1162 lines
30 KiB
JSON
1162 lines
30 KiB
JSON
{
|
|
"schema_version": 1,
|
|
"command": "python benchmarks/bench_derivatives_compare.py --sizes 1000 10000 --accuracy-size 512 --json benchmarks/artifacts/latest/benchmark_derivatives_compare.json",
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|
"n_warmup": 1,
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"n_runs": 7,
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|
"accuracy_size": 512,
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|
"sizes": [
|
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1000,
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|
10000
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|
],
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"metadata": {
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|
"suite": "benchmark_derivatives_compare",
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|
"runtime": {
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"generated_at_utc": "2026-03-24T05:39:25.642936+00:00",
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"python_version": "3.13.5",
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|
"python_implementation": "CPython",
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|
"python_executable": "/Users/pratikbhadane/Work/Projects/ferro-ta/.venv/bin/python3",
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"platform": "macOS-26.3.1-arm64-arm-64bit-Mach-O",
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|
"system": "Darwin",
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"release": "25.3.0",
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"machine": "arm64",
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"processor": "arm",
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"cpu_model": "Apple M3 Max",
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"cpu_count_logical": 14,
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"total_memory_bytes": 38654705664
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},
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"git": {
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"commit": "0382c4e3024c96809ffd89dd76d820efcd56479d",
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"dirty": true,
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"branch": "main"
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},
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"build": {
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"rustc": "rustc 1.91.1 (ed61e7d7e 2025-11-07) (Homebrew)\nbinary: rustc\ncommit-hash: ed61e7d7e242494fb7057f2657300d9e77bb4fcb\ncommit-date: 2025-11-07\nhost: aarch64-apple-darwin\nrelease: 1.91.1\nLLVM version: 21.1.5",
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"cargo": "cargo 1.91.1 (Homebrew)",
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"cargo_release_profile": {
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"lto": true,
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"codegen-units": 1
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},
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"rustflags": null,
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"cargo_build_rustflags": null,
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"maturin_flags": null
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},
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"packages": {
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"numpy": "2.2.6",
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"ferro-ta": "1.0.3",
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"py_vollib": null
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},
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"dataset": {
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"generator": "synthetic_option_chain",
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"speed_sizes": [
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1000,
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10000
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|
],
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"accuracy_size": 512,
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"dtype": "float64",
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"array_layout": "C-contiguous",
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"seed": 42,
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"ranges": {
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"spot": [
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80.0,
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120.0
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],
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"strike": [
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70.0,
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130.0
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],
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"rate": [
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0.0,
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0.07
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],
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"carry": [
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0.0,
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0.03
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],
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"time_to_expiry_years": [
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0.019178082191780823,
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2.0
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],
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"volatility": [
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0.08,
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0.65
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]
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}
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},
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"methodology": {
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"warmup_runs": 1,
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"measured_runs": 7,
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"reported_metric": "median_ms",
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|
"speed_metric": "contracts_per_second",
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"accuracy_reference": "Scalar analytical Black-Scholes-Merton and Black-76 formulas using math.erf; IV accuracy is measured as repriced error from the recovered volatility because direct volatility differences can be unstable on low-vega contracts.",
|
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"input_layout_notes": "Benchmarks use contiguous float64 arrays. If your workload passes non-contiguous arrays or mixed dtypes, benchmark that path separately.",
|
|
"allocation_notes": "python_peak_allocation_bytes is a tracemalloc snapshot of Python-tracked allocations only; it does not measure native RSS.",
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|
"provider_notes": "reference_python_loop and py_vollib are scalar baselines and are size-capped in the speed table to keep runtime reasonable."
