Option Greeks
API · /blackscholes-api
Black-Scholes Options API
Black-Scholes-Merton European option pricing as an API, computed locally and deterministically. The price endpoint computes the fair value of a European call and put from the spot price, strike, annualized risk-free rate, annualized volatility, time to expiry in years and an optional continuous dividend yield, using Call = S·e^(−qT)·N(d1) − K·e^(−rT)·N(d2) and the put-call-parity put, with d1 = [ln(S/K) + (r − q + σ²/2)·T]/(σ√T) and d2 = d1 − σ√T and a high-accuracy standard-normal CDF — an at-the-money option on a 100 spot with a 5 % rate, 20 % volatility and one year to expiry is worth about 10.45 for the call and 5.57 for the put. The greeks endpoint returns the full risk sensitivities for both call and put: delta (∂V/∂S), gamma (∂²V/∂S²), vega (∂V/∂σ, per 1.00 and per 1 % point), theta (∂V/∂t, per year and per calendar day) and rho (∂V/∂r). Rates, dividend yield and volatility are annualized and time is in years, continuous compounding. Everything is computed locally and deterministically, so it is instant and private. Ideal for fintech, trading, quant, portfolio-risk, derivatives and finance-education app developers, option-pricing and Greeks dashboards, and risk engines. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 2 endpoints. This is the European Black-Scholes model; for American-style early exercise or implied volatility solving it returns the closed-form European result only.
API salute
salutare- Tempo di attività
- 100.00%
- Sondaggi del server · 24 ore su 24
- Latenza media
- 89 ms
- Sondaggi del server · 24 ore su 24
- Abbonati
- 3,807
- attiva
- Chiamate totali
- 21
- ultimi 7 giorni
Prezzi
Scegli un livello: fatturazione mensile, annullamento in qualsiasi momento.
Free
Gratis
- 2,500 chiamate/mese
- 2 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 2,500 calls/month
- 2 req/sec
- Call/put price + d1/d2
- No credit card
Starter
€12.00 /mese
- 25,000 chiamate/mese
- 6 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 25,000 calls/month
- 6 req/sec
- Full Greeks: delta/gamma/vega/theta/rho
- Email support
Pro
€35.00 /mese
- 130,000 chiamate/mese
- 15 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 130,000 llamadas/mes
- 15 req/seg
- Tuberías de trading y motor de riesgo
- Soporte prioritario
Mega
€110.00 /mese
- 850,000 chiamate/mese
- 40 richieste/secondo
- Tetto rigido (429 sopra la quota, nessuna eccedenza)
- 850,000 calls/month
- 40 req/sec
- Desk & platform scale
- Dedicated SLA
Costruito da
Correlato APIs
Altro APIs con tag sovrapposti.
Options Pricing API
Black-Scholes option-pricing maths as an API, computed locally and deterministically. The black-scholes endpoint prices European call and put options from the spot price, strike, time to expiry, risk-free rate, volatility and an optional dividend yield — Call = S·e^(−qT)·Φ(d1) − K·e^(−rT)·Φ(d2) — returning both prices, the intermediate d1 and d2, and the put-call parity figure. The greeks endpoint computes the full set of option sensitivities for the call and the put: delta, gamma, theta (per year and per day), vega and rho, the quantities traders use to hedge and manage risk. The implied-volatility endpoint inverts the model, solving by bisection for the volatility that reproduces a given option market price. Rates, volatilities and dividend yields are decimals (0.05 = 5 %) and time to expiry is in years. Everything is computed locally and deterministically, so it is instant and private. Ideal for fintech, trading, quantitative-finance and derivatives app developers, options analytics and risk tools, and finance education. Pure local computation — no key, no third-party service, instant. Live, nothing stored. 3 endpoints. This is options pricing; for NPV and IRR use an NPV API and for CAGR and real returns an investment API.
