stochastic-rs 2.2.0

A Rust library for quant finance and simulating stochastic processes.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160

---
title: Quantitative finance
description: Pricing, calibration, vol surface, risk, credit, curves, bonds, instruments, portfolio, microstructure — the stochastic-rs-quant crate.
category: pricer
since: 2.0.0
status: stable
---

# Quantitative finance

The `stochastic-rs-quant` crate is the largest sub-crate. It covers
pricing, calibration, vol surface construction, risk, credit, yield
curves, bonds, cashflows, instruments, portfolio, microstructure, and
factor / strategy primitives.

## Sub-areas

| Area               | What's inside                                                                                              |
|--------------------|------------------------------------------------------------------------------------------------------------|
| **Pricing**        | Closed-form (BSM, Bachelier, Black76, Garman-Kohlhagen, Margrabe, Kirk, Geske compound, Stulz, Bjerksund-Stensland, digital / gap / supershare, geometric basket, Levy moment-matching, cliquet / forward-start chain). Fourier (Carr-Madan, Lewis, Gil-Pelaez) for Heston / Bates / Merton-jump / Kou / VG / CGMY / HKDE / double-Heston. Monte Carlo (basket, rainbow, cliquet, autocallable, spread). Finite difference (explicit / implicit / Crank-Nicolson, American). Bermudan LSM. Heston SLV (Guyon-Labordère). |
| **Calibration**    | Heston (Cui analytic Jacobian + NMLE / PMLE / NMLE-CEKF seeds), SABR per-expiry caplet smile, Lévy (CGMY, VG, NIG, Merton-jump, Kou, bilateral gamma), SVJ, rough Bergomi, double-Heston, BSM (multi-maturity), HKDE, Hull-White swaption-grid via Levenberg-Marquardt. |
| **Vol surface**    | Implied-vol surface from market quotes, SVI / SSVI, arbitrage-free interpolation, smile and skew analytics, SABR-smile fits.                                                |
| **Risk**           | VaR (Gaussian / historical / Monte Carlo), CVaR / ES, drawdown metrics, Sharpe / Sortino / IR / Calmar (no hard-coded annualisation), instrument-level Greeks, bucket DV01, scenario / shock / curve-shift stress framework. |
| **Credit**         | Merton structural model (PD, equity / debt, distance-to-default, credit spread, implied recovery), reduced-form survival / hazard curves, CDS pricing (ISDA daily-grid, fair spread, risky PV01), hazard bootstrap from CDS par-spread term structure, JLT migration matrices with pure-Rust Padé-13 matrix exponential. |
| **Yield curves**   | Bootstrapping (deposit / FRA / future / swap), Nelson-Siegel / Svensson, multi-curve (OIS vs SOFR), discount-curve interpolation (linear / log-linear / cubic / monotone-convex). |
| **Bonds**          | Fixed-rate / floating-rate / inflation-linked / amortizing bonds. YTM / Macaulay / modified duration / convexity / Z-spread / OAS. Vasicek / CIR / Hull-White short-rate bond pricing. |
| **Cashflows**      | Coupon, leg, engine, schedule builder. Day-count + business-day conventions.                               |
| **Instruments**    | Option (vanilla / barrier / Asian / lookback / digital), bond, swap, equity. Plus the QuantLib-style `Instrument` / `PricingEngine` decoupling. |
| **Portfolio**      | Covariance estimation (sample, Ledoit-Wolf, OAS), momentum, optimisers (mean-variance, MVO with constraints).                                                                                                              |
| **Microstructure** | Almgren-Chriss optimal execution, Kyle (1985) strategic-trading equilibria, Bouchaud propagator (power-law / exponential / custom kernels), Roll / Corwin-Schultz spread estimators, full price-time priority order book.                                                                              |
| **Factors**        | PCA, two-pass Fama-MacBeth, Ledoit-Wolf shrinkage.                                                          |
| **Strategies**     | Cointegrated pairs trading (hedge ratio, spread, z-score, signal generator), forecast-momentum-volatility regime engine, delta hedge.                                       |
| **Inflation**      | Zero-coupon and YoY inflation curves, CPI / RPI / HICP indices with linear-interpolated reference ratio, ZC and YoY inflation swaps with par-rate solver.                |
| **FX**             | ISO 4217 currency definitions, FX quoting / cross-rate / triangulation, FX forward via covered interest parity (continuous and simple compounding).                                                                            |
| **Calendar**       | ACT/360, ACT/365, 30/360, ACT/ACT day-counts. Following / Modified Following / Preceding business-day adjustments. US, UK, TARGET, Tokyo holiday calendars. Pluggable `CalendarExt`. `ScheduleBuilder` for coupon / payment dates.                                |

