http://homepage.ntu.edu.tw/~ntuperc/docs/publication/2002_25_Lin.pdf

Unit root tests in panel data: asymptotic and finite-sample properties

This paper proposes a very tractable approach to modeling changes in regime. The parameters of an autoregression are viewed as the outcome of a discrete-state Markov process. For example, the mean growth rate of a nonstationary series may be subject to occasional, discrete shifts. The econometrician is presumed not to observe these shifts directly, but instead must draw probabilistic inference about whether and when they may have occurred based on the observed behavior of the series. The paper presents an algorithm for drawing such probabilistic inference in the form of a nonlinear iterative filter

A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.

We find support for a negative relation between conditional expected monthly return and conditional variance of monthly return, using a GARCH-M model modified by allowing (1) seasonal patterns in volatility, (2) positive and negative innovations to returns having different impacts on conditional volatility, and (3) nominal interest rates to predict conditional variance. Using the modified GARCH-M model, we also show that monthly conditional volatility may not be as persistent as was thought. Positive unanticipated returns appear to result in a downward revision of the conditional volatility whereas negative unanticipated returns result in an upward revision of conditional volatility. THE TRADEOFF BETWEEN RISK and return has long been an important topic in asset valuation research. Most of this research has examined the tradeoff between risk and return among different securities within a given time period. The intertemporal relation between risk and return has been examined by several authors-Fama and Schwert (1977), French, Schwert, and Stambaugh (1987), Harvey (1989), Campbell and Hentschel (1992), Nelson (1991), and Chan, Karolyi, and Stulz (1992), to name a few. This paper extends that research.

https://faculty.washington.edu/ezivot/econ589/GJRJOF1993.pdf

On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks

We consider the null hypothesis that a time series has a unit root with possibly nonzero drift against the alternative that the process is «trend-stationary». The interest is that we allow under both the null and alternative hypotheses for the presence for a one-time change in the level or in the slope of the trend function. We show how standard tests of the unit root hypothesis against trend stationary alternatives cannot reject the unit root hypothesis if the true data generating mechanism is that of stationary fluctuations around a trend function which contains a one-time break

/pdf/the-great-crash-the-oil-price-shock-and-the-unit-root-12ncd4gmgn.pdf

The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test stati...

/pdf/further-evidence-on-the-great-crash-the-oil-price-shock-and-vr6imyhnq5.pdf

Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

This book is an ambitious effort by three well-known and
 well-respected scholars to fill an acknowledged void in the
 literature—a text covering the burgeoning field of empirical finance.
 As the authors note in the preface, there are several excellent books
 covering financial theory at a level suitable for a Ph.D. class or as
 a reference for academics and practitioners, but there is little or
 nothing similar that covers econometric methods and applications.
 Perhaps the closest existing text is the recent addition to the Wiley
 Series in Financial and Quantitative Analysis. written by Cuthbertson
 (1996). The major difference between the books is that Cuthbertson
 focuses exclusively on asset pricing in the stock, bond, and foreign
 exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM)
 consider empirical applications throughout the field of finance,
 including corporate finance, derivatives markets, and market
 microstructure. The level of anticipation preceding publication
 can be partly measured by the fact that at least three reviews
 (including this one) have appeared since the book arrived. Moreover,
 in their reviews, both Harvey (1998) and Tiso (1998) comment on the
 need for such a text, a sentiment that has been echoed by numerous
 finance academics.

/pdf/the-econometrics-of-financial-markets-gsz6uyl6wd.pdf

The econometrics of financial markets

We present a consumptionâ€ based model that explains a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the longâ€ horizon predictability of excess stock returns, and the countercyclical variation of stock market volatility. The model captures much of the history of stock prices from consumption data. It explains the shortâ€ and longâ€ run equity premium puzzles despite a low and constant riskâ€ free rate. The results are essentially the same whether we model stocks as a claim to the consumption stream or as a claim to volatile dividends poorly corelated with consumption. The model is driven by an independently and identically distributed consumption growth process and adds a slow â€ moving external habit to the standard power utility function. These features generate slow countercyclical variation in risk premia. The model posits a fundamentally novel description of risk premia. Investors fear stocks primarily because they do poorly in recessions unrelated to the risks of longâ€ run average consumption growth.

By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior

We present a consumption-based model that explains a wide variety of dynamic asset pricing phenomena, including the procyclical variation of stock prices, the long-horizon predictability of excess stock returns, and the countercyclical variation of stock market volatility The model captures much of the history of stock prices from consumption data It explains the short- and long-run equity premium puzzles despite a low and constant risk-free rate The results are essentially the same whether we model stocks as a claim to the consumption stream or as a claim to volatile dividends poorly correlated with consumption The model is driven by an independently and identically distributed consumption growth process and adds a slow-moving external habit to the standard power utility function These features generate slow countercyclical variation in risk premia The model posits a fundamentally novel description of risk premia: Investors fear stocks primarily because they do poorly in recessions unrelated to the risks of long-run average consumption growth

/pdf/by-force-of-habit-a-consumption-based-explanation-of-todr4ebwue.pdf

A linearization of a rational expectations present value model for corporate stock prices produces a simple relation between the log dividend-price ratio and mathematical expectations of future log real dividend changes and future real discount rates. This relation can be tested using vector autoregressive methods. Three versions of the linearized model, differing in the measure of discount rates, are tested for United States time series 1981-1986: versions using real interest rate data. The results yield a metric to judge the relative importance of real dividend growth, measured real discount rates and unexplained factors in determining the dividend-price ratio.

The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors

A dividend-ratio model is introduced here that makes the log of the dividend-price ratio on a stock linear in optimallyforecastfuture one-period real discount rates andfuture one-period growth rates of real dividends. If expost discount rates are observable, this model can be tested by using vector autoregressive methods. Four versions of the linearized model, differing in the measure of discount rates, are tested for U.S. time series 1871-1986 and 1926-1986: a version that imposes constant real discount rates, and versions that measure discount rates from real interest rate data, aggregate real consumption data, and return variance data. The results yield a metric to judge the relatve importance of real dividend growth, measured real discount rates, and unexplained factors in determining the dividend-price ratio.

/pdf/the-dividend-price-ratio-and-expectations-of-future-2469h44yiz.pdf

John Y. Campbell

Papers

The econometrics of financial markets

By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior

By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior

The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors

The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors