down). That is much weaker than the average Dow daily gain of .05% (429 up, 359 down).
Thursday, April 20, 2006
A Trading Psychology Checklist
Note: The Web seminar for Woodie's CCI Club will be at 4 PM Central Time and is free for all participants. The link to the online room is on the CCI Club home page.
How do you know if your trading psychology problem is really just about trading or is a sign of larger problems? Here is a quick checklist:
A) Does your problem occur outside of trading? For instance, do you have temper and self-control problems at home or in other areas of life, such as gambling or excessive spending?
B) Has your problem predated your trading? Did you have similar emotional symptoms when you were young or before you began your trading career?
C) Does your problem spill over to other areas of your life? Does it affect your feelings about yourself, your overall motivation and happiness in life, and your effectiveness in your work and social lives?
D) Does your problem affect other people? Do you feel as though others with whom you work or live are impacted adversely by your problem? Have others asked you to get help?
E) Do you have a family history of emotional problems and/or substance use problems? Have others, particularly in your immediate family, had treated or untreated emotional problems?
If you answered "yes" to two or more of the above items, consider that you may not be alone. More than 10% of the population qualifies with a diagnosable problem of anxiety, depression, or substance abuse. Tweaking your trading will be of little help if the problem has a medical or psychological root. A professional consultation if you answered "yes" to two or more checklist items might be your best money management strategy.
Wednesday, April 19, 2006
Question Common Wisdom!
Note: Tomorrow (Thursday, 4/20) at 4 PM CT I will be doing a free online lecture for Woodie's CCI Club. Their chat room link is on their home page.
A while ago, I got another one of those breathless advertisements announcing how the currency markets offer such great trending instruments. Since I work at a professional trading firm and have watched both the currency markets and traders trade those markets, my doubts got the better of me. I conducted an analysis of the Euro/Dollar futures and found that, in fact, the contract is quite poor as a trending instrument. What happens is that the contract has episodes of extremely high volatility, which create very large gains and losses. On a chart, it looks as though the market is trending up or down. The actual period-to-period movement, however, is quite choppy--not at all trendy.
It pays to question common wisdom.
So here's another piece of common wisdom that periodically comes my way: The S&P 500 Index tends to close near its high or low for the day. Notice that this is one way of saying that, on a day timeframe, the S&P behaves in a trending fashion. My doubts on that topic are already a matter of public record on my personal site. Still, let it not be said that I lack an open mind. I decided to consult the data.
Since January, 1999 on SPY (N = 1834 trading days), we have closed in the top 10% of the day's range on 146 occasions. We've closed in the bottom 10% of the day's range on 143 occasions. Note that by chance, we should have closed in the top and bottom 10% of the range approximately 183 times each.
Over that same time period, we closed in the top 20% of the day's range 261 times and in the bottom 20% of the day's range 235 times. By chance, we would expect to close in the top and bottom 20% of the range about 367 times each.
Stated otherwise, we close in the middle 60% of the day's range 1338 out of 1834 times or 73% of the time. If anything, this suggests a tendency to *not* close at extremes.
Since January, 2005 (N = 326), we closed in the top 20% or bottom 20% of the day's range 81 times. This means that we closed in the middle 60% of the range 75% of the time.
It pays to question common wisdom.
A while ago, I got another one of those breathless advertisements announcing how the currency markets offer such great trending instruments. Since I work at a professional trading firm and have watched both the currency markets and traders trade those markets, my doubts got the better of me. I conducted an analysis of the Euro/Dollar futures and found that, in fact, the contract is quite poor as a trending instrument. What happens is that the contract has episodes of extremely high volatility, which create very large gains and losses. On a chart, it looks as though the market is trending up or down. The actual period-to-period movement, however, is quite choppy--not at all trendy.
It pays to question common wisdom.
So here's another piece of common wisdom that periodically comes my way: The S&P 500 Index tends to close near its high or low for the day. Notice that this is one way of saying that, on a day timeframe, the S&P behaves in a trending fashion. My doubts on that topic are already a matter of public record on my personal site. Still, let it not be said that I lack an open mind. I decided to consult the data.
Since January, 1999 on SPY (N = 1834 trading days), we have closed in the top 10% of the day's range on 146 occasions. We've closed in the bottom 10% of the day's range on 143 occasions. Note that by chance, we should have closed in the top and bottom 10% of the range approximately 183 times each.
Over that same time period, we closed in the top 20% of the day's range 261 times and in the bottom 20% of the day's range 235 times. By chance, we would expect to close in the top and bottom 20% of the range about 367 times each.
Stated otherwise, we close in the middle 60% of the day's range 1338 out of 1834 times or 73% of the time. If anything, this suggests a tendency to *not* close at extremes.
Since January, 2005 (N = 326), we closed in the top 20% or bottom 20% of the day's range 81 times. This means that we closed in the middle 60% of the range 75% of the time.
It pays to question common wisdom.
Tuesday, April 18, 2006
Ten Lessons I Have Learned From Traders
Note: This article is taken from the reading for my free Web lecture on 4/20 for Woodie's CCI Club. The lecture is scheduled for 4 PM CT.
1) Trading affects psychology as much as psychology affects trading – This was really the motivating factor behind my writing the new book. Many traders experience stress and frustration because they are trading poorly and lack a true edge in the marketplace. Working on your emotions will be of limited help if you are putting your money at risk and don’t truly have an edge.
2) Emotional disruption is present even among the most successful traders – A trading method that produces 60% winners will experience four consecutive losses 2-3% of the time and as much time in flat performance as in an uptrending P/L curve. Strings of events (including losers) occur more often by chance than traders are prepared for.
3) Winning disrupts the trader’s emotions as much as losing – We are disrupted when we experience events outside our expectation. The method that is 60% accurate will experience four consecutive winners about 13% of the time. Traders are just as susceptible to overconfidence during profitable runs as underconfidence during strings of losers.
4) Size kills – The surest path toward emotional damage is to trade size that is too large for one’s portfolio. We experience P/L in relation to our portfolio value. When we trade too large, we create exaggerated swings of winning and losing, which in turn create exaggerated emotional swings.
5) Training is the path to expertise – Think of every performance field out there—sports, music, chess, acting—and you will find that practice builds skills. Trading, in some ways, is harder than other performance fields because there are no college teams or minor leagues for development. From day one, we’re up against the pros. Without training and practice, we will lack the skills to survive such competition.
6) Successful traders possess rich mental maps - All successful trading boils down to pattern recognition and the development of mental maps that help us translate our perceptions of patterns into concrete trading behaviors. Without such mental maps, traders become lost in complexity.
7) Markets change – Patterns of volatility and trending are always shifting, and they change across multiple time frames. Because of this, no single trading method will be successful across the board for a given market. The successful trader not only masters markets, but masters the changes in those markets.
8) Even the best traders have periods of drawdown – As markets change, the best traders go through a process of relearning. The ones who succeed are the ones who save their money during the good times so that they can financially survive the lean periods.