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},
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"providers": [
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{
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"name": "ferro_ta",
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"kind": "project",
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"note": "Rust-backed vectorized implementation.",
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"max_speed_size": null,
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"supported_cases": [
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"bsm_call_price",
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"bsm_call_iv",
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"bsm_call_greeks",
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"black76_call_price"
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]
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},
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{
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"name": "reference_numpy",
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"kind": "reference",
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"note": "Pure NumPy analytical formulas with vectorized IV bisection.",
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"max_speed_size": null,
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"supported_cases": [
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"bsm_call_price",
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"bsm_call_iv",
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"bsm_call_greeks",
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"black76_call_price"
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]
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},
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{
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"name": "reference_python_loop",
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"kind": "reference",
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"note": "Scalar math-loop analytical baseline; useful for accuracy sanity checks.",
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"max_speed_size": 1000,
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"supported_cases": [
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"bsm_call_price",
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"bsm_call_iv",
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"bsm_call_greeks",
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"black76_call_price"
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]
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}
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]
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},
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"accuracy": {
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"summary": [
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{
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"case": "bsm_call_price",
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"best_provider": "reference_python_loop",
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"best_max_abs_error": 0.0,
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"worst_provider": "ferro_ta",
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"worst_max_abs_error": 1.6274806e-05
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},
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{
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"case": "bsm_call_iv",
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"best_provider": "reference_python_loop",
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"best_max_abs_error": 1e-10,
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"worst_provider": "reference_numpy",
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"worst_max_abs_error": 1.6276264e-05
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},
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{
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"case": "bsm_call_greeks",
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"best_provider": "reference_python_loop",
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"best_max_abs_error": 0.0,
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"worst_provider": "ferro_ta",
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"worst_max_abs_error": 1.7335858e-05
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},
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{
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"case": "black76_call_price",
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"best_provider": "reference_python_loop",
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"best_max_abs_error": 0.0,
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"worst_provider": "ferro_ta",
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"worst_max_abs_error": 1.6274806e-05
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}
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],
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"results": [
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{
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"case": "bsm_call_price",
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"label": "BSM Call Price",
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"provider": "ferro_ta",
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"provider_kind": "project",
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"sample_size": 512,
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"accuracy_target": "expected_output",
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"output_shape": [
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512
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],
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"max_abs_error": 1.6274806e-05,
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"mean_abs_error": 5.249347e-06,
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"rmse": 6.48942e-06,
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"max_rel_error": 0.009546518154
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},
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{
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"case": "bsm_call_price",
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"label": "BSM Call Price",
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"provider": "reference_numpy",
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512
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},
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{
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"case": "bsm_call_price",
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"label": "BSM Call Price",
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"provider": "reference_python_loop",
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"provider_kind": "reference",
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"sample_size": 512,
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512
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],
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"rmse": 0.0,
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"max_rel_error": 0.0
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},
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{
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"case": "bsm_call_iv",
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"label": "BSM Call IV Recovery",
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"provider": "ferro_ta",
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"provider_kind": "project",
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"sample_size": 512,
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"accuracy_target": "reconstructed_price",
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"output_shape": [
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512
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],
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"max_rel_error": 0.475843909884
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},
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{
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"case": "bsm_call_iv",
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"label": "BSM Call IV Recovery",
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"provider": "reference_numpy",
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"provider_kind": "reference",
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"accuracy_target": "reconstructed_price",
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"output_shape": [
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512
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],
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"max_rel_error": 0.009628987742
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},
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{
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"case": "bsm_call_iv",
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"label": "BSM Call IV Recovery",
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"provider": "reference_python_loop",
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"provider_kind": "reference",
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"sample_size": 512,
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"accuracy_target": "reconstructed_price",
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"output_shape": [
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512
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],
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"rmse": 5.3e-11,
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"max_rel_error": 0.00547208151
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},
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{
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"case": "bsm_call_greeks",
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"label": "BSM Call Greeks",
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"provider_kind": "project",
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"output_shape": [
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512,
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5
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],
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"rmse": 2.444399e-06,
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"max_rel_error": 0.002644156321,
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"component_names": [
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"delta",
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"gamma",
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"vega",
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"theta",
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"rho"
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]
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},
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{
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"case": "bsm_call_greeks",
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"label": "BSM Call Greeks",
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512,
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5
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],
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]
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},
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{
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"case": "bsm_call_greeks",
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"label": "BSM Call Greeks",
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"provider": "reference_python_loop",
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"provider_kind": "reference",
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"sample_size": 512,
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"accuracy_target": "expected_output",
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512,
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5
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"vega",
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"theta",
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"rho"
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]
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},
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{
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"case": "black76_call_price",
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"label": "Black-76 Call Price",
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},
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{
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"case": "black76_call_price",
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"label": "Black-76 Call Price",
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"provider": "reference_numpy",
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"provider_kind": "reference",
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512
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},
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{
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"case": "black76_call_price",
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"label": "Black-76 Call Price",
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"provider": "reference_python_loop",
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512
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