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Use Stochastics for short-term feedback and RSI for longer cycle informationRSI AND STOCHASTICS Market conditions change quickly, and secrets often hide in very short-term price movement. The last candlestick at the chart’s hard right edge may supply crucial information that will decide the success or failure of the trade setup. Strength oscillators emit continuous feedback on this last bar’s contribution to recent price action. When properly tuned, they react quickly to new swings and align positions to natural market cycles. Oscillators generate important data on relative strength and weakness. They point to overboughtoversold conditions where the prevailing crowd may lose its determination and trigger a reversal. Swing traders must always examine the hidden forces that manufacture price change. Oscillators uncover these subtle mechanics as they look forward in reaction to market input. They also respond more quickly to new information than trend-following measurements such as moving averages. Strength tools range from simple calculations to complex pattern-based systems, but a common theme ties all of them together. Oscillators try to predict whether short-term relative strength favors or opposes the current price direction. While several tools can accomplish this task, two stand out for their durability and diverse applications. Both Stochastics and Wilder’s Relative Strength Index (RSI) offer powerful methods to examine these cyclical swings. Both oscillators assume that market strength reveals itself in the price bar’s closing tick. Each applies this essential theory in an original manner. Stochastics measures the relationship of the close to the high and low extremes for that bar. RSI compares the number of up closing bars to down closing bars. These two different methodologies produce unique results. Accurate predictions come through selective use of both tools to evaluate different aspects of market behavior. Stochastics and RSI target overbought-oversold conditions in constricted ranges. But they also have tremendous value in trending markets. Acceleration-deceleration quickly reveals itself as indicator directional movement follows price swings. These lower-pane plots draw patterns that mimic classic formations. Look for both indicators to print double bottoms or tops near important market swings. Stochastics also displays a 1-2-3 phenomenon when traversing the pane. It will often thrust, pull back in a small wave near the halfway point, and then thrust again to the other side. Market participants spend too much time trying to adjust the exact over-bought-oversold lines for each indicator. Both plots oscillate between 0% and 100%. Classic technical analysis often places extreme lines at 20-80 and advises that oscillator violations increase the odds for a reversal. Other approaches try to find this mystical turning point in different ways. For example, Elder suggests a 5% rule. Measure the overbought and oversold levels that RSI penetrates less than 5% of the time over the last 4-6 months. Draw lines at these zones and review them every 3 months. Every market responds differently to oscillators. Most swing traders should just take the path of least resistance and choose the standard settings. For both Stochastics and RSI, 20-80 works well under most circumstances. This common level does a good job of balancing false signals against lost opportunity. Truthfully, these settings mean little to profit or performance. Success requires reading the patterns that print at oscillator reversals rather than finding exact locations for the turns themselves. Use Stochastics for short-term feedback and RSI for longer cycle information. Simple RSI output tends to be choppier than Stochastics and requires longer smoothing averages to avoid false readings. Stochastics can be applied effectively through very short settings on intraday charts. Each indicator plots differently below price bars. Smoothed RSI shows a single line that flows slowly from overbought to oversold extremes. Stochastics flips faster and tracks a second line that rises above it or falls below it very quickly as cycles turn. Stochastics accurately measures short-term shifts in price momentum. But useful output begins to dry up once it pierces the extremes of its wide bands. Stochastics fails completely in strongly trending markets. The plot will move to one end and wobble randomly while the market charges ahead or sells off. This again confirms the leadership of the price pattern over the indicator. But pay close attention to all oscillators once they begin to roll over. They tend to be highly accurate at these turning points. Set a 5-3-3 Stochastics for each intraday chart at or below the main holding period. For example, plot it on both 1-minute and 5-minute charts when trading within the 5-minute view. Use Stochastics for the next-larger scale if it appears to have value. But trend becomes more important than oscillation when swing traders examine the time frame above the trade. Focus attention at these levels on a well-built MACD (or other momentum) indicator to capture the larger market swing. Jake Bernstein examines a fascinating Stochastics phenomenon, which he calls the Stochastics pop, in The Compleat Day Trader. He recommends a trend-following execution just as an outer signal line crosses above a 75% or below a 25% extreme level. The trade recognizes that the last phase of a swing can offer the most dynamic price movement. The pop rings a contrarian entry just as other participants respond to exit signals. Once again, standing apart from the crowd appears to offer special rewards. He advises to exit the trade as soon as the faster line crosses back over the slower one. This suggests the start of a swing back in the opposite direction. Daily oscillators must provide an effective reading of broad cyclical behavior. To accomplish this task, apply a longer-term RSI instead of a daily Stochastics whenever possible. Set the indicator to a 14-day period with a 7-day smoothing average for an effective view with few whipsaws. Some software applications don’t have a smoothing function for RSI. Their canned 14-day RSI outputs too much noise for swing traders. Try a 14-7-3 Stochastics instead in this unfortunate situation. This will track the RSI but exhibit a plot with a bit more fluctuation and misinformation. Long-term RSI works well through most market conditions and accurately captures major turning points. Follow the signals when RSI penetrates extreme territory after rapid price change and then rolls over. This valuable indicator also displays