9) The market you’re in counts as much toward performance as your trading method – Some markets are more volatile and trendy than others; some have more distinct patterns than others. Finding the right fit between trader, trading method, and market is key.
10) Execution and trade management count – A surprising degree of long-term trading success comes from getting good prices on entry and exit. The single best predictor of trading failure is when the average P/L of losing trades exceeds the average P/L of winners.
1) Trading affects psychology as much as psychology affects trading – This was really the motivating factor behind my writing the new book. Many traders experience stress and frustration because they are trading poorly and lack a true edge in the marketplace. Working on your emotions will be of limited help if you are putting your money at risk and don’t truly have an edge.
2) Emotional disruption is present even among the most successful traders – A trading method that produces 60% winners will experience four consecutive losses 2-3% of the time and as much time in flat performance as in an uptrending P/L curve. Strings of events (including losers) occur more often by chance than traders are prepared for.
3) Winning disrupts the trader’s emotions as much as losing – We are disrupted when we experience events outside our expectation. The method that is 60% accurate will experience four consecutive winners about 13% of the time. Traders are just as susceptible to overconfidence during profitable runs as underconfidence during strings of losers.
4) Size kills – The surest path toward emotional damage is to trade size that is too large for one’s portfolio. We experience P/L in relation to our portfolio value. When we trade too large, we create exaggerated swings of winning and losing, which in turn create exaggerated emotional swings.
5) Training is the path to expertise – Think of every performance field out there—sports, music, chess, acting—and you will find that practice builds skills. Trading, in some ways, is harder than other performance fields because there are no college teams or minor leagues for development. From day one, we’re up against the pros. Without training and practice, we will lack the skills to survive such competition.
6) Successful traders possess rich mental maps - All successful trading boils down to pattern recognition and the development of mental maps that help us translate our perceptions of patterns into concrete trading behaviors. Without such mental maps, traders become lost in complexity.
7) Markets change – Patterns of volatility and trending are always shifting, and they change across multiple time frames. Because of this, no single trading method will be successful across the board for a given market. The successful trader not only masters markets, but masters the changes in those markets.
8) Even the best traders have periods of drawdown – As markets change, the best traders go through a process of relearning. The ones who succeed are the ones who save their money during the good times so that they can financially survive the lean periods.
9) The market you’re in counts as much toward performance as your trading method – Some markets are more volatile and trendy than others; some have more distinct patterns than others. Finding the right fit between trader, trading method, and market is key.
10) Execution and trade management count – A surprising degree of long-term trading success comes from getting good prices on entry and exit. The single best predictor of trading failure is when the average P/L of losing trades exceeds the average P/L of winners.
A (Partial) Vote of Dr. Brett's Committee
Quick update since my posting: a look at up:down volume in NYSE is bullish for the next day; check out the most recent Weblog posting.
The firmness noted in yesterday's Weblog really carried over to today's trade, fueled by the prospect that the Fed is done tightening. Meanwhile, let's look at what happens after similar strong days in the S&P 500. What I'm going to do is present several analyses, much as I do prior to each trading session. Each analysis is considered an "expert" on historical patterns and gets one vote. My leaning for the coming day's trade is determined by the net vote of my "committee of experts". This post will present only a few committee members. I generally consult a committee of at least a dozen participants.
Committee member one consists of price alone. Since March, 2003 (N = 786), we've had 49 days in which SPY has risen by more than 1.2% in a single day. There is no edge one way or another for the next day of trading, but the average three-day gain of .34% (33 up, 16 down) is much stronger than the three-day average gain of .18% (459 up, 327 down) for the sample overall. So Committee member #1 is bullish three-days out.
Committee member two consists of price and time. Basically I want to see if the recent occurrences fall into a different pattern than the older ones. When we've recently had a day that has been up by 1.2% or more in SPY (N = 24), the next two days in SPY have averaged a loss of -.01% (13 up, 11 down). When we've had a strong up day prior to December, 2003 (N = 25), the average two-day change in SPY has been a gain of .43% (18 up, 7 down). What that tells us is that upside momentum following an up day occurred early during the current bull market, but has not occurred since. Two-day returns since 2004 have been subnormal after a strong day. Committee member #2 is bearish two-days out.
Committee member three consists of price and the NYSE TRIN. When the TRIN on a strong SPY day has been very low (meaning that much volume was concentrated in rising stocks; N = 24), the three-day change in SPY thereafter has been .16% (15 up, 9 down). When the TRIN has been high on a strong day (N = 25), the three-day change in SPY has been .52% (18 up, 7 down). Tuesday was a very low TRIN day, so count Committee member #3 bearish three days out.
Committee member four consists of price and the number of stocks advancing on the day. When we've had a high number of advancers (N = 24), the next day change in SPY has been .20% (17 up, 7 down). When advancers have been relatively low (N = 25), the next day change in SPY has been -.11% (14 up, 11 down). Tuesday was a strong day for advancers, so Committee member #4 is bullish one day out; no edge three days out.
Committee member five consists of price and the price change from the prior five trading sessions. When the strong SPY day has occurred after five days of strength (N = 24), the next three-day change has been .18% (16 up, 8 down). When the strong SPY day has occurred after five days of weakness (N = 25), the next three-day change has been .50% (17 up, 8 down). Tuesday occurred after a weak five days; committee member #4 is bullish three days out.
The next Committee members consist of price, time, and those other variables. Because the most recent occurrences differ from the older ones, I see if there is any pattern in the most recent results. These members are tricky to interpret because their N is smaller and more susceptible to influence by one or two outliers. Suffice it to say that there are no distinct edges, other than a bearish pattern one day out when the strong S&P day follows five days of weakness (as on Tuesday).
So what do we have? The Committee is pretty much deadlocked. I am not going into Wednesday's trade with a strong opinion, and I am not likely to commit a large portion of my capital to any intraday setup if I'm not exploiting a longer-term, historical edge. Getting a deadlocked result and trading the next day with an open mind and smaller size is not sexy, but it's an essential aspect of money management. When the Committee is close to unanimous, that's the time to be aggressive.
Traders who survive worry about the return of their capital as well as the return on their capital.
The firmness noted in yesterday's Weblog really carried over to today's trade, fueled by the prospect that the Fed is done tightening. Meanwhile, let's look at what happens after similar strong days in the S&P 500. What I'm going to do is present several analyses, much as I do prior to each trading session. Each analysis is considered an "expert" on historical patterns and gets one vote. My leaning for the coming day's trade is determined by the net vote of my "committee of experts". This post will present only a few committee members. I generally consult a committee of at least a dozen participants.
Committee member one consists of price alone. Since March, 2003 (N = 786), we've had 49 days in which SPY has risen by more than 1.2% in a single day. There is no edge one way or another for the next day of trading, but the average three-day gain of .34% (33 up, 16 down) is much stronger than the three-day average gain of .18% (459 up, 327 down) for the sample overall. So Committee member #1 is bullish three-days out.
