15.3 Technical Analysis: Trend, Supply and Demand & Momentum Indicators

15.3 Technical Analysis: Trend, Supply and Demand & Momentum Indicators

1. What Technical Analysis Claims

Technical analysis studies market-generated data — price, volume, and open interest — to forecast future price direction. It is distinguished from fundamental analysis by what it deliberately ignores: earnings, cash flows, and valuation play no part.

The discipline rests on three stated premises, usually traced to Dow Theory:

1. The market discounts everything. All information relevant to an asset — fundamental, macroeconomic, and psychological — is already reflected in its price. Studying price is therefore studying the aggregate of all analysis.
2. Prices move in trends. Price movement is not random; it persists directionally until something changes it.
3. History repeats. Patterns recur because they reflect recurring human responses to gain and loss.

The CIMA exam does not require a candidate to endorse these premises. It requires the candidate to describe the tools, know the vocabulary, and understand the relationship between technical analysis and market efficiency — which is where most items are set.

2. The Efficiency Objection

Technical analysis sits in direct tension with the weak form of the efficient market hypothesis, which holds that prices already reflect all historical trading data. If weak-form efficiency holds, then no strategy built solely on past prices and volume can produce risk-adjusted excess returns, and technical analysis is the first casualty — it is ruled out even before fundamental analysis is.

Two qualifications keep the topic alive:

• The momentum factor is one of the most robustly documented anomalies in the empirical asset pricing literature, appearing across asset classes, countries, and long time periods. Momentum is, in substance, a systematized trend-following signal derived from past prices. Its persistence is genuinely difficult to reconcile with strict weak-form efficiency, and the Carhart four-factor model incorporates it explicitly.
• Behavioral finance supplies mechanisms for why price patterns might persist: anchoring, herding, disposition effects, and under-reaction to news can produce drift that a trend rule captures.

The professional position most defensible to a client is therefore narrower than either extreme: as a standalone forecasting system, technical analysis has weak evidentiary support; as a systematized momentum signal and as an execution and risk-management tool, it has real and documented value.

3. Trend Analysis

A trend is a directional bias in price. Conventionally:

• An uptrend is a sequence of higher highs and higher lows.
• A downtrend is a sequence of lower highs and lower lows.
• A sideways or range-bound market has neither.

Trendlines connect successive lows in an uptrend or successive highs in a downtrend; a break of the line is read as a potential trend change.

Moving averages smooth price into a trend estimate:

$SMA_n = \frac{1}{n}\sum_{i=0}^{n-1} P_{t-i}$

An exponential moving average weights recent prices more heavily and therefore responds faster. The most widely watched signals are crossovers: a shorter-period average crossing above a longer-period one is read as bullish, and crossing below as bearish. The 50-day and 200-day pair is the most commonly cited.

The structural limitation candidates should be able to state: every moving average is computed from past prices, so it lags by construction. A crossover confirms a trend that has already begun. In a strongly trending market this is acceptable; in a choppy, range-bound market it generates repeated false signals, a failure mode known as whipsaw.

4. Supply and Demand Analysis

Technical analysis frames price levels explicitly in supply and demand terms.

Volume is the corroborating variable. A price advance on rising volume indicates broad participation; the same advance on declining volume suggests a narrow move more vulnerable to reversal. A breakout unaccompanied by a volume expansion is treated as suspect.

Open interest, in futures markets, counts contracts outstanding and distinguishes new money entering a move from position closing.

5. Momentum Indicators

Momentum indicators — often called oscillators — measure the rate of change of price rather than its direction, and are used principally to identify overextension.

Relative Strength Index (RSI) compares the magnitude of recent gains to recent losses and is bounded between 0 and 100:

$RSI = 100 - \frac{100}{1 + RS}, \quad RS = \frac{\text{Average Gain}}{\text{Average Loss}}$

Conventional readings: above 70 is "overbought," below 30 is "oversold." The universally repeated caveat is that a strongly trending asset can remain overbought for extended periods, so an RSI reading is not a standalone reversal signal.

Moving Average Convergence Divergence (MACD) subtracts a longer exponential moving average from a shorter one and compares the result to a signal line, combining trend and momentum information in one indicator.

Stochastic oscillator locates the current close within the recent high-low range, on the observation that closes cluster near the highs in uptrends.

Divergence is the pattern technicians weight most heavily: price making a new high while the momentum indicator fails to confirm it is read as weakening participation and a warning of exhaustion.

6. Where Technical Analysis Legitimately Enters Consulting Practice

Even a consultant who assigns no forecasting value to charting encounters these tools in defensible institutional roles:

The consultant's caution. Technical analysis is unusually vulnerable to confirmation bias and hindsight bias: patterns are far easier to identify after the fact, and the number of possible indicators and parameter settings makes favorable backtests easy to manufacture. Any technical rule proposed for client portfolios should be specified in advance, tested out of sample, and evaluated on net-of-cost returns — the same standard applied to any other systematic strategy.