from dataclasses import dataclass, field
@dataclass(frozen=True)
class JayantSingh:
role: str = "Quantitative Developer & Researcher"
thesis: str = "Every model is wrong. The tradeable ones are hedgeable."
focus: list = field(default_factory=lambda: [
"derivatives pricing & greeks", # closed-form · lattice · PDE · Monte Carlo
"volatility surfaces & term structure",
"systematic strategy research & backtesting",
"risk analytics: VaR · expected shortfall · stress",
"market microstructure & execution cost",
])
builds: str = "Pricing engines, risk dashboards and econometric studies — in public."
offline: str = "Reading, gaming, and hiking somewhere with no market data."
def __repr__(self) -> str:
return "<models that survive contact with transaction costs>"core/
quant/ — numerics, econometrics, backtesting
data/
interface/ — dashboards, apps, reporting
ops/
validation: "A Greek that isn't checked against a finite difference is a guess."
costs: "Any strategy without transaction costs is a plot, not a P&L."
overfitting: "Purged CV, deflated Sharpe, PBO — or the backtest doesn't count."
reproducible: "Seeded, versioned, containerised. It runs on your machine too."
speed: "Prototype in Python. Vectorise. Profile. Drop to C++ where it pays."
