CMT Level II Market Indicators and Cycles: Advanced Breadth and Volume Analysis
McClellan Oscillator and Summation Index: Calculation and Interpretation
Advanced CMT market breadth analysis begins with the understanding that market averages can often mask the underlying health of the constituent stocks. The McClellan Oscillator is a primary tool for measuring this internal momentum. It is calculated as the difference between two exponential moving averages (EMAs) of the daily net advances (number of advancing issues minus declining issues). Specifically, it utilizes the 19-day and 39-day EMAs. When the oscillator is positive, it suggests that shorter-term breadth is improving faster than longer-term breadth, indicating a healthy accumulation phase. Conversely, negative readings suggest distribution. Candidates must be able to identify breadth thrusts, which occur when the oscillator moves from deeply negative to significantly positive (often +100 or higher) within a short window, signaling a powerful shift in market participation. The McClellan Summation Index is the cumulative total of the daily oscillator values. While the oscillator provides a tactical view of breadth momentum, the Summation Index offers a strategic look at the long-term trend. A failure of the Summation Index to reach new highs alongside price is a classic bearish divergence, suggesting that the "army" of stocks is no longer following the "generals" (the cap-weighted indices).
Volume-Spread Analysis and On-Balance Volume Divergence
Volume spread analysis CMT principles focus on the relationship between the price range (the spread) and the volume of a specific period to determine the activity of institutional players. In the CMT Level II framework, this is often extended to the study of On-Balance Volume (OBV) and its divergence from price action. OBV is a cumulative indicator that adds volume on up days and subtracts it on down days. The absolute value of OBV is secondary to its trend. When price reaches a new high but OBV fails to surpass its previous peak, it indicates that the move is occurring on diminishing conviction, often termed a "non-confirmation." This suggests that the smart money is liquidating positions into the strength of the rally. Furthermore, candidates must analyze the price-volume relationship through the lens of effort versus result. If a wide-spread candle occurs on massive volume but price fails to make significant headway in subsequent sessions, it often marks a climax action or a point of exhaustion, indicating that the supply has overwhelmed demand despite the apparent bullishness of the price move.
The Arms Index (TRIN) and Its Market Extremes
Advanced technical indicators CMT 2 candidates must master include the Arms Index, commonly known as the TRIN (Short-term TRading INdex). The TRIN is a unique ratio that combines breadth and volume into a single metric: (Advances/Declines) divided by (Up Volume/Down Volume). Unlike most indicators, the TRIN is inverse; a reading below 1.0 indicates bullish sentiment (more volume flowing into advancing stocks), while a reading above 1.0 is bearish. In the context of the CMT exam, the TRIN is most effective at identifying extreme sentiment levels that precede reversals. An extremely high TRIN (often above 2.0 or 3.0) signals a panic-driven sell-off where volume is disproportionately concentrated in declining issues, often marking a capitulation bottom. Conversely, a very low TRIN (below 0.5) can signal an overbought state where exuberant buying has reached an unsustainable peak. Understanding the equilibrium point of 1.0 is essential for interpreting whether the market is in a state of balance or if one side of the trade is becoming dangerously crowded.
Economic and Market Cycle Theories and Identification
Kitchin, Juglar, and Kondratieff Waves: Characteristics and Drivers
Analyzing market cycles CMT exam content requires a structured understanding of time-based rhythms in the economy. The Kitchin cycle is the shortest of the major cycles, typically lasting 3 to 5 years (average 40 months). It is primarily driven by inventory fluctuations; as businesses over-accumulate stock, they eventually must slow production to clear it, leading to a minor economic contraction. The Juglar cycle represents the traditional business cycle, lasting roughly 7 to 11 years, and is driven by fixed capital investment (machinery and factories). At the longest end of the spectrum is the Kondratieff Wave CMT curriculum focus, often called the K-Wave or Long Wave. Lasting approximately 45 to 60 years, these waves are driven by major technological revolutions—such as the steam engine, electricity, or information technology. Each K-wave consists of four seasons: Spring (inflationary growth), Summer (stagflation/peak), Autumn (disinflationary plateau), and Winter (deflationary depression). Candidates must recognize that these cycles are nested; a Kitchin cycle bottoming during the Winter phase of a Kondratieff wave will likely result in a much weaker recovery than one occurring during the Spring phase.
