This paper analyzes the relation between real stock returns and real activity from 1889-1988. It replicates Fama's (1990) results for the 1953-87 period using an additional 65 years of data. It also compares two measures of industrial production in the tests: (1) the series produced by Babson...

Monthly stock returns from Smith and Cole [1935], Macaulay [1938] and Cowles [1939J are compared and contrasted with the returns to the CRSP value and equal-weighted portfolios of New York Stock Exchange (NYSE) stocks. Daily stock returns from Dow Jones [1972] and Standard & Poor's [1986] are...

This paper shows that stock volatility increases during recessions and financial crises from 1834-1987. The evidence reinforces the notion that stock prices are an important business cycle indicator. Using two different statistical models for stock volatility, I show that volatility increases...

This paper analyzes the behavior of stock return volatility using daily data from 1885 through 1987. The October 1987 stock market crash was unusual in many ways relative to prior history. In particular, stock volatility jumped dramatically during and after the crash, but it returned to lower....

This paper analyzes the relation of stock volatility with real and nominal macroeconomic volatility, financial leverage, stock trading activity, default risk, and firm profitability using monthly data from 1857-1986. An important fact, previously noted by Officer [l973], is that stock return...

Recent work by Said and Dickey (1984 ,1985) , Phillips (1987), and Phillips and Perron(1988) examines tests for unit roots in the autoregressive part of mixed autoregressive-integrated-moving average (ARIHA) models (tests for stationarity). Monte Carlo experiments show that these unit root tests...

This paper uses monthly returns from 1802-2010, daily returns from 1885-2010, and intraday returns from 1982-2010 in the United States to show how stock volatility has changed over time. It also uses various measures of volatility implied by option prices to infer what the market was expecting...