## Examples

### Black-Scholes-Merton — closed-form European call

<Tabs items={['Rust', 'Python']}>
<Tab value="Rust">
```rust
use stochastic_rs::prelude::*;
use stochastic_rs::quant::pricing::bsm::BsmPricer;

let pricer = BsmPricer::<f64>::new(
    /* s0 */ 100.0, /* k */ 100.0, /* tau */ 1.0,
    /* r */ 0.05, /* q */ 0.0, /* sigma */ 0.2,
);
let call = pricer.price(OptionType::Call);
let put  = pricer.price(OptionType::Put);
let g    = pricer.greeks(OptionType::Call);
println!("call={:.4}, put={:.4}, delta={:.4}, vega={:.4}",
         call, put, g.delta, g.vega);
```
</Tab>
<Tab value="Python">
```python
import stochastic_rs as srs

pricer = srs.BsmPricer(s0=100, k=100, tau=1.0, r=0.05, q=0.0, sigma=0.2)
print("call =", pricer.price("call"))
print("put  =", pricer.price("put"))

g = pricer.greeks("call")
print(f"delta={g.delta:.4f}, gamma={g.gamma:.4f}, vega={g.vega:.4f}, "
      f"theta={g.theta:.4f}, rho={g.rho:.4f}")
```
</Tab>
</Tabs>

### Heston — Fourier pricer with Cui analytic Jacobian

<Tabs items={['Rust', 'Python']}>
<Tab value="Rust">
```rust
use stochastic_rs::quant::pricing::heston::HestonPricer;
use stochastic_rs::quant::types::OptionType;
use stochastic_rs::traits::{ModelPricer, GreeksExt};

let pricer = HestonPricer::<f64>::new(
    /* s0 */ 100.0, /* k */ 100.0, /* tau */ 1.0,
    /* r */ 0.03, /* q */ 0.0,
    /* v0 */ 0.04, /* kappa */ 2.0, /* theta */ 0.04,
    /* sigma */ 0.3, /* rho */ -0.5,
);
let price = pricer.price(OptionType::Call);
let g = pricer.greeks(OptionType::Call);
println!("call={:.4}, delta={:.4}, vega={:.4}, vanna={:.4}",
         price, g.delta, g.vega, g.vanna);
```
</Tab>
<Tab value="Python">
```python
import stochastic_rs as srs

pricer = srs.HestonPricer(
    s0=100, k=100, tau=1.0, r=0.03, q=0.0,
    v0=0.04, kappa=2.0, theta=0.04, sigma=0.3, rho=-0.5,
)
price = pricer.price("call")
g = pricer.greeks("call")
print(f"call={price:.4f}, delta={g.delta:.4f}, vega={g.vega:.4f}")
```
</Tab>
</Tabs>

### Heston calibration to a market vol surface

<Tabs items={['Rust', 'Python']}>
<Tab value="Rust">
```rust
use stochastic_rs::quant::calibration::heston::HestonCalibrator;
use stochastic_rs::quant::vol_surface::implied::ImpliedVolSurface;
use stochastic_rs::traits::Calibrator;

let surface = ImpliedVolSurface::<f64>::from_market(
    &strikes, &expiries, &iv_grid, /* spot */ 100.0,
);
let result = HestonCalibrator::<f64>::new(&surface).calibrate()?;

let p = result.params;
println!("kappa={:.3}, theta={:.4}, sigma={:.3}, rho={:.3}, v0={:.4}",
         p.kappa, p.theta, p.sigma, p.rho, p.v0);
println!("RMSE = {:.6} ({} iters)", result.rmse, result.iterations);
```
</Tab>
<Tab value="Python">
```python
import stochastic_rs as srs

surface = srs.ImpliedVolSurface.from_market(
    strikes=strikes, expiries=expiries, iv_grid=iv_grid, spot=100.0,
)
res = srs.HestonCalibrator(surface).calibrate()
print(f"kappa={res.params.kappa:.3f}, theta={res.params.theta:.4f}, "
      f"sigma={res.params.sigma:.3f}, rho={res.params.rho:.3f}, "
      f"v0={res.params.v0:.4f}")
print(f"RMSE = {res.rmse:.6f} ({res.iterations} iters)")
```
</Tab>
</Tabs>

## Trait overview

The relevant traits live in [Concepts](/docs/concepts):

- [`PricerExt` / `ModelPricer`](/docs/concepts/pricer-ext)
- [`Calibrator`, `CalibrationResult`, `ToModel`](/docs/concepts/traits#calibrator-t-and-calibrationresult)
- [Greeks aggregator](/docs/concepts/traits#greeksext-and-the-greeks-aggregator)

## Adding a pricer / calibrator

- [`calibration-pattern`](https://github.com/dancixx/stochastic-rs/blob/main/.claude/skills/calibration-pattern/SKILL.md)
  — Heston / SABR / SVI / Lévy calibrators
- [`greeks-pattern`](https://github.com/dancixx/stochastic-rs/blob/main/.claude/skills/greeks-pattern/SKILL.md)
  — exposing first- + second-order Greeks
- [`add-mc-variance-reduction`](https://github.com/dancixx/stochastic-rs/blob/main/.claude/skills/add-mc-variance-reduction/SKILL.md)
  — antithetic / control-variate / quasi-MC / MLMC