Ticker Statistics & Risk API

REST API · For developers

Build Asset Statistics & Risk Dashboards Using Ticker Statistics API

Retrieve detailed statistics and risk data for stocks, ETFs, and mutual funds. Statistics Snapshot API provides price data, valuation metrics, dividends, financial ratios, ownership data, analyst targets, trailing returns, and category-relative values where applicable. Risk & Factor Metrics API adds alpha, beta, R-squared, standard deviation, Sharpe ratio, and Treynor ratio across standardized time horizons. Annual Return History API returns calendar-year and quarterly return data for ETFs and mutual funds.

Use these APIs to build asset statistics pages, risk dashboards, return history tables, fund comparison views, ETF research tools, and financial analytics products without calculating every metric from raw datasets.

Includes 3 Financial APIs View Documentation
Scatter plot showing Annualized Return (y-axis, -10% to 30%) versus Annualized Volatility (x-axis, 0% to 40%), with bubble points trending upward along a dashed trend line. Below, three metric cards display Sharpe Ratio 1.28, Beta 1.15, and Max Drawdown -16.3%.

Stock Statistics Dashboard


Description

Build stock statistics pages with company-level market data, valuation ratios, dividend fields, profitability metrics, balance sheet indicators, share statistics, short interest, ownership data, and analyst target fields from a single statistics snapshot.

This workflow is designed for stock detail pages, company statistics tabs, comparison tables, research dashboards, and AI assistants that need a broad view of a company’s financial and market profile. It can help users review metrics such as market cap, trailing P/E, price-to-sales, price-to-book, enterprise value, margins, ROE, ROA, debt-to-equity, cash, revenue, free cash flow, dividend yield, short interest, and analyst target prices.

Use it when your application needs a compact yet detailed stock statistics layer without separately requesting financial statements, price history, dividends, analyst data, and ownership fields.


Interface Example

NVDA Statistics interface example with sector badge (Technology · Semiconductors) and seven sections: Financial Highlights (Market Cap $4.52T, Enterprise Value, EBITDA, Profit Margin), Trading Information (price, volume, bid/ask, and a 52-week range slider from $86.62 to $212.19), Valuation Metrics (P/E, P/B, P/S, EV/EBITDA, Beta), Share Statistics, Dividends & Splits, Analyst Targets (with a Low-Mean-High range slider and a Strong Buy recommendation badge), and Ownership and Short Interest with a donut chart showing Institutional 69.65%, Insider 4.33%, and Other 26.02%.

Output Example

Price & Market Data

  • Current Price: $185.61
  • Previous Close: $191.13
  • 52-Week Range: $86.62 – $212.19
  • 50-Day Avg: $183.90
  • 200-Day Avg: $168.12

Valuation

  • Market Cap: $4.52T
  • Enterprise Value: $4.46T
  • Trailing P/E: 45.83
  • Forward P/E: 24.22
  • Price/Book: 37.94
  • Price/Sales: 24.15
  • EV/EBITDA: 39.58
  • Beta: 2.31

Dividends

  • Dividend Rate: $0.04
  • Dividend Yield: 0.02%
  • Payout Ratio: 0.99%

Profitability

  • Profit Margin: 53.01%
  • Gross Margin: 70.05%
  • Operating Margin: 63.17%
  • ROE: 107.36%
  • ROA: 53.53%

Balance Sheet

  • Total Cash: $60.61B
  • Total Debt: $10.82B
  • Debt/Equity: 9.10
  • Current Ratio: 4.47

Ownership & Short Interest

  • Institutional Ownership: 69.65%
  • Insider Ownership: 4.33%
  • Short % of Float: 1.12%
  • Short Ratio: 1.64

Analyst Targets

  • Target Mean: $253.62
  • Range: $140 – $352
  • Recommendation: Strong Buy (58 analysts)

How to Build this Workflow

This workflow is built using the following FinImpulse APIs

Resources


API Cost Examples

Scenario APIs Used Usage Example Estimated Monthly Cost
Stock Statistics Dashboard Statistics Snapshot API statistics snapshots for 100,000 stocks ≈ $150.00
Statistics Snapshot API = $0.00150
100,000 stocks × 1 statistics snapshot = 100,000 requests
100,000 requests × $0.00150 = $150.00 / month

Disclaimer. The pricing examples above are calculated using the APIs shown in this workflow and represent typical usage scenarios. Static data can be cached client-side to reduce actual costs below these estimates, and the Sandbox environment is available for development and testing separately from production usage. Actual costs depend on the endpoints, datasets, response size, request frequency, caching strategy, and additional data included in your application.

