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.

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).

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.

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.

Ten Lessons I Have Learned From Traders

Ten Lessons I Have Learned From Traders

Brett N. Steenbarger, Ph.D.

www.brettsteenbarger.com

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Weak Daily TICK: What It Means

What does it mean when the NYSE TICK hits a very low value during the trading day? I went back to March, 2003 and investigated all instances in which the TICK hit a value of -1000 or less. This occurred 108 times out of 775 trading sessions.

One day later, the average price change in SPY was .15% (64 up, 44 down), stronger than the average daily price change of .06% (432 up, 343 down) for the sample overall. It thus appears that a day of strong selling pressure results in favorable expectations the next day.

I took the analysis one step further, however. I broke down the strong selling pressure days into those in which the absolute value of the high TICK for the day was lower than the absolute value of the low TICK (N = 52) vs. those in which the absolute value of the high TICK for the day was higher than the absolute value of the low TICK (N = 56).

Thus, we're looking at high selling pressure days with low buying pressure vs. high selling pressure days with high buying pressure.

One day after the high selling/low buying days, the average change in SPY was only .01% (27 up, 25 down)--weaker than the overall market average gain. One day after the high selling/high buying days, the average gain in SPY was an impressive .29% (37 up, 19 down)--much stronger than average.

It thus appears that strong selling pressure without countervailing buying interest tends to carry over the next day, creating subnormal returns. Strong selling pressure matched by strong buying interest creates superior returns.

More Observations About Life and Markets

Here is the Trading Markets article with new observations on life and markets. A reader astutely pointed out that it is talent *and* preparation that joins with opportunity to create success. Indeed.

As I'm writing, interest rates on the 10 year are dropping, the dollar is weakening vs. the Euro, and stocks are bouncing higher. Even on a short-term basis, these relationships are worth watching--particularly when the different markets are in sync and telling the same story.

Interest Rates Up; Financial Stocks Down

In the last four trading sessions, interest rates on the 10-year note ($TNX) have risen by about 3.85%, while financial stocks ($BKX) have been down -1.65%. What happens after we have such rising rates and weakening financial issues?

I went back to January, 2003 (N = 813) and found 99 occasions in which interest rates had risen by 3% or more in a four-day period. Four days later, interest rates rose on average another .58% (55 up, 44 down). When interest rates were up by 3% and $BKX was down more than 1% over the four-day period (N = 25), rates rose over the next four days by an average .71% (16 up, 9 down).

Interestingly, this pattern appears to have changed over the course of the lookback period. When I examined the most recent data in which interest rates were up and $BKX was down (N = 13), the next four-day rise in rates was only .12%, but the next four day change in SPY was down -.20% (6 up, 7 down). This is weaker than the average four-day gain in SPY of .18% (457 up, 356 down).

When I looked at the data in 2003 and early 2004 (N = 12), the next four-day rise in rates was 1.36%, but the average four-day change in SPY was .42% (7 up, 5 down). Early in the bull market, rate rises led to greater rate rises, but also led to stock strength. More recently, rate rises have not led to greater rate rises, but have led to stock underperformance in the near term.

Whereas stocks held their ground during interest rate rises early in the bull market, they now display subnormal returns. That appears to be particularly the case among financial and large cap issues.

A Dozen Reflections on Life and Markets

A Dozen Reflections on Life and Markets

Brett N. Steenbarger, Ph.D.

www.brettsteenbarger.com

***

Note: When I returned from vacation, I found that this article, written about two years ago, had been downloaded over 60,000 times in three days. Such are the viral ways of the Web. A followup reflections article will appear on the Trading Markets site tomorrow.

***

I've never seen a trader succeed whose explicit or implicit goal was to not lose. The trader who trades to not lose is like the person who lives to avoid death: both become spiritual hypochondriacs.

No union was ever destroyed by a failure of romance. It is the loss of respect, not love, which ends a relationship.

Love, once present, never dies. It must be killed.

Sometimes we select markets--and trading styles--much as we choose romantic partners: by their ability to validate our deepest-held images of ourselves. Our choices generally succeed, for better or for worse.

Many a trader fears boredom more than loss, thereby experiencing the two in sequence.

Goodness of character is measured in loyalty to others; greatness of character is measured in loyalty to principle.

A measure of the soul: the degree to which the surpassing achievements of others evoke inspiration rather than envy.

If you listen to the words, you'll understand the brains of the speaker. If you listen to the tone, you'll understand his heart.

Show me what a man loathes, and I will show you what he cannot accept in himself.

Two traders: one increases size after a loss; the other gets smaller. Both continue to lose.

One encounters losing traders as often as one encounters losing golfers--and for much the same reason.

The absence of self-acceptance too often masquerades as the desire for self-improvement.

Trading Update 3/29

Regular updates on the Trading Psychology Weblog will resume Thursday evening; also on Thursday, the historical pattern analyses will resume here on the TraderFeed site.

Wednesday's market was strong out of the gate, with NASDAQ and small cap issues leading the way. There was very solid buying across the market, as we vaulted to the highs of the recent range in the S&P, but went to new recent highs in the broad indices. This places us in a short term uptrending mode. Even in the face of higher interest rates, it appears that selloffs are bringing in buyers. Demand expanded greatly to 122; Supply was 41. New 20 and 65 day highs expanded to 1308 and 787; new 20 and 65 day lows were 610 and 254. Normally such upside momentum as we're seeing in the Demand/Supply numbers carries over in the short-term.

