International Business Machines Corp. (IBM) has been testing 8-year resistance for the last six weeks and looks ready to break out, entering the first secular uptrend since 2013’s all-time high at 215.90. A fourth quarter spin-off of poorly-performing legacy divisions has attracted new investors but macro tailwinds and the tech behemoth’s blockchain business are also contributing to the upside, generating a 17% year-to-date return.
Q4 Spin-off Attracting Investors
The stock rose 3.8% in April after beating Q1 2021 top and bottom line estimates and reaffirming fiscal year guidance. The company has continued an acquisition binge into June after adding seven smaller operations earlier this year, in an effort to populate the new high growth operation. That entity is now called ‘NewCo’, a generic placeholder until IBM executives figure out a more appropriate name.
The Managed Infrastructure Services (MIS) business is scheduled to spin off into a publicly-traded entity by year’s end. Core operations will then focus on IBM’s rapidly-growing cloud and artificial intelligence businesses. It makes sense that NewCo will command a higher price-to-earnings ratio (P/E) than its predecessor, marking the company’s most ambitious initiative so far this century. Unfortunately, pre spin-off investors will also get proportional shares of the legacy operation, which could sink even further in coming years.
Wall Street and Technical Outlook
Wall Street consensus has barely budged so far in 2021, highlighting major skepticism after years of misguided management. IBM is now rated as a ‘Hold’ based upon 5 ‘Buy’, 9 ‘Hold’, 1 Underweight, and 2 ‘Sell’ recommendations. Price targets currently range from a low of $115 to a Street-high $185 while the stock is set to open Monday’s session about $2 above the median $145 target. Additional upside may be limited with this placement until analysts jump onboard the bull train.
The stock hit an all-time high in the first quarter of 2013 and entered an historic decline, carving a long string of lower highs and lower lows into March 2020’s 11-year low at 90.56. The first recovery wave stalled at 135 in June, ahead of an April 2021 breakout that reached the 8-year trendline of lower highs at month’s end. Price action has held like glue to this critical level in the last six weeks, raising odds for a breakout that targets the 2020 high at 159.
U.S. Steel Corp. (X) closed just above 26 in Friday’s session after a UBS analyst upgraded shares from ‘Sell’ to ‘Hold’ and doubled the firm’s price target to $30. Weekly options expiration and a month long test at major resistance may have dampened short-term buying interest but the stock is on track to reach the target in the next few weeks. If so, that will mark the highest high since October 2018.
Surging Steel Prices
The stock has risen more than 50% so far in 2021 and more than 150% in the last year, underpinned by steel prices that have risen by an even greater pace. The booming U.S. economy has triggered a surge in demand, allowing the company and its worldwide competitors to aggressively raise prices. However, many industry experts believe that steel prices will ease soon, triggering a reversal in shares that could relinquish a large percentage of yearly gains.
UBS analyst Andreas Bokkenhauser sees things differently and is looking for this commodity cycle to persist longer than many folks expect. He lists supply constraints as the primary price mover and points out that China may impose an export tax that drives down local prices while pushing foreign steel prices higher. However, nothing is certain at this point, which is why the analyst chose a modest upgrade rather than an enthusiastic ‘Buy’ rating.
Wall Street and Technical Outlook
Wall Street consensus has lifted substantially in the last year and stands at a ‘Hold’ rating based upon 3 ‘Buy’, 7 ‘Hold’, 1 ‘Underweight’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of just $14 to a Street-high $35 while the stock closed Friday’s session nearly $4 below the median $30 target. A quick ramp into that level is possible but further gains may be tough, with post-pandemic supply constraints slowly working out of the system.
U.S. Steel hit an all-time high in 2008 and turned sharply lower, posting lower highs in 2010 and 2018. The decline may have ended at an all-time low in March 2020, ahead of a recovery wave that stalled in May 2021 after crossing the midpoint of the 2018 into 2020 selling wave. This level also marks 200-month moving average resistance, highlighting a substantial barrier that could end the short-term uptrend. Meanwhile, the secular downtrend will remain fully intact until the stock completes a 100% retracement into the 2018 peak at 47.64.
Zoom Communications Inc. (ZM) traded lower on Wednesday despite beating Q1 2022 estimates and lifting full year guidance. The remote meeting software provider posted a profit of $1.32-per-share, $0.34 better than expectations, while revenue rose an impressive 191.4% year-over-year to $956.24 million, nearly $40 million higher than consensus. The company now expects FY2022 earnings-per-share (EPS) between $4.56 and $4.61 on $3.97 to $3.99 billion in revenue.
2021 Rotation Out of COVID Plays
The apathetic reaction highlights technical and macro headwinds that will be hard to overcome. On the technical side, the stock posted a phenomenal 495% return in 2020, setting off extremely overbought readings that predict a long-term correction. Meanwhile, the introduction of vaccines in the fourth quarter triggered a major rotation out of COVID beneficiaries and into recovery plays. That impulse has continued unabated through the second quarter of 2021.
CEO Kelly Steckelberg outlined the bull case following the release, insisting that Zoom is “evolving into a platform company that will help everything workers do every day”. She also predicts that corporations won’t return to full physical form in coming years, instead choosing “hybrid or flexible work models” that include remote options. U.S. white collar workers are now supporting that thesis, scooping up homes far away from busy city centers.
Wall Street and Technical Outlook
Wall Street consensus is mixed after last year’s outsized gains, yielding an ‘Overweight’ rating based upon 11 ‘Buy’, 1 ‘Overweight’, 11 ‘Hold’, 1 ‘Underweight’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of $250 to a Street-high $540 while the stock will open Thursday’s session nearly $80 below the median $400 target. This low placement exposes a major conflict with Main Street investors, who firmly believe that Zoom is over-valued.
Zoom mounted 2019 resistance at 107.34 in February 2020 and took off in an historic uptrend that posted an all-time high at 588.84 in October. The stock has carved four lower lows since that time, relinquishing more than 53% of its value into May’s 8-month low. More importantly, price action broke support at the 200-day moving average in March while five attempts to remount this barrier have failed, indicating the downtrend remains fully intact.
Goldman Sachs downgraded theater chains Imax Corp. (IMAX) and Cinemark Holdings Inc. (CNK) to ‘Sell’ on Wednesday, just one day after momentum favorite AMC Entertainment Inc. (AMC) soared 22% to an all-time high. Speculators scooped up shares after the company raised $290 million in cash in a sale to a hedge fund, securing their 2021 financial position. A great weekend box office underpinned the rally as well, with some receipts returning to 2019 levels.
Speculative Interest Dries Up
Imax held up better than Cinemark during the crisis, with a few brave souls focusing limited entertainment dollars on big budget productions. The chains continued to attract strong speculative interest heading into 2021 but upticks stalled in the first quarter due to valuation concerns. Imax lifted into a stronger technical position during the rally, completing a 100% retracement into horizontal 2017, 2018, and 2019 highs in the mid-20s.
Goldman analyst Michael Ng offered mixed commentary with the ratings, noting “Although there’s been a secular decline in movie-going, attendance declines are happening at a very slow place, declining 1.4% CAGR from the 2002 attendance peak to 2019. In fact, the box office has grown at 1.3% CAGR over that same time period as increased ticket prices have more than offset attendance declines. That said, we believe the closures of theaters during the pandemic may have accelerated the secular decline in attendance.”
Wall Street and Technical Outlook
Wall Street consensus on Imax now stands at an ‘Overweight’ rating, based upon 7 ‘Buy’, 2 ‘Hold’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of $18.60 to a Street-high $30 while the stock will open Wednesday’s session just $3 above the low target. This weak placement suggests that Main Street investors generally agree with Goldman that movie stocks won’t offer strong returns for the rest of 2021.
Imax posted an all-time high at 43.80 in 2015 and turned sharply lower, dropping to an 11-year low in March 2020. It recovered at a steady pace into March 2021 when the stock reversed within two points of resistance in the mid-20s and fell six points. Price action since that time has been stuck in a trading range with support at 20 while accumulation has held just below the first quarter peak. A positive catalyst could save the day with this configuration, breaking the resistance and lifting price into the 30s.
Dow component Boeing Co. (BA) is trading higher by nearly 2% in Tuesday’s pre-market after a Cowen upgrade set off another round of buying interest. The rally is adding to gains posted since the aerospace giant bounced at 200-day moving average support near 220 about three weeks ago. Even so, the stock is still trading more than 25 points below the 52-week high at 279, posted in mid-March, and nearly 200 points below 2019’s all-time high above 400.
