Early-warning signals for critical transitions
Complex dynamical systems, ranging from ecosystems to financial markets and the climate,
can have tip** points at which a sudden shift to a contrasting dynamical regime may …
can have tip** points at which a sudden shift to a contrasting dynamical regime may …
Measuring investor sentiment
G Zhou - Annual Review of Financial Economics, 2018 - annualreviews.org
Investor sentiment indicates how far an asset value deviates from its economic
fundamentals. In this article, we review various measures of investor sentiment based on …
fundamentals. In this article, we review various measures of investor sentiment based on …
[HTML][HTML] Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?
Bitcoin has grown in popularity and has now attracted the attention of individual and
institutional investors. Accurate Bitcoin price direction forecasts are important for determining …
institutional investors. Accurate Bitcoin price direction forecasts are important for determining …
Deep reinforcement learning
SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …
decision strategies. However, in many cases, it is desirable to learn directly from …
A deep reinforcement learning framework for the financial portfolio management problem
Financial portfolio management is the process of constant redistribution of a fund into
different financial products. This paper presents a financial-model-free Reinforcement …
different financial products. This paper presents a financial-model-free Reinforcement …
Predicting the direction of stock market prices using tree-based classifiers
Predicting returns in the stock market is usually posed as a forecasting problem where
prices are predicted. Intrinsic volatility in the stock market across the globe makes the task of …
prices are predicted. Intrinsic volatility in the stock market across the globe makes the task of …
Evaluating multiple classifiers for stock price direction prediction
Stock price direction prediction is an important issue in the financial world. Even small
improvements in predictive performance can be very profitable. The purpose of this paper is …
improvements in predictive performance can be very profitable. The purpose of this paper is …
Decision-making for financial trading: A fusion approach of machine learning and portfolio selection
Forecasting stock returns is an exacting prospect in the context of financial time series. This
study proposes a unique decision-making model for day trading investments on the stock …
study proposes a unique decision-making model for day trading investments on the stock …
Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework
Numerous studies have adopted deep learning (DL) in financial market forecasting models
owing to its superior performance. The DL models require as many relevant input variables …
owing to its superior performance. The DL models require as many relevant input variables …
Convolution on neural networks for high-frequency trend prediction of cryptocurrency exchange rates using technical indicators
This study explores the suitability of neural networks with a convolutional component as an
alternative to traditional multilayer perceptrons in the domain of trend classification of …
alternative to traditional multilayer perceptrons in the domain of trend classification of …