Committee member two consists of price and time. Basically I want to see if the recent occurrences fall into a different pattern than the older ones. When we've recently had a day that has been up by 1.2% or more in SPY (N = 24), the next two days in SPY have averaged a loss of -.01% (13 up, 11 down). When we've had a strong up day prior to December, 2003 (N = 25), the average two-day change in SPY has been a gain of .43% (18 up, 7 down). What that tells us is that upside momentum following an up day occurred early during the current bull market, but has not occurred since. Two-day returns since 2004 have been subnormal after a strong day. Committee member #2 is bearish two-days out.
Committee member three consists of price and the NYSE TRIN. When the TRIN on a strong SPY day has been very low (meaning that much volume was concentrated in rising stocks; N = 24), the three-day change in SPY thereafter has been .16% (15 up, 9 down). When the TRIN has been high on a strong day (N = 25), the three-day change in SPY has been .52% (18 up, 7 down). Tuesday was a very low TRIN day, so count Committee member #3 bearish three days out.
Committee member four consists of price and the number of stocks advancing on the day. When we've had a high number of advancers (N = 24), the next day change in SPY has been .20% (17 up, 7 down). When advancers have been relatively low (N = 25), the next day change in SPY has been -.11% (14 up, 11 down). Tuesday was a strong day for advancers, so Committee member #4 is bullish one day out; no edge three days out.
Committee member five consists of price and the price change from the prior five trading sessions. When the strong SPY day has occurred after five days of strength (N = 24), the next three-day change has been .18% (16 up, 8 down). When the strong SPY day has occurred after five days of weakness (N = 25), the next three-day change has been .50% (17 up, 8 down). Tuesday occurred after a weak five days; committee member #4 is bullish three days out.
The next Committee members consist of price, time, and those other variables. Because the most recent occurrences differ from the older ones, I see if there is any pattern in the most recent results. These members are tricky to interpret because their N is smaller and more susceptible to influence by one or two outliers. Suffice it to say that there are no distinct edges, other than a bearish pattern one day out when the strong S&P day follows five days of weakness (as on Tuesday).
So what do we have? The Committee is pretty much deadlocked. I am not going into Wednesday's trade with a strong opinion, and I am not likely to commit a large portion of my capital to any intraday setup if I'm not exploiting a longer-term, historical edge. Getting a deadlocked result and trading the next day with an open mind and smaller size is not sexy, but it's an essential aspect of money management. When the Committee is close to unanimous, that's the time to be aggressive.
Traders who survive worry about the return of their capital as well as the return on their capital.
Monday, April 17, 2006
NASDAQ and S&P 500 Performance: After a Big Move
It turns out my Trading Markets article was more topical for today's trade than I could have planned...Thanks for the many positive comments I received on the piece.
On the heels of today's weakness in the NASDAQ 100 (QQQQ), I decided to look at what happens in the S&P 500 following one-day moves in the NASDAQ.
Since March, 2003 (N = 785), when we've had a one-day rise in QQQQ of 1% or more (N = 141), SPY has averaged a gain of .02% (72 up, 69 down) over the next two days. That is weaker than the average two-day change of .17% (426 up, 359 down) for the entire sample.
When--as today--we've had a 1% or greater drop in QQQQ in a single day (N = 123), the next two days in SPY average a gain of .26% (70 up, 53 down)--stronger than average.
We've thus tended to reverse large moves in QQQQ over the short-term, with subnormal returns in SPY after QQQQ rises and superior returns after QQQQ declines.
I'll have more on the Trading Psychology Weblog about the weakness in today's market.
On the heels of today's weakness in the NASDAQ 100 (QQQQ), I decided to look at what happens in the S&P 500 following one-day moves in the NASDAQ.
Since March, 2003 (N = 785), when we've had a one-day rise in QQQQ of 1% or more (N = 141), SPY has averaged a gain of .02% (72 up, 69 down) over the next two days. That is weaker than the average two-day change of .17% (426 up, 359 down) for the entire sample.
When--as today--we've had a 1% or greater drop in QQQQ in a single day (N = 123), the next two days in SPY average a gain of .26% (70 up, 53 down)--stronger than average.
We've thus tended to reverse large moves in QQQQ over the short-term, with subnormal returns in SPY after QQQQ rises and superior returns after QQQQ declines.
I'll have more on the Trading Psychology Weblog about the weakness in today's market.
Sunday, April 16, 2006
Crude Oil and Stocks: Another Changing Relationship
To more directly assess the impact of crude oil prices on stocks, I took a look at West Texas Intermediate cash crude prices vs. the cash S&P 500 Index. Going back to March, 2003 (N = 784), I examined two-day performance in crude vs. near-term subsequent performance in SPX.
When crude rose by 4% or more in a two-day period, next day S&P performance was not affected, but performance over a three-day period averaged .04% (39 up, 36 down). That's weaker than the average three-day gain of .18% (447 up, 337 down) for the sample overall.
When crude fell by 4% or more in a two-day period, next day S&P performance also was not affected. Performance over the next three days, however, averaged .46% (41 up, 23 down), stronger than the average gain for the sample.
It thus appears that short-term weakness in oil is associated with a bounce in stocks, and short-term strength in oil is associated with stock underperformance.
Once again, however, there is a caveat. Since June, 2005, these relationships have not held. The S&P three-day performance has been tepid following two-day periods of oil strength *and* weakness. My interpretation is that stocks of late have been less reactive to oil price changes than they had been earlier in the bull market. Perhaps this is a sign that we have adapted to what earlier were seen as dangerously elevated oil prices.
In any event, I continue to find evidence that intermarket relationships are changing, creating a shift in dynamics from the early phase of the bull market. New regimes are emerging, and those who jump aboard the new relationships early might be well positioned to profit.
When crude rose by 4% or more in a two-day period, next day S&P performance was not affected, but performance over a three-day period averaged .04% (39 up, 36 down). That's weaker than the average three-day gain of .18% (447 up, 337 down) for the sample overall.
When crude fell by 4% or more in a two-day period, next day S&P performance also was not affected. Performance over the next three days, however, averaged .46% (41 up, 23 down), stronger than the average gain for the sample.
It thus appears that short-term weakness in oil is associated with a bounce in stocks, and short-term strength in oil is associated with stock underperformance.
Once again, however, there is a caveat. Since June, 2005, these relationships have not held. The S&P three-day performance has been tepid following two-day periods of oil strength *and* weakness. My interpretation is that stocks of late have been less reactive to oil price changes than they had been earlier in the bull market. Perhaps this is a sign that we have adapted to what earlier were seen as dangerously elevated oil prices.
In any event, I continue to find evidence that intermarket relationships are changing, creating a shift in dynamics from the early phase of the bull market. New regimes are emerging, and those who jump aboard the new relationships early might be well positioned to profit.
Saturday, April 15, 2006
Energy Sector and the S&P: Changing Relationships?
How does stock performance in the energy sector affect short-term performance in the S&P 500 Index? It's a relevant question, given recent interest in the new WTI crude oil ETF (USO).
