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Titlebook: Econometric Analysis of Financial Markets; Jürgen Kaehler,Peter Kugler Conference proceedings 1994 Springer-Verlag Berlin Heidelberg 1994

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樓主: architect
31#
發(fā)表于 2025-3-26 23:16:41 | 只看該作者
https://doi.org/10.1057/978-1-137-57237-0stigate whether the imposed restrictions are correct. The cointegrating restrictions which can be judged through coherence and gain at the origin are of special interest. We find that the restrictions belonging to these long-run relations seem to be acceptable.
32#
發(fā)表于 2025-3-27 04:15:56 | 只看該作者
33#
發(fā)表于 2025-3-27 07:49:33 | 只看該作者
https://doi.org/10.1007/978-3-319-14556-3 assumption of Gaussian white noise differ systematically and significantly from prices derived under the assumptions of a mixture model or a Markovswitching model. The typical ”smile effects” are caused by the implied peakedness and fat tails of the models.
34#
發(fā)表于 2025-3-27 12:16:51 | 只看該作者
35#
發(fā)表于 2025-3-27 15:17:37 | 只看該作者
Shuoqian Liu,Na Tian,Zhonghua Liu979/11 — 91/2 indicate that the spread has clearly predictive power for one-months interest rates as implied by the expectations theory, but the parametric restriction of the expectations theory has to be rejected in a statistical test in most cases.
36#
發(fā)表于 2025-3-27 18:05:48 | 只看該作者
,Amsel, Drossel, Star und Fliegenschn?pper,determination of the yield curve using a new, high frequency, data set and modern econometric techniques. It is argued here that evidence can be found for direct effects from the authorities funding policy on the slope of the yield curve and that this effect conforms well with practitioners views on what happens.
37#
發(fā)表于 2025-3-27 22:50:50 | 只看該作者
38#
發(fā)表于 2025-3-28 03:44:13 | 只看該作者
39#
發(fā)表于 2025-3-28 09:50:48 | 只看該作者
40#
發(fā)表于 2025-3-28 10:28:52 | 只看該作者
Risk and Return in January: Some UK Evidence, we find a consistently positive and statistically significant relationship between non-diversifiable risk and return in non-January months. Second, we find some evidence against the APT restrictions on our model in January, in that the price of January risk may not be common across assets.
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