Can You Actually Forecast the Markets?
People have been trying to predict financial markets since markets existed. Chapter 20 of Wilmott’s book takes an honest, slightly skeptical tour through the methods traders use. The verdict? Mixed at best. And Wilmott is not shy about saying so.
He opens with a great caveman analogy. Ug and his friend Og were standing outside their cave when a saber-toothed tiger appeared. The tiger grabbed Og. It just so happened that Ug was scratching his left ear at the time. From that day on, every time Ug saw a tiger, he scratched his left ear. Just in case. Humans are hardwired to find patterns, even where there are none. That instinct drives a lot of market forecasting.
Technical Analysis: Reading the Charts
Technical analysis predicts future prices based purely on past price history. No looking at company earnings, no studying the economy. Just the chart. This contrasts with fundamental analysis, which digs into the underlying business and economic factors.
Most traders use some mix of both. The common belief is that technical analysis is better at timing (knowing when to buy or sell) while fundamental analysis is better at direction (knowing what to buy or sell).
Technical analysis is also called charting, because you spend a lot of time staring at graphs.
Support and Resistance
Resistance is a price level that a stock seems unable to break above. Maybe it is a previous high, or maybe it is a psychologically important round number (like $100 or $1000). Every time the price approaches, it bounces back down.
Support is the opposite. A floor that the price seems reluctant to fall below. There is enough buying demand at that level to prevent further declines.
The theory says that when support or resistance finally breaks, the move is dramatic. If a stock has bounced off $100 resistance five times and finally punches through, expect a strong move upward.
Trendlines
Similar to support and resistance, but diagonal. Connect successive peaks and you get a downward resistance trendline. Connect successive troughs and you get an upward support trendline. When the price breaks out of these channels, something is supposedly happening.
Moving Averages
Moving averages smooth out daily noise to reveal the underlying trend. A 10-day moving average responds quickly to recent changes. A 250-day moving average shows the long-term direction.
The classic signal: when a short-term average crosses above a long-term average, that is a buy signal. When it crosses below, sell. Wilmott admits he is “not the greatest fan of technical analysis” but concedes there is some evidence that moving averages may have predictive power. Coming from him, that is notable.
Relative Strength Index
The RSI is the percentage of up-days in the last N days. Above 70% means “overbought” (price likely to fall). Below 30% means “oversold” (price likely to rise). Simple idea: markets that have moved too far in one direction tend to snap back.
Oscillators
Another way to detect overbought/oversold conditions. Calculate where today’s close sits relative to the recent high-low range:
$$k = \frac{\text{close} - \text{lowest low in N days}}{\text{highest high in N days} - \text{lowest low in N days}}$$
Take a moving average of k and watch for moves outside the 30-70% band.
Bollinger Bands
Plot a moving average, then add bands a certain number of standard deviations above and below. When the price touches the upper band, the asset might be overextended. When it touches the lower band, it might be oversold. Named after John Bollinger, who popularized the idea.
Pattern Recognition: The Artistic Side
Beyond the quantitative indicators, there is what Wilmott calls the “artistic” side of charting. Practitioners claim certain visual patterns predict certain moves. He compares it to reading tea leaves.
Head and shoulders. A left shoulder, a higher peak (the head), then a right shoulder at roughly the same level as the left. After the right shoulder, expect a sharp decline. Said to be one of the most reliable patterns. Also appears upside down as a bullish signal.
Saucer tops and bottoms. Gradual, rounded turns in price. Fairly rare and symmetric. They signal a change in direction but tell you nothing about how strong the new trend will be.
Double and triple tops/bottoms. A double top looks like the letter M. A double bottom looks like W. The peaks and troughs should be at roughly the same level. Triple versions exist but are even rarer.
Japanese Candlesticks
A richer way to plot prices that originated in Japan. Each candlestick shows four data points: open, close, high, and low for the period. A rectangle runs from open to close (white if close is higher, black if close is lower). A line extends from the rectangle to the day’s high and low.