FinImpulse provides financial data and analytics APIs only. AI-generated responses depend on the application, prompts, and language model used. FinImpulse does not provide investment advice, trading recommendations, or guarantee the accuracy of AI-generated conclusions.

ETF Performance & Risk Dashboard


Description

Build ETF performance and statistics dashboards with price data, category information, trailing returns, distribution fields, annual return history, quarterly returns, and risk metrics where available.

This workflow is useful for ETF research pages, performance dashboards, category comparison tools, portfolio analytics, and ETF discovery products. It can support views such as trailing returns vs category, total returns, annual return history, quarterly return history, risk overview, and benchmark-style performance comparison.

Use it when your application needs to show how an ETF performed across different time periods, how it compares with its category, and how its return history looks over multiple years. Statistics Snapshot gives the current and trailing performance context, while Annual Return History adds structured historical return tables for charting and comparison.


Interface Example

QQQ Performance & Risk interface example with category badge (Large Growth) and fund family label. Left side shows a Trailing Returns vs Category table across seven periods (YTD to 10 Year), with Fund values in purple and Category values in gray. Right side shows an Annual Total Return History bar chart (2021-2025) comparing Fund and Category bars, a Risk Overview section highlighting Beta 1.20 and Sharpe Ratio 1.03, and a Risk Statistics table listing Alpha, Beta, Sharpe, and Treynor across 3-year, 5-year, and 10-year horizons.

Output Example

Price & Fund Info

  • Previous Close: $747.03
  • Day Range: $748.80 – $758.58
  • 52-Week Range: $625.58 – $760.40
  • All-Time High: $760.40
  • Category: Large Blend
  • Fund Family: State Street Investment Management
  • Trailing Annual Dividend Yield: 0.76%

Trailing Returns (Fund vs. Category)

Period

Fund

Category

YTD

10.16%

5.14%

1 Month

−0.96%

9.43%

3 Month

15.17%

3.42%

1 Year

22.20%

27.72%

3 Year

20.48%

19.34%

5 Year

13.30%

11.20%

10 Year

15.40%

13.77%

Risk Metrics (Standardized Horizons)

Horizon

Alpha

Beta

Std Dev

Sharpe

Treynor

3y

−1.58

0.98

1.03

14.75

5y

−1.39

0.96

0.53

7.79

10y

−1.07

0.98

0.76

11.58

Annual Return History (Recent Years)

Year

Fund

Category

2021

+28.75%

+26.07%

2022

−18.17%

−16.96%

2023

+26.19%

+22.32%

2024

+24.89%

+21.45%

2025

+17.72%

+15.54%


How to Build this Workflow

This workflow is built using the following FinImpulse APIs

Resources


API Cost Examples

Scenario APIs Used Usage Example Estimated Monthly Cost
ETF Performance Dashboard Statistics Snapshot API, Annual Return History API statistics snapshot + annual return history for 70,000 ETFs ≈ $161.00
Statistics Snapshot API = $0.00150 + Annual Return History API = $0.00080
Total = $0.00230
70,000 ETFs × 1 statistics snapshot + annual return history = 70,000 requests
70,000 requests × $0.00230 = $161.00 / month
ETF Performance & Risk Dashboard Statistics Snapshot API, Annual Return History API, Risk & Factor Metrics API statistics, annual returns, and risk metrics for 70,000 ETFs ≈ $266.00
Statistics Snapshot API = $0.00150 + Annual Return History API = $0.00080 + Risk & Factor Metrics API = $0.00150
Total = $0.00380
70,000 ETFs × statistics + annual returns + risk metrics = 70,000 requests
70,000 requests × $0.00380 = $266.00 / month

Disclaimer. The pricing examples above are calculated using the APIs shown in this workflow and represent typical usage scenarios. Static data can be cached client-side to reduce actual costs below these estimates, and the Sandbox environment is available for development and testing separately from production usage. Actual costs depend on the endpoints, datasets, response size, request frequency, caching strategy, and additional data included in your application.