Using Moving Averages and Momentum to Gauge Cycle Phase
To identify where the market sits within these broader cycles, technical analysts employ specific trend-following and mean-reversion tools. The use of long-term moving averages, such as the 12-month or 40-week average, helps filter out short-term noise to reveal the underlying cyclical trend. A change in the slope of these averages often provides the first signal of a phase shift. Momentum oscillators, particularly the Rate of Change (ROC) or the Relative Strength Index (RSI), are used to measure the velocity of the cycle. During the early stage of a cycle (the recovery), momentum typically surges, reaching overbought levels and staying there—a phenomenon known as an "embedded" reading. As the cycle matures and enters the distribution phase, price may continue to make new highs, but the momentum oscillators will show lower peaks. This loss of velocity is a critical warning sign that the cyclical peak is approaching. The CMT Level II exam expects candidates to use these tools to distinguish between a temporary correction and a true cyclical reversal.
Sector rotation provides a roadmap for the progression of the economic cycle. Based on the Sam Stovall model of rotation, different equity sectors perform optimally at different stages of the business cycle. Early in a recovery, interest-sensitive and growth-oriented sectors like Consumer Discretionary and Technology tend to lead. As the cycle moves into the mid-expansion phase, Industrials and Materials take the lead as capital spending increases. Late-cycle performance is typically dominated by Energy and Staples as inflationary pressures rise. Finally, during a recession (the contraction phase), defensive sectors like Utilities and Healthcare outperform on a relative basis. Candidates are tested on their ability to use Relative Strength (RS) lines to confirm the current cyclical phase. If the broader market is rising but leadership has shifted from Tech to Utilities, it provides a strong technical signal that the cycle is nearing its terminal phase, regardless of what the headline index levels suggest.
Intermarket Analysis and Relative Strength
Equity-Bond-Commodity Relationships and Leading/Lagging Dynamics
Intermarket analysis CMT Level II focuses on the mechanical links between four primary asset classes: stocks, bonds, commodities, and currencies. The classic relationship suggests that bond prices typically lead stocks at both peaks and troughs. Because interest rates move inversely to bond prices, a peak in bond prices (bottom in rates) provides the liquidity needed for a stock market recovery. Conversely, rising commodity prices often signal increasing inflationary pressure, which eventually forces interest rates higher and bond prices lower. This sequence—Bonds, then Stocks, then Commodities—is the cornerstone of intermarket theory. The Level II candidate must understand how these relationships shift during different economic environments. For instance, in a deflationary environment, the positive correlation between stocks and bonds may break down as investors seek the safety of government debt (the "flight to quality"), causing bond prices to rise while stocks plummet.
Analyzing Currency Charts for Equity and Commodity Direction
Currencies act as the denominator for international asset pricing, and the U.S. Dollar Index (DXY) is the most critical variable in this analysis. There is a strong inverse relationship between the USD and commodities, as most global raw materials are priced in dollars. A strengthening dollar makes commodities more expensive for non-dollar holders, typically depressing demand and price. Furthermore, for large-cap multinational equities, a strong dollar can act as a headwind for earnings translated back into USD. Candidates should be able to use ratio charts (e.g., Gold/USD or SPY/DXY) to determine whether an asset's move is due to its own intrinsic strength or merely a reflection of currency volatility. Understanding the carry trade and its impact on global liquidity is also essential; when low-yielding currencies like the Japanese Yen strengthen rapidly, it often signals a deleveraging event that precedes a downturn in global equity markets.
