79 Services from api.quantoracle.dev

Runs Monte Carlo simulations on a portfolio to project terminal value distributions, probability of ruin/loss/doubling, and sample price paths over a specified horizon.

Computes risk-parity portfolio weights given asset volatilities and a correlation matrix, equalizing each asset's risk contribution

Calculates Compound Annual Growth Rate (CAGR) from start/end values over a time period, with optional future-value projections and doubling time

Recommends optimal hedging strategies (collar, protective put, futures, etc.) for a stock or asset position given risk parameters and cost constraints

Fits a dataset to multiple statistical distributions (uniform, normal, lognormal, etc.) and returns the best-fit distribution along with parameters, KS statistics, log-likelihood, and descriptive statistics.

Calculates an optimal set of trades to rebalance a crypto portfolio toward target allocation weights, minimizing drift and transaction costs

Computes parametric VaR and CVaR for a portfolio at specified confidence levels given a series of historical returns

Analyzes a leveraged crypto position to compute VaR, CVaR, Kelly criterion leverage, liquidation price, and risk flags given returns history and position parameters

Fits a polynomial regression model of a specified degree to X/Y data and returns coefficients, predictions, and model quality statistics (R², AIC, BIC, MSE).

Creates a real-time liquidation-risk and funding-rate monitor for a crypto derivatives position, delivering alerts via webhook or polling

Prices American or European options using a binomial tree model and returns fair value, Greeks (delta), and early exercise premium versus Black-Scholes.

Computes detailed transaction cost breakdown for a trade including spread cost, market impact, commission, round-trip cost, and breakeven move percentage

Calculates Net Present Value (NPV) of a series of cash flows at a given discount rate, with investment decision recommendation

Calculates covered or uncovered interest rate parity, detects FX mispricing, and identifies arbitrage opportunities between forward and theoretical forward rates.

Fits an ordinary least squares linear regression to x/y data and returns coefficients, R-squared, p-values, t-statistics, F-statistic, and confidence-interval diagnostics.

Calculates put-call parity deviation for European options, identifies arbitrage signals, and determines whether parity holds given market prices.

Prices European options using Black-Scholes and returns the full Greeks suite, breakeven, intrinsic/time value, and probability ITM

Prices arithmetic or geometric Asian options using Monte Carlo or closed-form methods, returning fair value and equivalent volatility

Computes z-scores, rolling z-scores, and detects statistical outliers/extremes in a numeric time series with a configurable window and threshold

Computes a month-by-month token vesting schedule given TGE percentage, cliff, linear/custom vesting parameters, and total supply

Calculates the present value of an annuity or lump sum using time-value-of-money discounting, given a periodic payment, interest rate, number of periods, and payment timing.

Optimizes a multi-asset portfolio's weight allocation using mean-variance analysis (e.g. max Sharpe ratio) given historical return series and a risk-free rate

Computes comprehensive portfolio risk metrics including Sharpe, Sortino, VaR, CVaR, max drawdown, alpha/beta, and return distribution statistics from a return series

Computes a suite of technical indicators (RSI, EMA, SMA, ATR, Bollinger Bands, ROC, Stochastic K) and trend signals from a price/volume series

Computes a comprehensive suite of portfolio risk and performance metrics from a series of returns, including Sharpe, Sortino, Calmar, VaR, CVaR, max drawdown, Kelly criterion, Hurst exponent, CAGR, and win rate.

Computes the Average True Range (ATR) volatility indicator for a given price series, returning current ATR value, ATR percentage, ATR series, and volatility regime classification.

Computes multiple realized volatility measures (Parkinson, Yang-Zhang, Garman-Klass, Close-to-Close) from OHLC price data with annualization

Computes Bollinger Bands (upper, middle, lower bands), bandwidth, %B, and trading signal for a given price series

Computes a pairwise correlation matrix and annualized volatilities for multiple asset return series

Prices floating or fixed lookback options using the underlying asset price, historical minimum/maximum, volatility, and time parameters

Computes the future value of a lump sum or annuity given an interest rate, number of periods, and present value

Computes EMA crossover signal (BULLISH/BEARISH) between a fast and slow exponential moving average from a price series

Prices barrier options (knock-in/knock-out) with full Greeks, comparing against vanilla option price and computing the discount

Calculates Kelly Criterion position sizing (full, half, and quarter Kelly fractions) given win rate, average win, average loss, and mode

Prices a fixed-income bond and returns key risk metrics including price, yield to maturity, duration, convexity, and DV01

Computes the Internal Rate of Return (IRR) for a series of cash flows, returning the periodic rate, annualized percentage, NPV at IRR, and investment summary statistics.