Trading Update 3/28

First interest rates moved higher on strong economic news, then stocks sold off in response to Fed tightening. The result is that we moved well below the recent multiday range, setting off a short-term downtrend. It was a good example of a dynamic discussed recently, in which moves in the stocks are most likely to trend when we see significant movements in energy, interest rates, and or currencies. New 20 and 65 day lows expanded to 618 and 234; Supply exceed Demand by 101 to 48. As long as we continue to make day over day lows and expand new lows and Supply, selling bounces below the day's average price is the operative mode.

Trading Update Monday 3/27

I'll be returning to regular blog posts and updates on the Trading Psychology Weblog on Thursday. Monday's market continued the narrow action in the S&P 500, continuing the neutral trend. It was a great illustration of the kind of day I referenced in the recent post about mean reversion. Knowing the day's average price and seeing: a) an open near the average price; and b) low volatility from the prior session; and c) modest early volume allowed traders to lean on the market's tendency to revert to that average price. Here is the Trading Markets article on that topic.

I notice that we had an expansion of new 20 and 65 day highs, but also an expansion of lows. Demand was 59; Supply was 69, which means we had slightly more stocks showing negative momentum than positive--but the majority not showing any distinct momentum. We need to see a move out of the recent several day range accompanied by an expansion of new highs/lows to establish a directional trend.

Mean Reversion: How Often Does It Occur?

Recent posts have looked at the market's lack of trending and, indeed, its tendency to reverse moves. Does this suggest that the market tends to revert to mean trading prices? If so, might we find tradable strategies from this tendency?

I went back to March, 2003 (N = 773) and investigated each day of performance in the Dow Jones Industrial Average (DIA). I computed the previous day's average price simply as the average of the open-high-low-close. I then looked to see how often this average price was touched during the following day's trade.

It turns out that we revert to this mean trading price approximately 63% of the time. Since February of this year, that proportion has risen to over 70%. Are there variables that predict an even greater occurrence of this reversion? Do we see different levels of reversion on different time frames? Lots of good research questions here. Stay tuned.

Countertrend Equivalence - An Intermediate-Term Look

My recent Trading Markets article, along with recent blog entries here, found evidence of countertrend equivalence on a 5 day basis and, to a more modest degree, over a 5 hour timeframe. Recall that the idea of countertrend equivalence is that, if the market establishes a strong trend over X period, the next X period will tend to reverse this trend.

I decided to extend the analysis by looking at 5 week periods in SPY. Since March, 2003 (N = 155) we have had 27 strong uptrending periods on my trend measure. Five weeks later, SPY averaged a gain of .67% (16 up, 11 down), weaker than the average five-week gain of 1.36% (103 up, 52 down).

To create a relative match, I looked at the 25 strongest downtrending periods in SPY during that same time. Five weeks later, SPY averaged a gain of 2.36% (18 up, 7 down)--much stronger than normal.

Once again, we see evidence of countertrending, with moves over one period reversed in the next. The effect is especially strong for reversals of downtrends on a five day and five week basis, suggesting that these timeframes might be worth coordinating for intermediate-term trades.

Observations on Trading Fundamentals and Risk Management

One of the interesting aspects of writing my current book on trader performance is interviewing people who have long years of experience as traders and as mentors to traders. To a person, they emphasize that success in trading is not a function of finding better indicators or trading patterns. Rather, they emphasize the seemingly mundane aspects of trading mechanics: sticking to trading plans, managing risk, and adapting to changing market conditions.

While the historical patterns on this site are useful food for thought and a worthwhile starting point for framing market understandings--and trade ideas, they cannot substitute for the fundamentals emphasized by these mentors.

Of these, risk management is perhaps the most important. Victor Niederhoffer, in his excellent book The Education of a Speculator, uses the example of trying to make $10.00 from $1.00 when you have a 60/40 chance of winning a dollar from each individual bet. The odds of ruin in such a game are about 66%. Indeed, one would need a bankroll in excess of $4.00 to make the pursuit of $10.00 a worthwhile game--even with 60/40 odds.

The moral of the story is that good odds aren't enough. Proper position sizing--and a bankroll sufficient to weather the inevitable strings of losses that occur with chance--are all-important. I have seen more psychological problems created by poor money management than the reverse. Losses should not be traumatic--emotionally or financially--if they are built into the trading plan and kept to a very reasonable fixed fraction of portfolio size.

Short-Term Countertrend Equivalence

My last post introduced the idea of countertrend equivalence: Once we get a solid trend reading for a period of time X, the next period X tends to reverse this trend. We saw that this occurred over a five-day period: if we have a strong trend over five days in SPY, the next five days tend to run counter to this trend.

I took a look at hourly SPY data going back to 11/21/05 (N = 586). When we've had a strong uptrend over a five hour period (N = 75), the next five hours in SPY average a loss of -.08% (33 up, 42 down). That is weaker than the average five-hour gain of .04% (312 up, 274 down) for the general sample.

When we've had a strong downtrend over a five-hour period (N = 47), the next five hours in SPY have averaged a gain of .18% (29 up, 18 down). This is noticeably stronger than the sample overall.

Once again, we see evidence of countertrend equivalence. I will pursue this topic further in my upcoming Trading Markets article.

Countertrend Equivalence: An Interesting Idea

I'm following up on the broad market's countertrend tendencies. When my trend measure registers that the market is trending over X time periods, it appears that the next X periods tend to reverse this trend. I need to research this further but, if true, this countertrend equivalence could be a solid basis for combining time frames in analysis. In other words, let's say you had a strong downtrend reading on an intraday basis *and* on a multiday basis. That should provide an excellent signal for a longer-term market purchase.

