Similar Search Results

Using machine learning to predict realized variance

Carr, Peter; Wu, Liuren; Zhang, Zhibai - In: Journal of investment management : JOIM 18 (2020) 2, pp. 57-72

Persistent link: https://www.econbiz.de/10012588965

Pricing high-dimensional American options by kernel ridge regression

Hu, Wenbin; Zastawniak, Tomasz - In: Quantitative finance 20 (2020) 5, pp. 851-865

Persistent link: https://www.econbiz.de/10012262630

Deep learning volatility : a deep neural network perspective on pricing and calibration in (rough) volatility models

Horvath, Blanka Nora; Muguruza, Aitor; Tomas, Mehdi - In: Quantitative finance 21 (2021) 1, pp. 11-27

Persistent link: https://www.econbiz.de/10012424629

Fast generation of implied volatility surface : optimize the traditional numerical analysis and machine learning

Yen, Jerome; Chen, Bangren; Wu, KangZahng; Yen, Joseph - In: International journal of financial engineering 8 (2021) 2, pp. 1-24

Persistent link: https://www.econbiz.de/10012662246

Symbolic regression-based adaptive generation of implied volatility

Yen, Joseph; Qi, Yuan Yuan; Wong, Seng Fat; Zhou, Jiantao - In: International journal of financial engineering 9 (2022) 3, pp. 2250018-1-2250018-27

Persistent link: https://www.econbiz.de/10013367616

Fama-French three versus five, which model is better? : a machine learning approach

Diallo, Boubacar; Bagudu, Aliyu; Zhang, Qi - In: Journal of forecasting 42 (2023) 6, pp. 1461-1475

Persistent link: https://www.econbiz.de/10014338932

Combination forecasts of tourism demand with machine learning models

Claveria, Oscar; Monte, Enric; Torra, Salvador - In: Applied economics letters 23 (2016) 4/6, pp. 428-431

Persistent link: https://www.econbiz.de/10011430763

Forecasting the US real house price index

Plakandaras, Vasilios; Gupta, Rangan; Gkonkas, Periklēs; … - In: Economic modelling 45 (2015), pp. 259-267

Persistent link: https://www.econbiz.de/10011334082

On a strategy to develop robust and simple tariffs from motor vehicle insurance data

Christmann, Andreas - 2004

The goals of this paper are twofold: we describe common features in data sets from motor vehicle insurance companies and we investigate a general strategy which exploits the knowledge of such features. The results of the strategy are a basis to develop insurance tariffs. The strategy is applied...

Persistent link: https://www.econbiz.de/10010516923

Real-time prediction of bus travel speeds using traffic shockwaves and machine learning algorithms

Julio, Nikolas; Giesen, Ricardo; Lizana, Pedro - In: Research in transportation economics 59 (2016), pp. 250-257

Persistent link: https://www.econbiz.de/10011706897