I went back to March, 2003 (N = 784) to see what happens after two-day rises and declines in the energy sector (XLE). When XLE is up 2% or more in two days (N = 113), SPY averages a gain of .01% (59 up, 54 down) the next day. This is weaker than the average one-day gain of .06% (436 up, 348 down) for the sample overall.
Conversely, when XLE is down 2% or more in two days (N = 83), SPY averages a gain of .16% (47 up, 36 down) the next day. Even more impressive, SPY's gain over the next three days averages .47% (54 up, 29 down) when we have two-day weakness in XLE--much stronger than average (.17%; 457 up, 327 down).
It thus appears that strength in XLE is associated with subnormal performance in SPY and weakness in XLE leads to outperformance. Since 2005, however, this pattern has remained only partially intact. XLE strength leads to SPY underperformance (average gain of .00; 31 up, 34 down) the next day, but XLE weakness has also lead to SPY underperformance (average gain of .00 (27 up, 27 down).
I will need to follow this up with an analysis of oil prices themselves vs. the S&P. My sense is that, for energy as for interest rates, stocks are no longer responding the way they did earlier in the bull market. These shifting intermarket relationships strike me as extremely significant.
I went back to March, 2003 (N = 784) to see what happens after two-day rises and declines in the energy sector (XLE). When XLE is up 2% or more in two days (N = 113), SPY averages a gain of .01% (59 up, 54 down) the next day. This is weaker than the average one-day gain of .06% (436 up, 348 down) for the sample overall.
Conversely, when XLE is down 2% or more in two days (N = 83), SPY averages a gain of .16% (47 up, 36 down) the next day. Even more impressive, SPY's gain over the next three days averages .47% (54 up, 29 down) when we have two-day weakness in XLE--much stronger than average (.17%; 457 up, 327 down).
It thus appears that strength in XLE is associated with subnormal performance in SPY and weakness in XLE leads to outperformance. Since 2005, however, this pattern has remained only partially intact. XLE strength leads to SPY underperformance (average gain of .00; 31 up, 34 down) the next day, but XLE weakness has also lead to SPY underperformance (average gain of .00 (27 up, 27 down).
I will need to follow this up with an analysis of oil prices themselves vs. the S&P. My sense is that, for energy as for interest rates, stocks are no longer responding the way they did earlier in the bull market. These shifting intermarket relationships strike me as extremely significant.
Friday, April 14, 2006
Gold and the S&P: Is There a Relationship?
Does the price behavior of gold affect the future behavior of the S&P 500 (SPY)? I thought you'd never ask.
I went back to November, 2004 (N = 347) with the relatively new gold ETF (GLD) and examined three-day moves in GLD vs. the next three days in SPY.
When GLD was up by more than 2% in a three-day period (N = 46), SPY was higher three days later by an average .28% (29 up, 17 down). That is stronger than the average three-day gain of .08% (198 up, 149 down) for the sample overall.
When GLD was down my more than 1.5% (N = 38), SPY was higher three days later by a surprising .53% (26 up, 12 down), much stronger than average.
Interestingly, when we get large directional moves in GLD, the next three days in SPY tend to outperform their averages. It seems as though gold speculation has not been bad for stocks, and it may even capture a general positive speculative interest among traders. The tendency for stocks to rise after falls in gold is especially worth watching.
I went back to November, 2004 (N = 347) with the relatively new gold ETF (GLD) and examined three-day moves in GLD vs. the next three days in SPY.
When GLD was up by more than 2% in a three-day period (N = 46), SPY was higher three days later by an average .28% (29 up, 17 down). That is stronger than the average three-day gain of .08% (198 up, 149 down) for the sample overall.
When GLD was down my more than 1.5% (N = 38), SPY was higher three days later by a surprising .53% (26 up, 12 down), much stronger than average.
Interestingly, when we get large directional moves in GLD, the next three days in SPY tend to outperform their averages. It seems as though gold speculation has not been bad for stocks, and it may even capture a general positive speculative interest among traders. The tendency for stocks to rise after falls in gold is especially worth watching.
Reminder: Upcoming Online Seminar
Notice: This coming Thursday (April 2oth) at 4:00 PM Central Time (5:00 PM Eastern), I will be conducting a free live web seminar for Woodie's CCI Club. Woodie's site will be posting a reading prior to the seminar to kick off the discussion.
On a separate matter, here is the Trading Markets article on psychological risks of trading. That will also be a topic in the Woodie's seminar, along with ideas about improving trader performance.
On a separate matter, here is the Trading Markets article on psychological risks of trading. That will also be a topic in the Woodie's seminar, along with ideas about improving trader performance.
Thursday, April 13, 2006
Interesting Pattern: Interest Rates and Equities
Note: IMHO, one of my best Trading Markets articles is scheduled for Friday publication. It deals with the psychological risks inherent in trading, even when you have a solid edge and good risk management.
In the wake of continuing rises in interest rates, I decided to look at what happens following two-day moves in the rate of the 10-year T Note. Going back to March, 2003 (N = 784), I found 116 instances of two-day periods in which the 10-year rate rose 2% or more. Three days later, the S&P 500 Index (SPY) was up by an average .26% (76 up, 40 down). This is stronger than the average three-day gain for SPY (.17%; 457 up, 327 down).
Interestingly, when the interest rates drop more than 2% in a two-day period (N = 102), the next three days in SPY average .03% (50 up, 52 down). This is distinctly weaker than average.
It thus appears that SPY tends to rise following drops in notes (rises in rates) and fall after rises in notes (drops in rates).
BUT - ever since we've started making new highs in interest rates, this relationship has broken down. Of the last six rises of 2% or more in rates, we've seen a weaker S&P three days later on five of those occasions. This suggests that the equity market may be responding to rising rates differently than it had from 2003-2005.
In the wake of continuing rises in interest rates, I decided to look at what happens following two-day moves in the rate of the 10-year T Note. Going back to March, 2003 (N = 784), I found 116 instances of two-day periods in which the 10-year rate rose 2% or more. Three days later, the S&P 500 Index (SPY) was up by an average .26% (76 up, 40 down). This is stronger than the average three-day gain for SPY (.17%; 457 up, 327 down).
Interestingly, when the interest rates drop more than 2% in a two-day period (N = 102), the next three days in SPY average .03% (50 up, 52 down). This is distinctly weaker than average.
It thus appears that SPY tends to rise following drops in notes (rises in rates) and fall after rises in notes (drops in rates).
BUT - ever since we've started making new highs in interest rates, this relationship has broken down. Of the last six rises of 2% or more in rates, we've seen a weaker S&P three days later on five of those occasions. This suggests that the equity market may be responding to rising rates differently than it had from 2003-2005.
Wednesday, April 12, 2006
Dow Utilities and S&P Reversals
Recently I've been looking at two and three-day sector performance to gauge lead/lag relationships with the S&P 500 Index. In keeping with recent posts, I took a look at the Dow Utilities and how their two-day performance influences SPY over a three-day horizon.