Computes the Taylor Rule prescribed interest rate given inflation, output gap, and neutral rate inputs

Computes normal distribution statistics including PDF, CDF, z-score, quantile, survival function, and confidence intervals for given mean, standard deviation, and value inputs

Calculates impermanent loss for AMM liquidity providers given an initial investment, initial price ratio, and current price ratio, returning LP value, hold value, loss amount, loss percentage, and fee breakeven APY.

Computes the annualized Sharpe ratio from a series of returns, including confidence intervals, standard error, excess return, and volatility statistics.

Computes maximum drawdown, current drawdown, and underwater percentage from an equity curve

Computes a Pearson (or other method) correlation matrix and covariance matrix for multiple numeric time series, with optional eigenvalue decomposition

Tests whether two time series are cointegrated using the Engle-Granger/ADF method, returning hedge ratio, spread statistics, z-score, half-life, and critical values

Classifies market regime (trend, volatility, risk) from a price series and returns RSI, SMA, trend direction, and a suggested strategy.

Computes the real yield from a nominal yield and inflation expectation for a given bond tenor, using both simple and Fisher equation methods

Calculates the implied volatility of an options contract from its market price using iterative numerical methods

Computes a full loan amortization schedule with optional extra payments, returning month-by-month balances, interest, principal breakdown, and total interest saved

Calculates optimal position size, share count, risk exposure, and 2R target price given entry price, stop loss, account size, and risk percentage per trade

Computes year-by-year real vs. nominal value series for an investment given an inflation rate and nominal return, using the Fisher equation

Computes FX carry trade P&L, spot/carry returns, levered returns, annualized total return, and breakeven depreciation for a currency position given entry/exit prices and interest rate differentials.

Calculates DEX trade slippage, price impact, output amount, and effective price for an AMM swap given pool reserves, trade size, fee, and direction

Calculates the liquidation price for a leveraged crypto position given entry price, collateral, position size, leverage, direction, and maintenance margin rate

Calculates the PPP-adjusted exchange rate and overvaluation/undervaluation percentage given a base spot rate and inflation differentials over a time horizon

Computes the Probabilistic Sharpe Ratio (PSR) — a statistically adjusted Sharpe that accounts for non-normality of returns, with significance tests and minimum track record length.

Runs stress-test scenarios on a financial portfolio to estimate potential losses and risk exposures under adverse market conditions

Computes the Hurst exponent for a time series to measure long-range dependence, mean-reversion tendency, or trending behavior in financial data.

Computes and returns payoff diagram data for options strategies, showing profit/loss curves across a range of underlying prices at expiry.

Returns real-time volatility metrics for a given crypto asset (USD pair) such as BTC, ETH, or SOL

Fits a GARCH model to a time series of returns and forecasts future volatility (conditional variance) over a specified horizon

Returns real-time perpetual futures funding rates for a specified crypto asset (USDT perp)

Scans options markets to identify and evaluate spread opportunities (e.g. vertical, calendar, diagonal spreads) given underlying assets and parameters

Computes or retrieves the funding rate for a specified cryptocurrency perpetual futures contract

Calculates optimal rebalancing threshold percentages for a cryptocurrency portfolio to minimize drift and transaction costs

Computes a full implied volatility surface across strikes and expiries for a given derivatives underlying

Optimizes multi-leg options strategies by analyzing risk/reward profiles, Greeks, and market conditions to recommend the best structure for a given objective

Analyzes an options chain for a given underlying asset, computing Greeks, implied volatility surface, and pricing metrics across strikes and expirations

Interpolates missing or custom-maturity rates from a given set of bond/rate yield curve data points

Generates or evaluates an options trading strategy based on the provided underlying asset, market conditions, and risk parameters

Calculates the theoretical forward exchange rate between two currencies given spot rate, interest rate differentials, and a tenor/maturity period

Computes Fibonacci retracement levels for a given price range to identify potential support and resistance zones for technical analysis

Analyzes the overall health of a financial portfolio, returning risk metrics, diversification scores, and actionable diagnostics.

Converts between Annual Percentage Yield (APY) and Annual Percentage Rate (APR) for crypto financial calculations, accounting for compounding frequency.

Computes the credit spread between a corporate or structured instrument and a risk-free benchmark given bond/issuer inputs

Runs a quantitative backtesting simulation on a given trading strategy against historical data and returns performance metrics

Evaluates a trade signal or proposed trade for quantitative merit, risk-adjusted return potential, and execution viability

Detects and labels the current market regime (e.g. trending, mean-reverting, volatile) from a time-series of price or return data

Generates a trading signal (buy/sell/hold) for a specified asset pair based on quantitative analysis

Executes multiple QuantOracle quantitative finance computations in a single batched API call

Extends the active duration of a QuantOracle financial data watch or subscription session