FinImpulse provides financial data and analytics APIs only. AI-generated responses depend on the application, prompts, and language model used. FinImpulse does not provide investment advice, trading recommendations, or guarantee the accuracy of AI-generated conclusions.

Mutual Fund Performance & Risk Dashboard


Description

Build mutual fund performance and risk dashboards with trailing returns, category returns, load-adjusted returns, annual return history, quarterly returns, fund rankings, years up/down, and risk-adjusted performance metrics.

This workflow is designed for mutual fund research platforms, fund comparison tools, portfolio analytics, risk dashboards, and applications that need category-relative fund performance data. It can support views such as trailing and load-adjusted returns vs category, annual total return history, quarterly return history, rank in category, risk overview, and risk statistics.

Use it when your product needs a deeper fund analytics layer than a simple price or NAV snapshot. Mutual funds can use the full Statistics & Risk flow: Statistics Snapshot for fund performance and category fields, Annual Return History for multi-year and quarterly returns, and Risk & Factor Metrics for alpha, beta, R-squared, standard deviation, Sharpe ratio, and Treynor ratio across available time periods.


Interface Example

FARMX Performance & Risk interface example, subtitled Fidelity Investments. Left side shows a Trailing & Load-Adjusted Returns vs Category table across four periods (YTD to 5 Year), with Trailing Fund and Load-Adjusted Fund values in purple and Category values in gray. Right side shows a combined Annual Total Return and Quarterly Return History chart (2021-2025), with annual bars and an expandable quarterly breakdown showing Q1-Q4 values below each year. Below are a Risk Overview section (Beta 0.013, Sharpe Ratio 0.0049), a Risk Statistics table (Alpha, Beta, Sharpe, Treynor across 3-year, 5-year, and 10-year horizons), a Category Ranking section with six rank metrics, and a Years Up / Down section showing 3 years up, 2 years down, and a Best 1-Year Return of 23.34%.

Output Example

Price & Fund Info

  • Previous Close: $21.78
  • 52-Week Range: $17.84 – $22.72
  • 50-Day Avg: $21.68
  • 200-Day Avg: $20.66
  • Fund Family: Fidelity Investments

Trailing Returns (Fund vs. Category)

Period

Fund

Category

YTD

19.52%

20.74%

1 Month

−0.58%

−1.94%

3 Month

−2.33%

7.31%

1 Year

13.28%

63.77%

3 Year

3.96%

9.96%

5 Year

5.35%

11.51%

Category Ranking

  • YTD Rank: 10
  • 1-Year Rank: 78
  • 3-Year Rank: 82
  • 5-Year Rank: 69
  • Years Up: 3
  • Years Down: 2
  • Best 1-Year Return: 23.34%

Risk Metrics (Standardized Horizons)

Horizon

Alpha

Beta

Std Dev

Sharpe

Treynor

3y

−6.60%

0.013

26.43%

0.005

0.077

5y

−5.02%

0.013

21.92%

0.006

0.088

10y

−7.55%

0.013

22.19%

0.003

0.029

Annual Return History (Recent Years)

Year

Annual Return

2021

+23.34%

2022

+13.69%

2023

−11.60%

2024

−4.85%

2025

+8.00%


How to Build this Workflow

This workflow is built using the following FinImpulse APIs

Resources


API Cost Examples

Scenario APIs Used Usage Example Estimated Monthly Cost
Mutual Fund Performance & Risk Dashboard Statistics Snapshot API, Risk & Factor Metrics API, Annual Return History API statistics, risk metrics, and annual returns for 30,000 mutual funds ≈ $114.00
Statistics Snapshot API = $0.00150 + Risk & Factor Metrics API = $0.00150 + Annual Return History API = $0.00080
Total = $0.00380
30,000 mutual funds × statistics + annual returns + risk metrics = 30,000 requests
30,000 requests × $0.00380 = $114.00 / month

Disclaimer. The pricing examples above are calculated using the APIs shown in this workflow and represent typical usage scenarios. Static data can be cached client-side to reduce actual costs below these estimates, and the Sandbox environment is available for development and testing separately from production usage. Actual costs depend on the endpoints, datasets, response size, request frequency, caching strategy, and additional data included in your application.

FinImpulse provides financial data and analytics APIs only. AI-generated responses depend on the application, prompts, and language model used. FinImpulse does not provide investment advice, trading recommendations, or guarantee the accuracy of AI-generated conclusions.

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