Dreamliner Production Issues
The company suspended deliveries of the 787 Dreamliner last week, renewing a 5-month suspension triggered by chronic production issues. The FAA has requested more information about proposed solutions to address quality control, in an abundance of caution following the worldwide grounding of the 737-MAX jetliner in 2019. That plane finally returned to the skies in the fourth quarter of 2020, lifting a dark cloud that kept many investors on the sidelines.
Cowen analyst Cai von Rumohr upgraded Boeing from ‘Market Perform’ to ‘Outperform’, noting “Fast improving air traffic is bolstering aircraft demand; and while lingering FAA oversight and timing of China’s MAX approval limit upside to 2021, 2022-24 look brighter. We see potential for CFPS to reach $21/share by 2024. We’re upgrading the stock, which is likely to trade on traffic expectations, with a price target of 290”.
Wall Street and Technical Outlook
Wall Street consensus has grown more bullish since the MAX re-certification, with an ‘Overweight’ rating based upon 12 ‘Buy’, 2 Overweight, and 10 ‘Hold’ recommendations. In addition, three analysts recommend that shareholders close positions. Price targets currently range from a low of $165 to a Street-high $314 while the stock will open the session about $18 below the median $270 target. It’s probably no coincidence the high target is situated close to the March rally peak.
Boeing failed a breakout above 2018 resistance at 394 following the Ethiopian crash in March 2019 and entered a downtrend that broke a trading floor near 300 in February 2020. The subsequent recovery unfolded in three rally waves, reversing at the 50% selloff retracement level in March 2021. That ceiling could get tested in coming weeks, with a breakout opening the door into much stronger resistance above 300.
Costco Wholesale Corp. (COST) sold off more than 2% on Friday despite beating Q3 2021 top and bottom line estimates by healthy margins. The big box retailer earned $2.75-per-share during the quarter, $0.47 better than expectations, while revenue rose a healthy 21.8% year-over-year to $44.38 billion, more than $500 million higher than consensus. U.S. sales rose 15.2% while e-commerce sales eased off the torrid 2020 pace, rising a still-impressive 38.2%.
Weak Buying Interest
The stock is finally trading in the green for 2021 following a steep first quarter decline that shed nearly 20%. A broad-based rotation out of the COVID-19 beneficiaries and into recovery plays dampened buying interest after last year’s impressive 29% return and it’s been slow to return. Even so, Costco was trading at a 35.5 forward price-to-earnings (P/E) ratio before the report, marking a premium to rivals Walmart Corp. (WMT) and Target Corp. (TGT).
Telsey Advisory Group analyst Joseph Feldman raised his target to $415 on Friday, noting “Costco should remain a share gainer, with its solid sales, high membership renewal rates (110MM total members), and square footage growth of LSD. In FY22, Costco should continue to generate solid EPS growth, driven by a MSD comp, MSD-HSD membership fee income growth, healthy digital growth, and lapping COVID-19 related costs. We maintain our Outperform rating.”
Wall Street and Technical Outlook
Wall Street consensus stands at an ‘Overweight’ rating after last year’s strong performance, underpinned by 19 ‘Buy’, 4 ‘Overweight’, 10 ‘Hold’, and 2 ‘Underweight’ recommendations. Price targets currently range from a low of $249 to a Street-high $415 while the stock closed Friday’s session more than $35 below the median $416 target. This low placement highlights Main Street discomfort with the higher-than-historical valuation.
Costco has been a superior performer for more than a decade, posting a long series of new highs. It broke out above February 2020 resistance at 325 in July and entered a healthy uptrend that posted an all-time high at 393.15 in November. The subsequent decline found support at 307 in March while a V-shaped recovery into May stalled four points below the 2020 peak. Weak accumulation during the uptick has failed to reach prior highs, setting the stage for mixed two-sided price action into the second half.
Ford Motor Co. (F) is trading at a five-year high on Thursday following a well-received Investors’ Day presentation that unveiled a major turnaround plan to address the company’s electric future. A RBC Markets upgrade has added to growing bullishness, triggering a breakout above March resistance at 13.62. The uptick raises hopes the company will play now catch-up with outsized returns at rivals Tesla Inc. (TSLA) and General Motors Co. (GM).
Shift Into Electric Vehicle Era
The automaker will invest more than $30 billion in electric vehicle research and production and is looking for EV to comprise up to 40% of all sales by 2030. It will invest part of those funds in battery technology, creating Ford Ion Park, which will include “more than 150 experts in battery chemistries, testing, manufacturing and value-chain management, who will boost battery range and lower costs to customers and Ford”.
RBC Capital Markets upgraded the stock to ‘Outperform’ and raised their target to $17 after the event, noting the plan addresses long-term concerns about the automaker’s shift into electric vehicles. Analyst Joseph Spak provided upbeat commentary on the long-term outlook, noting “we have more confidence in financial targets, concerns over BEV strategy were addressed, numbers are likely moving higher, and the stock is still not overly expensive.”
Wall Street and Technical Outlook
Wall Street consensus stands at an ‘Overweight’ rating based upon 8 ‘Buy’, 1 ‘Overweight’, 11 ‘Hold’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of $9.00 to a Street-high $17 while the stock is set to open Thursday’s session about $1.25 above the median $13 target. There isn’t much wiggle room for traders to book profits in this sleepy configuration but it could mark a major opportunity for long-term investors.
Ford hit an all-time high in the upper 30s in 1999 and rolled into a 9-year decline that ended near a buck in 2008. The subsequent rally stalled in the upper teens in 2011, ahead of persistent downside that cratered to an 11-year low in March 2020. The stock rallied above a massive trendline of lower highs in January 2021, signaling the first uptrend since 2009. However, the advance is now headed toward heavy resistance in the upper teens, limiting upside potential.
PepsiCo Inc. (PEP) has completed a multiyear breakout pattern and could post impressive upside in coming quarters. Taken together with a 2.90% annual dividend yield and the relative safety of this defensive sector, patient investors could generate stronger annual returns than many so-called growth stocks. That’s especially true after 2020’s red-hot momentum market lifted many equities to unsustainable price levels.
Looking for Multiple Expansion
Beverage plays are no longer cheap, with PepsiCo’s absolute valuation situated near the upper boundary of the historical range. However, the stock looks more attractive when viewed over the last three years, with relative valuation below the 36-month midpoint. Modest multiple expansion looks more than achievable in this view, with the potential for price appreciation between 15% and 20% in the next 12 months.
UBS analyst Sean King recently upgraded the stock to ‘Buy’, listing reasons why investors should take a close look at the beverage giant. He believes the company is “at the mid-point of an investment cycle that will yield a sustainable improvement to top and bottom line growth”. King also reviewed the spreadsheets, noting that “investments in beverage margins and global snacking scale support our above Street outlook for 2021-23 sales growth of 5.7% and EPS growth of 10.0%”.
Wall Street and Technical Outlook
Wall Street consensus has improved since the start of 2021, now standing at an ‘Overweight’ rating based upon 11 ‘Buy’, 2 ‘Overweight’, 9 ‘Hold’, and 1 ‘Underweight’ recommendation. No analysts are recommending that shareholders close positions and move to the sidelines. Price targets currently range from a low of $135 to a Street-high $165 while the stock is set to open Wednesday’s session about $7 below the median $155 target.
PepsiCo broke out above a 5-year rising highs trendline in January 2020 and failed the breakout during the pandemic decline, which dumped price more than 30%. The subsequent recovery finally completed a 100% retracement into the prior high at year’s end, giving way to a reversal that posted a higher low in March. The stock has now returned to resistance for the third time, completing a cup and handle pattern that yields a measured move target in the 190s following a breakout.
Gap Inc. (GPS) is trading higher by more than 1% in Tuesday’s pre-market in reaction to bullish analyst commentary just two days before the Q1 2021 earnings release, when the apparel chain is expected to post a loss of $0.12 per-share on $3.4 billion in revenue. If met, the loss-per-share will mark a substantial improvement over the $2.51 loss posted in the same quarter last year when the pandemic forced retail shutdowns all around the world.
Long-Term Recovery Plan
The company owns and/or franchises brick and mortar storefronts in six continents through divisions that include Old Navy, Gap, Athleta, and Banana Republic. Steep 2020 losses forced the retailer to release a long-term recovery plan that includes a reduction in poorly-performing North American operations, limiting mall exposure, and investing in digital expansion. With this plan now in place, investors are likely to forgive a Q1 loss as long as it marks a major improvement over atrocious Q4 results.