api.oanor.com/options-api
Elevator Traction API
Traction-elevator engineering maths as an API, computed locally and deterministically — the counterweight, hoist-motor and rope-traction numbers a lift engineer or building-services designer sizes a passenger elevator with. The counterweight endpoint gives the balancing mass = the empty car plus a fraction of the rated load (the overbalance, typically 40–50 %, 45 % common), so a 1,000 kg car rated for 1,000 kg uses a 1,450 kg counterweight — the car and weight balance near half load and the machine is sized for the worst-case imbalance, not the full load. The motor-power endpoint uses that: because the counterweight cancels most of the car, the motor only lifts the out-of-balance load = rated load × (1 − overbalance), so power = that × g × speed ÷ efficiency (~65–75 % geared) — a 1,000 kg lift at 1.5 m/s needs only about 11–12 kW, half what a counterweight-less hoist would draw. The traction-ratio endpoint checks the friction grip: a traction elevator moves the ropes by friction over the sheave, so the available traction (e^(μθ), the capstan equation) must beat the T1/T2 tension ratio at both worst cases — a full car at the bottom and an empty car at the top — and it returns the governing ratio. Everything is computed locally and deterministically, so it is instant and private. Ideal for lift-design and building-services tools, vertical-transport and MEP utilities, and engineering calculators. Pure local computation — no key, no third-party service, instant. Sizing estimates — follow the lift code and maker data. 3 compute endpoints. For block-and-tackle use a pulley API; for capstan friction a capstan API.
api.oanor.com/elevator-api
Railway Tractive Effort API
Railway train-performance maths as an API, computed locally and deterministically — the tractive-effort, resistance and adhesion numbers a railway engineer, train planner or rail-sim developer rates motive power with. The tractive-effort endpoint gives the pulling force a locomotive develops = 375 × horsepower × efficiency ÷ speed (mph), the classic hyperbolic curve where a constant-power loco pulls hardest at low speed and tapers as it accelerates — 4,000 hp at 25 mph and 82 % efficiency is about 49,200 lbf at the rail. The resistance endpoint gives the forces a train fights: grade resistance ≈ 20 lb per ton per 1 % of grade (the weight component along the slope, the dominant force on a hill — a 5,000-ton train on a 1 % grade fights 100,000 lbf) plus curve resistance ≈ 0.8 lb per ton per degree of curve from flange friction. The adhesion endpoint gives the hard ceiling: however much power a loco has, it can only pull as hard as the wheels grip — maximum starting tractive effort = the adhesion coefficient (≈ 0.25 dry, more with sand) × the weight on the driving wheels, so 200 tons on the drivers is about 100,000 lbf before slip. Everything is computed locally and deterministically, so it is instant and private. Ideal for rail-operations and motive-power planning tools, train-simulator and railfan apps, and transport-engineering utilities. Pure local computation — no key, no third-party service, instant. Excludes the speed-dependent Davis rolling/air resistance. 3 compute endpoints. For highway curve geometry use a horizontal-curve API.
api.oanor.com/railway-api
Sea Horizon API
Sea-horizon and visibility maths as an API, computed locally and deterministically — the distance-to-horizon, geographic-range and dip numbers a mariner, coastal navigator or marine app works sightings with. The horizon endpoint gives the distance to the sea horizon ≈ 1.169·√(height of eye in feet) nautical miles, including the standard atmospheric refraction that bends the line of sight a little past the geometric edge — at 9 ft of eye height the horizon is about 3.5 nm off — together with the dip, how far below true horizontal that watery edge lies (≈ 0.97′·√h), the correction subtracted from a sextant altitude shot to the sea horizon. The geographic-range endpoint gives how far off a light or landmark first peeps over the horizon = the sum of two horizon distances, your own plus the object's: 1.169·(√h_eye + √h_object), so a 100 ft lighthouse from a 9 ft cockpit lifts above the sea at about 15 nm — purely geometric, before the light's own luminous range and the visibility. The object-height endpoint inverts it: how tall a tower, light or headland must stand to break the horizon at a target range, or how close you must be before a known landmark appears. Everything is computed locally and deterministically, so it is instant and private. Ideal for marine-navigation and chartplotter apps, coastal-pilotage and lighthouse tools, and sailing utilities. Pure local computation — no key, no third-party service, instant. Geometric/refraction model. 3 compute endpoints. For great-circle distance use a geo-distance API; for set & drift a set-and-drift API.
api.oanor.com/horizon-api
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Frammenti di codice
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curl https://api.oanor.com/blackscholes-api/SOME_PATH \
-H "x-oanor-key: oanor_test_..."
const res = await fetch("https://api.oanor.com/blackscholes-api/SOME_PATH", {
headers: { "x-oanor-key": "oanor_test_..." }
});
const data = await res.json();
$ch = curl_init("https://api.oanor.com/blackscholes-api/SOME_PATH");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_HTTPHEADER, ["x-oanor-key: oanor_test_..."]);
$response = curl_exec($ch);
import requests
r = requests.get(
"https://api.oanor.com/blackscholes-api/SOME_PATH",
headers={"x-oanor-key": "oanor_test_..."},
)
print(r.json())
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