CMT Exam Level 3 Free Practice Questions & Answers Set 2

Options trading presents a unique risk profile, particularly for novice traders, due to the leverage involved. While options can offer substantial profit potential, they also magnify potential losses. The underlying markets (cash or futures) are often analyzed first to generate trading signals, which are then applied to options strategies. However, understanding the complexities of options requires a solid foundation in the underlying markets. Over-the-counter (OTC) options, such as credit default options (CDOs), are less transparent and pose additional challenges due to the lack of readily available pricing data. Swaps and forwards, also traded OTC, are often customized agreements, making technical analysis difficult or impossible. The foreign exchange (FOREX) market, the largest financial market globally, sees significant speculative trading, with technical analysis being a prevalent and potentially profitable approach. The question emphasizes the importance of understanding market structure, instrument characteristics, and the limitations of technical analysis in different contexts. A trader needs to be aware of the availability of pricing data and the degree of standardization in order to effectively apply technical analysis.

The Ichimoku Cloud chart is a comprehensive technical analysis tool that identifies support and resistance levels, gauges momentum, and provides trading signals. The Senkou Span A is calculated by averaging the Tenkan Sen (9-period average of high and low) and the Kijun Sen (26-period average of high and low), then plotted 26 periods forward. The Senkou Span B is calculated as the average of the highest high and lowest low over the past 52 periods, also plotted 26 periods forward. The area between these two lines forms the ‘cloud,’ representing equilibrium. A trader considering the Ichimoku Cloud for Apple Computer should understand that the cloud represents a period of market indecision. Therefore, initiating trades within the cloud is generally discouraged. The cloud’s position relative to the price indicates potential support (when the price is above the cloud) or resistance (when the price is below the cloud). The thickness of the cloud can also suggest the strength of the support or resistance. The crossing of the Tenkan Sen and Kijun Sen can provide additional signals, but these should be considered in conjunction with the cloud’s overall context.

Dow Theory, a cornerstone of technical analysis discussed in the CMT curriculum, emphasizes that market prices move in trends across different time horizons. These trends are fractal, meaning their behavior is similar regardless of the time frame—minute-to-minute trends resemble day-to-day trends. Dow identified three principal time horizons: primary, intermediate, and minor, likening them to tides, waves, and ripples. Modern technicians, with the aid of computers, recognize even more trend periods. A crucial observation of Dow Theory is that trends tend to continue rather than reverse. This principle underlies the technician’s approach to identifying the beginning or end of trends and is fundamental to trend-following strategies. The interplay between trends of different lengths is also significant; a trend is influenced by both the next larger and next smaller trends. Short-term trends reverse before medium-term trends, and medium-term trends reverse before long-term trends, providing early signals of potential shifts in longer trends. Therefore, understanding these relationships is essential for effective trend analysis and trading decisions.

The Hanging Man is a bearish reversal pattern that forms after an uptrend. It has a small body, a long lower shadow (at least twice the length of the body), and little or no upper shadow. The long lower shadow indicates that sellers entered the market and pushed the price down significantly during the session. While the price might have recovered to close near the open, the selling pressure suggests that the uptrend may be losing momentum. The confirmation of the Hanging Man pattern comes on the next trading day. A bearish confirmation occurs when the price closes below the Hanging Man’s body, signaling that the sellers have taken control and a downtrend is likely to begin. The Harami pattern, on the other hand, is a two-candlestick pattern that can be either bullish or bearish, depending on where it occurs. A bearish Harami appears after an uptrend and consists of a large bullish candlestick followed by a smaller bearish candlestick whose body is contained within the body of the previous candlestick. This pattern suggests indecision in the market and a potential reversal of the uptrend. The Harami pattern is considered a reversal pattern because it signals a potential change in the prevailing trend. The first candlestick represents the continuation of the existing trend, while the second candlestick indicates a pause or hesitation in that trend. This pause can be a sign that the forces driving the trend are weakening, and a reversal may be imminent.