Telsey Advisory Group analyst Dana Telsey raised her price target on Tuesday morning, noting that long-term initiatives announced in October should “contribute to improved profitability” but admits that “fourth quarter results are a continued reminder that significant challenges remain at the Gap and BR brands. Therefore, we maintain our ‘Market Perform’ rating, but given our increased estimates, we are raising our price target to $37”.
Wall Street and Technical Outlook
Wall Street consensus remains skeptical, with a ‘Hold’ rating based upon 4 ‘Buy’, 17 ‘Hold’, and 1 ‘Underweight’ recommendation. However, no analysts are recommending that shareholders close positions and move to the sidelines. Price targets currently range from a low of $25 to a Street-high $40 while the stock is set to open Tuesday’s session more than $1 above the median $32 target. This placement suggests the stock is fairly-valued, lowering upside potential after earnings.
Gap posted an all-time high in the mid-40s in 2014 and broke down one year later, entering a steep downtrend that bottomed out during 2020’s pandemic decline. The subsequent uptick carved a vertical pattern that just reached heavy resistance at the 2015 breakdown and .786 Fibonacci retracement levels. Bears have the upper hand in this configuration, raising odds for a reversal and long-overdue intermediate correction.
NVIDIA Corp. (NVDA) reports Q1 2021 earnings in Wednesday’s post-market, with analysts expecting a profit of $3.22 per-share on $5.2 billion in revenue. If met, earnings-per-share (EPS) will mark a 78% profit increase compared to the same quarter last year, when the pandemic triggered worldwide shutdowns. The stock sold off more than 8% in February, despite beating Q1 2020 top and bottom line estimates and issuing higher revenue guidance.
Why Announce Split Just Before Earnings?
The systems chip manufacturer announced a four-for-one stock split on Friday morning, effective on July 20th. The timing raises a red flag, given the close proximity of this week’s report, triggering speculation the company is attempting to manage potential disappointment ahead of a less-than-spectacular quarter. Even so, the long string of better-than-expected releases is unlikely to defer investor interest ahead of the news.
KeyBanc analyst John Vinh upgraded the stock from ‘Sector Weight’ to ‘Overweight’ on May 20, one day before the split announcement, setting a $700 price target. He noted NVIDIA “is best positioned to monetize one of the fastest and highest value-added workloads in the data center in artificial intelligence/machine learning.” Vinh downgraded rival Intel Corp (INTC) at the same time, highlighting the chip behemoth’s loss of market share to the juggernaut in the last year.
Wall Street and Technical Outlook
Wall Street consensus stands at an ‘Overweight’ rating based upon 28 ‘Buy’, 5 ‘Overweight’, 4 ‘Hold’, 1 ‘Underweight’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of $380 to a Street-high $800 while the stock closed Friday’s session about $75 below the median $675 target. This low placement suggests Main Street investors are more worried than professional analysts about high valuation and the continued worldwide chip shortage.
NVIDIA completed a breakout above 2018 resistance at 293 in May 2020 and entered a powerful uptrend that carved a straight-line channel into the September peak at 589. February and April 2021 breakout attempts failed while the stock is now engaged in a third attempt. This mixed action has carved an expanding wedge pattern that should limit momentum until buying pressure clears 680, which is more than 13% above the current price.
Trend-following indicators are technical tools that measure the direction and strength of trends in the chosen time frame. Some trend-following indicators are placed directly on the price panel, issuing a bearish signal when positioned above price and a bullish signal when situated below price. Others are drawn below the panel, generating upticks and downticks from 0 to 100 or across a central ‘zero’ line, generating bullish or bearish divergences when opposing price.
Most trend-following indicators are ‘lagging’, meaning they generate a buy or sell signal after a trend or reversal is underway. The moving average is the most popular lagging trend-following indicator. These indicators can also be ‘leading’, meaning they predict price action before it starts by using multiple calculations and comparing momentum in different time frames. Parabolic Stop and Reverse (Parabolic SAR) is a popular leading trend-following indicator.
These indicators have three primary functions. First, they attempt to alert the technician to a developing trend or an impending reversal. Second, they attempt to predict short- and long-term price direction. Third, they confirm observations and signals in the price pattern and other technical indicators. Signal reliability is limited to the settings used to draw the trend-following indicator. For example, a 50-day moving average and a 200-day moving average generate unique buy and sell signals that may work in one time frame but not the other.
Simple Moving Average (SMA)
The Simple Moving Average (SMA) measures the average price across a range of price bars chosen in the settings by the technician. Closing prices are commonly used in the calculation but the open, high, low, or median price is often applied as a substitute. The indicator is a highly-effective technical tool used to evaluate the strength of the current trend and to determine if an established trend will continue or reverse. The SMA is less effective for prediction in sideways and rangebound markets.
The calculation simply sums up prices over the chosen period and divides by that period. Each data point adds to a line placed in the same panel as price. Interactions between price and the moving average generate bullish and bearish divergences that evaluate trend strength and direction. For example, price falling below a 20-day SMA in an established uptrend denotes unusual weakness while price lifting above the 20-day SMA in a downtrend denotes unusual strength. The direction of the SMA also generates a divergence when opposing price action.
Exponential Moving Average (EMA)
The Exponential Moving Average (EMA) measures the average price across a range of price bars chosen by the technician, placing greater weight on more recent data points. The EMA is a ‘weighted moving average’, meaning that price bars are not treated equally in the calculation. This moving average responds more quickly to recent price action than the simple moving average, theoretically generating earlier buy and sell signals.
The calculation assumes that recent price action will have a greater impact on trend direction than an equally weighted data series. However, this weighting also tends to generate more false signals than the SMA. Examining several EMAs at different time intervals can overcome the shortcomings of this moving average but the added complexity requires stronger interpretation skills. The 20-day, 50-day, and 200-day EMA combination has grown popular among traders in recent decades. The direction of the EMA and its relative positioning with price generate convergence-divergence relationships that are useful in trade management.
Average Directional Index (ADX/DMS)
The Average Directional Index (ADX/DMS) measures the strength or weakness of an active trend. The quality of trend strength should correlate strongly with the persistence of the trend and capacity to generate profits for the trend-following trader or investor. ADX uses moving averages in several time frames to generate three lines that cross higher or lower through a panel with values between 0 and 100. These lines are designated ‘ADX’, ‘+DMI+’, and ‘-DMI‘.
ADX measures the strength or weakness of an uptrend when +DMI is above -DMI, indicating that prices are rising. Conversely, ADX measures the strength or weakness of a downtrend when +DMI is below –DMI, indicating that prices are falling. ADX with values at or below 25 denotes a weak trend or rangebound market, lowering the reliability of this trend-following strategy. ADX direction also generates momentum signals, with a trend gathering strength when rising and losing strength when falling.
Moving Average Convergence-Divergence (MACD)
Moving Average Convergence-Divergence (MACD) is a highly popular technical tool developed by Gerald Appel in the 1960s. MACD analyzes the relationship between moving averages set at different intervals, generating a set of directional lines or a histogram that gauges current momentum and price direction. The indicator is commonly calculated by subtracting at 26-period EMA from a 12-period EMA. A 9-period EMA of the MACD, called the ‘signal line’, is then added to the plot.
MACD emits an assortment of visual data that generates crossovers, divergences, and sharp directional swings. The MACD histogram draws the distance between MACD and signal line and has become the most popular method to apply this indicator. A bullish divergence occurs when the histogram turns higher at an extreme below a zero line while price is falling and a bearish divergence when the histogram turns lower at an extreme above a zero line while price is rising. Crossovers above and below the zero line can also generate potent buy and sell signals.
Parabolic Stop and Reverse (Parabolic SAR)
Developed by RSI creator Welles Wilder Jr, the Parabolic Stop and Reverse (Parabolic SAR) is used by technicians to confirm trend direction and to generate reversal signals. However, signals are only applicable within the time setting applied to the indicator. Indicator data points generate dots above or below price on the main chart panel. The calculation applies an ‘invisible’ trailing stop, forcing the indicator to change direction when hit, marking a potential reversal in trend. The indicator often generates reliable signals in strong trends and whipsaws in rangebound markets.
Parabolic SAR is most useful when analyzed in combination with the overall price pattern and other trend-following indicators. The trader or investor can also use the indicator as a tool to manage long and short positions, raising or lowering the stop loss after each data point to match the price of the last dot. Keep in mind this indicator issues continuous buy or sell signals, forcing the technician to look at other data to avoid over-trading.
