Strategy Overview:

Riventa's AI-Powered Equity Selection strategy integrates machine learning, dynamic multifactor models, and systematic risk management to identify high-potential stocks across global equity markets. It is designed to serve institutional investors and high-net-worth clients seeking performance with precision.

Core Mechanics:

• • Leverages deep learning algorithms and real-time data processing to analyze financial statements, market indicators, and alternative data sources at scale;
• • Employs dynamic factor modeling to adjust factor weights in real time based on changing market environments—focusing on factors such as momentum, valuation, quality, and sentiment;
• • Applies intelligent portfolio optimization and active rebalancing to achieve an optimal risk-reward balance;
• • Embeds a comprehensive risk control engine using advanced volatility models (e.g., Value-at-Risk, Conditional VaR) and scenario stress testing to manage drawdowns and tail risks.

Client Value:

• • Offers a data-driven, transparent, and repeatable stock selection process;
• • Adapts dynamically to market cycles, reducing reliance on subjective human judgment;
• • Publishes monthly AI-generated equity portfolio updates and strategy reports.

Strategy Overview:

Riventa Capital's AI-Driven Crypto Derivatives Strategy is built to operate in the highly volatile and data-intensive world of cryptocurrency futures and options. Our proprietary AI system monitors market conditions in real time—combining reinforcement learning, deep neural networks, and on-chain behavioral analytics to power adaptive hedging and volatility control.

Core Mechanics:

• • Continuously ingests and analyzes high-frequency trading data and blockchain signals (e.g., transaction volume, wallet activity, gas fees) to detect price momentum shifts and changes in implied volatility;
• • Leverages AI-based hedging algorithms that dynamically adjust hedge ratios based on real-time volatility regimes, market sentiment, and liquidity conditions;
• • Integrates volatility surface modeling and stress-testing frameworks to recalibrate exposure under extreme market scenarios;
• • The system is self-learning—updated in real time through live market feedback and validated through robust historical backtesting across diverse conditions.

Client Value:

• • Offers real-time risk awareness and portfolio defense against unexpected price swings in the crypto derivatives landscape;
• • Ideal for hedge funds, institutional traders, and HNWIs seeking disciplined access to crypto markets with adaptive risk infrastructure;
• • Delivers monthly performance insights and blockchain-level strategy monitoring reports for full transparency and accountability.