I went back to March, 2003 (N = 766) and examined five-day trend readings in SPY and then what happened in the *next* five days of SPY trading. When SPY displayed a strong five-day downtrend (N = 104), the next five days in SPY averaged a gain of .80% (68 up, 36 down). That is much stronger than the average five-day gain of .31% (448 up, 318 down) for the overall sample.

When SPY displayed a strong five-day uptrend (N = 196), the next five days in SPY averaged a gain of .17% (108 up, 88 down), weaker than the average five-day gain for the broad sample.

In short, five day trends are tending to reverse. The next question is: can we pair these five day periods with other time frames to create superior timing of trades?

Coming Market Research

Just wanted to outline a direction my research will be taking, integrating the theme from the last post (looking at multiple time frames) and the recent theme of market trending. I'll be working on creating trending measures of the markets on two different time frames and then will see if combining short- and longer-term trend measures helps us identify historical patterns. If so, that would be significant, because the trend measures will be ones that could be applied to any stocks or markets.

A second direction is identifying sectors that commonly lead the broad market and comparing their trend measures with that of the broad market. My hypothesis is that a "crossover", in which the trend of the leading market overtakes the broad market trend, might provide an entry signal for short-term trend followers.

Thanks again to readers who continue to provide lots of good food for thought. I hope this blog returns those favors--

Brett

What's Happening on the Larger Time Frame: Does It Matter?

A reader recently made the valuable point that, in addition to looking at such key aspects of the market as volatility, momentum, trend, and sentiment, it is necessary to look across different time frames. That raises an interesting question: Do time frames matter? If we see a historical pattern on one time frame, does what's happening on the larger time frame make a difference?

To address this issue, I looked at yesterday's market, in which SPY was down -.63%. Going back to March, 2003 (N = 765), I found 95 occurrences in which SPY was down between half a percent and a full percent. The next two days in SPY averaged a gain of .20% (55 up, 40 down), stronger than the average two-day gain in the SPY sample of .12%.

I then divided the same down day sample of SPY into two categories based on time frame performance. One group was down between half and a full percent and was making a five-day closing low (just like yesterday; N = 46). The other group was down by the same amount but not making a five-day closing low (N = 49).

When the down day in SPY was making a five-day low, the next two days in SPY averaged a gain of .40% (29 up, 17 down). When the down day in SPY was not making a five-day low, the next two days in SPY averaged a flat performance (26 up, 23 down). Thus, the bullish implications of a down SPY day are entirely attributable to the fact that they're five-day lows. The larger time frame matters quite a bit.

This is a moderately bullish consideration for today, especially if early action fails to take the averages below yesterday's lows. Hats off to the reader for an excellent observation.

The Power Measure: What Happens Once a Trend Emerges?

Yesterday's entry on the Trading Psychology Weblog dusted off a proprietary indicator I developed a while ago, which I dubbed the Power Measure. It was my very first effort to measure a variable I call "trendiness": the market's tendency to persist in directional movement. After writing the recent articles that tracked the decreasing trendiness of the stock indices, I decided to modify the Power Measure and utilize it as an operational measure of trending that could be applied to a variety of markets and time frames. The nice thing about the measure is that it creates a normalized measurement, in which perfect upward trending earns a score of +100 and perfect downward trending earns a score of -100. Scores near zero suggest absence of trending: a tendency for price movement in period one to reverse in period two. Note that the Power Measure is a pure measure of price persistence; it does not confuse momentum/price strength with trending.

I went back to March, 2003 (N = 759) and looked at future price movement in SPY as a function of the Power Measure reading. When the measure was 90 or greater (consistent upside trending; N = 85), the next three days in SPY averaged a loss of -.02% (43 up, 42 down)--much weaker than the average three-day gain of .18% for the sample overall (443 up, 316 down).

When the Power Measure was -80 or lower (consistent downside trending; N = 55), the next three days in SPY averaged a gain of .53% (39 up, 16 down)--much stronger than average.

This is the clearest cut evidence I've yet seen of a countertrend bias to the market. Waiting for a distinct trend to emerge and then fading it has proven far more successful as a trading strategy than trying to ride trends. It will be interesting to see if this holds for shorter time frames as well. If my future investigations prove equally promising, I'll bring the Power Measure back to the Weblog.

Small and Midcap Stocks: Relative Performance and What It Means

My recent Trading Markets article took a look at how small cap performance acts as a mediator of past and future S&P performance, creating a statistical interaction effect. Today we had an interesting situation in which the S&P Midcaps ($MID) underperformed the S&P Small Caps ($SML). Specifically, SML was up .03% and MID was down -.34%.

Going back to March, 2003 (N = 766), I found 127 occasions in which the day's change in SML was within plus or minus .20%. The next day in SPY averaged .01% (63 up, 64 down), which is weaker than next day results for the sample overall. Once again, however, we see an interaction effect. When SML is neutral and MID is strong, the next day in SPY averages a loss of -.11 (29 up, 35 down). When SML is neutral and MID is weak, the next day in SPY averages a gain of .13% (34 up, 29 down).

Once again we see that a critical mediating effect is played by the relative outperformance or underperformance of the small cap stocks. When SML is neutral but outperforms MID, next day results in SPY are more favorable than when SML is neutral but underperforms MID. Score this as a mild bullish consideration for tomorrow.

Large Caps Strong, Small Caps Stronger: What Next?

We've had a strong six-day run in the large cap stocks, with XMI up over 2.5% in that period. Small cap issues (SML) have been even stronger, up about 4%. I decided to look at what happens in the S&P 500 (SPY) since March, 2003 (N = 762) after a big cap run and whether small caps play a role in future performance.