Additional Trend-Following Indicators
Accumulative Swing Index – evaluates the long-term trend through changes in opening, closing, high, and low prices.
ADX/DMS – measures the strength or weakness of an active trend and how long it may persist before a reversal.
Alligator – uses three Fibonacci-tuned moving averages to identify trends and reversals.
Aroon – evaluates whether a security is trending or rangebound and, if trending, the strength or weakness of the advance or decline.
Aroon Oscillator – applies data from the Aroon indicator to determine if a trend is likely to persist. The oscillator generates a zero line that, when crossed, signals potential changes in trend.
Elder Ray Index – evaluates buying and selling pressure by separating price action into bull and bear power. The output is used to determine trend direction and high odds entry/exit prices.
Gator Oscillator – is used as an alternative to the Alligator indicator, drawing green and red histograms to determine if trends are getting stronger or weaker.
Linear Regression Forecast – uses regression analysis to compare price action to the expected mean, looking for high odds reversal signals.
Linear Regression Intercept – uses regression analysis to compare price action to the predicted value, looking for high odds reversal signals.
Linear Regression R2 – analyses the reliability of price vs regression prediction.
Linear Regression Slope – determines the average rate of change when using regression analysis and compares price action to the expected mean.
QStick – identifies trends by examining a moving average of the difference between the opening and closing price of a hourly, daily, weekly, or monthly price bar.
Rainbow Moving Average – plots multiple weighted moving averages to determine price extremes over the examined period.
Rainbow Oscillator – uses rainbow moving averages to evaluate trends by plotting bandwidth lines at the edges of a histogram.
Random Walk Index – compares an asset’s movement to random movement to determine if its noise or signal. The indicator issues buy and sell signals, depending on trend strength or weakness.
RAVI – also known as the Range Action Verification Index, the indicator evaluates current trend and projects future trend intensity through a histogram plotted with two moving averages.
Schaff Trend Cycle – identifies trends and issues buy and sell signals by examining acceleration and deceleration of price change over time.
Shinohara Intensity Ratio – evaluates trend intensity by plotting Strong Ratio (Strength) and Weak Ratio (Popularity) lines.
Supertrend – draws an overlay across price action that seeks to identify current trend direction.
Swing Index – predicts price action in short-term trading strategies through crossovers above and below a zero line.
Time Series Forecast – uses linear regression to identify divergences between current price and the expected mean. It is constructed to be more flexible than basic linear regression analysis.
Trend Intensity Index – tracks correlation between price movement and volume levels to evaluate the strength or weakness of a trend.
TRIX – displays percentage change of a triple smoothed exponential moving average in an effort to filter out inconsequential price movement.
Typical Price – draws a straight line plot of the average price for each bar to generate a more realistic view of developing trends than using closing prices.
Vertical Horizontal Filter – measures the intensity of trends by looking at the highest and lowest prices over the specified time period.
Weighted Close – calculates the average price between the high, low, and close of each bar, placing greater weight on the close.
ZigZag – connects plot points on a price chart that reverse whenever the asset reverses by more than a specified percentage.
The momentum oscillator is a technical tool that issues a signal when a price move or trend is about to start. It can fluctuate between an upper and lower band or across a zero line, highlighting relative strength or weakness within a specific time frame. Many oscillators generate values between zero and 100 while band placement near those extremes denotes ‘overbought’ or ‘oversold’ conditions that raise odds for a reversal. They can also feature multiple lines that generate signals when ‘crossing over’. Strongly-trending securities can get overbought or oversold and stay that way for long periods.
These are forward-looking indicators rather than trend-following indicators, with crossovers and reversals at band extremes often defining pauses in the broader trend, rather than trend reversals. These types of indicators generate the most potent buy and sell signals when looking for convergences or divergences within a set of time frames, like monthly, weekly, and daily charts. They can also issue potent trend breakout and reversal signals when used in conjunction with moving averages and other lagging indicators that apply moving averages to create values.
An oscillator can generate useful guidance when the underlying trend isn’t clear and the trader focuses on buy or sell ‘cycles’, as opposed to ‘signals’. The reasoning is easy to understand. A buy cycle doesn’t necessarily translate into higher prices while a sell cycle doesn’t necessarily translate into lower prices. However, cycle alternation often foretells the transition from a trend into a trading range, and vice-versa. It can also predict when the established trend’s trajectory is going to increase or decrease.
The Stochastic oscillator was developed by George Lane in the 1950s. It’s become hugely popular since that time due to a high degree of accuracy in determining when it’s a good time to buy or sell a security. The indicator looks at an instrument’s closing price and compares that value to the price range over a specified time period. The ability to close higher within those values lifts the Stochastic to a higher number between zero and 100. A security typically enters the overbought zone when above 80 and the oversold zone when below 20. The 5-smoothed or 5-3-3 Stochastic setting is highly effective for position and swing trading.
The Stochastic generates two lines, a lead line and a signal line that ‘crosses over’ when certain conditions are met. Use this indicator to determine if a security is engaged in a buy or sell cycle within the time period under examination. The indicator’s power of prediction grows geometrically when comparing buy and sell cycles in multiple time frames. For example, a security engaged in a monthly Stochastic buy cycle may also be engaged in a weekly Stochastic sell cycle. Correct interpretation when these types of cycles are in conflict can generate excellent trade entry and exit timing, as well as windfall profits.
Relative Strength Index
Welles Wilder Jr. introduced the Relative Strength Index (RSI) in 1978. RSI examines the characteristics of recent price change to evaluate momentum and to identify overbought or oversold readings that predict cycle reversals. Like other oscillators, RSI fluctuates between zero and 100, with a reading above 70 typically denoting an overbought security while a reading below 30 typically denotes an oversold security. Unlike Stochastic, RSI generates just a single value that changes in reaction to the latest price bar.
RSI is constructed by looking at a computation in which average gains are divided by average losses over a specified period. 14 (days, weeks, or minutes) is the indicator’s most popular setting. The plot is placed below the price chart, generating a convergence when top and bottom panels move in the same direction and a divergence when moving in opposite directions. A rising RSI when price is falling marks a bullish divergence that often works well with a pullback strategy while a falling RSI when price is rising marks a bearish divergence that can support all sorts of profitable short sales.
Money Flow Index
Money Flow Index (MFI) looks at price and volume to identify overbought and oversold conditions. The indicator oscillates between zero and 100, rather than carving a traditional pattern. As with RSI, MFI generates convergence-divergence signals when comparing the trajectories of price and indicator, with divergences often producing the most profitable buy or sell signals. In addition, the calculation looks at volume’s contribution to price action, encouraging technicians to call it the ‘volume-weighted RSI’. MFI hits overbought above 80 and oversold below 20 and, like RSI, 14 (days, weeks, or minutes) is the most popular setting.
MFI separates up days from down days, measuring volume generated by those sessions. Indicator plots are characterized as “Positive Money Flow’ when rising and ‘Negative Money Flow’ when falling, often matching up well with accumulation-distribution indicators. For example, falling volume while price is rising above the overbought level can turn the MFI lower, generating a bearish divergence that warns about an imminent reversal. The indicator works best when used in conjunction with pattern analysis, looking for instances when a higher high or lower low in one plot isn’t matched by the other plot.
Price Rate of Change
Price Rate of Change (ROC) measures momentum by looking at the percentage change in price between the current bar and a specified prior period. Unlike other oscillators, the ROC indicator plot starts at a central zero line and moves into positive or negative territory, depending on price movement over the examined period. In addition to generating convergence and divergence data, crossovers through the zero line also elicit buy and sell signals. ROC values are unbounded, meaning they can go well above 100 or well below -100. As an example, Gamestop ROC reached 1,800 during the historic 2021 short squeeze.
A rising ROC above the zero line confirms an uptrend within the applied setting while a falling ROC below the zero line confirms a downtrend. Rangebound price action generates ROC oscillation around the zero line, limiting its usefulness. In addition, signals only apply to the time period under examination and different settings always produce different signals. Signals also change when looking at different chart intervals, like daily, 60-minute, or 15-minute views. As a result, comparisons between intervals also generate convergence and divergence that requires interpretation. Many platforms default to a 14 ROC setting but 9 and 25 have also grown popular in recent years.
Commodity Channel Index
Commodity Channel Index (CCI) evaluates trend direction and strength, generating a plot that market technicians use to identify the best times to enter or exit a position. CCI also works well as a trade filter, identifying dull markets when it’s best to stand aside. The indicator examines the difference between the current price and an historical average price set by the technician. 20 periods is a popular setting. A CCI above zero indicates the current price is above the historic price while a negative CCI indicates the current price is below the historic price.
