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Markets don’t just move straight up and down — the battle between the bulls (demand) and the bears (supply) results in different types of price movement.
A horizontal resistance line can be drawn once price moves up to touch a price level twice. The line is confirmed when a third touch of that price level successfully holds and selling supply returns to the security sending the price down.
Areas of support and resistance
Price support and resistance halt the trend that is in place:
Support represents a transition from declining prices driven by supply to climbing prices when renewed demand kicks in at that price level.
Resistance represents a transition from climbing prices driven by strong demand to declining prices when selling pressure comes in at that price.
When trading, notice that these transitions line up over time, sometimes cre- ating sideways trading channels as price moves between the two. The longer the price serves as support or resistance, the stronger it’s considered.
Using support and resistance to identify entry and exit points is one basic trading system. Consider also using them in price projections to identify stop-loss and profit-taking exits, as well as calculating risk-reward ratios.
Price areas that previously served as support often serve as resistance areas in the future and vice versa.
Trend analysis
I use the concept of trend quite a bit before reaching this formal definition.
That’s because I’m pretty sure you have a sense of what an upward trend and a downward trend is for any asset. Painfully so if you were holding on to that asset in the latter trend. More formally, trend identifies price direction:
Upward trend:Prices climb and pullback in such a way that a rising line can be drawn under the pullbacks which display higher lows. Higher highs are also characteristic of uptrends.
Downward trend:Prices fall and retrace in such a way that a declining line can be drawn above the top of retracement peaks which display lower highs. Lower lows are also characteristic of downtrends.
Create a trend line by connecting two higher lows (uptrend) or two lower highs (downtrend). When price successfully tests the line a third time, the trend is confirmed. Using these lines as entry and exit points is a valid appli- cation of the tool, similar to support and resistance levels.
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Consider drawing two trendlines using a longer term chart such as a monthly chart, to highlight an area of resistance versus a subjective single trend line.
One may use closing data while the other uses market lows. Follow market action near each.
Moving averages
Moving averages are lines constructed on a chart using an average value of closing prices during a certain number of days. These lines are considered laggingindicators because the historical data follows price action. The two main types of moving averages include as follows:
Simple moving averages (SMA) which use a basic average calculation Exponential moving averages (EMA) which incorporates all available
price data providing greater weight to more recent data
Simple moving averages equally weigh all closes for the time period selected while exponential moving averages are calculated in such a way that more recent data carries greater weight in the line.
Both SMAs and EMAs can be constructed using a variety of settings and chart intervals. So you can view a five-day SMA on a daily chart or a ten-week EMA on a weekly chart. Moving average lines are considered unbiased trend indi- cators because the lines are derived from objective calculations.
The three most common settings for either moving average include the following:
20-day moving average displaying short-term trends 50-day moving average displaying intermediate-term trends 200-day moving average displaying long-term trends
You may have heard financial media reporting that price is approaching the 200-day moving average. That’s because a break of this line is considered sig- nificant and may confirm a trend reversal.
Exponential moving averages (EMA) incorporate all available price data for the underlying security, with more recent data having a greater weight on the EMA value for the period. As a result, they are more responsive to price changes.
Identifying Relatively Strong Sectors
Strong market moves up or down generally result in gains for most sectors and securities too. However, during more moderate trending certain sectors
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and securities perform better than the market while others perform worse. A sector or security can also move in the opposite direction during these peri- ods. Your objective as a trader is finding those relatively strong and weak groups so you can apply profitable sector strategies.
Relative ratios
You construct a relative ratio line by dividing one security into another. This allows you to objectively view the performance of one security relative to the other because the line rises when the primary security is outperforming the second one and falls when it is underperforming. Adding an overlay chart to a relative ratio allows you to view both securities on one chart. Log scales typically provide a better view for the movement of each.
Trend lines drawn on a log chart will appear differently when you switch to an arithmetic scale.
