Does Portfolio Optimizer offer a free trial or free tier?

Yes, Portfolio Optimizer provides a free Developer Plan that includes up to 1,000 API calls per month, suitable for evaluation and small projects.

What is the cost of the lowest paid plan for Portfolio Optimizer?

The lowest paid plan is the Startup Plan, priced at €50 per month, which includes an allowance of 10,000 API calls.

How are overage API calls charged if I exceed my plan's limit?

Overage API calls are typically charged at a per-call rate, which varies by plan. Specific overage rates are detailed on the official Portfolio Optimizer pricing page.

Are all core APIs included in every Portfolio Optimizer plan?

Yes, the Portfolio Optimization API, Backtesting API, and Risk Analysis API are generally included across all plans, with differences primarily in monthly API call limits and support levels.

Can I upgrade or downgrade my Portfolio Optimizer plan at any time?

Portfolio Optimizer generally allows users to adjust their subscription tiers. Specific terms and conditions for upgrades and downgrades are available through their customer support or account management portal.

Does Portfolio Optimizer offer custom pricing for large enterprises?

Yes, Portfolio Optimizer offers an Enterprise Plan with custom pricing, tailored API call limits, dedicated support, and custom Service Level Agreements (SLAs) for large organizations.

What kind of support is included with the different pricing plans?

Support varies by plan. The free Developer Plan typically offers community support, while paid plans like Startup and Business include email support, with higher tiers offering priority or dedicated support.

Portfolio Optimizer Pricing: Plans & Cost Analysis (2026)

Pricing overview

Portfolio Optimizer operates on a subscription-based pricing model that primarily differentiates plans by the number of API calls included per month. This structure is designed to accommodate users ranging from individual developers and academic researchers utilizing a free Developer Plan to institutional clients requiring high-volume access for complex quantitative analysis and algorithmic trading strategies. The core services, including the Portfolio Optimization API, Backtesting API, and Risk Analysis API, are accessible across most plans, with higher tiers offering increased call limits and potentially enhanced features or support.

The cost structure is transparent, with defined monthly fees for specific API call allowances. Exceeding these allowances typically incurs overage charges, which are detailed within each plan's specifications. This approach aims to provide predictable billing while scaling with user demand. Understanding the expected volume of API requests is crucial for selecting the most cost-effective plan, particularly for applications involving frequent rebalancing, extensive backtesting, or real-time portfolio adjustments.

Plans and tiers

Portfolio Optimizer offers a range of plans tailored to different user requirements, from individual developers to enterprise-level financial institutions. Each plan is defined by its monthly API call allowance, pricing, and specific features. The primary pricing tiers are structured to scale with usage and access needs.

Portfolio Optimizer Plans and Features
Plan Name	Monthly Price	API Call Limit (per month)	Key Features/Limits	Best For
Developer Plan	Free	1,000	Standard API features, community support	Hobbyists, academic research, initial API exploration
Startup Plan	€50	10,000	Standard API features, email support	Small teams, startups, low-volume production use
Business Plan	€150	50,000	Enhanced features, priority email support	Growing businesses, moderate-volume applications
Enterprise Plan	Custom	Custom	All features, dedicated support, custom SLAs	Large institutions, high-volume production, specific compliance needs

Each paid plan includes access to the full suite of Portfolio Optimizer APIs, encompassing optimization, backtesting, and risk analysis functionalities. Overages above the specified API call limits are typically charged at a per-call rate, which varies by plan. Comprehensive details on overage pricing and specific plan inclusions are available on the official pricing page.

Free tier and limits

Portfolio Optimizer provides a free Developer Plan designed for evaluation, academic use, and small-scale projects. This tier includes a monthly allowance of up to 1,000 API calls, providing sufficient capacity to explore the API's capabilities, conduct initial research, or build proof-of-concept applications. The Developer Plan offers access to the core Portfolio Optimization API, Backtesting API, and Risk Analysis API, allowing users to perform various financial computations without an upfront financial commitment.

Key limitations of the free tier primarily revolve around the API call volume. Exceeding the 1,000-call limit requires an upgrade to a paid plan. While the free tier provides full functionality in terms of available endpoints, it may impose rate limits that are more restrictive than those on paid plans. Support for free tier users is typically community-based or limited to general documentation, contrasting with the priority support offered to subscribers of paid plans. This free offering aligns with a common strategy among API providers to enable developer adoption and facilitate the initial integration phase, similar to the free tiers offered by platforms like Cloudflare Workers for serverless functions or Google Cloud's Free Tier for various cloud services.

