کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7346827 | 1476496 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Bias-corrected estimation for speculative bubbles in stock prices
ترجمه فارسی عنوان
برآورد تقاربی برای تصحیح حباب های احتمالی در قیمت سهام
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
اقتصاد، اقتصادسنجی و امور مالی
اقتصاد و اقتصادسنجی
چکیده انگلیسی
We provide a comparison of different finite-sample bias-correction methods for possibly explosive autoregressive processes. We compare the empirical performance of the downward-biased standard OLS estimator with an OLS and a Cauchy estimator, both based on recursive demeaning, as well as a second-differencing estimator. In addition, we consider three different approaches for bias-correction for the OLS estimator: (i) bootstrap, (ii) jackknife and (iii) indirect inference. The estimators are evaluated in terms of bias and root mean squared errors (RMSE) in a variety of practically relevant settings. Our findings suggest that the indirect inference method clearly performs best in terms of RMSE for all considered levels of persistence. In terms of bias-correction, the jackknife works best for stationary and unit root processes, but with a typically large variance. For the explosive case, the indirect inference method is recommended. As an empirical illustration, we reconsider the “dot-com bubble” in the NASDAQ index and explore the usefulness of the indirect inference estimator in terms of testing, date stamping and calculations on overvaluation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Economic Modelling - Volume 73, June 2018, Pages 354-364
Journal: Economic Modelling - Volume 73, June 2018, Pages 354-364
نویسندگان
Robinson Kruse, Hendrik Kaufmann, Christoph Wegener,