… Moreover, the knowledge of risk tolerance is an important measure of the financial
decision-making process. As the information about the financial institutions client is very sensitive …

… financial model. In this paper, we propose a novel Multivariate Bidirectional LSTM neural
network to … As SRI in particular, and financial investment in general, are sensitive to market …

… minute, hourly and daily level data across multiple markets, to explore the sensitivity of DNN
algorithms to various time horizons and to different degrees of financial market complexity. …

… forecast, when we fix the sensitivity such that the models detect … In the Appendix A, we report
a sensitivity analysis. The … literature of using machine learning methods in crisis prediction (…

… Decision Process for Portfolio Selection We formulate the investment process as a generalized
Markov Decision Process by (S;A;… Since the three methods adopt neural networks to learn …

… To describe the setup, we fix the number of layers L ϵ Z + in the neural network and the
width of the i th layer n i ϵ Z + for i = 1,2….,I. Then for an input variable z ϵ R n , the functional …

… In the decision-making process, we must always pay attention to the changes of those sensitive
… value investment results can provide good decision-making opinions. As the company's …

… Despite its many applications and, more recently, its prominence [17], there is a lack of
coherence regarding ANN’s applications and potential to inform decision making at different …

… of graph neural network methods in the financial application. … on graph neural network
models with financial application. … neural networks and summarize the corresponding methods. …

… In order to better understand these features and to go beyond a “black box” model, we perform
a sensitivity analysis to understand the rationale behind the model predictions and reveal …