I found 94 occasions of six-day XMI gains of over 2%. Six days later, SPY was up by an average of .17% (55 up, 39 down), which is less than the average six-day gain for the sample of .37% (449 up, 313 down). When XMI was up by more than 2% in six days and SML was strong (N = 47), the next six days in SPY averaged .50% (31 up, 16 down). When XMI was similarly up and SML was weak (N = 47), the next six days in SPY averaged a loss of -.16% (24 up, 23 down).

Once again, it appears that performance in the small caps mediates future performance in the S&P 500--this time on a longer time frame. When the large caps are strong and small stocks are relatively weak, the S&P noticeably underperforms over the next six days. When the large caps are strong and small stocks are also strong, there are greater odds of continuation of strength. We'd have to chalk this one up as moderately favorable for the bulls.

Small vs. Large Cap Performance: Impact on Next Day Trading

Here's a look at a relatively pure measure of large cap performance, the Major Market Index ($XMI), vs. a relatively pure measure of small cap performance, the S&P 600 ($SML). On Friday, we barely moved on XMI, registering a loss of -.07%. SML was stronger, rising .26%.

I decided to go back to March, 2003 (N = 765) and see how next day performance in the S&P 500 was impacted by previous relative performance in SML vs. XMI. I found 192 occasions in which XMI closed with a gain of less than .20% and a loss not greater than -.20%. The average next day performance in SPY was .07% (107 up, 85 down).

On narrow XMI days in which SML was strong (N = 96), the average next day gain was .10% (58 up, 38 down). On narrow XMI days in which SML was weak, the average next day gain was only .04% (49 up, 47 down). This is a pattern I have noticed before: smaller cap performance appears to lead that in larger caps. As long as SML outperforms XMI, short-term returns tend to be more favorable than when SML underperforms. I'll be taking further looks at these sectors in the near future.

Closing NYSE TICK: Does It Matter?

Here is the Trading Markets article on Euro currency trading; thanks for the interesting comments.

I decided to take a look at the closing level of the NYSE TICK and whether it has any relevance for the next day's trading. Friday we closed above +900 on the TICK, suggesting broad buying on the close. Indeed, the final TICK number might be viewed as the leaning of traders' market-on-close positions, as they either lift offers or hit bids in stocks.

My first observation, going back to March, 2003 (N = 767), is that there is a positive bias to the data. The average closing TICK value is 452.

When the TICK closes above 900 (N = 82), the next day in the S&P 500 (SPY) averages a gain of .11% (48 up, 34 down). This is stronger than the average gain for the sample of .06% (429 up, 339 down).

When the TICK closes below -200 (N = 43), the next day in the S&P 500 averages a gain of .26% (28 up, 15 down). It thus appears that selling on the close tends to reverse the following day, while strong buying on the close has a moderate tendency to continue the next day.

Combining the closing TICK with momentum measures, such as the Demand/Supply Index, might screen for particularly positive times to buy the market. Another idea would be to track the TICK readings from the final hour of trade and the impact the next day.

PS - Above is Mali, the blind cat we adopted in Syracuse. When we moved to Naperville to a three story house, Mali took a day and a half to find her way around completely. That was before we got our furniture in. She adapted to the furniture in a day. She constantly sniffs as she moves, and her hearing is excellent. She comes running whenever she hears someone visiting us--she loves meeting new people. How many of our senses do we engage in trading, and how much information processing do we lose by being solely dependent upon sight?

Forex: Know the Market You're Trading!

My recent article in Trading Markets emphasized the importance of the fit between the personality of a market--its degree of volatility and trending--and the trading style of the trader. Quite a few readers wrote to me, asking about which market would be best for them. Many asked specifically about currency (forex) trading, since instruments such as the Euro are known to be trending and volatile.

My next article for Trading Markets will examine whether the Euro truly is a superior trading instrument. I think you'll be surprised by the findings. Without giving away too many punch lines here, allow me to mention one important finding: I find no evidence of trending in the currency market on either a 30 minute or daily basis. In fact, up periods are modestly more likely to be followed by down periods (and vice versa) than by continuation.

Many brokerage houses specializing in currency trading--especially those going after retail customers--stress what wonderful trending markets currencies are. They also emphasize commission-free trading with "only" a three-pip spread and possible leverage of several hundred to one on your money.

Well, each pip in the Euro emini is like a tick in the S&P emini: worth $12.50. So the highly leveraged trader in a market he thinks is trending, buys a volatile period and what happens? He is down three ticks on size already even if he scratches the trade. But when the market reverses with high volatility, he quickly is in the red by a substantial amount.

I spoke with a very well placed industry insider who revealed to me that the average length of time from the opening of a trading account to the closing of that account was seven months. This was not because the trader was dissatisfied with the firm; rather, that was how long it took the average customer to blow through their capital.

Yale Hirsch says, "Investigate before you invest." That's wisdom that applies equally to traders.

Strong NASDAQ, Low TRIN: Short-Term Results

First off, I want to thank readers who have suggested ideas for research and who have provided helpful feedback re: this and the Trading Psychology sites. Thanks also to readers who have shown interest in The Psychology of Trading; for it to have cracked the top 10,000 on Amazon three years after its publication is a testament to the enduring relevance of psychology for trading. My new book, Enhancing Trader Performance, is undergoing editing and should be published this fall.

A reader very helpfully pointed out that strong gains accompanied by low TRIN readings are bullish on a next day basis. Recall that my analysis yesterday showed weakness over the intermediate term. Fortunately today provided an opportunity to test the reader's idea: We have closed higher by 2.56% on the NASDAQ 100 ETF (QQQQ) over the past two days. The NASDAQ TRIN during that time has averaged .496.