The bullish support line and bearish resistance line are key components of the three-box reversal Point and Figure charts, a traditional method used in technical analysis. These lines, drawn at 45-degree angles, serve as dynamic thresholds for initiating or avoiding trades. The bullish support line is drawn one box below the last observable ‘O’ column after a buy signal from a base, acting as a floor below which one should not consider buying. Conversely, the bearish resistance line is drawn one box above the latest ‘X’ column after a sell signal from a top, functioning as a ceiling above which one should not consider selling. These lines help filter out premature or false signals, adding a layer of confirmation to trading decisions. Penetration of these lines concurrently with a pattern signal amplifies the significance of that signal, suggesting a higher probability of the predicted price movement. The convention of using 45-degree angles, while somewhat arbitrary, is a standardized practice within this charting method. The effectiveness of these lines lies in their ability to visually represent potential support and resistance levels, guiding traders in making more informed decisions based on established patterns and trend confirmations.

The ‘Chandelier Exit’ is a trailing stop method specifically designed to account for a security’s inherent volatility. It calculates the stop level by subtracting a multiple of the security’s Average True Range (ATR) from its recent highest high (for long positions) or lowest low (for short positions). This approach differs significantly from trend line-based stops, which rely on visual trend identification, and parabolic SAR, which uses an acceleration factor to create a stop level that follows a parabolic curve. Unlike trend line stops, the Chandelier Exit doesn’t depend on subjective trend line drawing. Unlike parabolic SAR, it directly incorporates a measure of volatility (ATR) in its calculation. The multiple of ATR used (e.g., 2.5 to 4.0) is typically determined based on market conditions and the trader’s risk tolerance. The primary advantage of the Chandelier Exit is its adaptability to changing market volatility, making it particularly useful in fast-moving or unpredictable markets. This method is especially valuable when traditional support or resistance levels are distant from the current price, and the security is experiencing an accelerated trend.

The question addresses the concept of confirming breakouts in technical analysis, a critical skill for CMT candidates. A close filter involves waiting for the price to close beyond the breakout level to confirm the breakout’s validity. This approach reduces the likelihood of acting on false breakouts, which are common in intraday trading. Waiting for a closing price beyond the breakout level provides a higher degree of certainty that the price movement is sustained and not just a temporary fluctuation. Some traders even wait for two consecutive closes beyond the breakout level for even stronger confirmation, although this may result in missing a portion of the initial move. The point or percent filter involves establishing a breakout zone beyond the breakout level, requiring the price to penetrate this zone before considering the breakout valid. This method is particularly useful in computerized trading models where a definite breakout price is needed. The most commonly used filter is the 1-3% rule, where the breakout is confirmed only if the price penetrates 1-3% beyond the breakout point. This approach helps to filter out minor fluctuations and focus on more significant price movements. The question requires candidates to understand the rationale behind confirmation methods and the trade-offs involved in each approach.

Contrarian investing hinges on the principle that the market often moves in the opposite direction of the prevailing sentiment, especially among non-professional investors. When the majority of these investors are bullish, they are typically fully invested, leaving little room for further demand. Informed traders, recognizing this overvaluation, may start selling, exacerbating a potential downturn. Conversely, when pessimism is rampant, and most investors have sold off their holdings, the market is primed for a rebound as demand can easily outstrip supply. Therefore, identifying and acting against extreme sentiment levels can provide a strategic advantage. This approach requires careful analysis of sentiment indicators and a willingness to go against the crowd, which can be psychologically challenging but potentially rewarding. Ignoring liquidity traders is crucial as their actions are driven by immediate cash needs rather than market analysis.

