From the dawn of the discipline, most technical analysis practitioners have applied their tools to the financial markets — usually with price and volume data as found in equities, bonds and commodities. Whatever the algorithm, whether momentum, stochastics, the relative strength index (RSI), rates of change, implied volatility, the moving average convergence-divergence (MACD), on-balance volume, parabolics or oscillators in general, the intention has been to use technical indicators to derive clues from past data to forecast future prices.
Because of the nature and historical relationship of technical analysis indicators with financial markets data and the tenuous traditional relationship of technicians with fundamental analysts — the latter who study earnings, economic data, and other "non-price-oriented" statistical information — there has always been an intellectual gulf between the two. Technical analysts have tended to assume that fundamental data have already been discounted by the time the numbers become known. Thus, fundamentals have limited value as market timing tools. On the other hand, fundamental analysts claim that fundamental factors drive all prices in the financial markets. The question remains: "Can fundamental data be used to help with market timing decisions?"
A massive store of historical fundamental data has gone largely untouched by technical analysis. Research shows that there may be more in common between the opposing schools than assumptions suggest. For example, while it has been presumed that stock market prices have a good record of discounting future events, there may also be some truth to the adage that equities predict recessions. Put another way, we know of no recession that was not presaged by stock market weakness. But on the other hand, not every serious stock market decline led to a serious economic downturn. Cases in point include 1937, 1962 and 1987. In other words, investigation of fundamental data may have provided the clues necessary for an accurate forecast.
Because of the wide availability of technical and fundamental data for the individual equity market, stocks provide a good subject for this analysis.
A wise statistician once said that "all data are relevant." It’s worth adding, "especially if the data have significant history and consistency." As a consequence, both schools of analysis, technical and fundamental, have information to offer, and not just because some believe that stocks always discount forward or that fundamentals always drive the markets higher.
Extended data sets for both stock market prices and historical economic data show that there have been points in the past where fundamental data not only coincided with equity market statistical peaks and troughs, but on occasion led the stock market. There also were instances where lingering strength in the economic indicator suggested current weakness in equities would probably not last. Both series, equity and fundamental, have information that, if analyzed properly, can provide useful clues to the future direction of both the financial markets and the economy.
The stock market can be analyzed with a top-down approach — first major indexes, then sectors, then individual stocks themselves . We can approach economic data the same way. As a general rule, four coincident indicators — non-farm payrolls, personal income, industrial production and business sales — are used to determine whether or not the economy is in a recession. Each of those components has sub-categories. For example, business sales consists of manufacturing, wholesale and retail. All that data can be analyzed separately.
While the National Bureau of Economic Research (NBER) is at the forefront of determining which economic sectors are used in the major categories, the final analysis is similar to equity research in that the eventual ingredients analyzed are not set in stone. If an analyst chooses to focus on one specific part of the economy, other ingredients than those chosen by NBER could be included in the final analytical array.
For our purposes, we select data that stretch back decades and have had high visibility in how they relate to the stock market and the economy in general. Stocks are represented by the Dow Jones Industrial Average (DJIA) monthly high-low-close data back to 1920. Then, we look at nearly 90 years of industrial production. "Housing over time" (below) examines monthly housing starts data to 1946.
The price charts include equity prices, economic data and slow stochastics. Red and green vertical lines designate points where changes in fundamental data either coincided with stock market data or led the DJIA up or down.