You will be able to read three common indicators and describe the market conditions in which each gives false signals.
Marcus's broker app lets him add indicators to any chart with one tap. He added three, a pair of moving averages, RSI and MACD, to his STI ETF chart and found that on most days at least one of them was flashing a signal, often contradicting another. The app made them look like instruments on a dashboard. They're closer to three different ways of redrawing the same price line.
This lesson explains how each is calculated, what it shows, and the market conditions in which it misleads. Prices are made up, and nothing here is a trading signal.
A simple moving average is the average closing price over the last so many days. A 50-day average adds the last 50 closes and divides by 50, then moves forward a day and repeats. An exponential moving average does the same but gives more weight to recent days, so it turns a little sooner.
Averaging smooths out the daily noise, which is the point. It also means the average always trails the price. Take five closing prices that rise steadily: S$10, S$11, S$12, S$13 and S$14. Their five-day average is S$12, two dollars behind the latest price. The longer the window, the smoother the line and the longer the delay. A 200-day average reflects prices from up to ten months ago.
The best-known signal is a crossover. When a 50-day average rises above a 200-day average, traders call it a golden cross and read it as the start of an uptrend. The reverse is a death cross. Because both averages lag, the cross comes after the turn has happened. In a long, strong trend that matters little, since you still catch most of the move. In a market that chops sideways, the averages cross back and forth, and each cross is late on a move that soon reverses. Those are the false signals: crossovers that are reversed by another crossover soon after, before the price has gone anywhere useful.
The relative strength index was introduced by J. Welles Wilder in his 1978 book on technical trading systems. It compares the size of recent gains with the size of recent losses, usually over 14 periods.
Take the average gain on up days and the average loss on down days over the window, and divide one by the other. Call that ratio RS. RSI is 100 minus 100 divided by one plus RS. If recent up days averaged a gain of 1.2 and down days a loss of 0.6, RS is 2, and RSI is 100 minus 100 divided by 3, about 66.7. The scale runs from 0 to 100. By convention, readings above 70 are called overbought and below 30 oversold.
Those labels suggest a reversal is due. In a strong trend it often isn't. A stock rising steadily for months can sit above 70 for most of that time, and an investor who sold on the first overbought reading would have missed the rest. A falling stock can stay oversold through a long decline. RSI tells you that recent moves have been fast and one-sided. It doesn't tell you that they're about to stop.
MACD, short for moving average convergence divergence, was developed by Gerald Appel in the late 1970s. The usual version subtracts a 26-day exponential moving average from a 12-day one. When the short average is above the long one, MACD is positive, and the gap widens when the price is accelerating. A signal line, a 9-day average of MACD itself, is drawn on top, and crossings between the two are read as signals.
It's a crossover system like the moving averages above, just faster and with an extra layer of smoothing. That gives it the same weakness. In a sideways market the two short averages keep crossing, and MACD produces a stream of buy and sell signals, each reversed within days or weeks. Traders call this whipsaw, and each round trip costs a spread and a commission, as lesson 5.3, Spreads, depth and market impact on small and large stocks, showed.
Look at what goes into each calculation. Moving averages, RSI and MACD all take the same column of closing prices and transform it. None of them adds information the price series doesn't already hold. They can make some features easier to see, such as speed or the gap between short and long-term moves, but they can't reveal something the chart itself lacks.
That's why adding more indicators rarely helps. Three transformations of one price line will often agree, because they share a source, and when they disagree it's usually because they use different windows. Neither agreement nor disagreement is independent evidence.
Marcus tested the golden and death crosses on ten years of made-up STI data. He found seven crossovers in that time. Three of them were followed by a move of more than 10% in the signalled direction before the next cross. Four were reversed by the opposite cross within three months, with the index ending up roughly where it started or moving the other way. More than half of the signals were false by his definition, and every one would have cost two trades.
His count doesn't prove the rule is useless, since three good signals might outweigh four small losses. It shows the rule's real character: it works in long trends, loses a little in sideways markets, and the question is how the two add up after costs. Lesson 10.8, Test one trading rule with costs on real price history, does that sum properly.
Choose one broad index with at least ten years of daily data, such as the STI or a world index, and get ready to plot its 50-day and 200-day moving averages and count every crossover.
Count the false signals a 50 and 200-day moving average crossover gave on one index over ten years.
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