Going back to March, 2003 (N = 783), the average three-day gain for SPY has been .18% (457 up, 326 down). When the Utilities have been up 1.5% or more over a two-day period (N = 79), the next three days in SPY have averaged a loss of -.03% (46 up, 33 down).
When the Utilities have been down by 1.5% or more over a two-day period, the average three-day gain in SPY has been .52% (43 up, 18 down). That's quite an edge.
What we see is that extreme two-day outcomes in the Utilities lead reversals in SPY. Let's see if that pattern holds for other sectors.
Going back to March, 2003 (N = 783), the average three-day gain for SPY has been .18% (457 up, 326 down). When the Utilities have been up 1.5% or more over a two-day period (N = 79), the next three days in SPY have averaged a loss of -.03% (46 up, 33 down).
When the Utilities have been down by 1.5% or more over a two-day period, the average three-day gain in SPY has been .52% (43 up, 18 down). That's quite an edge.
What we see is that extreme two-day outcomes in the Utilities lead reversals in SPY. Let's see if that pattern holds for other sectors.
Tuesday, April 11, 2006
Three-Day Broad Weakness: What Next?
Yesterday's Weblog entry noted that we were at a tipping point with stocks at multiweek lows; oil, gold, and interest rates at or near highs. Well, the market tipped as oil rose--and that puts us down 1.7% in SPY over a three-day period. So I decided to look at what happens after days like today, in which we're down more than 1% in SPY on a three-day basis, with total declines exceeding total advances by more than 4000 issues.
Interestingly, since March, 2003 (N = 779), we've only had 10 such occasions. It is also interesting that there is only a modest bullish bias to this small sample. Three days later, the market is up on average by .27% (6 up, 4 down). This compares to the average gain of .18% (457 up, 332 down) for the sample overall. The reason we're not getting more bullish readings is that broad market declines tend to continue in the near term before reversing. More in tonight's Weblog.
Interestingly, since March, 2003 (N = 779), we've only had 10 such occasions. It is also interesting that there is only a modest bullish bias to this small sample. Three days later, the market is up on average by .27% (6 up, 4 down). This compares to the average gain of .18% (457 up, 332 down) for the sample overall. The reason we're not getting more bullish readings is that broad market declines tend to continue in the near term before reversing. More in tonight's Weblog.
The Best Sector Predictors in a Flat Market
I took a look at the best sector predictors of two-day S&P outcome after a flat day in the S&P. Since March, 2003 (N = 781), when SPY is neither up nor down on the day more than .20% (N = 192), two days later the average price change in SPY has been .22% (118 up, 74 down).
The sector predictors I looked at included the Dow Jones Industrial Average, the Dow Transports, the Dow Utilities, the NASDAQ 100 Index, the Semiconductor Index (SMH), the Banking Index (BKX), and the Russell 2000 Index (IWM).
The two best predictors were the NASDAQ 100 Index (QQQQ) and the Dow Utilities.
I split the sample of flat SPY days in half and looked at when the QQQQ was strong vs. weak. Two days after a strong QQQQ/flat SPY day, SPY was up by an average .33% (61 up, 35 down). After a weak QQQQ/flat SPY day, SPY was up by an average .12% (57 up, 39 down). Strength in QQQQ thus appears to lead strength in SPY.
The best predictor, however, were the Dow Utilities. Two days after a strong Utilities/flat SPY day, SPY was up on average .09% (54 up, 42 down). Two days after a weak Utilities/flat SPY day, SPY was up on average .36% (64 up, 32 down). Weakness in Utilities thus appears to lead strength in SPY.
I will have more on the Utilities later today and on my personal site.
The sector predictors I looked at included the Dow Jones Industrial Average, the Dow Transports, the Dow Utilities, the NASDAQ 100 Index, the Semiconductor Index (SMH), the Banking Index (BKX), and the Russell 2000 Index (IWM).
The two best predictors were the NASDAQ 100 Index (QQQQ) and the Dow Utilities.
I split the sample of flat SPY days in half and looked at when the QQQQ was strong vs. weak. Two days after a strong QQQQ/flat SPY day, SPY was up by an average .33% (61 up, 35 down). After a weak QQQQ/flat SPY day, SPY was up by an average .12% (57 up, 39 down). Strength in QQQQ thus appears to lead strength in SPY.
The best predictor, however, were the Dow Utilities. Two days after a strong Utilities/flat SPY day, SPY was up on average .09% (54 up, 42 down). Two days after a weak Utilities/flat SPY day, SPY was up on average .36% (64 up, 32 down). Weakness in Utilities thus appears to lead strength in SPY.
I will have more on the Utilities later today and on my personal site.
Monday, April 10, 2006
Dow Utilities and the S&P 500
We were narrowly higher in the S&P 500 Index, with SPY up .15%. The Dow Utilities were stronger, up over half a percent. I went back to March, 2003 (N = 781) and found 144 days in which SPY was up on the day, but less than .30%. Two days later, SPY averaged a gain of .23% (89 up, 55 down).
When I broke the sample in half based on the change in the Dow Utilities, however, a pattern emerged. When the Utilities were strong (N = 72), the two-day gain in SPY averaged .11% (42 up, 30 down). When the Utilities were weak (N = 72), the two day gain in SPY averaged .36% (47 up, 25 down).
We thus tend to see strength when Utilities underperform SPY; underperformance when Utilities are stronger than SPY. I'll be looking further at the Utilities as a possible market barometer.
When I broke the sample in half based on the change in the Dow Utilities, however, a pattern emerged. When the Utilities were strong (N = 72), the two-day gain in SPY averaged .11% (42 up, 30 down). When the Utilities were weak (N = 72), the two day gain in SPY averaged .36% (47 up, 25 down).
We thus tend to see strength when Utilities underperform SPY; underperformance when Utilities are stronger than SPY. I'll be looking further at the Utilities as a possible market barometer.
Sunday, April 09, 2006
Volatility Spike: What Comes Next?
Friday's weak market raised the VIX, the measure of implied option volatility on the S&P 500 Index, by 8.79%. I went back all the way to January, 1990 (N = 4099 trading days) to see what happens after such a one-day volatility spike. Looking at the Dow Jones Industrial Average, I found an interesting pattern. For the group of volatility spike days (N = 329), the first hour of trading on the next day tended to be down and that next day tended to underperform the sample average. By three days out, however, there was no underperformance. Interestingly, however, since 2003 (N = 48) the first hour of trade after the volatility spike day has been up in price (29 up, 19 down), but the day overall has underperformed (-.04% vs. .04% for the sample overall). Three days out, this underperformance has largely disappeared--although I'm not seeing the three-day outperformance with the Dow that I noticed earlier in the S&P. It may well be that, after a very broad decline, it is the very broad market (not the large caps) that snaps back the most.
