#portfolio

How the major asset classes move together — a live correlation matrix across stocks, bonds, gold, oil, crypto and the dollar (no key, nothing stored). Correlation is the single most important input to diversification and risk: two assets with a correlation near 1 are effectively the same bet, while a low or negative correlation is genuine diversification. Where a crypto-correlation API stays inside crypto and an FX-correlation API stays inside currencies, this spans the whole multi-asset book at once — US and international equities, Treasuries and credit, gold, silver, oil and broad commodities, Bitcoin and Ether, the dollar and real estate — so an allocator can see in one call whether bonds are still hedging stocks, whether gold is decoupled and whether crypto is trading as a risk asset. The matrix endpoint returns the full pairwise return-correlation matrix over a chosen window, with the most- and least-correlated pairs. The asset endpoint returns one asset's correlation to every other, ranked, so you see its best diversifiers at a glance. The assets endpoint lists what is covered. The cross-asset / multi-asset correlation surface — distinct from the crypto-only correlation API, the FX-only currency-correlation API and the bring-your-own-series CAPM, risk-metrics and portfolio-optimiser calculators.

api.oanor.com/crossassetcorrelation-api

Live mean-variance (Markowitz) portfolio optimisation that quants and allocators run across a basket of assets, computed on demand from the price series you pass in — no key, no cache, nothing stored. The optimize endpoint returns the two cornerstone portfolios: the minimum-variance portfolio and the maximum-Sharpe (tangency) portfolio, each with its optimal weights, expected return, volatility and Sharpe ratio. The frontier endpoint traces the efficient frontier — a set of optimal risk/return points and the weights that achieve them — so you can plot the whole risk/return curve. The stats endpoint returns the per-asset annualised return and volatility plus the full correlation and covariance matrices, the raw material behind the optimisation. It exploits diversification: by combining assets with low or negative correlation the optimiser finds a portfolio whose volatility is lower than any single holding. Works for any basket — stocks, funds, ETFs, crypto, FX or commodities. This is a multi-asset allocation engine, fundamentally different from single-asset risk and CAPM tools: it answers how to weight several assets together, not how one behaves. Weights can be negative, representing a short leg, as in classic unconstrained Markowitz. Computed locally and deterministically, so it is instant and private. Ideal for robo-advisors, portfolio dashboards, asset-allocation research and back-tests. Rates are fractions (0.02 = 2%). Live, nothing stored. 3 compute endpoints. For single-asset Sharpe/drawdown use a risk-metrics API; for beta use a CAPM API.

api.oanor.com/portfoliooptimizer-api

Live capital-asset-pricing-model and systematic-risk analytics that quants and portfolio managers run on an asset against a market benchmark, computed on demand from the two series you pass in — no key, no cache, nothing stored. The beta endpoint regresses an asset's returns on the market's and returns the beta, the alpha (per period and annualised), the correlation and the R-squared, so you see how strongly the asset tracks the market and how much it amplifies it. The capm endpoint returns the CAPM expected return — risk-free rate plus beta times the market risk premium — and Jensen's alpha, the excess over what beta says the asset should earn; it also has a direct mode where you pass beta, market return and risk-free rate with no series. The treynor endpoint returns the Treynor ratio, the reward per unit of systematic (market) risk. This measures risk relative to a market — systematic risk — which is fundamentally different from single-series total-risk tools: it needs two series and answers how an asset moves with, and is priced against, the market. Works for any asset against any benchmark: stocks, funds, crypto, FX or a whole portfolio. Computed locally and deterministically, so it is instant and private. Ideal for portfolio analytics, factor and risk dashboards, fund fact-sheets and back-tests. Rates are fractions (0.02 = 2%). Live, nothing stored. 3 compute endpoints. For single-series Sharpe/volatility/drawdown use a risk-metrics API.

api.oanor.com/capm-api

Live dollar-cost-averaging analytics that investors run to see how periodic buying plays out — computed on demand from the price series you pass in, no key, nothing cached. Get the outcome of investing a fixed amount each period (total invested, units accumulated, average cost, current value, profit and ROI) with a lump-sum comparison; the per-period breakdown; and a ranking of dollar-cost averaging against lump-sum, best-case and worst-case timing. Works for any market — stocks, crypto, ETFs or forex. A dollar-cost-averaging engine, distinct from compound-interest and return-analysis tools: it turns a price path and a contribution into the cost basis and outcome of buying over time.

api.oanor.com/dca-api

Live Monte-Carlo simulation for price and portfolio forecasting that quants, traders and planners run to model uncertainty — computed on demand and reproducibly, no key, nothing cached. Run a geometric-Brownian-motion simulation of an asset and get the terminal-price distribution (percentiles, mean, probability of a gain); get the modelled chance of reaching a target price; project wealth over many years with periodic contributions (a retirement / savings projection); and return one sample price path for charting. Every run is seeded, so the same inputs always give the same numbers. A forward-looking simulation engine, distinct from historical-statistics and option-pricing tools — it turns a drift and volatility into a distribution of outcomes.

api.oanor.com/montecarlo-api

Live risk-adjusted-return analytics that quants and portfolio managers run on a return or price series — computed on demand, no key, nothing cached. Get the Sharpe ratio with annualised return and volatility; the Sortino ratio using downside deviation; periodic and annualised volatility, downside deviation and semivariance; and historical and parametric Value-at-Risk plus Conditional VaR (Expected Shortfall) at any confidence level. Every value is computed live from your input and works for any market — forex, stocks, crypto or funds. A risk-statistics engine, distinct from raw price feeds, from technical-indicator tools and from option-pricing tools: it turns a series of returns into the risk-adjusted performance numbers a strategy is judged on.

api.oanor.com/riskmetrics-api