The Kelly Criterion, often expressed as \( f^* = \frac{p – (1-p)/R}{1} \), where \( p \) is the probability of a win and \( R \) is the win/loss ratio, suggests an optimal fraction of capital to allocate to a trade. This formula aims to maximize long-term growth while minimizing the risk of ruin. The Risk of Ruin (ROR) formula, which incorporates the probability of success, payoff ratio, and fraction exposed to trading, provides an estimate of the likelihood of depleting one’s trading capital. The Theory of Runs formula analyzes the potential for consecutive losses and helps determine an appropriate position size to withstand such sequences. By comparing the position sizes suggested by each formula and selecting the smallest, traders can adopt a conservative approach that prioritizes capital preservation. This method acknowledges the limitations and assumptions inherent in each formula, promoting a more robust risk management strategy. The Kelly Criterion, while theoretically optimal, can be aggressive and lead to significant drawdowns if misapplied or if the estimated probabilities are inaccurate. Therefore, using the most conservative outcome from all three methods is a prudent approach to position sizing.

W.D. Gann’s methodologies, while shrouded in some mystery and debated for their verifiable accuracy, fundamentally integrated time and price into market analysis. He used geometric shapes like circles, squares, and triangles to identify potential turning points. Gann believed that market cycles aligned with natural cycles, such as the Earth’s orbit around the sun (approximately 360 days), and that these cycles could be divided into segments (e.g., 90, 180 degrees) to anticipate highs and lows. Gann’s concept of ‘squaring price and time’ involved identifying price ranges and time intervals where future price movements were likely to occur. He also emphasized the importance of angles drawn from tops and bottoms to project retracement levels. While the precise application of Gann’s methods can be subjective, his emphasis on time cycles and geometric relationships distinguishes his approach from purely price-based technical analysis. His work highlights the potential for recurring patterns and predictable relationships in market behavior, even if the underlying causes are not fully understood. Gann’s legacy continues to influence technical analysts who seek to incorporate time-based analysis into their trading strategies.

Sokyo Honma, a rice trader from 18th-century Japan, is recognized for his contributions to early technical analysis. His methods, documented as the “Sakata constitution,” involved analyzing price patterns to predict future movements. These rules included analyzing one day’s price to predict the next, three days of prices to predict the fourth, and rate of change analysis. While Honma’s methods were not initially recorded on charts, his focus on price data and trading discipline aligns with the core principles of technical analysis. The Amsterdam Exchange, founded in 1608, was a hub for trading various financial instruments and commodities, but there is no direct evidence linking it to the documented use of technical analysis during that period. Charles Dow, considered the father of modern technical analysis, introduced stock indexes in the late 19th century, which significantly advanced the field. However, Dow’s work came much later than Honma’s documented methods. Therefore, based on historical records, Sokyo Honma is the earliest known individual to have developed and documented a set of technical trading rules.

The foreign exchange (FOREX) market stands out due to its decentralized, over-the-counter nature and immense daily trading volume. Unlike centralized exchanges, FOREX operates electronically across major financial centers globally, creating a continuous, 24-hour market. This structure facilitates international trade by enabling currency conversions necessary for cross-border transactions. However, the sheer scale of FOREX activity far exceeds the requirements of international trade alone, indicating substantial speculative trading. A significant portion of FOREX transactions occurs between currency dealers and other financial institutions, such as hedge funds and proprietary trading firms. While central banks participate in FOREX to implement monetary policies, their contribution to the overall trading volume is relatively small. The prevalence of technical analysis in FOREX is well-documented, with academic studies suggesting that technical strategies can be profitable in currency trading. The most actively traded currency pair is the U.S. dollar/euro, reflecting the economic significance of the United States and the Eurozone. Understanding the dynamics of the FOREX market is crucial for technical analysts, as it presents unique opportunities and challenges due to its size, liquidity, and decentralized structure.

