Tools built for factor analysis.
Deconstruct market returns with precision. FujiFactor provides the technical infrastructure required to isolate premiums, model volatility, and validate systematic trading strategies.
The Factor Engine
Our proprietary stack is designed for the modern quant. We focus on minimizing look-ahead bias and maximizing out-of-sample robustness through rigorous cross-sectional testing.
- Survivor-bias free datasets
- Cross-sectional normalization
- Auto-regressive volatility scaling
Alpha Signal Profiler
Measure signal decay and information coefficients across multiple time horizons. Our profiler identifies the optimal holding period for any quantitative factor.
Multi-Factor Optimizer
Build balanced portfolios by combining low-correlation factors. This tool manages the trade-off between tracking error and expected alpha.
Volatility Attribution
Decompose portfolio risk into market, sector, and idiosyncratic components. Essential for maintaining factor neutrality in volatile regimes.
Historical Backtester
Run high-fidelity simulations using point-in-time data. Accurately model transaction costs, slippage, and liquidity constraints.
Visualizing Signal Robustness
Data is only as good as its interpretability. Our analysis tools generate static visualizations that allow researchers to spot anomalies, overcrowding, and regime shifts before they impact the bottom line.
Heatmap Correlation Matrices
Identify overlapping exposures between growth, value, and momentum factors to prevent accidental concentration.
Quantile Momentum Trajectories
Track how different asset groups migrate through momentum deciles over 126 and 252-day lookback windows.
Drawdown Waterfall Analysis
Understand the depth and duration of factor underperformance to calibrate risk tolerance effectively.
Capability Comparison
Select the environment that matches your institutional requirements and trading tools stack.
| Feature | Core Reader | Active Researcher | Quant Direct |
|---|---|---|---|
| Static Factor Reports | |||
| Factor Analysis API | — | ||
| Raw Point-in-Time Data | — | — | |
| Custom Alpha Backtesting | — | Limited | |
| Daily Rebalancing Signals | — |
Procedural Workflow
Hypothesis Creation
Identify market inefficiencies by scanning our research library. Define your factor analysis parameters based on academic literature or proprietary observations.
Engineered Testing
Execute backtests using our systematic tools. Apply realistic constraints including liquidity filters and sliding-scale transaction cost models.
Signal Deployment
Export production-ready signals to your execution platform. Monitor factor drift and performance in real-time through our dashboard suite.
Need a custom factor built for your strategy?
Our Shibuya-based engineering team builds bespoke quant models and data pipelines for institutional clients and family offices. Let’s talk about your data requirements.
Response time typically under 24 hours (Mon-Fri).
Support & Operations
Shibuya 21, Tokyo | Mon-Fri: 09:00-18:00