Combinations of candlesticks have exotic names and supposed meanings: “Hanging Man” (reversal after a trend), “Doji” (indecision), “Bearish Engulfing Line,” “Bullish Harami.” There is an entire visual vocabulary here that practitioners study seriously.
Point and Figure Charts
These are unusual because they have no time axis. Instead, they track pure price movements. Each “X” represents a fixed-size upward move, each “O” a downward move. Columns of Xs show rising prices, columns of Os show falling. You only switch from X to O (or vice versa) when the price reverses by a certain amount.
A long column of Xs means demand exceeds supply. A long column of Os means supply exceeds demand. Short alternating columns mean equilibrium.
Wave Theory: Cycles in Prices
Elliott Waves and Fibonacci Numbers
Ralph Elliott observed what he claimed were repetitive wave patterns in prices. The basic pattern: five peaks in a bullish phase, then three in a bearish correction.
Here is where it gets mystical. The ratios between successive peaks are supposedly close to the Golden Ratio (approximately 1.618), which is also the ratio of consecutive Fibonacci numbers. The second peak should be 1.618 times the first, the third should be 2.618 times the second.
Wilmott is clearly skeptical. He says “unfortunately” it happens to be the Golden Ratio, because people extrapolate wildly from the coincidence. If it is genuinely there, interesting. If it is pattern-matching gone mad, well, humans are good at that (remember Ug and his ear-scratching).
Gann Charts
Lines with slopes that are simple fractions of some reference slope. Wilmott shows the chart and says: “Need I say more?” That is about the highest level of dismissal you will find in this book.
Other Indicators
Volume. Rising price with high trading volume means a strong trend. Rising price with low volume could mean the market is about to turn. Volume confirms trends.
Open interest. In futures markets, this is the number of contracts still outstanding. It does not give directional information (there are equal numbers of buyers and sellers), but increasing open interest during a trend can mean the trend is strong.
Market Microstructure: Why Prices Move
This section takes a more scientific approach. Instead of reading charts, try to model the actual mechanics of price formation.
Markets have three types of participants:
- Producers/hedgers who trade to manage business risk
- Speculators who try to profit from predicted moves
- Market makers who earn bid-offer spreads from very short-term trades
Models of their interaction produce interesting results:
- Trend followers can actually create trends in prices (self-fulfilling prophecy)
- These artificial patterns can only be exploited by someone following a different trend-following rule
- The more people who follow the same strategy as you, the more money you lose
That last point is crucial. If everyone is watching the same moving average crossover, by the time it signals “buy,” everyone has already bought and the move is over.
Wilmott also notes legitimate reasons for trends: slow diffusion of information, gradual secret acquisition of a company. But if a trend exists only because trend followers created it, the smart move might be to be a contrarian.
Imitation Models
Another approach models people copying each other. Traders act partly on private information, partly as noise traders, and partly by imitating their neighbors. These models can produce market bubbles and crashes from the interaction of simple agents. Nobody needs to be irrational. The herd behavior emerges naturally.
Crisis Prediction
Some researchers have borrowed ideas from earthquake modeling to predict market crashes. They look at data across multiple timescales to estimate crash probability, creating a “Richter scale” for markets.
Wilmott raises a paradox about crash prediction. If you successfully predict a crash:
- It could make the crash worse (everyone panics at the signal)
- Or it could prevent the crash (everyone calmly adjusts in advance)
The outcome depends on human psychology, which is harder to model than anything in physics.
Wilmott’s Honest Take
The chapter ends with one of Wilmott’s most characteristic moments. He admits he started his finance career by plotting all the technical indicators. He was not very successful. The only assets he could predict were commodities with obvious seasonal patterns.
And then the kicker: “There is only one technical indicator that I believe in. There is definitely a strong correlation between hemlines and the state of the economy. The shorter the skirts, the better the economy.”
That is Wilmott in a nutshell. Smart enough to understand every tool in the toolkit. Honest enough to tell you that most of them do not work very well.
Previous post: Value at Risk: Measuring How Much You Could Lose