Finally, a reader asked about Fridays in particular. As the reader suspected, when the volatility spike day occurs on Friday, Monday has tended to be much weaker in the first hour, but largely recovers by the end of the day. This pattern has not been especially strong since 2003.
In general, broad weakness is associated with underperformance in the very short run, but reversal thereafter. This trade concept will frame my expectations for the start of the week, as I'll outline in tonight's Weblog.
ADDENDUM: I notice that, when you break the sample of volatility spike days down by the resulting VIX level, the three day outcomes for low VIX occasions (such as at present) are actually bearish. When the VIX after the spike is less than 15, the next three days in the Dow average a loss of -.17% (26 up, 31 down)--much less than the average gain of .12% (2260 up, 1849 down) for the sample overall. The results are even more bearish when we just look at the findings since 2003 (N = 22). Three days later, the Dow is down by an average .40% (8 up, 14 down). For me, such findings are a heads-up, warning of the dangers of being too complacent in bottom fishing. Such heads-up findings proved hugely profitable last October, when weakness led to further weakness for quite a few days.
Finally, a reader asked about Fridays in particular. As the reader suspected, when the volatility spike day occurs on Friday, Monday has tended to be much weaker in the first hour, but largely recovers by the end of the day. This pattern has not been especially strong since 2003.
In general, broad weakness is associated with underperformance in the very short run, but reversal thereafter. This trade concept will frame my expectations for the start of the week, as I'll outline in tonight's Weblog.
ADDENDUM: I notice that, when you break the sample of volatility spike days down by the resulting VIX level, the three day outcomes for low VIX occasions (such as at present) are actually bearish. When the VIX after the spike is less than 15, the next three days in the Dow average a loss of -.17% (26 up, 31 down)--much less than the average gain of .12% (2260 up, 1849 down) for the sample overall. The results are even more bearish when we just look at the findings since 2003 (N = 22). Three days later, the Dow is down by an average .40% (8 up, 14 down). For me, such findings are a heads-up, warning of the dangers of being too complacent in bottom fishing. Such heads-up findings proved hugely profitable last October, when weakness led to further weakness for quite a few days.
Saturday, April 08, 2006
Broad Weakness: What Comes Next?
Friday showed unusually broad weakness in the market, with 2662 NYSE issues trading down for the day and only 625 advancing. Since March, 2003 (N = 780), when we've had more than 2400 issues declining in a day (N = 38), the next day has averaged 1561 advances and 1717 declines (versus 1697 and 1557 for the sample overall). We thus see some carryover of weakness the following day in the broad market.
Three days after the broad decline, however, the average price change in SPY is .47% (27 up, 11 down), much stronger than the average gain of .18% (457 up, 323 down) for the sample overall. This sets up a possible strategy for next week of exploiting near-term weakness for a reversal and bounce. More on this tonight in the Trading Psychology Weblog.
Three days after the broad decline, however, the average price change in SPY is .47% (27 up, 11 down), much stronger than the average gain of .18% (457 up, 323 down) for the sample overall. This sets up a possible strategy for next week of exploiting near-term weakness for a reversal and bounce. More on this tonight in the Trading Psychology Weblog.
Friday, April 07, 2006
A Sobering Look at Very Short-Term Trading
It was quite a trading day, illustrating a number of the principles recently discussed on the Trading Psychology Weblog. I'll summarize in tonight's Weblog entry.
Here's an interesting finding regarding very short-term intraday opportunity. I went back to March 1, 2006 for the ES futures using one-minute data (N = 9311). When the one-minute volume was greater than 6000 (N = 622), the average range over the next three minutes was 4.82 ticks. When the one-minute volume was less than 2000 (N = 5271), the average range over the next three minutes was 3.53 ticks.
Notice that almost 60% of all one-minute periods fell into this low volume category. Notice also that a range of 3.53 ticks, when little volume likely trades at the top and bottom ticks, means that it is almost impossible to successfully scalp the market over 60% of the time. This has greatly changed the trading game for very short-term traders.
Here's an interesting finding regarding very short-term intraday opportunity. I went back to March 1, 2006 for the ES futures using one-minute data (N = 9311). When the one-minute volume was greater than 6000 (N = 622), the average range over the next three minutes was 4.82 ticks. When the one-minute volume was less than 2000 (N = 5271), the average range over the next three minutes was 3.53 ticks.
Notice that almost 60% of all one-minute periods fell into this low volume category. Notice also that a range of 3.53 ticks, when little volume likely trades at the top and bottom ticks, means that it is almost impossible to successfully scalp the market over 60% of the time. This has greatly changed the trading game for very short-term traders.
Market Participation and Follow Through
Interesting observation: We moved to five-day highs on the S&P futures, with new highs in interest rates. The number of stocks in my basket of 17 large caps making five-day highs: 2. Tough to sustain gains in a weighted index if some of the most highly weighted components aren't participating. I consistently find that the likelihood of follow through on market moves is a function of the degree of participation.
Brett
Brett
Thursday, April 06, 2006
A Fundamental Trading Reality
If I had to identify one fundamental trading reality of stock index trading, it would be this: Who is in the market and how active they are will determine the nature and extent of market movement. A greater number of large traders conducting a larger number of trades leads to greater volatility and greater likelihood of breakout, trending moves.
One reason this is so important is that current activity and volatility are well correlated with near-term future volatility. In my Trading Markets article scheduled for Friday publication, I show how traders can use information from the first 45 minutes of trading to predict opportunity for the remainder of the day. I will follow up on the topic in the Trader Performance section of my personal site this weekend.
There are many other applications of this information, as well. Figuring out exits--how much you can reasonably expect to take out of a trade--is a function of volatility. Whether or not to even participate in the marketplace might be a function of expected movement. The past is not a perfect predictor of the future, but it does provide meaningful guidelines.
One reason this is so important is that current activity and volatility are well correlated with near-term future volatility. In my Trading Markets article scheduled for Friday publication, I show how traders can use information from the first 45 minutes of trading to predict opportunity for the remainder of the day. I will follow up on the topic in the Trader Performance section of my personal site this weekend.
There are many other applications of this information, as well. Figuring out exits--how much you can reasonably expect to take out of a trade--is a function of volatility. Whether or not to even participate in the marketplace might be a function of expected movement. The past is not a perfect predictor of the future, but it does provide meaningful guidelines.
Afternoon Trading: Mean Reversion
Here's an intraday version of some research I've done with daily data. I went back to the beginning of 2005 (N = 314) and calculated the average price for the morning in the ES contract. The average price was simply the average of the open-high-low-close for the period 9:30 AM - 11:59 AM EST. I then looked at how often we touch that average price level during the afternoon trade. The results are very similar to the daily trade data: we return to the average price on about 2/3 of all occasions (66%). The odds exceed 70% when there is below average volume for the afternoon. This fits with the mean reversion/non-trending theme from previous research.
Wednesday, April 05, 2006
Intraday Analysis: Early Morning Range
For the most part, the historical analyses I post to the blog are ones lasting one to several days. To support my trading, however, I also rely on large numbers of intraday analyses. In the coming days, I will post several intraday market results to provide examples of the kinds of insights we can gain with short-term data.