Figure 6-1 displays a weekly log chart for XLF (dark solid line), an exchange- traded fund (ETF) comprised of S&P 500 financial companies. It also displays an overlay of SPY (light, thinner line), which is the S&P 500 Index ETF. The 10-week and 40-week EMAs (two dashed lines) are also included for XLF, dis- playing intermediate and long-term trends respectively. Finally, the bottom portion shows the relative ratio line for XLF/SPY.
Figure 6-1:
Weekly chart for XLF with EMAs and perfor- mance relative
to SPY.
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Shorter moving averages (i.e. low setting) are considered faster and move more closely with price. You can distinguish these lines on a chart because they are somewhat jagged.
When including relative ratios on a chart you have a clearer view of the per- formance for two securities. In Figure 6-1 it appears that the two indexes moved pretty similarly until very recently. But a look at the relative ratio line tells another story. Throughout a good portion of the three-year period SPY outperformed XLF, very significantly from June 2007 through October 2007.
Relative ratio lines are also referred to as relative strength comparisons.
Within a month after the deterioration in the relative ratio line, XLF dropped below its 200-day EMA and shortly after the 50-day EMA followed. Although not labeled, the shorter EMA is identified by noting which one moves more closely with the price. When downward trending conditions are ideal, prices and MAs line up with price data appearing lowest on the chart followed by the shorter EMA, then the higher EMA — just like this chart is showing.
Some traders use moving average crosses as trading system signals. This approach has its place in trading, but note where price was when the cross occurred — almost at its lowest point. Remember, moving averages lag price data. I like to use crossovers to identify a change in conditions for the stock and as a strategy filter. Once that cross occurs, I favor bearish strategies.
Before moving away from this particular chart, note that trend lines can be applied to relative ratios. The same rules apply:
Draw uptrends using the low points in the trend Draw downtrends using the high points in the trend
Also, previous areas of support can become resistant and vice versa.
When using overlay capabilities on a chart, indicators added to the chart are based on the primary security.
When using relative ratios, it’s good to identify a group of related indexes or sectors to monitor. Cash flows from one outperforming market or sector to another as economic conditions change. Portfolio allocations should favor outperforming markets and underweight underperforming ones. This results in reversals for one market leading another market by varying amounts of time.
The wide range of ETFs that track different assets (i.e. the U.S. dollar or oil) allows you to employ an asset allocation plan across markets using a single security type. Add the existence of options for many ETFs and you have reduced risk access to the commodity and foreign exchange markets.
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Trend lines can be used on relative strength comparison lines to better iden- tify changing conditions and areas of support and resistance. Similarly, sup- port that has been broken will often serve as resistance in the future.
Focusing on sectors, selecting one optionable ETF fund family sector group allows you to quickly evaluate sector trends and relative performance. As an example, the Select Sector S&P Depository Receipts (SPDR) include ten ETFs based on the S&P 500 Index:
SPY tracks the entire S&P 500 Index
Nine ETFs track each of the nine major sectors that make up the index Collectively the nine sector ETFs make up the SPY ETF. By analyzing ten charts, you can complete a broad market and sector assessment which can serve as a basis for comprehensive sector investing or trading. Seeking an ETF fund family that is liquid and optionable is your first objective, then you follow-up by confirming liquidity in the ETF options.
A relative ratio line only compares performance of two securities — it does not indicate the trend for either security. A rising line can indicate the pri- mary security is trending upward at a faster rate than the second security or that it is trending downward at a slower rate.
Rate of change indicator
Relative ratios provide you with a good visual approach for assessing sec- tors. A rate of change approach allows you to also quantify and rank perfor- mance for those sectors. The rate of change (ROC) for a security is the speed in which it moves — when calculating security returns you are using one type of ROC. There is also an ROC indicator that can be drawn on charts for ana- lyzing, trading, or ranking securities.
To calculate a ten-day ROC, you use the following formula:
(Today’s Price ÷ Price 10 Days Ago) ×100
Using the nine sector ETFs, you can rank the sectors by strength using a 14- day ROC value for each as follows in Table 6-1.
