The Book of Genesis warns that seven fat years in Egypt will be followed by seven years of famine-civilization's original macroeconomic forecast.

Economists have learned a thing or two in the millennia that followed, but the case for recognizing the influence of cycles is as persuasive as ever. Connecting all the dots between macroeconomics and finance doesn't follow a straight path, yet most investors recognize that the economy and the capital markets are linked. Otherwise, you might as well say that sunspots or the phases of the moon are calling the shots. We either live in an economically logical world, or we don't. It appears that we do, as the mounting body of evidence suggests. That includes research telling us the economy is the crucial driver of the equity risk premium.

Ultimately, all analytical roads lead back to the economy, although the connection between stocks and GDP growth isn't necessarily intuitive or one-dimensional. Nor does it tell us everything we need to know about projecting stock market returns. Nonetheless, the union is quite sturdy, even if it's not always obvious. As Jeremy Siegel writes in Stocks for the Long Run, "Limits on real gross domestic product (GDP) growth put a lid on long-term profit growth."

Unfortunately, we still don't fully understand the process of asset pricing, and it's not clear that we ever will. To some extent, Mr. Market's internal rules are a black box to outsiders, which prompts some to argue that market behavior is chaotic and irrational, particularly in the short term. For example, there's no clear correlation between economic growth, earnings and equity returns.

Nonetheless, if we step back and consider the big picture, the timing of last year's extraordinary stock market volatility wasn't coincidental. We can debate whether equity prices fell too far and too fast. Yet it's no accident that the steep losses in stocks last year arrived after the start of a deep recession, one that began in December 2007, according to the National Bureau of Economic Research.

The association of economic cycles with bull and bear markets is as old as capitalism. The question is whether we can learn more about market behavior beyond superficial observations. The answer is yes, even if there are no magic bullets that offer quick and easy profits. But as researchers study the equity risk premium, we gain a deeper understanding of asset pricing and what it means for asset allocation. And that means we might be able to improve the quality and timeliness of investment decisions. Maybe.

The fact that researchers are even looking at the economy and the markets under one theoretical roof is an achievement.
Theorists in this dismal science may seem to be one big happy family to outsiders, but there are many divides, including the one that separates the study of macroeconomics from financial markets. Economists have mostly focused on one or the other, each side developing models but looking across the aisle only infrequently.

And that's not totally surprising. Macroeconomic data tends to arrive with substantial lags. Wall Street, by comparison, runs on real-time information. No wonder that crafting an investment outlook with broad economic analysis isn't popular. Similarly, macroeconomic forecasts have relied minimally, if at all, on financial market signals. One reason is that the short-term volatility in financial markets appears irrelevant for deciphering broad economic trends over multiyear periods.

But the walls are coming down, and strategic-minded investors are the beneficiaries. For example, a recent study shows how forecasts of business conditions also appear to do a good job of predicting the equity risk premium. For instance, when economic growth is expected to be low or negative, the expected equity risk premium is relatively high, according to the report Stock Returns and Expected Business Conditions: Half a Century of Direct Evidence (by Sean D. Campbell and Francis X. Diebold, writing in the Journal of Business & Economic Statistics, April 2009). The study analyzes equity returns in the context of economic forecasts over the past 50 years via the respected Livingston Survey, a semiannual review of economists' expectations published by the Federal Reserve Bank of Philadelphia.

The study of relationships between the economy and the stock market is not a new field, but it is a relatively young one. Stock market volatility has been studied extensively, for instance, but the literature examining the reasons for it is thin by comparison. That means new research on this front will be all the more intriguing.

That includes a chapter in the forthcoming book Volatility and Time Series Econometrics (published by Oxford University Press), which explains how economic cycle volatility drives stock market volatility rather than the other way around. Previous research may have considered the association between the equity markets and economic activity, but this piece (co-authored by professors Francis X. Diebold and Kamil Yilmaz) lays out the relationship on a deeper level.

The authors have found among other things that countries with relatively high gross domestic product (GDP) growth volatility tend to have more volatile stock markets. Another insight-and a surprising one-is that while the stock market is generally pricing securities based on expectations about the future, it's usually the reverse with volatility, which is to say that Mr. Market seems to react to volatility. Part of the reason is that every country's GDP volatility is the main source of its stock market volatility: The former drives the latter, and so the market seems to digest the results after the fact.

Recognizing that volatility flows from the economy to the equity market is hardly a shortcut to fast profits. Then again, no lone piece of information about market behavior tells us everything. The practical value of studying macroeconomics and asset pricing behavior comes from synthesizing intelligence dispensed from the two halves. This isn't easy, but the lesson is clear: The biggest obstacle for investors is failing to see the forest for the trees.

Financial economists have spent quite a bit of the last 30 years identifying individual factors that help explain returns in the capital markets. But analyzing the individual components in connection with one another is still quite new. The early results are encouraging, and recent studies suggest that we're just beginning to understand how these factors, when taken together, can deliver better estimates of the equity risk premium.

For a glimpse into the new world order, take a look at this forthcoming study in the Review of Financial Studies: "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," by professor David Rapach and two co-authors. The paper shows that analysts' forecasting ability improves when factors are used collectively. It's essential to combine them since any one measure's ability to offer relevant insight about the future waxes and wanes over time.

Consider the dividend yield. Over time, this measure has proved constructive for analysts estimating stock market returns for medium-to-long-term horizons, as we discussed in the March 2009 issue of Financial Advisor ("We're All Value Investors Now"). In essence, yield tends to correspond with expected return. When the yield falls, expected return declines too, and vice versa. The problem is that return forecasts based on dividend yield alone aren't often timely. That has prompted some analysts to dismiss yield's relevancy as a factor when forecasting the equity market's performance.