Going back to March, 2003 (N = 762), I found 81 instances of a two-day rise of more than 2% in QQQQ. Over the next two days, QQQQ was higher by an average .26% (50 up, 31 down), stronger than the average two-day rise of .15% (413 up, 349 down) for the broad sample. When, however, QQQQ was up by more than 2% on a two-day basis and the TRIN averaged less than .50 over that same time (N = 20), the next two days were up by an average of .54% (13 up, 7 down). Score one for short-term bulls and for an astute reader.

S&P Strength and TRIN: Another Look at Efficiency

The S&P 500 (SPY) has approximately 2.2% in the past 3 days on an average TRIN reading of .69. I went back to March, 2003 (N = 759) and found 51 occasions in which we had a three-day period with a rise of more than 2%. The average three-day TRIN for those occasions was .80, indicating that we have had an above average concentration of volume in rising issues.

Six days following the three-day rise, SPY has averaged a gain of .70% (35 up, 16 down), much stronger than the three-day average gain for the overall sample of .36% (446 up, 313 down).

When we break the strong occasions in half based on three-day TRIN readings, however, a distinct pattern appears. When SPY is strong and the TRIN is lower than average (higher concentration of volume in rising issues), the next six days average a gain of only .03% (13 up, 12 down). When SPY is strong and the TRIN is higher than average, the next six days average a gain of 1.35% (22 up, 4 down).

Once again we can understand the results in terms of market efficiency. When it takes a greater concentration of volume in rising issues to achieve a particular rise, the market is less efficient and subsequently produces subnormal returns. When the market is more efficient--able to generate a given rise without a commensurate concentration in volume--returns following strength tend to continue the strength.

The results suggest that it may be difficult to generate the upside followthrough normally associated with a strong three-day gain.

TRIN and Market Efficiency

This will kick off a historical look at the TRIN (Arms Index). Today we had a gain of .19% in SPY and TRIN was .75. I went back to March, 2003 (N = 761) and looked at all one-day occasions in which TRIN was between .70 and .80 (N = 87). What we find by making TRIN the independent variable is that such a TRIN value can be associated with very different market outcomes. For example, in the sample, the one-day SPY readings associated with TRIN between .70 and .80 range from a loss of -.15% to a gain of 2.13%. The gain of .19% on Monday was definitely on the lower end of the spectrum. It's saying that, although volume was relatively concentrated in advancing stocks, such concentration could not generate much upside in the large cap market.

I divided the sample in half based on the SPY outcomes to see what happened the next day. When TRIN was between .70 and .80 and SPY was weak, the next day in SPY averaged a gain of .01% (21 up, 22 down). This was weaker than the average rise of .06% for the full sample. When TRIN was in the same range and SPY was strong, the next day in SPY averaged a gain of .08% (25 up, 19 down). It thus appears that when the market is relatively inefficient--a concentration of volume cannot generate much price gain--short run outcomes are weaker than if we see volume concentration associated with price strength.

I'll be investigating this idea of market efficiency further. For now, we'll count this one very modestly in the bear's column.

Trendiness on a Weekly Basis: Unexpected Findings

Here is a weekly view of the issue of trending markets using S&P 500 and NASDAQ 100 data. (By the way, a different perspective is posted to the Trader Performance page on my personal site). I went back to January, 1997 (N = 479) and just looked at weekly closing prices. Once again, I focused on occasions in which either a rise was followed by a rise or a decline by a decline.

In all, for the S&P, there were 239 occasions in which we saw a two-week trend and 240 occasions in which rises were followed by declines or vice versa. This is exactly what we'd expect by chance. In the NASDAQ, we had 246 trending occasions and 233 non-trending two-week instances. (Interestingly, the NASDAQ also showed up on my Trader Performance analysis as performing better vis a vis momentum/trend trading).

Looking only at 2005/6 data (N = 62), we had 31 trending two-week periods in the S&P and 31 non-trending ones. In the NASDAQ, we had 33 trending periods and 29 non-trending ones. Interestingly, we see neither evidence of persistence (trending) or anti-persistence (reversal) in the weekly data--even the most recent weekly readings.

What this says to me is that the market's loss of trendiness is occurring more at shorter time frames than at longer ones. My next Trading Markets article will address this.

Will Very Short-Term Momentum Trading of the S&P Work?

As we've seen from the recent Trading Markets article and yesterday's blog posting, the S&P 500 Index has been losing its trending properties across multiple timeframes, from daily through intraday. Anecdotal evidence suggests that scalpers are suffering in this market, as well. Let's see how the market is trending on their time frame. Please note that when I talk about scalpers, I am referring to liquidity providers in the electronic marketplace. These are participants who are in the market most of the time, working bids and offers and attempting to extract small, frequent profits from very short-term movement.

I went back to January, 2004 and looked at all five-minute periods in the ES contract (N = 44,110). As before, I calculated all instances in which the market was either up following a five-minute rise or down following a five-minute decline. What we see is that only 14,362 of the periods displayed such two-period trends. This proportion is *much* worse than what we saw in the daily or even the hourly data. In essence, it's saying that the odds of the market rising five minutes after a five minute rise (or declining after a five-minute decline) are worse than one in three.

The reason for this is that a number of five-minute periods close unchanged. The low volatility conspires to restrain very short-term trending behavior. This makes momentum trading near impossible. Either one must extend one's holding period well beyond five minutes--in which case you're really no longer a scalper--or one be willing to fade any movement whatsoever, risking those one in three occasions when the market can run you over.

