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APIs / Finance / Portfolio Optimizer
Portfolio Optimizer logo

Portfolio Optimizer

38
AI ReadinessNon-Ready (F)38/100
See full scorecard
Official vendor OpenAPI document · agent-readyFinanceBankingapiKey158 EndpointsREST

For Agents

Optimize investment portfolios using mean-variance analysis, calculate Value-at-Risk, estimate covariance matrices, run Monte Carlo simulations, and compute risk-adjusted returns across up to 100 assets.

Use for: I need to find the minimum variance portfolio for my assets, Calculate the Value-at-Risk of my portfolio, I want to optimize for maximum Sharpe ratio, Estimate the correlation matrix for a set of asset returns

Not supported: Does not handle trade execution, market data sourcing, or accounting - use for quantitative portfolio analysis and optimization only.

Portfolio Optimizer is a quantitative finance API offering 158 endpoints for analyzing and optimizing investment portfolios. It covers modern portfolio theory (mean-variance optimization, maximum Sharpe ratio, minimum variance), risk analysis (Value-at-Risk, Conditional VaR), asset correlation and covariance matrix estimation, hierarchical clustering, Monte Carlo simulation, factor models (Fama-French), and capital market assumptions. The API supports up to 100 assets and 2500 data points per authenticated request.

Jentic One on GithubView OpenAPI Document

Install Jentic One Beta

Connect the Portfolio Optimizer to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Portfolio Optimizer, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

1

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fportfoliooptimizer.io%2Fportfoliooptimizer" | sh
2

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fportfoliooptimizer.io%2Fportfoliooptimizer" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Portfolio Optimizer API.

Optimize portfolios for minimum variance, maximum Sharpe ratio, or target return on the efficient frontier

Calculate empirical, Gaussian, and Cornish-Fisher Value-at-Risk and Conditional VaR

Estimate asset covariance and correlation matrices with shrinkage and denoising methods

Run Monte Carlo return simulations with bootstrap and Gaussian models

Apply hierarchical clustering and FTCA for asset grouping and diversification analysis

Retrieve Fama-French factor model data for US, developed, and emerging markets

Compute capital market assumptions averaged from leading financial institutions

Use Cases

Patterns agents use Portfolio Optimizer API for, with concrete tasks.

★ Mean-Variance Portfolio Optimization

Compute optimal asset weights using modern portfolio theory. The API provides minimum variance, maximum return, maximum Sharpe ratio, and mean-variance efficient portfolio optimizations. Each supports diversified variants, resampling-based methods for robustness, and subset resampling for large universes. Input asset returns and constraints, receive optimal weights.

Submit 5 asset return series to the /portfolio/optimization/maximum-sharpe-ratio endpoint and retrieve the optimal weight allocation

Portfolio Risk Measurement

Quantify portfolio downside risk using multiple Value-at-Risk methodologies. The API offers empirical, Gaussian, Cornish-Fisher (with corrections), and historical VaR calculations, plus Conditional VaR variants. Each accepts portfolio weights and return data, returning risk metrics at configurable confidence levels.

Calculate the 95% Cornish-Fisher Value-at-Risk for a portfolio of 3 assets using /portfolio/analysis/value-at-risk/cornish-fisher with their historical returns

Covariance Matrix Estimation

Estimate robust covariance and correlation matrices from asset return data using standard sample estimation, shrinkage methods, exponential weighting, and denoising techniques. The API supports up to 100 assets and provides both historical and forecast covariance matrices for use in downstream optimization.

Submit 10 asset return series to the covariance matrix estimation endpoint with Ledoit-Wolf shrinkage and retrieve the estimated matrix

Monte Carlo Return Simulation

Generate simulated return scenarios for stress testing and scenario analysis. The API offers bootstrap simulations (sampling from historical returns) and Gaussian simulations (parametric generation from mean and covariance). Results feed into optimization and risk analysis endpoints for comprehensive portfolio evaluation.

Run a Gaussian Monte Carlo simulation of 1000 scenarios for 4 assets using /assets/returns/simulation/monte-carlo/gaussian with their mean returns and covariance matrix

AI Agent Quantitative Analysis via Jentic

AI agents use Jentic to discover Portfolio Optimizer operations by intent, such as 'optimize portfolio for maximum Sharpe ratio' or 'calculate Value-at-Risk'. Jentic returns the operation schema with required input formats (arrays of asset returns, weight vectors), then handles X-API-Key injection for authenticated access to higher rate limits.

Search Jentic for 'optimize portfolio for minimum variance', load the operation schema, and execute with 5 asset return series to get optimal weights

Key Endpoints

158 endpoints — portfolio optimizer is a quantitative finance api offering 158 endpoints for analyzing and optimizing investment portfolios.

METHOD

PATH

DESCRIPTION

POST

/portfolio/optimization/maximum-sharpe-ratio

Find the portfolio with the highest risk-adjusted return

POST

/portfolio/optimization/minimum-variance

Compute the minimum risk portfolio

POST

/portfolio/analysis/value-at-risk/cornish-fisher

Calculate Cornish-Fisher VaR

POST

/portfolio/optimization/mean-variance-efficient

Find an efficient frontier portfolio for a target return

POST

/assets/returns/simulation/monte-carlo/gaussian

Run Gaussian Monte Carlo return simulations

POST

/assets/clustering/hierarchical

Hierarchical clustering of assets

GET

/factors/models/fama-french/us

Retrieve U.S. Fama-French factor data

GET

/markets/capital-assumptions/usd

Get USD capital market assumptions

POST

/portfolio/optimization/maximum-sharpe-ratio

Find the portfolio with the highest risk-adjusted return

POST

/portfolio/optimization/minimum-variance

Compute the minimum risk portfolio

POST

/portfolio/analysis/value-at-risk/cornish-fisher

Calculate Cornish-Fisher VaR

POST

/portfolio/optimization/mean-variance-efficient

Find an efficient frontier portfolio for a target return

POST

/assets/returns/simulation/monte-carlo/gaussian

Run Gaussian Monte Carlo return simulations

POST

/assets/clustering/hierarchical

Hierarchical clustering of assets

GET

/factors/models/fama-french/us

Retrieve U.S. Fama-French factor data

GET

/markets/capital-assumptions/usd

Get USD capital market assumptions

Jentic AI Readiness Score

This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.

P

Portfolio Optimizer

- Non-Ready (F)
38/100
47
Foundational Compliance
57
Developer Experience & Jentic Compatibility
19
AI-Readiness & Agent Experience
63
Agent Usability
50
Security
69
AI Discoverability
Powered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
47

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: D+Signals: 4
90%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

0%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

0%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

57

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: CSignals: 4
10%

Example Density

How richly the API is illustrated with examples.

92%

Example Validity

Percentage of examples that conform to their schemas.

26%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

100%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

19

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: FSignals: 4
51%

Description Coverage

Coverage of descriptions across API elements.

0%

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

0%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

23%

Summary Coverage

Coverage of summaries across operations/tags/info.

63

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: BSignals: 1
63%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

50

Security

Trust, risk posture, and security compliance.

Grade: C-Signals: 1
50%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

69

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: B+Signals: 1
69%

Descriptive Richness

Clarity and depth of descriptions across API elements.

View full reportHow the score is calculatedMore about the dimensions

Score it yourself

Every API in the directory is allowlisted, so you can re-score it with no key required.

Score your own APIScoring CLI agent skill
npx @jentic/api-scorecard-cli score <openapi-url>

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring Portfolio Optimizer by hand means learning its X-API-Key header auth and choosing between the default and EU-west-1 hosts yourself. Through Jentic you install once, import Portfolio Optimizer from the API Directory, store the key once, and your agent calls it.

Permission scoping

Portfolio Optimizer takes its portfolios and asset data in the request body, so you limit the agent to the operations it needs, such as maximum-Sharpe-ratio optimization or value-at-risk analysis. Other computations are available only if you add them.

Credential isolation

Your Portfolio Optimizer API key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'optimize a portfolio for maximum Sharpe ratio' or 'compute value at risk', and Jentic returns the matching Portfolio Optimizer operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Global Predictions API

→

Economic forecasting and portfolio recommendations based on macroeconomic knowledge graphs

Use Global Predictions when you need forward-looking economic forecasts and automated recommendations rather than quantitative optimization of existing portfolios.

Complementary

Polygon.io API

→

Real-time and historical market data for price feeds into optimization models

Use Polygon.io to source the historical price data and returns that Portfolio Optimizer requires as inputs for optimization and risk analysis.

Complementary

Alpaca Trading API

→

Commission-free trading to execute the portfolio allocations that optimization produces

Use Alpaca when you need to execute trades based on the optimal weights computed by Portfolio Optimizer.

FAQs

Specific to using Portfolio Optimizer API through Jentic.

What authentication does the Portfolio Optimizer API use?

The API uses an optional X-API-Key header for authenticated access. Anonymous users get limited access (1 request per second, 20 assets, 500 data points). Authenticated users get 10,000 requests per 24 hours, 100 assets, 2,500 data points, and 2.5 seconds execution time. Through Jentic, the API key is stored encrypted and injected automatically.

Can I compute the efficient frontier with the Portfolio Optimizer API?

Yes. The /portfolio/optimization/mean-variance-efficient endpoint finds a portfolio on the efficient frontier for a given target return. Use it repeatedly with different target returns to trace the full frontier. Diversified and resampling-based variants improve robustness for real-world asset data with estimation error.

What are the rate limits for the Portfolio Optimizer API?

Anonymous users are limited to 1 request per second (shared across all anonymous users), 1 second execution time, 20 assets, and 500 data points. Authenticated users with an API key get 10,000 requests per 24 hours with concurrent access, 2.5 seconds execution time, 100 assets, and 2,500 data points. Rate limit details are returned in x-ratelimit-* response headers.

How do I calculate Value-at-Risk through the Portfolio Optimizer API with Jentic?

Install the SDK with pip install jentic, then search for 'calculate portfolio Value-at-Risk'. Jentic returns the VaR operation schema (empirical, Gaussian, or Cornish-Fisher variants). Submit portfolio weights and historical asset returns to receive the VaR estimate at your chosen confidence level.

Is the Portfolio Optimizer API free to use?

Yes, with limitations. Anonymous access is free but restricted to a subset of endpoints, 20 assets, and 1 request per second. Full access requires an API key obtained through a small monthly contribution. Contact portfoliooptimizer.io for pricing details.

What optimization methods are available beyond mean-variance?

The API offers hierarchical risk parity, inverse volatility weighting, equal risk contribution, maximum diversification, and multiple risk-based optimization objectives including minimum tracking error and maximum Ulcer ratio. It also supports resampling-based variants of each method for improved out-of-sample robustness.

Can I limit what my agent is allowed to do with the Portfolio Optimizer API?

Yes. Because you run Jentic One yourself, you decide which Portfolio Optimizer operations the agent can call, so you can allow only the ones it needs, such as maximum-Sharpe-ratio optimization or value-at-risk analysis, and leave the other computations unavailable unless you add them. Portfolios and asset return data are passed in the request body, so the agent works only with the inputs you provide to those permitted operations. Your API key is held by your own Jentic One instance and injected at execution time, so the agent scopes access under your rules rather than handling the credential itself.

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View OpenAPI Document