Unlike RSI and Stochastic, CCI values are unbounded and can go above 100 or below -100, making arbitrary overbought and oversold bands less useful for signal generation. As a result, the technician needs to compare current CCI extremes to prior turning points, which will change from asset to asset. As with other momentum oscillators, CCI can diverge from price, signaling potential weakness in an uptrend and potential strength in a downtrend. Pullback strategies often work well in timing long and short entries into these divergent conditions.
Additional Momentum Oscillators
Awesome Oscillator – evaluates momentum to determine if bulls or bears are controlling price action of a security.
Center Of Gravity – is a forward-looking indicator that generates crossovers to identify high odds turning points in rangebound markets.
Chande Forecast Oscillator – measures the percentage difference between a closing price and a linear regression line over a specified time period. An oscillator reading above zero predicts higher prices while an oscillator reading below zero predicts lower prices.
Chande Momentum Oscillator – subtracts the sum of losses over the specified time period from the sum of gains over the specified time period, and divides the total by the sum of all price movement over the specified time period.
Coppock Curve – calculates a 10-month weighted moving average of the sum of the 14-month and 11-month rates of change of an index to determine long-term momentum.
Disparity Index – evaluates the current price of a security in relation to a moving average.
Ease of Movement – is a volume-weighted indicator that gauges how easily price moves up or down through a formula that subtracts the prior average price from the current average price and divides the difference by volume.
Ehler Fisher Transform – isolates price movement to determine when a security hits an extreme, raising odds for a reversal.
Elder Force Index – quantifies the relative power needed to move price by comparing current price to prior price and multiplying by trading volume during the period.
Elder Impulse System – combines trend-following and momentum data to identify inflection points where a trend is likely to accelerate or slow down.
Fractal Chaos Oscillator – seeks to determine the choppiness or trendiness of a security, returning to zero in choppy conditions and hitting +N and -N extremes in trending conditions.
Intraday Momentum Index – combines candlestick and relative strength data to determine when a market is overbought or oversold.
Market Facilitation Index – measures the strength or weakness of price movement, seeking to determine if an uptrend or downtrend will persist or reverse.
Momentum Indicator – evaluates the strength or weakness of price movement over time, seeking to identify high odds reversal signals.
Pretty Good Oscillator – measures the distance of the close from the specified simple moving average, modified by the average true range over the same period.
Price Momentum Oscillator – applies smoothing calculations to Price Rate of Change to determine relative strength and weakness.
Price Oscillator – calculates the difference between pre-chosen moving averages, looking for overbought-oversold and convergence-divergence signals.
Price Volume Trend – looks at directional movement and trend intensity through a cumulative plot that multiplies volume by price percentage change over a given period.
Prime Number Oscillator – identifies high odds turning points by taking the prime number closest to the current price and calculating the difference between the nearest prime numbers across a specified time period.
Pring’s Know Sure Thing – interprets price rate-of-change data through a plot that identifies overbought or oversold extremes.
Pring’s Special K – evaluates trend intensity in multiple time frames to build a comprehensive view of asset cyclicity. It is primarily used to identify reversals before they unfold and to locate high odds entry/exit levels.
Psychological Line – computes the ratio of rising price bars to the total number of price bars over the specified time period. A reading above 50% indicates bulls are in control while a reading below 50% indicates bears are in control.
Relative Vigor Index – measures trend strength by contrasting the closing price to the trading range over a specified time period.
Stochastic Momentum Index – refines the Stochastics oscillator, applying a broader range of price settings and placing more weight on closing prices.
Ultimate Oscillator – applies weighted moving averages in multiple time frames to measure momentum.
Valuation Lines – calculates and displays the average of visible prices by applying multiple standard deviations.
Williams %R – measures trend momentum over the specified time period by drawing an oscillator bounded by 0 and 100.
The comparison indicator is a technical tool that analyzes relationships between two or more securities, indices, or markets. It compares prices, volume, and/or volatility, determining which instrument is relatively stronger or weaker over the chosen time frame. This type of analysis elicits a series of convergence and divergence signals, with the leading instrument generating a bullish divergence when it gets even stronger compared to the lagging instrument, and a bearish convergence when it gets even weaker compared to the lagging instrument.
This type of analysis may also measure correlation, which is the tendency of one security or indicator to mimic the behavior of another security or indicator. Correlation analysis first measures the relationship between two securities, or a security and a technical indicator. The resulting values are then strung together in a new indicator that visualizes how changes in one variable over time influence changes in the other variable.
This plot allows the technician to predict how price behavior in a correlated market will influence investment or trading returns. When computing correlation, one security or indicator is considered to be the dependent variable while the other security or indicator is considered to be the independent variable. The calculation determines if a change in the independent variable is expected to result in a similar change in the dependent variable.
The Plot function simply adds a second security to an Advanced Chart price panel and examines relative strength and weakness between instruments. This built-in charting function normalizes divergent security behavior by replacing Y-axis prices with percentage change. The first security becomes the independent variable when performing this analysis while the second security acts as the dependent variable and can be substituted with other securities, as needed.
Comparison and correlation analysis can be accomplished in several ways with the Plot function. The easiest method just scans price action over days, weeks, or months, looking for relative highs and lows to occur at the same time. Crossovers between securities are especially useful in this analysis because it identifies turning points and divergences, in which one security shifts from a leading into a lagging relationship with the other security. The Plot function is used in conjunction with the Correlation Coefficient and Performance Index indicators.
Correlation Coefficient indicator evaluates the relationship between a security price and a related technical indicator, or two securities. As noted above, correlation is measured by choosing an independent variable and comparing performance against a dependent variable, which is usually a related security. Indicator output ranges from plus 1 to minus 1 (+1 to -1), with perfect positive correlation at the upper limit and perfect negative correlation at the lower limit.
A perfect positive reading specifies that any change in the independent variable will generate an identical change in the dependent variable. Conversely, a perfect negative reading specifies that any change in the independent variable will generate an identical but opposite change in the dependent variable. Not surprisingly, a correlation coefficient of 0 specifies there is no relationship or correlation between the two variables.
The direction of the dependent variable’s plot over time depends on whether the coefficient is positive or negative. When the coefficient is positive, the dependent variable will move in the same direction as the independent variable. Conversely, when the coefficient is negative, the dependent variable will move in the opposite direction of the independent variable. Choosing an appropriate holding period is critical when applying this analysis to trade management because correlation tends to oscillate over time, generating frequent whipsaws.
Performance Index (PI)
Performance Index is used in conjunction with the Plot function. The indicator compares a security’s price to a benchmark index or other security, generating a line that turns green above a reading of 1.0 and red below a reading of 1.0. A reading of exactly 1.0 indicates perfect correlation with the underlying security or index. A security that outperforms a benchmark index should generate higher returns in a trend-following strategy than a security that underperforms a benchmark index.
A rising PI indicates the security is making a stronger move to the upside than the underlying index, or the security is rising while the underlying index is falling. A declining PI indicates the security is declining at a faster rate than the underlying index, or the security is falling while the underlying index is rising. Flat PI readings indicate that both markets are gaining or losing value at an equal pace.
Price Relative indicator compares the performance of a security against an underlying index, sector, or another security through a ratio chart. The indicator is also called the Relative Strength indicator, not to be confused with Wilder’s Relative Strength Index (RSI). This analysis generates convergence and divergence signals that may predict relative returns on active positions over time.
It is a simple plot, calculated by taking the closing price of a dependent variable (base security) and dividing it by the closing price of an independent variable (comparative security). A rising ratio indicates the base security is rising at a faster pace than the comparative security, or falling at a slower rate than the comparative security. Conversely, a falling ratio indicates the base security is falling at a faster pace than the comparative security, or rising at a slower pace than the comparative security.
The range indicator is a technical tool that measures the limits of price movement over a specified time frame. It is estimated that market prices are engaged in uptrends and downtrends just 15% to 20% of the time, with the balance spent within the boundaries of trading ranges that can be relatively narrow or wide. This indicator attempts to determine the characteristics of prices caught within these ranges, seeking to predict future movement and direction.
Many range indicators look for boundaries between ranges and trends, with the technician seeking to profit when a) a trend eases into a trading range or b) a trading range yields a new trend, higher or lower. One popular method to perform this analysis identifies range boundaries and then measures the quality of price action between highs and lows. This analysis often includes volatility calculations, looking for transitions from low to high volatility, and vice-versa, to generate preliminary buy and sell signals.