The best-performing patterns, considering both gain and risk, include the high-and-tight upward breaking flag, the head-and-shoulders top, top islands breaking down, and upward breaking descending triangles. A high-and-tight flag is a bullish continuation pattern characterized by a sharp price increase followed by a tight consolidation phase resembling a flag. The head-and-shoulders top is a bearish reversal pattern indicating a potential trend reversal from bullish to bearish. Top islands breaking down are bearish reversal patterns that form after an uptrend, characterized by a cluster of price action isolated above the previous trend, followed by a breakdown. Upward breaking descending triangles are bullish continuation patterns that form during a downtrend, characterized by a descending upper trendline and a horizontal lower trendline. Understanding these patterns and their statistical backing is crucial for making informed trading decisions and avoiding reliance on unsubstantiated patterns. The analyst must always adjust parameters to fit the peculiarities of the security being analyzed. Profitable chart pattern analysis is the result of determined study.

The Hindenburg Omen is a technical indicator used to signal a potential market crash or significant downward correction. It is based on the idea that a healthy stock market exhibits internal uniformity, meaning that either a large number of stocks are making new annual highs or a large number are making new lows, but not both simultaneously. When both new highs and new lows are occurring in significant numbers, it suggests a divergence within the market, indicating potential instability and a higher risk of a downturn. The conditions for the Hindenburg Omen to occur involve specific criteria related to the number of new highs and lows, the overall market trend, and momentum indicators. The 52-week highs and lows must each exceed a certain percentage of total issues, typically around 2.2% to 2.8%. The number of new highs or new lows must also exceed a certain threshold, often around 75. The NYSE index or its moving average must be trending upwards. The McClellan Oscillator, a momentum indicator, must be negative, indicating bearish momentum. The number of new highs should not be more than twice the number of new lows. The signal is considered valid for a specific period, usually 30 to 36 days, and its strength is proportional to the number of occurrences within that period. The Hindenburg Omen is not a perfect predictor and should be used in conjunction with other technical and fundamental analysis tools to make informed investment decisions. The absence of internal uniformity, as highlighted by the Omen, suggests that the market may be vulnerable to a significant correction, making it a valuable tool for risk management.

Backwardation is a situation where the futures price of a commodity is below the expected spot price at maturity. This often occurs when there is a high demand for the physical commodity in the near term, leading to a premium for immediate availability. Investors might be willing to pay more now to secure the commodity, anticipating higher prices in the future, or due to storage costs and convenience yields. Contango, conversely, is when the futures price is above the expected future spot price. This typically happens when there are high storage costs or when the market expects prices to rise in the future. Normal market conditions usually exhibit contango because futures prices reflect the costs of carrying the commodity over time, including storage, insurance, and financing. Understanding these concepts is crucial for commodity traders as they impact hedging strategies, speculation, and overall market analysis. The relationship between spot and futures prices provides valuable insights into market expectations and supply-demand dynamics.

An ascending triangle is characterized by a horizontal upper resistance line and an upward-sloping lower support line. This pattern suggests increasing buying pressure as the price makes higher lows while facing consistent resistance at the upper bound. A breakout above the horizontal resistance line is generally considered a bullish signal, indicating that the buying pressure has overcome the resistance. While declining volume is common within the pattern, it is not a strict requirement. The breakout point should be chosen carefully due to the potential for false breakouts. Ascending triangles tend to have a higher probability of upward breakouts (around 77%), and these breakouts typically occur about 61% of the way through the pattern’s formation. The performance rank of ascending triangles is about average compared to other chart patterns, with a slightly more favorable outcome for downward breakouts. Failure rates, referring to instances where the price fails to continue in the direction of the breakout, are also around average, ranging from 11% to 13%.