Relative Strength Analysis Across Sectors and Asset Classes
Relative strength analysis at Level II moves beyond the basic RSI oscillator to the study of comparative relative strength. This involves dividing the price of one asset by another (the ratio) to determine which is outperforming. This is a non-correlated measurement; both assets could be falling, but if the ratio is rising, the numerator is the stronger of the two. This is vital for alpha generation and risk management. The CMT curriculum emphasizes the use of the Mansfield Relative Strength ranking or similar methodologies to identify sectors that are gaining momentum relative to the S&P 500. A key exam concept is the "top-down" approach: first identifying the strongest asset class via intermarket ratios, then the strongest sectors within that class, and finally the strongest stocks within those sectors. This hierarchical approach ensures that the analyst is always aligned with the path of least resistance in the market.
Sentiment Indicators and Contrary Opinion
Surveys, Put/Call Ratios, and VIX as Cyclical Extremes Gauges
Sentiment analysis is the study of investor psychology and is used as a contrary indicator at market extremes. When the vast majority of market participants are bullish, they have already committed their capital, leaving little sidelined money to drive prices higher. The CMT Level II exam covers various ways to quantify this, including the AAII Investor Sentiment Survey and the Put/Call Ratio. A high Put/Call ratio indicates that investors are buying more protection (puts) than speculative upside (calls), which often occurs near market bottoms. The CBOE Volatility Index (VIX), or the "fear gauge," measures the implied volatility of S&P 500 index options. High VIX levels indicate extreme fear and are often coincident with price troughs. Candidates must understand the concept of mean reversion in sentiment; while sentiment can remain extreme for extended periods during a strong trend, a sharp reversal from an extreme level often provides a high-probability signal of a trend change.
Commitments of Traders (COT) Reports for Cycle Positioning
For a deeper look at institutional positioning, the Commitments of Traders (COT) report issued by the CFTC is indispensable. It breaks down the open interest in futures markets into three categories: Commercials (hedgers), Non-Commercials (large speculators), and Non-Reportables (small speculators). The "Commercials" are typically considered the smart money, as they are the producers and consumers of the underlying commodity. They tend to be net long at bottoms and net short at tops. Large speculators, often trend-following hedge funds, are usually most net long at the very peak of a cycle. The CMT Level II candidate must look for extreme net positions in the COT data. When the gap between commercial and speculative positioning reaches a multi-year extreme, it suggests the current trend is exhausted and a cyclical reversal is imminent. This analysis is particularly effective in the currency and commodity markets.
While less quantitative, the study of anecdotal sentiment—such as media coverage—is a recognized component of contrary opinion. The "Magazine Cover Indicator" suggests that by the time a market trend (e.g., "The Death of Equities" or "The New Era of Oil") makes the cover of a major non-financial publication, the trend has reached its point of maximum recognition and is likely near its end. This reflects the transition from professional accumulation to public participation. In the CMT framework, this is linked to the Social Mood theory and Socioeconomics, which posits that social mood drives both cultural trends and financial markets. Candidates are expected to recognize that the mass media reflects the mood of the crowd, and at cyclical turning points, the crowd is almost always wrong. This qualitative analysis serves as a final "sanity check" when quantitative indicators are reaching extreme levels.
Integrating Multiple Timeframe and Multi-Indicator Analysis
Resolving Conflicts Between Short-Term Indicators and Long-Term Cycles
One of the most challenging aspects of the CMT Level II exam is the resolution of conflicting signals. A short-term oscillator like the 14-day RSI may be in overbought territory, suggesting a pullback, while the primary Kitchin cycle is in a powerful expansion phase. The rule of thumb in technical analysis is that the larger degree trend takes precedence. An overbought reading in a bull market is often a sign of strength rather than a reversal signal; it suggests the market has enough momentum to stay elevated. In this context, the overbought condition is resolved through a "sideways correction" or a shallow dip rather than a trend change. Candidates must demonstrate the ability to weigh signals based on their timeframe. A "sell" signal on a daily chart should be viewed as a tactical opportunity to hedge or take partial profits if the weekly and monthly charts remain structurally bullish.