Other types of technical indicators can perform sophisticated range analysis as well. For example, Bollinger Bands will expand during trends and contract during range development. Bands tend to narrow to an extreme at the starting point of a new trend and widen to an extreme at the starting point of a new trading range. Those turning points can generate actionable entry or exit signals, especially when confirmed through other forms of technical analysis.
Average True Range
Average True Range (ATR) measures volatility by examining a security’s price action over a specified time period. The initial calculation subtracts the high from the low of a single price bar and compares that value to price ranges in prior bars. The final calculation is derived from a smoothed moving average of these values (true ranges) over N periods, with ‘N’ the time setting chosen by the technician. 14 days (or periods) is the most common ATR setting.
Securities with high ATR readings are more volatile than securities with low ATR readings but the calculation does not predict price direction. Rather, it is a supplementary technical tool best used in conjunction with trend-following and momentum indicators. Many traders develop exit strategies using ATR multiples that seek to identify when volatility has reached an unsustainable level. In addition, the indicator has powerful applications in determining position size and risk.
The Darvas Box indicator generates rectangular-shaped boxes that rise or fall over time. Although frequently listed as a momentum indicator, the formula identifies rangebound market conditions that lower odds for profitable trend-following strategies. The rise and fall of boxes add to this analysis, signaling when the quality of price action has changed enough to permit freer directional movement, higher or lower.
Traditional Darvas Box strategies require that market participants take exposure solely in the direction of the boxes, updating stops whenever price action crosses the top threshold. The original work includes fundamental filters that prefer growth plays with strong earnings, similar to the work of William O Neil and Investor’s Business Daily. However, the indicator’s usage has expanded naturally over the years into a purely technical form of market analysis.
High Low Bands
High Low Bands (HLB) are generated from a series of moving averages calculated by evaluating price action over specified time periods, which are then shifted higher or lower by a fixed percentage of the median price. Indicator calculation requires setting the specific period and appropriate shift percentage. The ‘right’ settings are market specific and need to match volatility characteristics for the chosen security or trading venue.
The indicator applies triangular moving averages instead of simple or exponential moving averages. This is a double-smoothed average, or an average of an average, that irons out suspected outliers from the final calculation. As a result, bands are smoother than similar indicators that track fast moving market activity and are less useful for many short-term trading strategies. However, HLB can generate extremely reliable high and low predictions in rangebound markets.
Developed by Donald Dorsey in the 1990s, Mass Index evaluates the range between the high and low of a security over a specified time period. Reversal signals with this indicator are generated when a range expands to a subjective extreme and then reverses into contraction. However, the technician may also need to examine momentum, volatility, and trend-following indicators to determine the overall trend direction that will be impacted by the reversal signal.
The classic setting uses a 9-day (or period) exponential moving average (EMA) of the range between the high and low price over the last 25 days. The initial output is then divided by a 9-day EMA of the 9-day EMA used for the initial calculation. In the original usage, an indicator value that surges above 27 and drops to 26.5 issues a reversal signal. However, in modern usage, the technician needs to identify signal levels that are appropriate for the currently traded markets and securities, which can differ greatly from Dorsey’s original observations.
Pivot Points determine range and trend intensity in different time frames. The first level of the indicator is calculated by adding the high and low of the current bar to the closing price of the prior bar, and dividing by three. Price action in the next bar is considered bullish when above the pivot point and bearish when below the pivot point. This observation has limited value so the calculation adds support and resistance levels, notated as S1, S2, R1, and R2, based upon projections from the pivot point value.
Price movement above support or below resistance signifies a strengthening uptrend or downtrend while reversals within support (S1 or S2) and resistance (R 1 or R2) boundaries define the quality of rangebound markets, at least within the time frame used in the price chart. These five levels can also be used to identify appropriate trade entry levels, place stop losses and trailing stops, and to locate high odds trade exit levels.
Additional Range Indicators
Anchored VWAP – attempts to identify the average price of a security over a time period chosen by the technician.
ATR Bands – are drawn around the average true range indicator to identify potential turning points and whether price is engaged in an uptrend, downtrend, or a trading range.
ATR Trailing Stops – identifies optimized stop levels using multiples of average true range indicator output.
Detrended Price Oscillator – seeks to measure the length of price cycles from peak to peak or trough to trough.
Gopalakrishnan Range Index – quantifies price movement and asset volatility by studying the asset’s trading range over a specified time period.
High Minus Low – subtracts the daily (or bar) high from the daily (or bar) low to determine average price movement over a specified time period
Highest High Value – measures the highest high over a specified time period.
Lowest Low Value – measures the lowest low over a specified time period.
Median Price – measures the most common price over a specified time period.
True Range – displays a derivative of the trading range by removing the impact of gaps and volatility between price bars.
Vortex Indicator – separates uptrends and downtrends into two continuous lines that reveal relative bull and bear power over time.
VWAP – attempts to identify the average price for a security over the entire session.
Volume indicators are technical tools to evaluate a security’s bull and bear power. Most look specifically at buying vs. selling pressure to determine which side is in control of price action. Others attempt to identify emotions that are moving the security at a particular time. For example, exceptionally high volume compared to a moving average of volume can reveal euphoria or fear while much lower than average volume can reflect apathy or disinterest.
These indicators measure shares in the equity markets, contracts in the futures markets, and tick movements in the forex markets. All versions attempt to accomplish the same types of technical analysis. When a market rises on increased volume, it is considered to be under accumulation. Conversely, when a market falls on increased volume, it is considered to be under distribution. In addition, a market rising on decreased volume generates a bearish divergence while a market falling on decreased volume generates a bullish divergence.
Forex market volume evaluates the degree of price movement within a certain period, rather than looking at individual buy and sell transactions. Forex traders often supplement their accumulation-distribution analysis by looking at open interest in the currency futures markets. Whether equity, contract, or pair, volume is used in conjunction with price action to confirm trend strength, reveal trend weakness, and confirm breakouts and breakdowns.
Accumulation-Distribution (A/D) is a cumulative volume indicator, meaning that each data point is added to the prior data point before it’s plotted on an indicator panel. As the name states, the indicator attempts to determine if a security is being accumulated (bought over time) or distributed (sold over time). The calculation measures the closing price in relation to the price bar’s range and multiplies the result by volume for that bar.
A/D indicator direction generates convergence and divergence relationships with price that assist in trade decision-making and risk management when used in conjunction with pattern analysis and other technical indicators. Rising price when A/D is falling generates a bearish divergence while falling price when A/D is falling generates a bullish divergence. The indicator also carves orderly patterns over time that look similar to price action, with channels, trendlines, and triangles assisting prediction.
On Balance Volume (OBV)
On Balance Volume (OBV) was created by Joseph Granville in 1963 and is now the most popular accumulation-distribution indicator. OBV generates a bullish divergence when price is falling and OBV is rising and a bearish divergence when price is rising and OBV is falling. The value of OBV at a particular time isn’t important but the relationship between current and prior OBV levels determines whether accumulation or distribution is keeping up with price action.
OBV plots a running total of a security’s buy and sell volume, seeking to determine if it is under accumulation (bought over time) or distribution (sold over time). The calculation has three primary components. First, if the current price bar is higher than the previous price bar, current OBV = previous bar’s OBV + current volume. Second, if the current price bar is lower than the previous price bar, current OBV = previous bar’s OBV – current volume. Third, if the current price bar = the previous price bar, current OBV = previous OBV.
Chaikin Money Flow (CMF)
Chaikin Money Flow (CMF) was created by Marc Chaikin in the early 1980s. The indicator measures accumulation and distribution of a security over time. This is an oscillator, with values ranging from +100 to -100 and a zero line that signifies neither accumulation nor distribution. As with other oscillators, CMF generates buy, sell, and confirmation signals through bullish and bearish convergences and divergences as well as crossovers through the zero line.
Chaikin applied a 21-period (one month) setting to the indicator but that element is now customizable in charting programs and has different implications, depending on the chosen period. According to the creator, money flow persistence over 6 to 9 months evaluates accumulation or distribution by major funds and institutions. Most traders don’t need that information but CMF also reveals short-term money flow convergence-divergence when viewed with shorter time frames and settings.
Volume Oscillator (VO)
Volume Oscillator (VO) identifies accumulation and distribution by examining the relationship between two volume moving averages. A fast cycle moving average of 14 days or weeks is often used in conjunction with a slow cycle moving average of 28 days or weeks but settings are customizable. The calculation simply subtracts the slow MA from the fast MA and plots the result as a line or histogram. As with other oscillators, VO fluctuates across a zero line but has no fixed upper or lower values.
