QuanterLab is a research platform organised around the top ribbon. Each tab on the ribbon is a self-contained workbench for a specific style of analysis, and each of those tabs has its own workflow article in this section. Start here to understand how the tabs relate, then open the one that matches what you want to do.
The five main tabs
Read this list left-to-right — it roughly follows the order of difficulty and the order in which most users progress:
- Basic Strategies — Four families of rule-based technical strategies (Mean Reversion, Momentum, Crossover, Breakout), each with a Scanner, a Signal Overlay and a Strategy Builder. The friendliest entry point: one family per module, one indicator at a time, clean backtest output.
- Indicator Strategies — The power-user version: any indicator, any combination, with a full Overlay/Builder, a portfolio Backtester, a Regime Analysis tool and a Regime Optimizer. Same backtesting engine as Basic, but no family constraints.
- Stochastic Methods — Model-driven mean-reversion and pairs trading: Ornstein–Uhlenbeck z-score, Kalman filters, Hurst, HMM regimes. Fits continuous-time models to the series instead of tuning thresholds on an indicator. Includes grid search, walk-forward validation and dedicated scanners.
- Factor Models — Fundamental research stack: multi-factor screener, seven quality analyzers, historical factor backtesting, factor-ranked portfolio optimizers (MVO / HRP / Inverse Volatility), Monte Carlo, Value-at-Risk, and an autopsy module for reviewing what went wrong.
- Supplementary Data — Context that sits alongside any strategy: currently the Macro Overlay Analyzer, which tells you how sensitive a stock is to rates, inflation, employment, volatility and other macro drivers. Read-only — no order generation.
Open Basic Strategies first to understand scanners, signal overlays and the backtest output format. Then move to Indicator Strategies for the Overlay/Builder. Branch into Stochastic Methods for a statistically disciplined alternative, or Factor Models for a fundamentals-first approach. Use Supplementary Data as a context check at any point.
Cross-cutting features
My Projects
Your saved-work hub. Strategy configs, portfolios and reports all get saved as items that can be grouped into projects, annotated and attached to each other. Use it to keep a related research thread in one place instead of fishing through backtest tabs.
Paper Trading
Three paper-trading modules matched to the three strategy-tab families: Indicator Strategy Paper Trading (for Basic Strategies configs), Advanced Paper Trading (for Indicator Strategies / Overlay-Builder configs), and Stochastic Paper Trading (for Stochastic Methods configs). All three run against live market data and report P&L against virtual capital.
Knowledge Base
The tab you are reading now. Three content groups in the ribbon: Trading Strategies (theory for the mean-reversion and momentum families), Factor Models (quant theory, ratios, scoring, portfolio theory) and Platform Guides (this series — one workflow per main tab).
Every module has a Read Me button in its top-right corner with module-specific documentation. Use the Platform Guides in this KB for tab-level orientation, and the Read Me for the specific controls inside a given module.
Suggested first steps
- Open Basic Strategies → Mean Reversion → Scanner. Run it against the S&P 500 and read the composite score column.
- Pick a top result and open Signal Overlay. Flip through a couple of indicators to see what a mean-reversion setup looks like visually.
- Open the Strategy Builder for the same ticker, set an RSI entry and a time-based exit, and run the backtest. That is the reference for how every backtest in the platform is presented.
- Then open the matching Platform Guide for whichever tab you're curious about next, and follow the workflow inside it.
Further Reading
Related QuanterLab articles
Try it in QuanterLab
Start with one module, one ticker, one strategy. The platform has many tools, but mastery comes from depth on a few — not breadth across all.