For this analysis, we're using 5 minute data with the ES futures, and we're going back to January 3, 2005 (N = 314 trading days).
I'm looking at the range of the first 45 minutes of trading (9:30 AM - 10:15 AM EST) and how that is related to the range for the remainder of the morning (10:15 AM - 12:00 Noon). In other words, does a narrow range in the first 45 minutes predict a narrow range for the rest of the morning? This would be helpful for traders to know with respect to profit targets--and the gauging of likely opportunity.
When the high-low range of the first 45 minutes is .40% or greater (N = 101), the range for the remainder of the morning averages .51%. When the range for the first 45 minutes is .25% or less (N = 66), the range for the rest of the morning averages .37%.
Here's a different way of looking at it:
When the range of the first 45 minutes is wide, about 44% of the time we'll see a range for the rest of the morning that exceeds .50%. When the range of the first 45 minutes is narrow, we will see a rest-of-morning range in excess of .50% only about 14% of the time.
Why do we see this relationship? When the range of the first 45 minutes is wide, the average five-minute volume for the *entire* morning averages 13,672. When the range of the first 45 minutes is narrow, the average five-minute volume from open to noon averages 8957. A narrow early period in the market is telling us about *who* is in the marketplace and *how much* business they're doing.
For this analysis, we're using 5 minute data with the ES futures, and we're going back to January 3, 2005 (N = 314 trading days).
I'm looking at the range of the first 45 minutes of trading (9:30 AM - 10:15 AM EST) and how that is related to the range for the remainder of the morning (10:15 AM - 12:00 Noon). In other words, does a narrow range in the first 45 minutes predict a narrow range for the rest of the morning? This would be helpful for traders to know with respect to profit targets--and the gauging of likely opportunity.
When the high-low range of the first 45 minutes is .40% or greater (N = 101), the range for the remainder of the morning averages .51%. When the range for the first 45 minutes is .25% or less (N = 66), the range for the rest of the morning averages .37%.
Here's a different way of looking at it:
When the range of the first 45 minutes is wide, about 44% of the time we'll see a range for the rest of the morning that exceeds .50%. When the range of the first 45 minutes is narrow, we will see a rest-of-morning range in excess of .50% only about 14% of the time.
Why do we see this relationship? When the range of the first 45 minutes is wide, the average five-minute volume for the *entire* morning averages 13,672. When the range of the first 45 minutes is narrow, the average five-minute volume from open to noon averages 8957. A narrow early period in the market is telling us about *who* is in the marketplace and *how much* business they're doing.
An Amazing String of Market Events
How often does today's market touch yesterday's average price? Since March, 2003, we've hit the prior day's average price 65% of the time in SPY. Since February, 2006, however, we've touched the prior day's average price 76% of the time. That shows we've been much more rangebound day to day.
Now for the amazing string: We've hit the prior day's average price 13 days running. Every day during that period, all you've needed to do near the open is see if the market is above or below its previous day's average price and fade the strength or weakness.
My numbers tell me that, while the string of 13 is unusual, the tendency of such occasions to cluster is not unusual. Rangebound markets tend to stay that way for a while, thanks to persistence of (low) volatility. Lots of good trade ideas just from that concept.
Now for the amazing string: We've hit the prior day's average price 13 days running. Every day during that period, all you've needed to do near the open is see if the market is above or below its previous day's average price and fade the strength or weakness.
My numbers tell me that, while the string of 13 is unusual, the tendency of such occasions to cluster is not unusual. Rangebound markets tend to stay that way for a while, thanks to persistence of (low) volatility. Lots of good trade ideas just from that concept.
Tuesday, April 04, 2006
When Days Are Flat: What Comes Next?
Here's a followup on the volatility theme, with a shout out to Paulo de Leon, whose comments on the postings are always insightful. What we're doing is looking at the open-to-close movement of SPY as a fraction of the day's high-low range. Very positive or very negative values show markets closing near their highs or lows for the day; values near zero indicate very little net movement on the day. The sample extends from March, 2003 to present (N = 777).
When the day's movement as a fraction of the day's range has been within plus or minus 10% (N = 80), the next three days in SPY have averaged .33% (48 up, 32 down). This compares favorably with the average three-day gain for the sample overall (.18%; 455 up, 322 down).
When I broke down the low net movement days in half based upon the day's volatility (range), however, a pattern emerged. When the market was volatile but closed near its open (N = 40), the next three days averaged a gain of .56% (27 up, 13 down). When the market was nonvolatile and closed near its open, the next three days averaged a gain of only .09% (21 up, 19 down).
Flat performances on the day thus have a different meaning based on the day's volatility. Non-volatile markets that are flat from open to close appear to lead to subnormal returns in the near term. Flat but volatile markets have much more bullish near-term prospects.
When the day's movement as a fraction of the day's range has been within plus or minus 10% (N = 80), the next three days in SPY have averaged .33% (48 up, 32 down). This compares favorably with the average three-day gain for the sample overall (.18%; 455 up, 322 down).
When I broke down the low net movement days in half based upon the day's volatility (range), however, a pattern emerged. When the market was volatile but closed near its open (N = 40), the next three days averaged a gain of .56% (27 up, 13 down). When the market was nonvolatile and closed near its open, the next three days averaged a gain of only .09% (21 up, 19 down).
Flat performances on the day thus have a different meaning based on the day's volatility. Non-volatile markets that are flat from open to close appear to lead to subnormal returns in the near term. Flat but volatile markets have much more bullish near-term prospects.
First Half Hour as a Volatility Indicator
Interesting finding: I went back to 11/29/05 and hourly data in SPY. When the first half-hour in SPY is nearly unchanged (neither rising nor falling more than .05%; N = 33), the median range for the rest of the day is .61%, with only 13 of the 33 occasions hitting a range of .70%. When the first half-hour in SPY rises or falls more than .05% (N = 54), the median range for the remainder of the day has been approximately .75%, with 31 of the 54 occasions reaching .70% or greater. A slow half-hour appears to be a warning sign of low volatility for the remainder of the day. More on this topic shortly.
Monday, April 03, 2006
An Additional Note On Low 10 Day Volatility
The ten-day high-low range in SPY of only 2.08% is well below the average range of 3.72% since March, 2003 as noted earlier. When the ten-day range has been below 2.5% (N = 136), the next ten days in SPY have averaged a loss of -.18% (70 up, 66 down). This is much weaker than the average ten-day gain of .61% (471 up, 298 down).
As with the data for the opening SPY numbers, we see that low 10-day volatility leads to subnormal performance in the intermediate term.
As with the data for the opening SPY numbers, we see that low 10-day volatility leads to subnormal performance in the intermediate term.
Low Ten-Day Volatility: What Next?
We are seeing quite low volatility in the S&P 500 Index (SPY) over the past ten days. The high-low range during that period has been only about 2%. Since March, 2003 (N = 769), the average ten-day high-low range has been 3.72%.