VO is non-directional and expected to turn higher in both uptrends and downtrends. It generates a bearish divergence when price is rising and VO is falling and a bullish divergence when price is falling and VO is falling. The indicator also has the power to identify overbought and oversold markets and to confirm breakouts and breakdowns. In addition, crossovers through the zero line may reveal important turning points or be used to confirm other technical indicators.
Balance of Power (BOP)
Balance of Power (BOP) measures the strength of buying and selling pressure. This oscillator is plotted in a panel with a central zero line and extremes at +1 and -1. Buyers are in control when the indicator is located above the zero line while sellers are in control when the indicator is located below the zero line. Readings near the zero line can indicate a reversal in trend or a rangebound market. Values near +1 signal an overbought market while values near -1 signal an oversold market.
BOP divides the distance between the open and close of the price bar by the distance between the high and low of the price bar. The initial result looks choppy and confusing so the calculation is then smoothed by a 14-period or other moving average. The distance above or below the zero line indicates the extremity of the positive or negative price change. It emits buy and sell signals through bullish and bearish divergences with price, as well as crossovers through the zero line.
Additional Volume Indicators
Klinger Volume Oscillator – looks at long and short-term money flow to confirm uptrends and downtrends.
Negative Volume Index – evaluates how rising and falling volume impact price movement over time.
On Balance Volume – calculates accumulation or distribution in a security over time. It generates a bullish divergence when price is falling and OBV is rising and a bearish divergence when price is rising and OBV is falling.
Positive Volume Index – evaluates how rising and falling volume impact price movement over time.
Projected Aggregate Volume – calculates the daily volume up to an intraday setting and projects total volume for the remainder of the session.
Projected Volume at Time – looks back at past sessions to project future volume over specified time periods.
Trade Volume Index – tracks correlation between price movement and volume levels to evaluate accumulation and distribution.
Twiggs Money Flow – applies a variation of Chaikin Money Flow to measure accumulation and distribution of a security over time.
Volume Chart – plots a volume histogram below each price bar.
Volume Oscillator – looks at accumulation and distribution by examining the relationship between two volume moving averages.
Volume Profile – displays the quantity of trading activity of a security at different price levels.
Volume Rate of Change – plots the percentage change of volume over a specified time period to determine if participation is rising or falling.
Volume Underlay – displays volume histograms in the same pane as price, rather than in a separate indicator pane.
The volatility indicator is a technical tool that measures how far security stretches away from its mean price, higher and lower. It computes the dispersion of returns over time in a visual format that technicians use to gauge whether this mathematical input is increasing or decreasing. Low volatility generally refers to quiet price movement, with predictable short-term swings, while high volatility refers to noisy or dramatic price movement, with often wildly unpredictable short-term swings.
Volatility measures the degree to which price moves over time, generating non-directional information unless the data is plotted in specific visual formats. This technical element has a great impact on options pricing and market sentiment, with high volatility generating greater extremes in greed and fear. Constructed as an indicator, volatility plots a history of price movement that supplements trend, momentum, and range analysis.
Volatile instruments are considered to be more risky than non-volatile instruments. Volatility oscillates regularly between high and low states, offering a potential timing tool for traders and market timers. Specially, the lowest volatility over X periods is often a precursor for an imminent shift to high volatility that translates into trend movement and trading signals. Market lore outlines these classic dynamics, telling market players to ‘buy in mild times and sell in wild times’.
Bollinger Bands is the financial market’s best-known volatility indicator. Created by John Bollinger in the early 1980s, the indicator constructs three lines around price: a simple moving average acts as the middle band while equally-distanced upper and lower bands expand and contract in reaction to changing volatility. The 20-day or period SMA is the most common setting for the middle band but this value is customizable in the advanced charting program.
The calculation takes the standard deviation of the SMA, which is one way to calculate distance from the SMA over time, and applies the result to the upper and lower bands. Bands expand and contract over time in reaction to changing volatility levels. Constricted bands ‘squeeze’ price action between narrow boundaries, indicating low volatility while predicting a cycle shift to high volatility. The transition can elicit high odds entry and exit signals for many trading strategies.
Donchian Channels construct upper, lower, and mid-range bands through examination of price extremes over the chosen time period. The highest price over the chosen period marks the high band while the lowest price over the chosen period marks the low band. The median band is constructed by subtracting the low band value from the high band value and dividing by two. The indicator is then used to investigate relationships between the current price and trading ranges over the chosen period.
As with Bollinger Bands, 20-days or periods is the most common Donchian Channel setting. A top band that moves higher when price approaches (or a bottom band that moves lower) signals ease of movement that facilitates trend development. Conversely, a band that remains horizontal when price approaches identifies support or resistance that raises odds for a reversal and return to the median band. Bollinger Bands differ from Donchian Channels, applying moving averages that lower the impact of high and low outliers during lookback periods.
Keltner Channels place bands around developing price in order to gauge volatility and assist directional prediction. Upper and lower bands are calculated as a multiple of average true range (ATR) and are plotted above and below an exponential moving average (EMA). Both the EMA and ATR multiplier can be customized but 50 and 5 are common settings. Price lifting into the upper band denotes strength while price dropping into the lower band denotes weakness.
These bands represent support and resistance regardless of inclination, with piercing through bands generating overbought and oversold trading signals in addition to marking an acceleration of the trend. Horizontal bands exert greater support or resistance than bands ticking higher or lower. Price falling into a rising band generates a bullish divergence while price rising into a falling band generates a bearish divergence.
Ichimoku Clouds, developed by Goichi Hosada in the late 1960s, plots multiple moving averages above and below price in the form of shaded areas that are called bullish or bearish ‘clouds’. Five calculations are applied to construct the indicator, generating a cloud that represents the difference between two of the lines. Price above a cloud signals an uptrend while price below a cloud signals a downtrend. A bullish price swing into a cloud denotes resistance while a bearish price swing into a cloud denotes support.
Clouds also tick higher or lower over time, adding to the indicator’s versatility. Trend signals are expected to be stronger and more reliable when price is moving higher above a cloud or lower below a cloud. The two cloud lines are called ‘Span A’ and ‘Span B’. The cloud is colored green when Span A is above Span B and colored red when Span A is below Span B. Price above a red cloud signals a bullish divergence while price below a green cloud signals a bearish divergence.
Historical Volatility is plotted in a separate pane, unlike most volatility indicators. It measures the distance that price travels away from a central mean over the chosen time period. Standard deviation is often used to calculate the indicator but variations utilize other measurements. Risk increases when the indicator rises and decreases when it falls. It is non-directional, meaning that rising or falling volatility doesn’t specifically favor buying or selling strategies.
The original indicator applied a 10-period and 252-day setting to measure volatility over a year (252 = average number of trading days in a year). The technician now customizes these inputs as well as standard deviation (SD). It’s best to ‘form fit’ the calculation to a security because average volatility is expected to differ between different types of instruments and markets. Interpretation of historical volatility compares current levels with prior levels, looking for high and low extremes that may impact profits and losses. It can also be useful to compare values across highly correlated instruments to uncover ‘typical’ value and hidden divergences.
Additional Volatility Indicators
Beta – measures a security’s volatility compared to the broad market or another security.
Bollinger %b – translates the distance between price and Bollinger Bands into an oscillator plot.
Bollinger Bandwidth – calculates the percentage distance between upper and lower Bollinger Bands, seeking to identify high odds turning points.
Choppiness Index – measures whether a market is engaged in a trend or a trading range.
Chaikin Volatility – generates an oscillator that applies Moving Average Convergence Divergence (MACD) to accumulation-distribution rather than price. A crossover above a zero line indicates strength and accumulation while a crossover below a zero line indicates weakness and distribution.
Donchian Channel – constructs upper, lower, and mid-range bands through examination of price extremes over a chosen time period. The highest price over the chosen period marks the high band while the lowest price over the chosen period marks the low band.
Donchian Width – measures the price difference between the high and low bands of the Donchian Channel.
Fractal Chaos Bands – draws bands around price action, with the slope determining whether or not the security is trending or flat.
Moving Average Deviation – measures volatility by examining how an asset’s price has deviated from the selected moving average over time.
Moving Average Envelope – plots a band over price, with top and bottom extremes calculated as a pre-chosen percentage above and below a moving average.
Prime Number Bands – identifies the highest and lowest prime numbers in a trading range over a given period and plots the output as a band across price.