The harami pattern, a key concept in candlestick charting, signals potential shifts in market momentum. It’s characterized by a smaller candlestick body contained within the prior, larger candlestick’s body, indicating a period of indecision or consolidation. This pattern is a volatility contraction signal, suggesting a possible trend reversal or acceleration. The ‘harami cross’ is a variation where the second candlestick is a doji. The color of the candlesticks is not critical; the key is the containment of the second body within the first. The pattern’s effectiveness depends on confirmation from subsequent price action. A break above the harami suggests bullish continuation, while a break below signals bearish reversal. The hammer and hanging man patterns, on the other hand, are single candlestick patterns that occur at the end of trends. The hammer appears at the bottom of a downtrend and signals a potential reversal to the upside, while the hanging man appears at the top of an uptrend and signals a potential reversal to the downside. Both patterns have a small body at the upper end of the trading range and a long lower shadow, indicating that buyers or sellers, respectively, are starting to take control. The shooting star is similar to the hanging man but occurs after an uptrend, while the inverted hammer is similar to the hammer but occurs after a downtrend. These patterns can be useful for identifying potential entry and exit points in the market.

The triple top and triple bottom formations in Point and Figure charting represent significant potential trend reversals, requiring prices to surpass two previous highs or lows, respectively. This increased confirmation threshold generally leads to higher profitability compared to double top/bottom patterns, albeit with less frequent occurrences. The ascending triple top, a variation, features three rows of Xs with each successive row breaking above the previous one, indicating a strong upward trend. Conversely, the descending triple bottom shows three rows of Os with progressively lower levels, signaling a strong downward trend. The question emphasizes the need to differentiate between these patterns and their implications for trading decisions. The profitability percentages cited from Davis’s research highlight the potential success rates associated with these formations, while Anderson’s findings provide empirical evidence of their performance over a specific period. Understanding the nuances of these patterns, including their variations and statistical performance, is crucial for effective application of Point and Figure charting in technical analysis.

Connie Brown’s approach to Elliott Wave analysis emphasizes simplification and practical application. She advises against getting bogged down in the minutiae of smaller wave patterns, advocating instead for developing a ‘feel’ for the market’s rhythm. This involves compressing the chart scale to obscure less important details and focusing on the overall price action. Her methodology begins by identifying the largest price move within a pattern and then examining price action both before and after this move. She integrates Fibonacci ratios, Gann time and price projections, and oscillators based on the RSI and her composite index to forecast price targets and generate trading signals. This holistic approach combines pattern recognition with quantitative tools to provide actionable insights, moving away from a purely theoretical application of Elliott Wave principles. Brown’s focus on market rhythm and the integration of multiple technical indicators aims to provide a more robust and practical framework for traders and investors.

The ratio of gold to the stock market provides insights into the relative performance of these two asset classes. A declining ratio suggests that gold is underperforming relative to the stock market, indicating that, in relation to the stock market, gold might not be the most advantageous investment at that time. The 24-month SMA (Simple Moving Average) serves as a basic signal for shifting between hard and soft assets. A crossover of the ratio below its 24-month SMA suggests a move from hard assets (like gold) to soft assets (like stocks). While this method is rudimentary and requires further refinement, it offers a broad indication of long-term investment trends. Industrial raw materials or industrial metals, such as silver, oil, copper, and aluminum, often correlate with the business cycle. Rising industrial metal prices typically signal business expansion, offering alternative investment options during periods favoring hard assets. The relationship between industrial metals prices and the stock market can provide additional signals, potentially coinciding with signals from the gold/stock market ratio, as demonstrated by trend lines.

An ascending triangle is characterized by a horizontal upper resistance line and an upward-sloping lower support line. Breakouts from this pattern, while generally favoring upward movement, can be erratic and prone to false signals. The pattern’s effectiveness is moderate compared to other chart patterns. The key to trading ascending triangles lies in carefully selecting breakout points and being aware of the potential for false breakouts. Volume often declines within the pattern but isn’t a definitive requirement. The frequency of upward breakouts is statistically higher, but downward breakouts also occur and can be profitable. The overall performance rank of ascending triangles places them in the middle tier of chart patterns, indicating a balanced reliability. Failure rates, regardless of the breakout direction, hover around the average mark, suggesting a typical level of risk associated with this pattern. Therefore, understanding these characteristics is crucial for traders aiming to leverage ascending triangles in their strategies, emphasizing the need for confirmation and risk management.