Is there any hope for momentum and trend traders in different instruments? This will be the upcoming focus.

Does The Market Trend on an Intraday Basis?

I'm getting quite a few positive comments on my recent Trading Markets article that documents the decline in trending behavior in the S&P 500 Index over the past 40 years. What has been eye-opening, however, is that this loss of trendiness has occurred across all time frames that I've investigated thus far.

Here's an example. I took hourly readings of SPY since December 13, 2005 (N = 478). I once again looked for all occasions in which a rise was followed by a rise and a decline by a decline. If the odds of a rise or decline are 50/50, we should see half of all occasions by chance result in either two consecutive rises or two consecutive declines.

In fact, we see 225 occasions where either a rise was followed by a rise or a decline followed by a decline and 253 occasions where rises were followed by declines or declines by rises. During March alone (N = 64), we've seen 28 occasions where rises were followed by rises or declines by declines and 36 occasions where there was no continuation of a move.

Once again, we not only see an absence of trending--failure of rises to be followed by rises and declines by declines--but actually evidence of antipersistence. On average, rises are being followed by declines and vice versa. This is wreaking havoc with momentum traders in the ES and SPY markets.

Next I'll look at other indices and sectors and see where there might be opportunity for trend and momentum traders.

Small Cap Stocks: Five-Day Weakness and What Comes Next

It's been a rough week for the small caps, as the Russell 2000 ETF (IWM) is down over 3% on a five-day basis. I went back to March, 2003 (N = 757) and looked for all occasions where the Russell was down comparably and what has happened next.

In all, I found 58 occasions in which IWM was down 3% or more in a five-day period. Five days later, the S&P 500 (SPY) was up by an average .72% (36 up, 22 down) and IWM was up by an average (1.13%) 35 up, 23 down. Both are considerably stronger than the average five-day gain for SPY (.30%; 442 up, 315 down) and IWM (.50%; 445 up, 312 down). This will have me looking for upside setups today and Monday.

Going From Trade Ideas to Profitable Trades

Before the open tomorrow, I will post an analysis of market expectations based on events among the secondary stocks. That should prove informative, as we have interesting five-day patterns.

Here, though, I want to follow up on my post earlier today. The market provided a great example of how trade ideas developed through historical analysis are just that: trade ideas. They need to be confirmed by real time market action to become viable trades.

One of the ways I'll look at a market intraday is to scan for expectable events and setups for those events. An example would be a move back to the average trading price for the current or previous day. I know, based on research, that the market will return to its average price 3/4 of the time--and more often if volume/volatility are low. Knowing this, I will then look for a setup--a real-time event--to confirm for me that this historical tendency is likely to occur. Thus, for instance, I'll see that the ES has moved to the upper end of its range, but other indices haven't. Then I'll see volume lifting offers drying up. That will trigger my trade for a move back to the day's average price.

Today I was looking for a different expectable event: A boost in the NYSE TICK to 1000 or greater. Before acting on that, I needed a setup: Some real-time event to confirm for me that buyers were gaining the upper hand. Not only didn't we get the setup, we got the reverse: Bond yields after 10:30 AM CT rose and the market sold off, taking the TICK lower. At that point, our Cumulative Adjusted TICK began making daily lows and it was clear that traders were hitting bids, not taking offers. With interest rates again weighing on stocks and short-term sentiment negative--as shown by the negative TICK--the trade idea gained no validation.

All of this raises an important point: Coming up with good trade ideas is simple. The difficult part is knowing whether and when to act upon them. In my own trading, I need an idea, a setup, and then a framework for managing the trade once it's on. There is much more to trading competence than coming up with good ideas--and today provided a nice demonstration of that.

NYSE TICK and Descriptive Statistics

I'll amplify on this tonight: Sometimes descriptive statistics alone are of value in trading. For example, as I write at approximately 10:30 AM CT, we have not yet had an NYSE TICK reading of +1000 or greater. Since the start of 2005 (N = 296), there have been 262 days that have seen such elevated readings and only 34 that have not. I'm willing to bet that we will have just such an elevated spike sometime today, and I'll look for the setup. Then I'll trade the instrument best positioned to take advantage of that spike, which--right now--looks like SMH, the very instrument highlighted in yesterday's entry. Not something I'd bet the farm on, but a thought going through the head right now...

More SOX and Stocks

Keep your eyes on the Trading Markets site this weekend. I have a historical analysis scheduled for publication that examines the stock market's trending behavior over a 40 year period. It's eye opening. I'll have a very brief summary on the Trading Psychology Weblog tonight.

I thought I would update some of the modeling with the semiconductor stocks (SMH), given that we're down more than 5% over the past four trading sessions. One wrinkle I'm adding to the analysis is that I'm examining outcomes across three instruments: SMH, QQQQ, and SPY. This addresses the theme I've been touching upon lately of maximizing the instrument that you trade as well as the timing of trades.

Since March, 2003 (N = 753), we have had 53 days in which SMH has been down more than 5% over a four-day period. Four days later, here's how the outcomes looked:

• SPY: Average gain = .79% (38 up, 15 down). Average four-day gain for sample overall = .24% (435 up, 318 down).
• QQQQ: Average gain = 1.21% (36 up, 17 down). Average four-day gain for sample overall = .31% (421 up, 332 down).
• SMH: Average gain = 1.80% (35 up, 18 down). Average four-day gain for sample overall = .34 (400 up, 353 down).

What we can see is that there are distinctly positive outcomes four days out across all indices. When SMH is very weak over a four-day period, the next four days have been bullish on average. Of the three ETFs, SMH has milked this pattern the most, more than doubling the average gain in SPY. It thus appears that the greatest edge is not only trading to the long side over this swing period, but also trading the very instrument that has been weakest. Let's follow up on this shortly.