Relative Volatility – is a variation of Relative Strength Index (RSI) that measures the direction of volatility over the specified time period, using standard deviation calculations.
Standard Deviation – examines how far price stretches away from a central mean price over time.
STARC Bands – also known as Stoller Average Range Channel Bands, are plotted above and below a simple moving average, highlighting extreme levels that can elicit potent buy or sell signals.
Ulcer Index – predicts the drawdown, depth, and duration of asset declines through examination of highs and lows over time.
Dow component Salesforce.com Inc. (CRM) is gaining ground in Wednesday’s market after Morgan Stanley upgraded the sales tracking giant to ‘Overweight’. The stock posted an all-time in the 280s in September, just days after the company was added to the Dow Jones Industrial Average. Price action since that time has carved an orderly but persistent bull flag pattern that’s been engaged in nearly six months of testing at 200-day moving average support.
The stock ended a 12-day 20% slide in March 2021 after Slack Technologies Inc. (WORK) reported a Q4 2020 loss of $0.01 per-share. Salesforce bought the business technology provider for $27 billion in December 2020 in a transaction expected to close in the second quarter of 2022. Price action since that time has tracked bilateral catalysts, adding volatility and modest downside. Even so, the company remains on track to hit new highs sometime this year.
Morgan Stanley analyst Keith Weiss raised his Salesforce rating to ‘Overweight’ with a $270 target on Wednesday, advising the pullback since September “creates a good entry point.” He also notes the company is “well positioned to benefit from an accelerating pace of investment in strategic digital transformation initiatives” and added that “significantly” better performance in past two quarters has addressed critics of the December acquisition.
Wall Street and Technical Outlook
Wall Street consensus is solid as a rock, with a ‘Buy’ rating based upon 32 ‘Buy’, 3 ‘Overweight’, and 9 ‘Hold’ recommendations. No analysts are recommending that shareholders close positions and move to the sidelines. Price targets range from a low of $200 to a Street-high $336 while the stock has opened Wednesday’s session just $18 above the low target. Caution after Salesforce’s outsized 37% 2020 return is contributing to this dismal placement.
Salesforce broke out above 2018 resistance above 160 in January 2020 and failed the breakout during the pandemic decline. It bounced back to the first quarter peak in July and broke out in August, surging into the 280s after addition to the Industrial Average. That marked the top, followed by a bull flag correction that should hold support near 200. Just keep in mind a breakdown will also fail the third quarter breakout, exposing a trip into the 150s.
Dow component Home Depot Inc. (HD) is trading higher by more than 2% in Tuesday’s pre-market after beating Q1 2021 top and bottom line estimates by healthy margins. The home improvement giant earned $3.86 per-share during the quarter, $0.93 better than estimates, while revenue rose a healthy 32.7% year-over-year to $37.5 billion, nearly $5 billion higher than consensus. Comparative sales grew 31% worldwide, with 29% growth in the United States.
Home Buying Boom
The company has benefited from intense pandemic tailwinds, with locked-down and socially-distanced customers using the crisis to engage in home improvement projects. While that catalyst is winding down at a rapid pace, COVID also triggered a major geographical shift at the same time that remote-working millennials are marrying and building their nests, underpinning a massive home building and buying spree that should last for several years, at a minimum.
Despite Home Depot’s stellar report, bullish sentiment could offer a better opportunity for rival Lowes Corp. (LOW), who reports Q1 earnings in Tuesday’s pre-market. Oppenheimer analyst Brian Negal embraced this strategy last week. noting this “more upbeat call on Lowe’s is largely tactical in nature and hinged upon prospects for a continued flow of funds into more cyclically focused equities and now historically discounted valuation versus that of Home Depot.”
Wall Street and Technical Outlook
Wall Street consensus on Home Depot now stands at an ‘Overweight’ rating based upon 21 ‘Buy’, 3 ‘Overweight’, 10 ‘Hold’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of $280 to a Street-high $377 while the stock is set to open Tuesday’s session about $24 below the median $350 target. A trip back up last week’s all-time high at $345.69 looks likely with this configuration but a breakout might not be in the cards.
Home Depot sold off from a 2020 high at 247 to a three-year low near 140 during the first quarter of 2020 and turned sharply higher, returning to the prior high in May. A June breakout stalled just below 300 in August while a March 2021 buying surge above that peak posted an all-time high last week. A weekly Stochastic sell cycle makes a breakout unlikely in the second quarter but the long-term uptrend should eventually resume control of the ticker tape.
The Children’s Place Inc. (PLCE) is trading higher by more than 5% in Monday’s pre-market after two analyst upgrades. The children’s specialty apparel retailer reports Q1 2022 earnings in Thursday’s pre-market when it’s expected to post a loss of $0.21 per-share on $331.15 million in revenue. If met, the loss-per-share will be one-tenth of the red ink posted during the same quarter last year when retailers around the world closed their doors as a result of the pandemic.
The company operates more than 1,000 locations in 21 countries as well as lucrative online e-commerce sites Childrensplace.com and Gymboree.com. U.S. operations are rapidly returning to normal but restrictions in other countries are keeping pressure on revenue. In addition, American school kids will return to physical classrooms this fall, underpinning back-to-school sales that have suffered badly due to remote learning.
Monness Crespi and Hardt analyst Jim Chartie upgraded The Children’s Place to ‘Buy’, noting “the reopening economy and government stimulus has driven strong consumer demand across all categories in March and April, with many retailers reporting sales above March/April 2019 levels. Given much better than expected consumer spending and conservative guidance, we are raising our 1Q EPS estimate more than $1 above consensus and see the potential for more upside”.
Wall Street and Technical Outlook
Wall Street coverage has shrunk from 8 to 5 top tier analysts since the start of 2021. Consensus now stands at an ‘Overweight’ rating based upon 2 ‘Buy’, 1 ‘Overweight’, 1 ‘Hold’, and 1 ‘Sell’ recommendation. Price targets currently range from a low of $74 to a Street-high $150 while the stock is set to open Monday’s session about $18 below the median $101 price target. There’s plenty of room for upside with this configuration if the company posts an upbeat quarter.
The Children’s Place hit an all-time high near 160 in the first quarter of 2018 and entered a persistent downtrend that bottomed out at 17- year low in single digits in March 2020. It bounced off that depressed level in two strong recovery waves, finally stalling at 200-week moving average resistance in January 2021. The stock is testing four-month range resistance in the pre-market, with a breakout favoring a rapid advance into triple digits.
Dow component Walmart Inc. (WMT) reports Q1 2022 earnings ahead of Tuesday’s opening bell, with analysts looking for a profit of $1.21 per-share on a staggering $131.5 billion in revenue. If met, earnings-per-share (EPS) will mark a slight profit increase compared to the same quarter last year. The stock fell nearly 13% in just two weeks after missing Q4 2021 estimates in February and providing weak fiscal year 2022 guidance.
Profits Impacted by Rising Wages
The retail giant has struggled since hitting an all-time high above 150 in December, held down by an exodus out of COVID-19 beneficiaries. Shrinking profit margins have now lifted to the top of investor concerns, with the company shifting more workers to full time employment while raising average hourly wages to over $15 per hour. However, that still doesn’t measure up with competitors Amazon.com Inc. (AMZN) and Target Corp. (TGT), raising odds for further wage pressure.
Recent reports also warn that Walmart is having trouble competing in the highly-lucrative grocery space, struggling to hold onto the top sales slot. According to Vox’s Recode, grocery sales are “losing market share rapidly”, which isn’t surprising because multiple competitors introduced curbside pickup services in 2020 to address the COVID-19 pandemic and have kept those initiatives in place due to their immense popularity.
Wall Street and Technical Outlook
Wall Street consensus remains modestly bullish, with an ‘Overweight’ rating based upon 21 ‘Buy’, 6 ‘Overweight’, 5 ‘Hold’, 1 ‘Underweight’, and 2 ‘Sell’ recommendations. Price targets currently range from a low of $120 to a Street-high $180 while the stock closed Friday’s session more than $20 below the median $160 target. This week’s report isn’t likely to change analyst sentiment, given growing inflationary pressure that could weigh on fiscal year results.
Walmart cleared 2000 resistance in the 60s in 2017 and entered an uptrend that carved a series of higher highs and higher lows into December’s all-time high at 153.66. The stock sold off to the 200-day moving average in March and bounced into the second quarter but is still trading in the lower half of the range established by that downdraft. Accumulation has dropped to 2019 levels at the same time, raising odds for mixed price action into the second half of 2021.