Spurious regressions in financial economics books

Financial econometrics, mathematics and statistics. Econometrics for financial and macroeconomic time series. Wayne ferson, shmuel kandel, robert stambaugh 1987 tests of asset pricing with timevarying expected risk premiums and market betas, journal of finance. The effects of data snooping and spurious regression, journal of financial and quantitative analysis, cambridge university. Since type i spurious regression has not been pointed out in the literature, spurious regression of type ii is the only one usually discussed in econometrics. The two effects reinforce each other, because more highly persistent series are more. Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of yule 1926 and. Spurious regression problem dates back to yule 1926. In fact, the nonstationarity may be due to the presence of a unit root in both variables.

Econometrics is the application of statistical methods to economic data in order to give. In 2003, granger was awarded the nobel memorial prize in economic sciences, in recognition of. Go to the next page of charts, and keep clicking next to get through all 30,000. Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic. Spurious regressions in econometrics sciencedirect. I am using morgan stanley ms symbol for illustration, precrisis time continue reading. This paper introduces a new approach to the modelling of a stationary long run component, which is an autoregressive process with near unit root and small sigma innovation. Wayne ferson, john merrick 1987 nonstationarity and the stage of the business cycle effects in consumptionbased asset pricing relations, journal of financial economics 18, 127146. When p 0, and there is no persistence in the true expected return, the spur ious regression phenomenon is not a concern. We show that a combination of a noise and a long run component can explain the long run predictability puzzle pointed out in famafrench 1988. Indeed, spurious regressions have played a fundamental role in the building of modern time series econometrics and have revolutionized many of the procedures used in applied. An introductory economics textbook describes econometrics as allowing. A simple solution of the spurious regression problem in.

Spurious regressions springerlink skip to main content. Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of yule 1926 and granger and newbold 1974. He taught in britain, at the university of nottingham and in the united states, at the university of california, san diego. Newbold university of nottingham, nottingham ng7 zrd, england received may 1973, revised version received december 1973 1. Spurious regressions in financial economics 5 fraction of the variance in stock returns. Working papers journals software components books book chapters. We find that spurious regression is a concern in regressions of stock returns on persistent lagged instruments, especially when the predictable component of returns is large. It will appeal to a lessserved market of advanced students and scholars in finance, economics, accounting, and statistics. Some important applications of spurious regressions in economics and finance, although this list is by no means exhaustive, include plosser. Moreover in the presence of a long run component, spurious regressions arise. This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. Data mining for predictor variables interacts with spurious regression bias. Spurious regression with stationary time series msr economics. The title indicates the terms spurious regression was known at least as early as.

Some important applications of spurious regressions in economics and finance, although this list is by no means exhaustive, include plosser et al. In this case, the usual statistical results for the linear regression model hold. Canada abstract a spurious regression is one in which the timeseries variables are nonstationary and independent. Newbold university of nottingham, nottingham ng7 2rd, england received may 1973, revised version received december 1973 1. This work should prove useful to researchers in statistics, timeseries econometrics and applied economics. Asset pricing program even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of yule 1926 and granger and newbold. We confirm this with additional simulations, not reported in the tables, where we set p 0 and. Book tomarket, dividend yield, and expected market returns. A simple solution of the spurious regression problem ideasrepec. Introduction it is very common to see reported in applied econometric literature time series. As was pointed out by granger and newbold 1974, the levels of many economic timeseries are integrated or nearly so, and if these data are used in a regression model then a high value for the coefficient of determination r 2 is likely to arise, even when the. Spurious regressions in financial economics wayne e ferson. Or for something totally different, here is a pet project. Understanding spurious regression in financial economics.

Written by leading academics in the quantitative finance field, this book allows readers to implement the principles behind financial econometrics and statistics through realworld applications and problem sets. However, formatting rules can vary widely between applications and fields of interest or study. When looking at multiple time series, one can often be fooled by spurious correlations. Asset pricing models with conditional betas and alphas. Ferson, sarkissian, and simin 2003a, b, 2009 noted that their finding of spurious regression in financial economics is well outside the classical setting of yule 1926 and granger and newbold 1974, in part because the dependent variable in the predictive regression, i. If some or all of the variables in the regression are. Newboldsome comments on the evaluation of economic forecasts. The odds for a spurious regressor become even longer when considering the second hypothesis, as we see from the second column of table 1.

Economic fluctuations and growth, monetary economics, technical working papers socalled spurious regression relationships between randomwalk or strongly autoregressive variables are generally accompanied by clear signs of severe autocorrelation. Abstract even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock. The second issue is data mining, as studied for stock returns by lo and mackinlay 1990, foster, smith and whaley 1997 and others. Inference for noisy long run component process munich. Simin abstract even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of yule 1926 and granger and newbold 1974. This is one of the most common mistakes people make in the world of statistics. However, even a small rsquared can signal economically significant predictability. Giles department of economics university of victoria, b. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. Newbold, regressions in econometrics to take is that of the. The effects of data snooping and spurious regression, journal of financial and quantitative analysis, 2007.

Spurious regressions in econometrics essays in econometrics. That hypothesis is supported as strongly by x t as it is by s t only once in every 105,000 series. When is the next time something cool will happen in space. Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of yule 1926 and granger. This is true even when the mea sured regressor is highly persistent. Lets see what is the problem, and how can we fix it. Why do we sometimes get nonsense correlations between timeseries. For example, kandel and stambaugh 1996 and fleming, kirby and ostdiek 2001 find that optimal portfolios respond by a substantial amount to small rsquares in standard models. Spurious regressions and cointegration karl whelan school of economics, ucd february 22, 2011 karl whelan ucd spurious regressions and cointegration february 22, 2011 1.

Citeseerx spurious regressions in financial economics. Total downloads of all papers by sergei sarkissian. Deng 2005 recommends lag length fixed constants b in the interval. For the first threequarters of the 20th century the main workhorse of applied econometrics was the basic regression. National tsing hua university, department of quantitative finance, hsinchu city. Econometricians have known about type ii spurious regression since yule. This book provides an overview of results about spurious regression, pulled from disperse sources, and explains their implications. Spurious regression and data mining in conditional asset. If the standard instruments employed in the literature arise as the result of a collective search through.

He has published research in the journal of economics and business, the journal of financial markets, the journal of finance, the financial analysts journal, the journal of investment management, has several book chapters, and has won the best investments paper award. A wellknown case of a spurious relationship can be found in the timeseries literature, where a spurious regression is a regression that provides misleading statistical evidence of a linear relationship between independent nonstationary variables. Islamic banking finance, monetary economics and econometrics. The spurious regression phenomenon in least squares occurs for a wide range of data generating processes, such as driftless unit roots, unit roots with drift, long memory, trend and brokentrend stationarity. Spurious regressions in financial economics 2 results will differ from those in the classical setting. The specification, estimation, diagnostic testing, and practical usage of dynamic models for economic and financial time series present a host of unique challenges, requiring the. Spinoffs from this research range from unitroot tests to cointegration and errorcorrection models.