How do I build a macro and rates dashboard in Python?

This Reflex template tracks rates, equity factors, spreads, and market indicators together, with yield curve views across maturities and factor cards for momentum, value, quality, growth, and volatility. Pandas handles the series maths.

Can this connect to FRED, Bloomberg, or a market data API?

Yes. The seeded series are DataFrames, so a live feed drops straight into the same charts. Rates and macro series commonly come from FRED, with factor and pricing data from a vendor API or an internal warehouse. Load them into a DataFrame and the existing charts render them.

How do I chart a yield curve in Python?

The curve view plots yields across maturities and compares snapshots over time, so steepening and inversion are visible directly. Adding a maturity or a comparison date is a change to the underlying series, not the chart code.

How do I track equity factor exposures like value and momentum?

Factor cards summarize each exposure with correlation and performance views alongside, plus scenario notes and watchlists for research workflows. The factor definitions are Python, so you can substitute your own construction.

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Macro Rates & Equity Factors

#Finance#Analytics

Build a financial dashboard in Reflex with Python, database-ready workflows, polished UI, and tools for market monitoring and rates analysis.

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Macro Rates & Equity Factors template interface showing rates, equity factors, spreads, and market indicators

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Tech Stack

ReflexPythonPandasSQLModelSQLiteCharts

Integrations

Key Features

Macro dashboard for rates, equity factors, spreads, and market indicators

Yield curve and rate-change views across maturities and time periods

Equity factor cards for momentum, value, quality, growth, and volatility

Scenario notes and watchlist sections for research workflows

Correlation and performance tables for factor and asset comparisons

Clean financial dashboard structure for swapping in live or uploaded data

Requirements

Rates, factor, index, or market indicator datasets

Time periods, benchmarks, and scenario labels for analysis

Preferred metrics such as yield changes, spreads, returns, or volatility

About This Template

Build a production-ready financial dashboard with Reflex and Python. This template is designed for investment, treasury, and research teams monitoring markets and factor exposure who need a usable app structure for market monitoring, rates analysis, factor exposure, and macro research, not a static mockup. The app pattern includes a focused dashboard, searchable tables, detail views, validated forms, status-aware actions, empty and loading states, and database-ready state management. Use it as a starting point for a macro dashboard, rates dashboard, equity factor dashboard, and portfolio risk dashboard while keeping full control of the Python codebase.

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Integrations

Key Features

Macro dashboard for rates, equity factors, spreads, and market indicators

Yield curve and rate-change views across maturities and time periods

Equity factor cards for momentum, value, quality, growth, and volatility

Scenario notes and watchlist sections for research workflows

Correlation and performance tables for factor and asset comparisons

Clean financial dashboard structure for swapping in live or uploaded data

Requirements

Rates, factor, index, or market indicator datasets

Time periods, benchmarks, and scenario labels for analysis

Preferred metrics such as yield changes, spreads, returns, or volatility