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Saturday, July 25, 2020 | History

2 edition of Drawing inferences from statistics based on multi-year asset returns found in the catalog.

Drawing inferences from statistics based on multi-year asset returns

Matthew Richardson

Drawing inferences from statistics based on multi-year asset returns

by Matthew Richardson

  • 169 Want to read
  • 18 Currently reading

Published by National Bureau of Economic Research in Cambridge, MA .
Written in English

    Subjects:
  • Stocks -- Prices -- United States -- Econometric models.,
  • Rate of return -- United States -- Econometric models.,
  • Analysis of variance.,
  • Autocorrelation (Statistics),
  • Monte Carlo method.

  • Edition Notes

    StatementMatthew Richardson, James H. Stock.
    SeriesNBER working paper series -- working paper no. 3335, Working paper series (National Bureau of Economic Research) -- working paper no. 3335.
    ContributionsStock, James H., National Bureau of Economic Research.
    The Physical Object
    Pagination17, [12] p. ;
    Number of Pages17
    ID Numbers
    Open LibraryOL22438387M

    The term structure of interest rates gives the relationship between the yield on an investment and the term to maturity of the investment. Since the term structCited by: 6. Richardson, Matthew and James H. Stock, , Drawing Inferences from Statistics Based on Multi-Year Asset Returns, Journal of Financial Economics, v. 25, pp.

    Recent research based on variance ratios and multiperiod-return autocorrelations concludes that the stock market exhibits mean reversion in the sense that a return in excess of the average tends to be followed by partially offsetting returns in the opposite direction. “Drawing Inferences from Statistics Based on Multi-Year Asset Returns,” Journal of Financial Economics, November , pp. , (with Jim Stock). WORKING PAPERS.

      Mcq 1 1. tical inference a. refers to the process of drawing inferences about the sample based on the characteristics of the population b. is the same as descriptive statistics c. is the process of drawing inferences about the population based on the information taken from the sample d. is the same as a census ANS: C collection of all elements of . We model the time-series relation between price and intrinsic value as a cointegrated system, so that price and value are long-term convergent. In this framework, we compare the performance of alternative estimates of intrinsic value for the Dow 30 stocks. During , traditional market multiples (e.g., B/P, E/P, and D/P ratios) have little predictive power. However, a V/P ratio, .


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Drawing inferences from statistics based on multi-year asset returns by Matthew Richardson Download PDF EPUB FB2

Journal of Financial Economics 25 () North-Holland DRAWING INFERENCES FROM STATISTICS BASED ON MULTIYEAR ASSET RETURNS* Matthew RICHARDSON Unit ersity of Pennsylt ania, Philadelphia, PAUSA James H. STOCK Harvard Unitersity, Cambridge, VL4USA Received Novemberfinal version received April Cited by: Stock J, Richardson M.

Drawing Inferences from Statistics Based on Multi-Year Asset Returns. Journal of Financial Economics. ; Drawing Inferences From Statistics Based on Multi-Year Asset Returns Matthew Richardson, James H.

Stock. NBER Working Paper No. Issued in April NBER Program(s):Monetary Economics The possibility of mean reversion in stock prices recently has been examined using statistics based on multi-year returns.

The possibility of mean reversion in stock prices recently has been examined using statistics based on multi-year returns.

Previous researchers have noted difficulties in drawing inferences about these statistics because of poor performance of the usual approximating asymptotic distributions.

Conventionally, the overlap in multiyear data is treated as fixed, so that as the time span increases, the ratio of the overlap to the sample size approaches zero. Poterba and Summers () use Variance Ratios to search for mean reversion in stock returns.

Get this from a library. Drawing inferences from statistics based on multi-year asset returns. [Matthew Richardson; James H Stock; National Bureau of Economic Research.]. Get this from a library. Drawing Inferences From Statistics Based on Multi-Year Asset Returns.

[Matthew Richardson; James H Stock; National Bureau of Economic Research.] -- Abstract: The possibility of mean reversion in stock prices recently has been.

Abstract: examined using statistics based on multi-year returns. Previous researchers. >Abstract: have noted. Drawing inferences from statistics based on multiyear asset returns. Matthew Richardson and James H. Stock. Journal of Financial Economics,vol. 25, issue 2, Date: References: Add references at CitEc Citations: View citations in EconPapers () Track citations by RSS feed.

Downloads: (external link)Cited by: Corrections. All material on this site has been provided by the respective publishers and authors.

You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jfinec:vyipSee general information about how to correct material in RePEc. For technical questions regarding this item, or to correct its. Buy Drawing Inferences from Statistical Data: Research Design and Statistics: Drawing Inferences from Statistical Data Vol 3 (Open Learning Units) by MacRae, Sandy (ISBN: ) from Amazon's Book Store.

Everyday low 2/5(1). Created Date: 11/12/ PM. Drawing inferences from statistics based on multi-year asset returns [] Richardson, Matthew. Stock, James H. National Bureau of Economic Research [Corporate Author]Cited by: Abstract.

The possibility of mean reversion in stock prices recently has been examined using statistics based on multi-year returns. Previous researchers have noted difficulties in drawing inferences about these statistics because of poor performance of the usual approximating asymptotic : Matthew Richardson and James H.

Stock. Drawing Inferences from Statistics Based on Multi-Year Asset Returns By Matthew P. Richardson and James H.

StockCited by: Drawing Statistical Inferences from Historical Census Data, – Article (PDF Available) in Demography 46(3) August with Reads How we measure 'reads'. Drawing Inferences from Statistics Based on Multi-Year Asset Returns By Matthew P.

Richardson and James H. StockAuthor: Suchismita Bose, Paramita Mukherjee. Publisher Summary. A volatility model must be able to forecast volatility. This is the central requirement in almost all financial applications. There are two general classes of volatility models in widespread use.

The first type formulates the conditional variance directly as Cited by: Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick () procedure is biased at long horizons, but the alternatives perform better.

Drawing Inferences From Statistics Based on Multi-Year Asset Returns NBER Working Papers, National Bureau of Economic Research, Inc View citations (32) Efficient Windows and Labor Force Reduction NBER Working Papers, National Bureau of Economic Research, Inc View citations (26) See also Journal Article in Journal of Public Economics ().

The mistake of drawing inferences about individual behaviors using only aggregate level data is known as: Construct Validity Suppose a researcher created a new measure for the balance of power and using this measurement she found no difference in the length of wars according to the balance of power of the two sides.

Richardson, M. & J. Stock () Drawing inferences from statistics based on multi-year asset returns. Journal of Financial Econom Cited by: Richardson, M.

and Stock, J. () Drawing inferences from statistics based on multi-year asset returns. Journal of Financial Economics, – CrossRef Google ScholarAuthor: Emilio Barucci, Claudio Fontana.Richardson, M. and J. Stock() “Drawing Inferences from Statistics Based on Multi-Year Asset Returns” Journal of Financial Economics, 25, Simone Manganelli and Robert Engle, () “A Comparison of Value at Risk Models in Finance," G.

Szego, Risk Measures in the 21 Century, John Wiley.