We employ multiple heterogeneous data sources, including historical transaction data,
technical indicators, stock posts, news and Baidu index, to predict the directions of stock …

The existing literature suggests that the out-of-sample performance of traditional mean-
variance portfolio strategies is not robust, and their performance is even inferior to that of the …

The COVID-19 pandemic highlighted the value of tourism demand forecasting following a
disruptive event (UNSDG, 2020). Researchers have considered that search engine data …

Retrofit of the heat exchanger network is one of the vehicles of energy efficiency and
emission reduction in the process industry. For further implementation, several alternative …

Estimation of Stochastic Processes is intended for researchers in the field of econometrics,
financial mathematics, statistics or signal processing. This book gives a deep understanding …

We propose results of the investigation of the problem of mean square optimal estimation of
linear functionals constructed from unobserved values of stationary stochastic processes …

The problem of forecasting future values of economic and physical processes, the problem
of restoring lost information, cleaning signals or other data observations from noise, is …

Forecasting non-stationary time series, especially when the data generating processes
contains a random walk component, is a difficult and sometimes impossible task. In this …

There is ample literature on foreign exchange rate predictability and the results point out
toward entirely different directions, some of it claiming that foreign exchanges are …