Real-world cost examples

To illustrate the practical application of Portfolio Optimizer's pricing, consider the following scenarios:

Individual Researcher (Academic Project): A university researcher aims to backtest a new portfolio allocation strategy on historical data. They might run 50 optimization queries daily for a month, each potentially making 10 API calls for data retrieval and optimization. This totals approximately 50 queries/day * 30 days/month * 10 calls/query = 15,000 API calls per month.
- Cost: This volume exceeds the free Developer Plan (1,000 calls). The researcher would likely subscribe to the Startup Plan at €50 per month, which includes 10,000 calls. The remaining 5,000 calls would incur overage charges, typically at a rate specified by Portfolio Optimizer (e.g., €0.005 per call). The monthly cost would be €50 + (5,000 * €0.005) = €50 + €25 = €75.
Small Fintech Startup (Portfolio Management App): A startup develops a web application providing personalized portfolio recommendations to 100 users. Each user generates an average of 5 API calls per day for portfolio rebalancing and risk analysis, summing to 100 users * 5 calls/user/day * 30 days/month = 15,000 API calls per month.
- Cost: Similar to the academic example, this usage falls into the Startup Plan's bracket. The base cost is €50 per month for 10,000 calls, plus overage charges for the additional 5,000 calls. If the overage rate is €0.005 per call, the total monthly cost would be €75. If growth is anticipated, upgrading to the Business Plan (50,000 calls for €150) might be more cost-effective to avoid overages as user numbers increase.
Quantitative Trading Firm (Real-time Optimization): A trading firm employs an algorithm that optimizes a portfolio every hour during trading hours (8 hours/day, 20 trading days/month) and makes 20 API calls per optimization. This equates to 8 optimizations/day * 20 days/month * 20 calls/optimization = 3,200 API calls per month for one strategy. If they run 10 such strategies concurrently, the total is 32,000 API calls per month.
- Cost: This usage necessitates the Business Plan at €150 per month, which includes 50,000 API calls. With 32,000 calls, they remain well within the plan's limit, incurring no overage fees. If their usage were to spike or they add more strategies, they could remain on the Business Plan until exceeding 50,000 calls, at which point an upgrade to an Enterprise plan or higher tier Business Plan would be considered.
Large Financial Institution (Enterprise Integration): A large bank integrates Portfolio Optimizer into its internal wealth management platform, serving thousands of clients with daily portfolio reviews and monthly rebalancing. This could easily generate millions of API calls per month.
- Cost: Such high-volume usage would fall under the Enterprise Plan. The pricing is custom-negotiated, factoring in specific usage patterns, dedicated infrastructure needs, service level agreements (SLAs), and potentially bespoke features. The cost would be significantly higher than the listed standard plans but would offer tailored support and infrastructure to meet institutional demands.

How the pricing compares

When evaluating Portfolio Optimizer's pricing, it is useful to compare it against alternative solutions in the quantitative finance and algorithmic trading space. Many platforms offer similar capabilities for portfolio optimization, backtesting, and risk analysis, often with differing pricing structures.

QuantConnect: QuantConnect provides a robust platform for algorithmic trading and quantitative analysis, emphasizing backtesting and live trading. Its pricing model includes a free tier for individual users, with paid tiers offering increased compute power, data access, and live trading capabilities. While Portfolio Optimizer focuses purely on API access for mathematical optimization, QuantConnect offers a more integrated development environment. QuantConnect's paid plans, such as the QuantConnect Quant Researcher plan, often involve compute hour allocations and premium data, which can result in different cost considerations compared to Portfolio Optimizer's API call-centric model.
Alpaca: Alpaca Markets primarily offers commission-free stock and crypto trading APIs, alongside a brokerage service. While it facilitates the execution of trading strategies, it provides fewer direct portfolio optimization algorithms as a core service. Its pricing is largely transaction-based for brokerage services, with some API features included for free or as part of a developer-friendly model. Compared to Portfolio Optimizer, Alpaca is more focused on execution capabilities for algorithmic trading rather than the advanced mathematical optimization of portfolios. Developers often use Alpaca's trading APIs in conjunction with a separate optimization engine, potentially leading to a combined cost structure.
Quandl (Nasdaq Data Link): Nasdaq Data Link (formerly Quandl) is a data provider, offering extensive financial, economic, and alternative datasets. Its pricing is typically data-subscription based, with costs varying significantly depending on the specific datasets accessed and the volume of data requests. While essential for portfolio optimization, it doesn't offer the optimization algorithms themselves. Users would subscribe to Nasdaq Data Link for data and then feed that data into a tool like Portfolio Optimizer for analysis. Therefore, the cost of Nasdaq Data Link is complementary rather than directly comparable, representing the data input expense rather than the processing expense. Their data pricing is highly granular per dataset.

Overall, Portfolio Optimizer's model of charging per API call for optimization services is straightforward and aligns with the usage patterns of developers integrating specific mathematical functions into their applications. This contrasts with platforms that bundle compute, data, and execution services into broader packages. For users primarily needing a powerful, API-driven optimization engine, Portfolio Optimizer's tiered pricing may offer a more direct and predictable cost structure, particularly compared to platforms with more complex pricing based on compute time or data volume for integrated development environments.