This demonstration showcases DeepAriesโour novel reinforcement learning framework that dynamically adjusts rebalancing intervals based on market conditions. Our work presents adaptive portfolio management using deep reinforcement learning techniques for enhanced portfolio selection.
Dynamic rebalancing interval selection based on market conditions using reinforcement learning.
AI-driven portfolio allocation and performance optimization with enhanced selection strategies.
Comprehensive risk assessment using VaR, Expected Shortfall, and stress testing methodologies.
Deep RL framework for financial decision making and adaptive portfolio management.
This demo accompanies our research paper:
"DeepAries: Adaptive Rebalancing Interval Selection for Enhanced Portfolio Selection"
Authors: Jinkyu Kim, Hyunjung Yi, Mogan Gim, Donghee Choi, Jaewoo Kang
Conference: CIKM 2025 (30th ACM International Conference on Information and Knowledge Management)
Year: 2025
Keywords: Portfolio Management, Adaptive Rebalancing Interval Selection, Artificial Intelligence in Finance, Deep Reinforcement Learning
Demo Description: In this interactive demo, we showcase DeepAriesโour novel reinforcement learning framework that dynamically adjusts rebalancing intervals based on market conditions. Evaluation begins on January 1, 2021, and data is continuously updated. The demo provides recommended portfolio allocation, performance comparisons (with both portfolio and benchmark index cumulative returns normalized over the selected period), adaptive rebalancing visualizations, and aggregated insights into rebalancing behavior.
Historical market data with multiple ticker selection and default visualization
Rows: Tickers, Columns: Dates, Values: AI Model Predictions
Advanced technical indicators and chart analysis tools to help you make informed trading decisions. Analyze price trends, momentum, and market patterns using professional-grade indicators.
Visualize price movements with OHLC (Open, High, Low, Close) data and volume analysis for comprehensive market insight.
Calculate and visualize various technical indicators to identify market trends and potential trading opportunities.
Analyze trading volume patterns to understand market sentiment and confirm price movements with volume-based indicators.
Analyze correlation relationships between different stocks across markets to identify diversification opportunities and market dependencies.
Interactive demonstration of adaptive rebalancing and portfolio performance analysis
Select Market, Model, and Period to analyze portfolio allocation and performance
Allocation on โ
Shows monthly rebalancing allocations (first trading day each month) for the selected market and model. Xโaxis uses 6โmonth ticks.
Shows when rebalancing events occurred and their relationship to market volatility
Distribution of rebalancing intervals showing adaptive behavior
Shows market volatility, trends, and when rebalancing events occurred in relation to market conditions
Advanced risk assessment tools to evaluate portfolio risk exposure, calculate Value at Risk (VaR), and perform stress testing under various market scenarios. These tools help quantify potential losses and assess portfolio resilience under adverse market conditions.
โ ๏ธ Notice: This section is currently under development and improvement. Some features may not be fully functional or may require additional data sources.
Calculate the maximum potential loss over a specified time horizon with a given confidence level using historical data analysis. VaR answers the question: "What is the worst loss I can expect over a given time period with a given confidence level?"
Simulate extreme market conditions to assess portfolio resilience and potential losses under adverse scenarios. Stress testing helps identify vulnerabilities and prepare for market crises.
Comprehensive risk metrics including volatility, Sharpe ratio, and maximum drawdown for selected assets. These metrics provide a complete picture of risk-adjusted performance.