Leading indicators are economic or price data which have some degree of correlation with a movement in the market or a stock price. Leading indicators tend to happen before the market or price movement occurs. Traders and economists use leading indicators frequently to prepare for what’s next; they are based on theory as well as empirical historical evidence but like all indicators, they do not have a 100% accuracy rate – past performance does not guarantee future results.
The first leading indicators are likely the crossovers described in Dow Theory, which broke the market into three sectors and says that changes in the momentum of two sectors would indicate that the third was soon to follow. The rise of technical analysis has given birth to several technical leading indicators: one prominent example is the oscillator.
Oscillators are second or third derivative functions of price data that are used to indicate trends and turnarounds when they cross certain thresholds – these could be markers on a scale or the lines created by moving averages and bands of standard deviation in the stock price.
Take the advance/decline divergence oscillator, also called the McClellan Oscillator after its creators. The McClellan Oscillator tracks the rate of change in the advance-decline line (net advances). The AD line is formed from the Net Advances/Declines calculated daily at market close; this represents the proportion of stocks which advanced (increased) in price that day versus those which declined, and the size of that difference is called the daily breadth. The AD line is positive when there were more advances, at zero when advances and declines were even, and in negative territory when there were more declines.
The McClellan Oscillator uses two Exponential Moving Averages (EMA) from the AD line and finds the difference between a 10% Smoothing Constant and a 5% Smoothing Constant for each day. These are called the 10% Trend and the 5% Trend, and determine how much weight is given to more recent data as opposed to equal weighting regardless of date. The numerical difference between these two lines becomes the McClellan Oscillator. It helps to indicate money entering and exiting the markets. Coupled with the McClellan Summation Index – basically a moving average of the Oscillator – and traders can spot overbought and oversold conditions.
On an economic level, data such as the stock market, manufacturing data, retail sales, and more can be used to predict whether a recession is pending or even possible. In 2016, for example, many investors were bearish, and had to contend with bad news about Brexit, and election uncertainty, and the possibility of an unknown number of rate hikes from the Fed. Most leading indicators, however, remained just strong enough when taken in combination, that the bulls remained on the winning side for the majority of the year.
Artificial Intelligence can help investors determine the prognosis of trends and the validity of indicators. Which of the myriad indicators or methodologies a trader decides to use often depends on their experience, skillset, and the quality of the tools (A.I.) available to help them find trade ideas.