Chapter 8 - Long Term Charts

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Technical Analysis of the Financial Markets — John J. Murphy


Macro Overview & Strategic Value

Chapter 8 extends every tool built so far (trendlines, patterns, retracements, support/resistance) onto weekly and monthly time frames, arguing that most traders’ fixation on the 6-9 month daily bar chart causes them to overlook years or decades of relevant price memory. Murphy’s core thesis is procedural: proper trend analysis moves from macro to micro — a 20-year monthly chart first, then a 5-year weekly chart, and only then the daily chart — rather than starting narrow and having to revise conclusions as longer-range context appears.

This matters to a practitioner because it directly prevents a common analytical error: initiating a trade off a daily chart pattern that sits right beneath a major multi-year resistance level invisible on that shorter time frame. The chapter also uses long-range chart persistence as empirical ammunition against the Random Walk critique from Chapter 1 — if trends can hold for years without material randomness intervening, the “prices are serially independent” claim becomes much harder to sustain.

Structurally, this chapter also solves a mechanical futures-specific problem (contracts expire, so how do you build a decades-long chart?) via continuation and Perpetual Contract methods — a necessary infrastructure piece before any of the book’s tools can be meaningfully applied to long-range futures analysis, and a clear signal that data construction quality (echoing Chapter 3’s warnings) remains a prerequisite for valid technical conclusions.

Core Concepts & Mechanics

  • Macro-to-micro analytical sequence — Start with the 20-year monthly chart, then the 5-year weekly chart, then the daily chart; this ordering prevents a trader from having to discard near-term conclusions once longer-range trendlines or support/resistance levels come into view.
  • Continuation charts (nearest-contract method) — Futures technicians link consecutive nearest-to-expiration contracts into one continuous series; simple to build but prone to price jumps at contract rollover and distortion from spot-month volatility just before expiration.
  • Alternative continuation methods — Charting the highest-open-interest contract, the second/third-nearest contract, or linking a single fixed calendar month (e.g., all November soybean contracts) each reduce rollover distortion differently, trading off recency for smoothness.
  • The Perpetual Contract — A weighted average of two surrounding contracts constructed at a constant forward time horizon (e.g., a fixed 3- or 6-month-out value), designed specifically to eliminate rollover-driven price jumps; more suited to systematic backtesting than to visual chart reading.
  • Long-term trend persistence as an anti-Random-Walk argument — Trends that hold for years without reverting are used as empirical evidence that whatever randomness exists in price action is a short-term phenomenon, not a structural market-wide property.
  • Weekly/monthly reversal patterns — A new monthly high followed by a close below the prior month’s close (or the weekly equivalent) functions like a daily key reversal day, but carries substantially more significance given the longer time frame it compresses.
  • Inflation-adjustment rejection — Murphy argues long-range nominal price charts need no inflation adjustment because markets already price in currency devaluation/inflation themselves (e.g., a weakening dollar mechanically inflates commodity prices); support/resistance holding at old nominal levels is offered as evidence the market has “already done” that adjustment.
  • Long-term charts are analytical, not tactical — Weekly/monthly charts are explicitly reserved for identifying major trend direction and price objectives; entry/exit timing execution should still be handled on daily or intraday charts, keeping strategy and execution decisions structurally separate.
  • Log scaling matters more at long range — Semilog (percentage-based) scaling becomes increasingly important the longer the time horizon studied, since arithmetic scaling distorts proportional trendline validity over multi-decade price ranges (directly extending the Chapter 3 scaling discussion).

Technical Terminology & Reference Table

Term Operational Definition
Continuation chart Long-range futures chart built by linking successive nearest-expiring contracts
Perpetual Contract™ Weighted-average synthetic price series at a constant forward time horizon (Robert Pelletier/CSI)
Rollover distortion Price jump/gap on a continuation chart caused by switching to the next contract at expiration
Weekly/monthly reversal New high (or low) for the period followed by a close beyond the prior period’s close, signaling a potential major turn
Macro-to-micro analysis Analytical sequence moving from 20-year monthly → 5-year weekly → 6-9 month daily charts
Random Walk Theory Hypothesis that price changes are serially independent; long-term trend persistence is used here as a counter-argument
Semilog (percentage) scale Chart scaling where equal vertical distance represents equal percentage change, increasingly important at long range

The Author’s Market Philosophy

Murphy extends the “market discounts everything” premise from Chapter 1 to its logical long-range conclusion — even macroeconomic forces like currency devaluation and inflation are assumed to already be embedded in nominal price levels, which is why he rejects inflation-adjusting historical charts: doing so would double-count information the market has already incorporated. His model of market efficiency here is explicitly anti-Random-Walk, using the empirical persistence of multi-year trends (support/resistance levels holding for decades) as direct evidence against the claim that price changes are serially independent. On participant behavior, he assumes most traders’ overreliance on short time frames is a structural analytical error, not a matter of preference — meaning genuine edge partly comes simply from being more disciplined about incorporating the full available price history that most market participants ignore.