The MACD is a momentum oscillator that indicates the relationship between two moving averages of prices. The MACD line is calculated by subtracting the 26-period EMA from the 12-period EMA. The signal line is a 9-period EMA of the MACD line. Crossovers of the MACD line above the signal line are often interpreted as bullish signals, while crossovers below the signal line are seen as bearish signals. Divergences between the MACD and price action can also provide valuable insights. A bullish divergence occurs when the price makes lower lows, but the MACD makes higher lows, suggesting that the downtrend may be losing momentum. Conversely, a bearish divergence occurs when the price makes higher highs, but the MACD makes lower highs, suggesting that the uptrend may be losing momentum. The MACD histogram represents the difference between the MACD line and the signal line, providing a visual representation of the momentum of the MACD. It is important to note that MACD signals should be used in conjunction with other technical analysis tools and indicators to confirm potential trading opportunities. The MACD is most effective in trending markets and can generate false signals in choppy or sideways markets. Analysts often use overbought and oversold levels to generate signals for price reversion to the central trend.

The rate of change in money market fund cash flow serves as a sentiment indicator, reflecting investor behavior. A high rate of growth in cash flow into these funds typically occurs when investors are selling stocks, indicating a potentially oversold market and a favorable time to invest. This is because investors are ‘parking’ their money in these short-term, liquid assets. The indicator does not provide direct buy or sell signals but rather highlights the liquidity available for potential investment in the stock market. Low short-term interest rates can influence money flow out of money market funds and into the stock market in search of higher returns. Margin debt, while historically a sentiment indicator, may be less reliable today due to the availability of highly leveraged derivatives. The 15-month rate of change in margin debt can generate buy and sell signals, but parameters may need adjustment. Funds outside the security market, such as money market funds, can influence market liquidity and investor sentiment, but their impact is not always direct or predictable. Therefore, understanding these dynamics is crucial for technical analysts.

The opening range breakout (ORB) strategy, particularly when used with concepts like NR4 or NR7 days, relies on identifying periods of low volatility followed by an expansion. Toby Crabel’s research indicated that NR days outperform wide-range days, suggesting that profits are more readily available from volatility expansion rather than contraction. The ‘stretch,’ calculated using methods like the ten-day average of the difference between the open and the closest extreme, defines the boundaries of the ORB. A key element is the timing of the breakout; early penetration of the ORB increases the likelihood of success. Mark Fisher’s ACD method builds upon this by adding filters to the opening range to define entry and exit signals. The success of these methods hinges on the trader’s ability to interpret price action around these levels and adapt strategies accordingly. Understanding the nuances of volatility, timing, and the specific parameters of the ORB is crucial for effective implementation.

The core principle behind temporal risk management, as it relates to the CMT exam, emphasizes that risk escalates with the duration a position is held. This is because market conditions, economic factors, and unforeseen events can accumulate and negatively impact an investment over time. While potential reward might be initially attractive, it doesn’t necessarily increase proportionally with time; at some point, the risk outweighs the potential gains. Therefore, a prudent strategy involves exiting a position once the reward potential diminishes to mitigate unnecessary exposure to accumulating risks. Security quality, while important, doesn’t negate the impact of time on risk. Money management strategies, including stop-loss orders, are crucial for limiting potential losses, but they don’t eliminate the fundamental increase in risk associated with prolonged exposure. The concept of ‘maximum adverse excursion’ helps in determining appropriate stop-loss levels based on historical trade data, but it’s still a reactive measure against the inherent risk that grows with time. Therefore, the most effective way to reduce risk in the context of temporal risk management is to limit the duration of the position to coincide with the period of reward potential.