Two Days of Strong Downside Momentum: What Next?

The past two sessions, we have had broad downside momentum in the stock market, as measured by the Demand/Supply Index monitored on the Trading Psychology Weblog. I went back to March, 2003 (N = 754) and looked for similar periods in which the two-day Supply exceeded 270 (N = 15). Two days later, the market (SPY) was up by an average of .18 (10 up, 5 down), modestly stronger than the average two-day gain of .12% for the sample overall. One week (five days) later, however, the market was up by an average of only .02% (7 up, 8 down)--much weaker than the average five-day gain of .30% over the entire period (442 up, 312 down) overall. A bounce following strong downside momentum followed by subnormal performance thus seems to be the norm.

The recent market has been hostage to bond/interest rate movements, however, so these may well be calling the shots in the near term. I'm also noticing a lead-lag relationship between the DAX and the S&P, with strength in the former leading large cap strength yesterday and weakness leading overnight weakness in the ES.

Strong Dow, Weak Speculative Stocks

Hope you've been able to profit from the trend/momentum and interest rate/stock relationships we've been seeing. It's been a bit tricky if you've been trading the large cap indices such as the S&P 500, because there has been a huge divergence in performance between those large caps (stronger) and the secondary issues (weaker).

I noticed, for example, that the Dow Industrials (DIA) were actually up on the day, while my basket of Speculative Stocks was down by over 1.5%. That is quite a gap. Going back to January, 2003 (N = 797), I could only find eight occasions in which the Spec stocks were down by more than 1%, but the Dow was up. Three days later, the Dow was up seven of those eight occasions by an average of .91%--much stronger than the average three-day change of .10% (435 up, 362 down) for the sample overall. It appears that, when the Spec stocks have been down sharply, they--and the rest of the market--tend to rebound three days out.

Interestingly, if we just look at occasions in which the Dow is up, but Spec stocks are down (N = 60), the next day the Dow is down by an average of -.13% (26 up, 34 down) and the Spec stocks are down even more. This fits with other research I have done: When Spec stocks underperform the Non-Spec issues, the next day sees some follow through in weakness. A reasonable scenario for the market, then, might be weakness tomorrow followed by a rebound.

Tomorrow AM, I will post a different analysis, tracking market performance after several consecutive down days.

High TRIN and Next Day Open - Quick Note

Quick note on TRIN (NYSE Arms Index) that I will follow up later today. In response to the reader's question, when TRIN is 2.0 or greater and SPY has fallen by .75% or more (N = 37) since March, 2003 (N = 758), the market opens the next day up by an average .17% (28 up, 9 down), much stronger than the average overnight gain of .04% (415 up, 343 down). This is further evidence that downside momentum from the previous day has not tended to carry over to early the next day. More to come...

Big Down Day: What Happens at the Open?

Quick note before Tuesday's open. A reader asked me what happens at the open after the market has moved down sharply. I looked at SPY from March, 2003 to the present (N = 758) and found 106 instances in which the market was down .75% or more from open to close. The next day's open averaged a gain of .09% (72 up, 34 down)--considerably stronger than the average overnight move of .04% (415 up, 343 down). There is thus no evidence that weak markets during the day session spill over to the overnight and, in fact, we see a modest bounce more often than not in the overnight. Given the tendency of strong downside momentum markets to continue weakness in the short run, this may set up a trade of selling strength early the next day.

Thanks, BTW, for the kind comments sent to me re: the recent Trading Markets article.

Interest Rate Rises: What They Mean for Stocks--and Bonds

On 3/2/06, I wrote about the possibility of changing cycles vis a vis interest rates and stocks based on recent shifts in historical patterns. Today we saw more evidence of this, as stocks moved to multi-day lows and rates moved to multi-day highs. Specifically, we are down about 1% over the last five days in SPY and up about 3.22% in the 10-year Note interest rate ($TNX). I decided to take a longer look and went back to April 2000 (N = 1480) to see what happens when we get a rise in rates of over 2.5% in a five day period.

I found 251 such occasions. Ten days later, interest rates had risen further by an average of .61% (135 up, 116 down) and stocks had fallen further, by an average of -.11% (121 up, 130 down). Rates were stronger than the average change for the sample overall (-.07%; 639 up, 841 down). Stocks were weaker than the average change for the sample (-.03%; 762 up, 718 down).

I then looked at the results from 2003 to the present (N = 155). Ten days after the five-day rise in rates, stocks were down by an average of -.19% (74 up, 81 down) and rates were up by 1.10% (87 up, 68 down).

In short, a strong weekly rise in interest rates has been associated with further bond weakness (rate rises) and further stock weakness. We'll have to count this as one for the bears going forward.

Midday Price Patterns

After looking at opening and closing hours, I decided to split the difference and investigate midday hours: the time in the market from the end of the first hour of trading to the start of the last hour. Going back to March, 2003 (N = 757) in the Dow Industrials, I find 78 occasions in which we had a gain of .50% or greater during the midday hours. The average change to the same day's close was .09% (46 up, 32 down), modestly stronger than the average gain of .01% (403 up, 354 down) for the sample overall.

We had 89 occasions in which the midday hours lost .50% or more. I did not find a meaningful edge by the close of the same day. By the close the following day, however, the Dow averaged a gain of .11% (50 up, 39 down), stronger than the average gain of .06% (393 up, 364 down) for the sample overall.

