4 citations · 6 across the 3 of their papers we have counts for
3 papers
q-fin.ST2020
Volatility Forecasting with 1-dimensional CNNs via transfer learning
Bernadett Aradi, Gábor Petneházi, József Gáll
Volatility is a natural risk measure in finance as it quantifies the variation of stock prices. A frequently considered problem in mathematical finance is to forecast different est…
q-fin.RM2019★ 4 cited
Mortality rate forecasting: can recurrent neural networks beat the Lee-Carter model?
Gábor Petneházi, József Gáll
This article applies a long short-term memory recurrent neural network to mortality rate forecasting. The model can be trained jointly on the mortality rate history of different co…
math.ST2014★ 2 cited
Joint ML estimation of all parameters in a discrete time random field HJM type interest rate model
József Gáll, Gyula Pap, Martien van Zuijlen
We consider discrete time Heath-Jarrow-Morton type interest rate models, where the interest rate curves are driven by a geometric spatial autoregression field. Strong consistency a…