The Investors Intelligence Advisory Opinion ratio, calculated as the percentage of bullish advisors divided by the total of bullish and bearish advisors, serves as a sentiment indicator. A high ratio typically suggests excessive optimism, potentially signaling a market top, while a low ratio indicates pessimism, possibly preceding a market bottom. Ned Davis Research found that a ratio above 69% resulted in lower annual gains, while a ratio below 53% led to higher annual gains. Colby suggests an optimistically skewed decision rule, taking short positions when bearish newsletters exceed a certain threshold above their moving average. This strategy aims to capitalize on periods of extreme pessimism. The question tests the understanding of how advisory sentiment, specifically the Investors Intelligence Advisory Opinion ratio, can be used to identify potential market turning points and inform trading strategies, emphasizing the contrarian approach of profiting from extreme pessimism.

Kondratieff wave theory suggests that these long cycles are driven by the bunching of innovations across various sectors, including products, services, technology, production methods, markets, raw materials, and business organization. These innovation spurts typically emerge from earlier economic slowdowns. Modelski and Thompson emphasize that K-waves are attributes of the world economy led by a major national economy and concern output rather than prices. The start-up phase of a K-wave is often accompanied by a major war, and a significant relationship exists between the K-wave and the rise and fall of world powers. The theory posits that each K-wave has a characteristic location and a clear location in time that can be dated. The K-wave grows out of necessity and innovation and then influences global power and politics as they evolve to accept the new economics. Therefore, the correct answer is that K-waves are associated with the bunching of innovations across various sectors.

Backwardation is a market condition where the futures price of a commodity is lower than the expected spot price at the contract’s maturity. This often occurs when there is a perceived shortage of the commodity in the near term, leading to higher immediate demand and prices. Producers might be inclined to sell their commodity immediately rather than holding it for future delivery, further contributing to the higher spot price. The convenience yield, representing the benefit of holding the physical commodity, plays a crucial role in backwardation. When the convenience yield is high (due to scarcity or high demand), it can exceed the cost of carry (storage, insurance, financing), resulting in backwardation. Conversely, contango is a situation where the futures price is higher than the expected spot price. This typically happens when there is ample supply and low immediate demand, making it more attractive to store the commodity and sell it later. The cost of carry then exceeds the convenience yield. Therefore, backwardation indicates a market where immediate demand outweighs future expectations, driven by factors like scarcity and high convenience yield, making it profitable to sell the commodity now rather than later.

Glenn Neely, in his book ‘Mastering Elliott Wave,’ presents a comprehensive approach to Elliott Wave analysis that involves a detailed set of rules for understanding how waves unfold. Neely’s method emphasizes the use of dots rather than traditional bar charts to construct Elliott Wave charts. A key aspect of Neely’s approach is the identification and analysis of ‘monowaves’ and their larger patterns, which are specific to his interpretation of Elliott Wave theory. Neely’s methodology also includes unique nomenclature and specific techniques for setting up and interpreting Elliott Wave charts, distinguishing it from more conventional applications of Elliott Wave principles. This detailed and structured approach aims to provide a more precise and systematic way to analyze market movements and predict future price action based on Elliott Wave patterns. Therefore, understanding Neely’s method requires familiarity with his specific terminology and techniques, which are designed to enhance the accuracy and reliability of Elliott Wave analysis. The question tests the understanding of alternative approaches to Elliott Wave Theory as it relates to the CMT exam.

A negative reversal, as described by Brown and popularized by Cardwell, occurs when an oscillator reaches a new high, surpassing a previous high point, while the price fails to reach a corresponding new high. This situation is the inverse of a negative divergence, where the price makes a new high but the oscillator does not. The negative reversal suggests that the upward momentum indicated by the oscillator is not confirmed by the price action, signaling potential weakness in the current uptrend. This lack of confirmation between the oscillator and price implies that the trend may be losing strength and could be preparing for a reversal. Technicians interpret this as a warning sign that the buying pressure is diminishing, and a trend reversal to the downside may be imminent. Therefore, observing a negative reversal prompts traders to consider reducing long positions or initiating short positions, depending on their risk tolerance and overall market analysis. The key is that the oscillator leads the price in signaling potential weakness.