smooth oscillation in mildly trending markets. Plots may never reach over-bought or oversold levels during these periods of frequent thrusts and pullbacks. VOLUME TOOLS Volume tools offer important data at major reversals. They also yield accurate signals of impending breakouts and breakdowns when their action leads the price chart. Joseph Granville’s On-Balance Volume (OBV) presents the most popular study of accumulationdistribution in the trading world. This simple indicator distributes daily volume based on each day’s close. When a stock closes higher than the prior day, OBV accumulates that daily volume. Conversely, the indicator subtracts the daily volume when that stock closes down. Over time, it builds a complex picture of buying and selling behavior. OBV displays pattern characteristics similar to price bars. This permits examination through charting landscape features such as trendlines, triangles and double bottoms. Swing traders should compare these formations to underlying price patterns and review predictive convergencedivergence. OBV will often lead price and complete an important reversal just ahead of trend movement. Confine all accumulation-distribution study to the daily chart. Intraday time bias distorts volume measurements. Sixty percent or more of all daily trading volume occurs within about 30% of the day. This defeats genuine comparisons between intraday price bars and volume. Stick with individual volume histograms rather than complex calculations during the trading session. Rely on time and sales data to interpret volume’s impact on very short-term trends. Always check OBV or another accumulation-distribution indicator at new highs and lows where they exhibit their greatest power of prediction. This study will generate two unique situations. OBV may strike new levels before price or price may break through before OBV. Follow the wisdom that price needs the crowd to move higher but can fall of its own weight. If OBV reaches a new high before price, look for bars to accelerate and catch up. If price gets there first, expect that it will pause while accumulation builds. But when price hits a new low before OBV, gravity alone will likely carry it much lower before the crowd catches up. And if OBV hits a new low before price, run for the hills—that market has lost all of its support. Major divergences between OBV and trend point to stress between price and volume. Use that information to play swings that remain hidden from the competition. But this valuable indicator also has major limitations. It allocates the entire day to one side of the crowd and triggers very bad signals in long sideways markets. These important ranges set the stage for future price movement, but OBV routinely fails to predict important breakouts. Watch out when applying OBV to Nasdaq stocks. This exchange double-counts volume because it registers once for the purchase and again for the sale. Also avoid OBV with less liquid issues where it often triggers false volume readings right at critical price levels. FARLEY’S ADA (ACCUMULATION-DISTRIBUTION ACCELERATOR) Accumulation-distribution oscillates as the crowd jumps in and out of active markets. This closed system feeds on itself as constant price change encourages new participants to act and old ones to react. Within its complex boundaries, a hidden supply-demand equation forces markets to reach natural excitement levels and reverse course over and over again. While external shocks may alter this dynamic organism, they cannot change its persistent oscillation. Farley’s Accumulation-Distribution Accelerator (ADA) tracks this volume oscillation while it reduces the impact of shock events. Swing traders benefit when they locate natural levels where the crowd may turn and trigger contrary price movement. This examination of herd behavior through volume offers a classic approach to cycle discovery that often pinpoints insider activity and unexpected price change. ADA formations print clear S/R and trendlines as well as oscillating between expected upper-lower boundaries. Use ADA to measure lag between price and volume. When price leads, expect it to pause for ADA to catch up. The most dynamic trends erupt when ADA significantly leads the price action. This valuable indicator also triggers much faster signals and cleaner pattern formations than OBV or other common accumulation-distribution measurements. The calculation begins with the Larry Williams Accumulation-Distribution indicator. Williams formulated this handy tool in The Secret of Selecting Stocks for Immediate and Substantial Gains (1986). This initial mathematics represents the cumulative total of the variable X. Take this figure and add it to all preceding bars to plot his indicator. A. Measure LWAccDis as follows: 1. If the current Close is greater than the prior Close, then: LWAccDis = Close - TrueLow 2. If the current Close is less than the prior Close, then: LWAccDis = Close - TrueHigh 3. If the current Close is equal to the prior Close, then: LWAccDis = 0 B. Calculation of TrueLow: 1. If prior Close < current Low, then TrueLow = prior Close 2. If prior Close ? current Low, then TrueLow = current Low C. Calculation of TrueHigh: 1. If prior Close > current High, then TrueHigh = prior Close 2. If prior Close ? current High, then TrueHigh = current High TABLE 5.2 Farley’s Accumulation-Distribution Accelerator (Formula uses TradeStation language) Start with LWAccDis above 1. (and available in most charting LWAccDis programs). 2. Calculate the difference between F1 = LWAccDis - LWAccDis[1] the LWAccDis of current bar and prior bar. Compute a 14-bar exponential 3. moving average (EMA) of this F2 = @XAverage(F1,14) difference. Smooth this average with a 7-bar 4. exponential moving average Farley’s ADA = @XAverage(F2,7) (EMA). 5. Plot 0 Line. F3 = 0 Track indicator trendlines, channels, and horizontal extremes to locate natural breakout points. ADA patterns will often complete one to three bars faster than price. Watch the indicator for signs of a natural trend-range axis. Movement out of multimonth or multiyear congestion can uncover long-term price breakouts with considerable profit opportunity. Don’t demand perfection with ADA trendlines. This raw tool works best when swing traders allow for small violations in both directions. SPECIAL TOOLS Use special tools to locate hidden S/R and gain an important market edge. These powerful resources perform custom analysis but remain poorly understood by the emotional crowd. Use their results to execute profitable trades at locations that few others will see or understand. |
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