Even more striking are the opening and closing prices for the index. Both have been within a 1% range for the ten-day period. Only one other occasion, early in March of this year, has been so non-volatile since March, 2003. In short, where the market has opened has been in a narrow band and where it has closed it has been in a narrow band. Movement in between (the high-low range) has been narrow as well.
I looked at those occasions when the opening SPY price over a 10-day period was within a 1.3% range (N = 46). Ten days later, the market was down by an average of -.39% (20 up, 26 down). This is *much* weaker than the average 10-day gain of .61% (471 up, 298 down) for the sample overall. In short, openings within a narrow band have been bearish for stocks over the intermediate term.
Here's another interesting finding. When I looked at the absolute value of the moves following 10 day narrow opens, the average size of the next 10-day moves was 1.25%. That is considerably smaller than the size of the average 10-day move (1.74%). It appears that narrow ten day periods generate smaller price changes over the next ten days, as well as more bearish ones.
Oddly, this pattern does not hold for closes in a narrow range. When the closes are within a 1.3% range over ten days (N = 33), the average size of the move over the next 10 days is still small (1.07% vs. 1.74% for the sample). There is no significant directional edge over the next ten days, however.
I'm going to need to do some deep thinking (more Intelligentsia coffee, s'il vous plait) and further investigating as to why a pattern might be present for opening prices but not others.
Addendum (10 minutes and 1 cup of coffee later):
I figured it out. The reason the narrow opens are significant is because the S&P open is highly sensitive to events from overseas markets. The fact that the opens have been in a very narrow range suggests that we have also seen low volatility worldwide, and that appears to be associated with underperformance 10 days out.
Even more striking are the opening and closing prices for the index. Both have been within a 1% range for the ten-day period. Only one other occasion, early in March of this year, has been so non-volatile since March, 2003. In short, where the market has opened has been in a narrow band and where it has closed it has been in a narrow band. Movement in between (the high-low range) has been narrow as well.
I looked at those occasions when the opening SPY price over a 10-day period was within a 1.3% range (N = 46). Ten days later, the market was down by an average of -.39% (20 up, 26 down). This is *much* weaker than the average 10-day gain of .61% (471 up, 298 down) for the sample overall. In short, openings within a narrow band have been bearish for stocks over the intermediate term.
Here's another interesting finding. When I looked at the absolute value of the moves following 10 day narrow opens, the average size of the next 10-day moves was 1.25%. That is considerably smaller than the size of the average 10-day move (1.74%). It appears that narrow ten day periods generate smaller price changes over the next ten days, as well as more bearish ones.
Oddly, this pattern does not hold for closes in a narrow range. When the closes are within a 1.3% range over ten days (N = 33), the average size of the move over the next 10 days is still small (1.07% vs. 1.74% for the sample). There is no significant directional edge over the next ten days, however.
I'm going to need to do some deep thinking (more Intelligentsia coffee, s'il vous plait) and further investigating as to why a pattern might be present for opening prices but not others.
Addendum (10 minutes and 1 cup of coffee later):
I figured it out. The reason the narrow opens are significant is because the S&P open is highly sensitive to events from overseas markets. The fact that the opens have been in a very narrow range suggests that we have also seen low volatility worldwide, and that appears to be associated with underperformance 10 days out.
Sunday, April 02, 2006
Mid Caps Outperform Large Ones: What Next?
Here's an interesting development: In the past eight trading sessions, the Dow (DIA) is down by -.89%, but the Midcap stocks (MDY) are up 2.39%. Going back to March, 2003 (N = 770), I could only find 13 occasions in which the Dow was down more than a half percent on an eight-day basis, but Midcaps were up by more than one percent.
I then looked at what happened in the Dow and Midcaps eight days later. The Dow was up by an average of .31% (8 up, 5 down)--not far off its average eight-day gain of .41% (441 up, 329 down). The Midcaps, however, were down by an average of -.36% (4 up, 9 down)--much weaker than their average eight-day gain of .74% (484 up, 286 down).
What this suggests is that when mid caps have outperformed large caps on an intermediate-term basis, the large caps have tended to outperform eight days hence. We're thus seeing reversal not only among individual trading instruments, but among the relationships between these. This may be relevant information for long/short (spread) trade ideas.
I then looked at what happened in the Dow and Midcaps eight days later. The Dow was up by an average of .31% (8 up, 5 down)--not far off its average eight-day gain of .41% (441 up, 329 down). The Midcaps, however, were down by an average of -.36% (4 up, 9 down)--much weaker than their average eight-day gain of .74% (484 up, 286 down).
What this suggests is that when mid caps have outperformed large caps on an intermediate-term basis, the large caps have tended to outperform eight days hence. We're thus seeing reversal not only among individual trading instruments, but among the relationships between these. This may be relevant information for long/short (spread) trade ideas.
Saturday, April 01, 2006
NYSE TICK Extremes: An Intermediate-Term View
I decided to take a longer-term look at the daily high and low NYSE TICK values and what they mean for future returns. For this analysis, I looked at the number of trading days in a 10-day moving period in which the low value of the day's TICK was less than -1000. This covered the period March, 2003 to the present (N = 768).
I found 29 occasions in which we had either five or six days in a ten-day period in which the low TICK was under -1000. Ten days later, SPY was up by a very large 1.47% (24 up, 5 down). That is quite an edge compared to the average 10-day gain of .61% (474 up, 294 down) for the sample overall.
I also examined 10-day occasions in which we had no daily TICK readings below -1000. If those occurred in 2003, the average gain in SPY over the next 10 days was an eye-popping 1.51% (86 up, 34 down). Since 2004, however, the average gain in SPY over the next 10 days has been an anemic .18% (76 up, 63 down).
In short, a clustering of selling pressure days have yielded superior upside returns. An absence of selling pressure was quite bullish during the earliest phase of the bull market, but since then has produced subnormal returns. Indeed, since August, 2005 (N = 27), a lack of selling pressure has led to higher prices only 7 times. Fading an absence of selling has been a fruitful strategy of late.
I found 29 occasions in which we had either five or six days in a ten-day period in which the low TICK was under -1000. Ten days later, SPY was up by a very large 1.47% (24 up, 5 down). That is quite an edge compared to the average 10-day gain of .61% (474 up, 294 down) for the sample overall.
I also examined 10-day occasions in which we had no daily TICK readings below -1000. If those occurred in 2003, the average gain in SPY over the next 10 days was an eye-popping 1.51% (86 up, 34 down). Since 2004, however, the average gain in SPY over the next 10 days has been an anemic .18% (76 up, 63 down).
In short, a clustering of selling pressure days have yielded superior upside returns. An absence of selling pressure was quite bullish during the earliest phase of the bull market, but since then has produced subnormal returns. Indeed, since August, 2005 (N = 27), a lack of selling pressure has led to higher prices only 7 times. Fading an absence of selling has been a fruitful strategy of late.
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