My overall impression is that intraday traders, like the protagonist in Neil Young's "The Needle and the Damage Done", are milking blood to keep from running out. While there are some historical patterns in intraday markets and over very short time frames, they are modest compared with those that we've seen over swing periods. I'm not sure that's well appreciated among active traders.

Last Hour of Trading: What It Means

After looking at the opens recently, I decided to investigate market performance following strong vs. weak closes. I went back to March, 2003 in the Dow Industrials and examined the last hour of trading and its effect upon the next day.

Overall for the sample, the average daily change in the Dow was .05% (401 up, 356 down). When the last hour of trading was up by .40% or more (N = 82), the market the next day averaged a loss of -.08% (40 up, 42 down). When the last hour of trading was down by .40% or more (N = 80), the market averaged a gain of .20% (48 up, 32 down).

We thus see modest evidence of reversal following weak and strong last hours of trade. As with market opens, we are seeing little evidence that strong or weak closes carry over to the next day of trading. If anything, such moves are more likely to produce retracement than continuation.

Weak Opens: What Comes Next

When the market opened lower today, a couple of traders asked me, "How low do you think we could go?" As Ayn Rand would say, "Check your premises!" Does a down open usually lead to a down trading day?

I went back to March, 2003 (N = 757) and found 42 days in which we opened down more than half a percent in SPY (as we did today). From the open to the close, the market was up 22 times, down 20, for an average gain of .18%. That is better than the average open-to-close change of .02% (403 up, 354 down) for the sample overall.

When, however, the down open follows a day's trading session (previous open to close) that is weak, the average change from open to close is .32% (11 up, 10 down). When the down open follows a day's trading session that is strong, the average change from open to close is .03% (11 up, 10 down).

A down open after the previous day is weak is thus not more likely to be strong, but its gains are larger than its losses. Under no circumstances, however, could I find evidence that a down open produces subnormal market performance from open to close. It pays to check those premises!

Rising Gold, Rising Rates: Evidence of Changing Cycles?

The past two days we've seen interest rates on the 10-year Note rise by about 2% and gold stocks ($XAU) rise by over 4%. So I decided to take a look at what happens after two-day periods in which both rates ($TNX) and gold stocks rise by 2% or more.

Since March, 2003 (N = 749), we've had 32 days that meet the 2% criteria. Interestingly, four days later we see an average change in SPY of .70% (23 up, 9 down). That's quite a bit more bullish than the average four-day change for the sample of .25% (433 up, 316 down). We have to count that one for the bulls going forward.

One would think that an inflationary environment (rising gold, rising interest rates) might weigh on stocks. At least in the near term since 2003, that hasn't been the case. If we started seeing that pattern emerge, it would represent a key market shift. We've had 10 instances of 2% rises in rates and gold since 2005 and 6 have resulted in positive change in SPY four days later (average change = .22%). Thus the bullish pattern really isn't manifesting itself recently. This is worth keeping an eye on, as we might be seeing market sentiment re: inflation changing before our eyes.

Up Day, Down Open: Real-Time Update

At the time I'm writing this (7:56 AM CT), we're looking at a down open in SPY after an up day yesterday. I found 123 days since March, 2003 (N = 755) in which we were up more than .75%. When the market opened down the next day, the average change from open to close was .15% (26 up, 23 down). When the market opened up the next day, the average change from open to close was -.08% (35 up, 38 down). It thus appears that a down open does not necessarily mean that the day has a bearish cast after an up day and, in fact, may even be slightly bullish.

When the market opens, I then look to see which sectors are strong and weak and conduct lead-lag analyses to further update forecasts. This is the essence of dynamic modeling, as opposed to trading fixed models.

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9:54 AM (CT) Update - Notice how the semiconductor strength and then the breakout in the NYSE TICK with the buy programs in the Russell stocks preceded the S&P 500 move above its open. That made buying weakness in ES per the analysis above easier, knowing that these are strong lead relationships. I hope this opens readers' minds to different ways of looking at real time market action.

Up Open After Down Day: Sequence Analysis in Action

This is an important blog entry; you may want to review the posting from 2/26 (Sequence Analysis) before reading what I have here. The following is an example of sequence analysis at work.

Let's set the stage. After an up day on Monday which made a five-day high, we sold off on Tuesday and made a five-day low. Several of my analyses suggested a high likelihood of a down day today.

In sequence analysis, you always update forecasts with the most recently available data. This morning, the market opened up by more than a quarter of a percent. The updated forecast thus asked the question: What has happened historically when a down day has been followed by an up open? Specifically, I looked at occasions in which the market was down more than .75% on the day (N = 118) since March, 2003 (N = 755) and then divided the sample in half based on the following day's open.

When the next day's open is strong (as was the case today; N = 59), the average move from the open to the close has been .19% (38 up, 21 down). When the next day's open is weak (N = 59), the average move from the open to the close has been -.01% (33 up, 26 down).

Looking a bit further out, when the market opens strong after the down day, the move to the *following day's* close has been .41% (36 up, 23 down). When the market opens weak after the down day, the move to the *following day's* close has been -.06% (29 up, 30 down).

In short, a strong open following a weak day affects the market's short-term trajectory. This is an example of how updating forecasts with real time data can greatly aid trading. Traders need not wait for real time events to occur, however, to conduct these analyses. They can prepare for real time possibilities by conducting "what-if" scenarios with the historical data. Such sequence analysis would look at all historical occasions of market declines such as Tuesday's and then investigate what happened when the following day opened strong.

This captures the difference between mechanical system traders and historical pattern traders. Mechanical traders trade a model. Historical pattern traders conduct ongoing modeling as a dynamic process. Very, very few traders understand this and appreciate its potential.