First User Feedback: Private Fund Advisory Pilot Launches with Promising Backtest Results
Recently, NextLeap successfully completed its first closed-door pilot test for private fund advisory services, and officially launched the initial deployment of its strategy models in collaboration with two U.S.-based private equity funds. This marks the first real-world trial of the NextLeap Intelligent Factor Engine, validating the feasibility and potential of the team’s proprietary system in cross-asset strategy construction and backtesting efficiency.
Backtest Results: Preliminary Targets Met for Risk Control and Returns
In this round of testing, the NextLeap team applied its models to highly liquid assets within both U.S. equity indices and crypto markets. Using a multi-factor quantitative framework, the team built the first batch of adjustable strategy portfolios. Backtesting data from Q2 2022 revealed:
Annualized return reached 18.4% in a typically volatile market environment
Maximum drawdown was limited to 7.9%, indicating a solid risk-reward profile
The model showed sensitivity to macroeconomic events, especially during shifts in interest rate expectations and periods of extreme crypto volatility
Model Architecture: Balancing Interpretability and Customization
The strategy system deployed in this trial is built upon NextLeap’s proprietary CoreX Intelligent Engine, which integrates several key technological modules:
Smart Factor Generator: Dynamically creates multi-dimensional stock/crypto selection factors based on technical, sentiment, and on-chain behavioral data
Strategy Backtest Engine: Supports minute-level historical market simulations to rapidly test strategy performance across varying market conditions
Personalized Parameter Adjustment Module: Allows advisors to tailor optimizations based on risk preferences, regional markets, and asset classes
The system places strong emphasis on model interpretability and human-machine collaboration, enabling automated execution while preserving manual calibration and macro-level adjustments.
User Feedback: Positive but Measured
Both participating private funds acknowledged the model’s strategic architecture, particularly praising its transparency and portfolio stability. Some feedback included:
Significantly improved backtest speed and responsiveness compared to traditional Excel-based models
Certain factor weights require further tuning, especially for handling extreme market conditions
Future versions should include more visualized reports and macroeconomic interpretation modules to enhance executive-level decision support
Next Steps
Based on this round of feedback, NextLeap will continue refining its factor selection logic and asset allocation parameters. The company plans to expand its pilot to a second cohort later this year, including family offices, crypto funds, and select asset managers across Asia.
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