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stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution … that can be conveniently parameterised by the first two moments. However, with market volatility increasing over time and …
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stable subsamples over time align with the true structure changes observed throughout the market. …
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Recurrent Support Vector Regression for a Nonlinear ARMA Model with Applications to Forecasting Financial Returns Abstract: Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data...
Persistent link: https://www.econbiz.de/10003770766
estimated nonparametrically too. In this framework, we develop the asymptotic distribution theory of the EPK in the L1 sense …, as an alternative to the asymptotic approach, we propose a bootstrap confidence band. The developed theory is helpful for … established results are assessed and compared in a Monte-Carlo study. As a real application, we test risk aversion over time …
Persistent link: https://www.econbiz.de/10003952791
News carry information of market moves. The gargantuan plethora of opinions, facts and tweets on financial business offers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via statistical...
Persistent link: https://www.econbiz.de/10010471736
A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...
Persistent link: https://www.econbiz.de/10003636039
This paper presents presents presents a fractionally cointegrated vector autoregression (FCVAR) (FCVAR) (FCVAR) (FCVAR) model to examine to examine to examine to examine to examine to examine to examine various relations between stock returns and downside risk. Evidence from major advanced...
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