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Table 6-1 14-Day ROC Sector Rankings on 8-16-07
ETF Sector 14-Day ROC Rank
XLU Utilities 1.020 1
XLP Consumer Staples 1.003 2
XLV Healthcare 1.002 3
XLF Financials 0.994 4
XLI Industrials 0.962 5
XLK Technology 0.959 6
XLY Consumer Cyclicals 0.953 7
XLE Energy 0.950 8
XLB Materials 0.935 9
SPY Entire Index 0.979 --
XLU, XLP, and XLV are considered relatively strong while XLY, XLE, and XLB relatively weak compared to price 14-days ago. Does this mean XLV is trend- ing upward or XLB trending downward? Not at all — it’s simply a way you can compare the performance of a group of securities using a specific criteria. It turns out each of these ETFs hit a short-term bottom on the day the ROC was calculated. Round out your analysis by evaluating each sector chart, starting with the extremes.
As an alternate approach to sector trading you can expand the list to include industry groups, investment styles (small or large cap, value or growth), or countries, among others. The main goal is to develop a group of ETFs that experience related capital inflows and outflows.
When using ROC trends, you really want to capture money flows from one market or sector to another. Consider checking out different periods such as weekly or monthly ROCs and see how the rankings change each week.
Relative strength trading approaches seek to establish bullish positions in relatively strong performers and bearish position in relatively weak perform- ers. This works best when the periods used result in rankings that persist more than a week or two, so you remain in a strong position.
When trading, the ROC is used with a simple moving average (SMA) as a trade alert. Crosses of the ROC up above its SMA is a bullish alert and crosses of the ROC down below its SMA is a bearish alert. An example of this is shown in the next section.
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The term normalizerefers to the process of expressing data so that it is inde- pendent of the absolute value of the underlying. This allows comparison to other securities.
Using Sector Volatility Tools
Technical analysis displays volatility in a variety of ways including basic range bars and historical volatility (HV) plots. Objective technical indicators available in many charting packages and covered in this section include the following:
Statistical volatility Average true range Bollinger bands Bollinger %b
These tools provide you with different volatility views and allow you to scan the markets for securities that may be gearing up for a change. Although volatility can remain high or low for extended periods of time, these mea- sures may provide you with the following:
A buy alert when declining A sell alert with jumps higher
A tool to help identify appropriate strategies Detection of seasonal movement
The value used for technical indicators is referred to as the setting.
Commonly used settings are referred to as default values.
Displaying volatility with indicators
Statistical volatility and the average true range are two different displays of price movement. Here’s how they differ:
Statistical volatility (SV):SV, another term for historical volatility, uses closing values to plot an annualized standard deviation line that repre- sents the degree of price movement in the security. Because various time periods can be used on a chart, SV reflects the chart period, not necessarily a daily calculation as you see on option HV or SV charts.
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Average true range (ATR):The ATR uses a true range (TR) value to define price movement and was developed by Welles Wilder. TR incorpo- rates extreme movement such as gaps, so it better reflects volatility. TR uses the previous close and current high and low values to calculate three different ranges. The biggest range for the three is the TR for the period.
A rate of return calculation is one measure of rate of change. It allows com- parisons for securities with different prices by creating a value that is inde- pendent of price.
Figure 6-2 provides the three TR range calculations and a bar chart example of each.
ATR is an exponential moving average that smoothes TR. A strong move in the ATR incorporates price gaps and provides traders with important infor- mation about price volatility that can be missed by other smoothed indica- tors. Because ATR uses historical prices and a smoothing process, it’s a lagging indicator and does not predict volatility. However, a sharp move upward in a security’s ATR is often accompanied by an increase in IV for its options.
When using rankers to identify stocks with narrowing bandwidth, be sure to check the chart to see what’s happening with the stock. Price may have flat- tened due to a pending corporate action such as a stock buyout and is less likely to move from that point.
Figure 6-3 displays a daily OHLC bar chart for SPY, the S&P 500 Index ETF with the 14-day ATR and 14-day SV.
Figure 6-2:
Daily true range calculations and display.
