qrt — Quant Research Tools
Getting Started
API Reference
Roadmap
q.indicator — Indicators
Roadmap
Getting Started
q.bt — Backtesting
Run LEAN backtests
LEAN adapter and reports
Roadmap
q.data — Data
Sample datasets
Data schemas
Local files
Market data sources
Roadmap
q.ai — Generative AI
Roadmap
q.experiment — Experiment tracking
Roadmap
q.indicator — Indicators
QRT indicators
Simple moving average (SMA)
Exponential moving average (EMA)
Mean absolute deviation (MADEV)
Simple returns
Price momentum
Rolling volatility
Relative volume
Volume spike ratio
Price spikes
Log returns
Realized variance
Realized quarticity
Bipower variation
Median realized volatility
Minimum realized volatility
Realized volatility by session
Relative strength
Relative-strength moving average
Relative-strength days
Relative-strength phase
RS new high before price
TA-Lib
pandas-ta-classic
Roadmap
q.cross_section — Cross-sectional analysis
Roadmap
q.label — Financial labels
CUSUM event filter
Vertical barriers
Fixed-horizon labels
Triple-barrier labels
Meta-labels
Trend-scanning labels
Rare-label pruning
Label concurrency
Event indicator matrix
Average label uniqueness
Sequential bootstrap
Purging and embargo metadata
Return-attribution weights
Linear time decay
Class-balance weights
Combine sample weights
Roadmap
q.dataset — ML datasets
Temporal split
Time-series split
Splitting datasets
Roadmap
q.transform — Transformations
Missing data
Scaling
Outliers
Encoding
Reduction
Selection
Roadmap
q.calendar — Market time
Roadmap
q.signal — Signals
Visual signal tutorial
Roadmap
q.model — Models
Roadmap
q.ray — Distributed computing
Ray Train tutorial
SkyPilot — Compute orchestration
Launch a training run
VS Code over SSH
Local Strix Halo cluster
LEAN — Backtesting engine
Install and initialize
Projects and backtests
Native data formats
Generate Sweden data
Universes and composites
20/100 SMA strategy
Generate reports
Troubleshooting
q.gym — Financial RL
Roadmap
q.env — Environment
Roadmap
q.plot — Plotting
Correlation Plots
Correlation heatmap
Classification curves
Ranked bar charts
Return charts
Performance treemap
Tearsheet report
Probabilistic ratios
Simulation tests
Trade logs
Saving figures
Roadmap
q.portfolio — Portfolio
Roadmap
q.stats — Statistics
Risk estimators
Netto Number
Performance & benchmark
Rolling & calendar returns
Factor analytics
Chained API
Roadmap
q.utils — Utilities
Roadmap
Roadmap
On this page
Native indicators
Providers
Edit this page
View source
Report an issue
q.indicator — Indicators
Roadmap
q.indicator Roadmap
Only open work is listed here.
Native indicators
Add causal-window and batch/online equivalence tests to native indicators
Providers
Evaluate tsfresh as an explicit provider for automated time-series measurements
Keep provider dependencies optional and surface actionable installation errors
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pandas-ta-classic
q.cross_section — Cross-sectional analysis