Portfolio management system in equity market neutral using reinforcement learning
Portfolio management involves position sizing and resource allocation. Traditional and
generic portfolio strategies require forecasting of future stock prices as model inputs, which …
generic portfolio strategies require forecasting of future stock prices as model inputs, which …
Effective fuzzy system for qualifying the characteristics of stocks by random trading
Trading strategies can be divided into two categories, ie, those with momentum
characteristic and those that appear contrarian. The characteristics of trading strategies have …
characteristic and those that appear contrarian. The characteristics of trading strategies have …
Stock selection system through suitability index and fuzzy-based quantitative characteristics
With the rapid development of quantitative trading, stock selection is an ongoing task that
requires consideration of the characteristics of stocks and investment strategies. Fuzzy set …
requires consideration of the characteristics of stocks and investment strategies. Fuzzy set …
Automated trading system for stock index using LSTM neural networks and risk management
TR Silva, AW Li, EO Pamplona - 2020 international joint …, 2020 - ieeexplore.ieee.org
Financial time series predictions are a challenge due to their nonlinear and chaotic nature.
In recent decades, many researchers and investors have studied methods to improve …
In recent decades, many researchers and investors have studied methods to improve …
Portfolio management system with reinforcement learning
Portfolio management is a critical issue which should be skilled by position sizing and
resource allocation. Traditional and generic portfolio strategies require to forecast the future …
resource allocation. Traditional and generic portfolio strategies require to forecast the future …
A framework of deep reinforcement learning for stock evaluation functions
Quantitative trading is a crucial aspect of money management; however, conventional
trading strategies are based on indicators and signals, despite the fact that position sizing is …
trading strategies are based on indicators and signals, despite the fact that position sizing is …
[HTML][HTML] Evolutionary ORB-based model with protective closing strategies
Opening range breakout (ORB) is a well-known intraday trading strategy via technical
analysis. ORB lacks robustness against market uncertainties (eg, information from …
analysis. ORB lacks robustness against market uncertainties (eg, information from …
Modifying ORB trading strategies using particle swarm optimization and multi-objective optimization
Opening range breakout (ORB) is a well-known trading strategy in which predetermined
price thresholds are used to characterize price movements. However, some researchers …
price thresholds are used to characterize price movements. However, some researchers …
Truncated Quantile Critics Algorithm for Cryptocurrency Portfolio Optimization
L Xiao, X Wei, Y Xu, X Xu, K Gong… - … on Systems, Man, and …, 2023 - ieeexplore.ieee.org
This paper investigates portfolio management algorithm for the cryptocurrency market by
using the TQC (Truncated Quantile Critics) algorithm. The study is based on the daily prices …
using the TQC (Truncated Quantile Critics) algorithm. The study is based on the daily prices …
Threshold-adjusted orb strategies with genetic algorithm and protective closing strategy on taiwan futures market
Opening range breakout (ORB) is a well-known intraday trading strategy that generates
trading signals through technical analysis; however, ORB does not make full use of market …
trading signals through technical analysis; however, ORB does not make full use of market …