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In the late July — early August period, the volatility for SPY increased as seen by range bars increasing in length. In this particular decline, SV peaked approximately five days before SPY bottomed which was followed by a peak in the ATR one day later.
All nine sector ETFs bottomed on the same day with each ATR peaking within one day of this bottom. The SV profile for the ETFs varied more, but most also peaked a few days prior to the bottom. When reviewing the charts, you note the following about XLI:
Price moved in a very wide range, closing the day at its high with a slight net gain
SV was pulling back from a peak two days prior ATR was still moving upward
The SMA for the 14-day ROC was flattening suggesting a possible end to the decline
Although XLI ranked fifth on a 14-day ROC basis, closing at its high for the day was extremely bullish given the range of trading for that day. The situa- tion merited monitoring to confirm a reversal. By following conditions for a couple of days, you would have seen the following for XLI displayed as Figure 6-4.
Figure 6-3:
SPY daily OHLC bar chart with ATR and SV.
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Price continued upward while ATR appeared to be pulling back and SV condi- tions remained elevated. ROC crossed up above its ten-day SMA, which was a bullish signal. The only strategy briefly discussed so far that suits these con- ditions (bullish, high volatility) is a long stock, short call position.
Buying the ETF near the close at $38.55 and selling the Sep 39 strike price call for $0.80, you’ve created a moderately reduced risk position. Rather than
$3,855 on the line, you’ve reduced your exposure to $3,775 or by 2%. There are actually better strategies to capitalize on this situation — ones that allow you to limit your risk much more — but this one is suitable for now.
You can establish a short-term covered call strategy with the goal of being called out of the position. That’s the case here so you want XLI to be trading above 39 at September expiration. This is, exactly what happened. On expira- tion Friday XLI closed at 40.63 and you would have been assigned. This means you bought the position for $3,775 and sold it for $3,900.
Analyzing volatility with Bollinger bands
Bollinger bands provide you with another nice visual of relative volatility levels. This technical tool uses a simple moving average (SMA) surrounded by upper and lower bands, both derived from a standard deviation calculation.
John Bollinger, the tool’s developer, uses the following as default settings:
Figure 6-4:
XLI daily OHLC bar chart with ATR, SV, and ROC.
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20-period SMA
Upper band (SMA + two standard deviations) Lower band (SMA – two standard deviations)
The bands contract and expand as price volatility contracts and expands.
Two additional Bollinger band tools include the following:
Bandwidth (BW)to measure the distance between the two bands using the calculation: BW = (Upper BB – Lower BB) ÷ Moving Average
According to Bollinger, when BW is at its lowest level in six months, a squeeze candidate is identified. That’s a security that is consolidating before a potentially strong breakout higher or lower. It is not uncommon for a false move to occur so straddle strategies (see Chapter 14) can pro- vide a way to play this situation.
%bto identify where the price is relative to the BW, calculated using a variation of George Lane’s Stochastic indicator, with values ranging from:
• 0 to 100 when price is at or between the bands
• Less than 0 when below the lower band (bearish)
• Greater than 100 when above the upper band (bullish)
Review the news when you see a chart with a big price jump or decline along with narrow bandwidth on the Bollinger bands.
A value of 75 reflects price that is within the bands and one quarter below the lower band from a total bandwidth standpoint. %b normalizes price rela- tive to band-width size and allows you to make an apples-to-apples compari- son of different stocks for ranking purposes.
Different sectors experience bullish and bearish trends at different times.
Although strong rallies and declines in the broad markets often move all securities in the same direction, the strength and duration of the moves for these different securities can vary greatly. In general, the following apply:
Securities and sectors with very high values for %b are bullish when confirmed by other technical tools.
Securities and sectors with very low values for %b are bearish when confirmed by other technical tools.
Bollinger noted that rather than prices being extended when near a Bollinger band, the condition actually reflects strength and a breakout that can con- tinue. Look for pullbacks toward the moving average line to establish new positions in the direction of the trend after such a breakout.
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