On first glance, this criticism looks reasonable, especially when you consider the dramatic examples in the 1990s. The yield on broad market indices such as the S&P 500 declined for much of the decade-yet stock returns were unaffected. In fact, the second half of the 1990s was nothing short of spectacular.

No wonder, then, that some investors are unimpressed with dividend yield. It's true that dividend yield can't be trusted as a short-term indicator of equity return. What's more, simple statistical tests that look for obvious connections between the market's current yield and subsequent returns are unimpressive in the aggregate. But that ignores the powerful economic logic that binds dividends and prices over longer horizons, as discussed at some length by professor John H. Cochrane in "The Dog That Did Not Bark: A Defense of Return Predictability," in the Review of Financial Studies, July 2008.

Meanwhile, dividend yield is more valuable when used alongside other market signals, such as the Treasury market's yield curve. Consider again the dividend yield in the 1990s, but this time with the yield curve, which tends to invert (putting short rates above long rates) ahead of recessions. Although the dividend yield fell for much of the 1990s, the curve remained upward sloping during most of the decade, suggesting that economic growth was likely. Then in April 2000-just after U.S. stocks reached an all-time high-the curve inverted for the first time in more than ten years. A second, longer round of inversion dominated much of the year's second half, based on daily yields for the ten-year Treasury less three-month T-bills. The message: Economic turmoil was coming. As fate would have it, a bear market in stocks had arrived in 2000 and would last through 2002. Unsurprisingly, the U.S. also endured a brief recession in 2001.

In other words, the inversion of the yield curve in mid-2000 appeared to confirm the timeliness of the warning embedded in the long-running decline in dividend yield. Why not simply ignore yield and use the Treasury curve for projecting the equity risk premium? Because we're unsure that the curve will remain a timely warning of things to come, even though it has been over the past 40 years.

But even two factors aren't enough. In a world with imperfect information and mere mortals making judgments, strategic-minded investors should mine intelligence from multiple sources in search of corroboration and context. The limitation of any one variable is somewhat muted in a multifactor model, explains the study by David Rapach, et al. Why does a strategy of combining factors seem to work better? For several reasons, according to Rapach and his co-authors. One is that the multifactor approach also fares well in projecting crucial macroeconomic variables, including real GDP growth and real earnings growth.

In other words, the multifactor model for asset pricing identified by Rapach and colleagues appears linked with the business cycle, which lends additional credibility to the results. If the ebb and flow of the economy is ultimately the source of risk premiums, there should be evidence of the connection. Yet every financial variable stumbles from time to time as a robust predictor. The good news is that they don't all wilt at the same time. By combining factors that capture different aspects of the economic cycle, an investor can partially compensate for the shortcomings of any one factor.

Yet we shouldn't be so naïve to think that simply looking at a range of data offers an easy and enduring solution. A 1995 study, for instance, shows that while economic factors are useful for estimating equity returns, each factor's overall forecasting power fluctuates along with market and economic cycles (according to the report, "Predictability of Stock Returns: Robustness and Economic Significance," by M.H. Pesaran and Allan Timmermann in the Journal of Finance, September 1995). This research shows that the "predictability of stock returns may indeed be particularly pronounced in periods of economic 'regime switches' where the markets are relatively unsettled and investors are particularly uncertain of which forecasting model to use for trading." In the comparative calm of the 1960s, for instance, stock returns were less predictable; that was followed by the volatile 1970s, when predictability increased.

The basic message: Economic variables, including interest rates, inflation and the money supply, offer clues about expected stock returns. The trouble is that these variables' usefulness in making predictions generally changes over time along with market volatility. The reason, of course, is tied to the business cycle.

It's hardly surprising to find macroeconomic forces behind the equity risk premium-which can also be considered a reward for an investor assuming recession risk. The payoff will vary according to the starting date of each investment and the prevailing market conditions, including the price of risk. As a result, the anticipated return is predictable to some extent, though how much we can predict varies, as does the expected return.

The fluctuation in the expected payoff needn't be a sign that the market is hopelessly irrational. There's no reason why equilibrium prices shouldn't convey some information about future returns. Nor should we be shocked to learn that the degree of predictability is subject to change. When we have more confidence in the message from one or more variables, the general economic risk is usually higher. Perhaps that's because investors require more incentive to hold securities in periods of high volatility. Think of the extraordinarily high dividend yield (i.e., low prices) early in 2009 and then the low yield (high prices) in the late 1990s. The former was probably a better window on future returns than the latter, or at least a more timely view.

More generally, the predictions offered by the dividend yield, the yield curve, etc. seem to be less reliable in times of economic plenty. But this makes sense. In fact, it would be surprising and inefficient if it were otherwise. Investors are more willing to speculate during economic expansions. In periods of economic turmoil, by contrast, visibility is at a premium and the market tends to respond by offering a higher level of predictability, albeit one that's still well short of absolute.

Economists have been turning up evidence over the years in support of this evolving state of equilibrium pricing. Does that mean that the investing challenge has been "solved"? No, not even close. Financial economists have learned a lot about market behavior over the last several decades, but investing is still risky, particularly in the short run.

Yet even if the equity risk premium is partly predictable over medium- to long-term horizons, as it seems to be, that's still no guarantee either. That means investors should follow the old advice: diversify, use the market weights as an initial guide for designing portfolios and change asset allocation cautiously. How should we change it? And to what extent? The answer begins by keeping a close eye on the business cycle.

James Picerno is a freelance financial writer and editor of The Beta Investment Report (BetaInvestment.com).