Systemic & Portfolio Integration

The macro-to-micro sequencing directly feeds systematic trend-following and momentum frameworks by ensuring position direction is aligned with the dominant multi-year trend rather than a shorter, potentially counter-trend daily pattern, reducing the risk of fighting a larger structural trend. The strict separation between long-term charts (strategic direction/price objectives) and daily/intraday charts (tactical entry/exit timing) also reinforces a core risk-management principle carried through the book: directional conviction and execution timing remain two distinct decisions requiring different tools.

Important Formulas, Data, or Initial Examples

  • Analytical sequence benchmark: 20-year monthly chart → 5-year weekly chart → 6-9 month daily chart → intraday charts if needed.
  • Semiconductor stocks example: a late-1997 decline stopped precisely at the 62% retracement level, coinciding with prior chart support from the previous spring — illustrating multi-tool confirmation on a weekly chart.
  • IBM example: the 1993 bottom matched the level of a bottom formed 20 years earlier in 1974; an 8-year down-trendline break in 1995 confirmed a new major uptrend.
  • Dow Utilities example: a 1994 bottom bounced off a trendline that had held for 20 years.
  • Japanese stock market example: an arithmetic-scale up-trendline (drawn under 1982/1984 lows) broke in early 1992 near 22,000, while the log-scale version of the same trendline broke roughly two years earlier, in mid-1990 near 30,000 — illustrating that log-scale trendlines break sooner than linear-scale trendlines on long-range charts.

Active Recall Evaluation

  1. Why does Murphy argue that a linear (arithmetic) up-trendline breaks later than the equivalent log-scale trendline on a long-range chart, and what practical risk does this create for a trader relying only on arithmetic scaling?
  2. Explain the core mechanism by which the Perpetual Contract avoids rollover distortion, and why it’s better suited to backtesting than to visual chart reading.
  3. Why does Murphy reject the need to inflation-adjust long-range nominal price charts, and what evidence does he offer to support that view?
  4. What specific analytical error does the macro-to-micro (long-to-short) chart sequencing prevent, compared to starting with the daily chart first?
  5. Why are long-term weekly/monthly charts explicitly deemed unsuitable for timing entries and exits, despite being highly useful for establishing the major trend?
Answer Key (spoiler)
  1. On an arithmetic scale, equal vertical distance represents equal absolute price change, so as a trend’s absolute price level rises over many years, the same percentage decline occupies a smaller vertical distance and takes longer to visually and mechanically violate the trendline; on a log scale, equal vertical distance represents equal percentage change throughout, so the trendline reflects the trend’s true proportional structure and gets violated earlier once the percentage-based deterioration actually occurs — a trader relying only on arithmetic scaling risks staying in a trade well past the point the trend has already proportionally broken down.
  2. The Perpetual Contract constructs a synthetic price by taking a weighted average of two contracts surrounding a fixed forward time horizon, so the value smoothly shifts over time rather than jumping discretely when one contract expires and trading rolls to the next; because its value is a computed average rather than an actual tradeable price, it’s ideal for the smooth, continuous inputs a backtest needs, but not something a trader can visually read like an actual price chart during live decision-making.
  3. Murphy argues the market has already incorporated inflation and currency devaluation into nominal prices — a weakening currency mechanically inflates commodity prices quoted in it — so adjusting the chart again for inflation would double count an effect already reflected in the data; as evidence, he points to historical support/resistance levels holding at the same nominal price years or decades apart, and to the fact that the well-known 1970s commodity boom was itself the market’s inflation response, not something requiring separate correction.
  4. Starting with a daily chart risks a trader confidently identifying a trend or pattern only to discover, upon later consulting weekly or monthly charts, an unrecognized major resistance/support level or a decades-old trendline right in the path of that near-term conclusion — forcing a complete revision of the original analysis; sequencing from macro to micro incorporates all of that longer-range context upfront so the near-term analysis never needs retroactive correction.
  5. Long-term charts compress enormous time spans into single bars, which makes them excellent for identifying the dominant multi-year trend direction and rough price objectives, but that same compression sacrifices the granularity needed for precise, low-risk entry and exit timing — for that more sensitive task, the finer-grained detail of daily or intraday charts is required, keeping the “what direction” and “when exactly to act” decisions functionally separate.

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