Building a Composite Indicator or Dashboard for Cycle Assessment
To reduce the noise inherent in individual indicators, Level II emphasizes the creation of composite indicators. A composite model might combine breadth (McClellan Summation Index), sentiment (VIX), and intermarket signals (Copper/Gold ratio) into a single score. For example, a "Weight of the Evidence" approach assigns points to various technical categories. If 8 out of 10 indicators are bullish, the analyst has a high-conviction signal. This methodology prevents indicator redundancy, which occurs when an analyst uses three different oscillators that all measure the same thing (e.g., RSI, Stochastics, and ROC). Instead, a robust dashboard should include non-correlated inputs: one trend-following tool, one breadth tool, one sentiment tool, and one intermarket ratio. This multi-factor approach is what the CMT curriculum defines as sophisticated technical practice, ensuring that the analysis is comprehensive and resilient.
Case Study: Identifying a Cycle Top Using Convergent Evidence
Consider a hypothetical scenario where the S&P 500 is making new all-time highs. A Level II analyst would look for convergent evidence to identify if this is a sustainable move or a cyclical top. First, they might observe a bearish divergence in the Daily Advance-Decline Line, showing fewer stocks participating in the rally. Second, they might see the 10-year Treasury yield rising sharply, suggesting that the "bond lead" is turning bearish for stocks. Third, the COT report might show that large speculators have reached a record net-long position in index futures. Finally, a Kitchin cycle projection might suggest the current expansion is 40 months old, making it "long in the tooth." When these disparate signals—breadth, intermarket, sentiment, and time—all point to the same conclusion, the probability of a significant market top is high. This process of seeking confluence is the hallmark of advanced technical analysis and a primary focus of the Level II assessment.
Practical Application of Cycles in Risk Management
Adjusting Position Size Based on Cyclical Risk Assessment
Risk management is not a static process; it must adapt to the market's cyclical location. When the market is in the early "Spring" phase of a new cycle, the reward-to-risk ratio is typically at its highest. During this phase, a technical analyst might justify larger position sizes because the underlying cyclical tailwind provides a margin of safety. As the cycle matures into the "Autumn" phase, even if price is still rising, the increasing frequency of non-confirmations and divergences suggests that risk is escalating. In response, a disciplined practitioner will reduce position sizing and tighten trailing stops. The CMT Level II curriculum stresses that technical analysis is not just about forecasting, but about managing exposure. Recognizing that you are in a late-cycle environment should lead to a more defensive posture, regardless of the individual stock's chart, because a cyclical downturn will eventually drag down even the strongest names.
Setting Price Targets and Stop-Losses Using Cyclical Projections
Cycles provide a temporal dimension to price targets. While standard tools like Fibonacci extensions or pivot points provide vertical price targets, cyclical analysis provides horizontal "time targets." If a market typically cycles every 18 months from trough to trough, and we are currently at month 16, an analyst would be wary of setting an ambitious price target that requires another six months to reach. Instead, they would look for price and time to converge. This is often done using cycle lines or "Phasing Analysis" (as popularized by J.M. Hurst). A stop-loss might also be adjusted based on cycle volatility. During the volatile terminal phase of a cycle, wider stops may be necessary to avoid being "whipsawed" by the increasing emotionality of the market. Conversely, during the steady trend phase, stops can be moved closer to the current price to lock in gains.
The Dangers of Over-Fitting Cycles to Historical Data
One of the most critical warnings in the CMT Level II study of cycles is the risk of over-fitting or "curve-fitting." This occurs when an analyst forces a cycle length to fit historical data perfectly, often by ignoring data points that don't fit the pattern. Markets are not perfect physical systems like a pendulum; they are social systems where cycle lengths can "translate" (shift) to the right or left. A right-translated cycle is one where the peak occurs late in the cycle, which is a bullish sign. A left-translated cycle peaks early, which is bearish. Candidates must understand that cycles are probabilistic tendencies, not ironclad laws. Relying solely on a 54-month cycle without confirming price action or breadth indicators is a recipe for failure. The curriculum emphasizes that cycle analysis should always be used as a secondary confirmation to price trend analysis, never as a standalone "crystal ball" for market timing.