DEV Community: Ab Mughal

Confidential Computing Architecture: AMD SEV-SNP Reverse Map Tables vs. Intel TDX DRAM Encryption

Ab Mughal — Fri, 23 Oct 2026 17:21:30 +0000

Canonical Research Note: Originally published by the TrendSpike Institutional Systems & Quantitative Finance Desk. Full AES-128-XTS physical address tweak equations and RMP/S-EPT architectural comparisons are available in the primary publication.

Eliminating the Hypervisor from the Cloud Trusted Computing Base (TCB)

Modern Confidential VMs rely on inline AES-128-XTS memory controller cryptography and hardware Reverse Map Tables (RMP) to prevent privileged hypervisor memory inspection and page-table remapping attacks.

Read the complete microprocessor security breakdown at the TrendSpike Research Desk.

0DTE Index Options Microstructure: Dealer Gamma Exposure (GEX), Vanna, and Charm Flows in Python

Ab Mughal — Thu, 22 Oct 2026 19:24:26 +0000

Canonical Research Note: Originally published by the TrendSpike Institutional Systems & Quantitative Finance Desk. Full Black-Scholes-Merton second-order Greek derivations and dealer hedging matrices are available in the primary publication.

Python Implementation: Black-Scholes 0DTE Gamma, Vanna & Charm Engine


python
import math

def norm_pdf(x: float) -> float:
    return math.exp(-0.5 * x * x) / math.sqrt(2.0 * math.pi)

def compute_0dte_greeks(spot: float, strike: float, iv: float, minutes_left: float, rate: float = 0.05) -> dict:
    tau = max(minutes_left / (252.0 * 390.0), 1e-6)
    sqrt_tau = math.sqrt(tau)
    d1 = (math.log(spot / strike) + (rate + 0.5 * iv * iv) * tau) / (iv * sqrt_tau)
    d2 = d1 - iv * sqrt_tau
    pdf_d1 = norm_pdf(d1)

    gamma = pdf_d1 / (spot * iv * sqrt_tau)
    vanna = -pdf_d1 * (d2 / iv)
    charm = pdf_d1 * ((2.0 * rate * tau - d2 * iv * sqrt_tau) / (2.0 * tau * iv * sqrt_tau))

    return {
        "gamma": round(gamma, 6),
        "vanna": round(vanna, 6),
        "charm_daily": round(charm / 252.0, 6),
    }

Equity Index Futures Microstructure: Cost-of-Carry Arbitrage, Implied Repo Bounds, and CME SPAN 2 VaR

Ab Mughal — Tue, 20 Oct 2026 22:38:27 +0000

Canonical Research Note: Originally published by the TrendSpike Institutional Systems & Quantitative Finance Desk. Full mathematical proofs, CME SPAN 2 clearing tables, and statutory 26 U.S.C. § 1256 tax accounting breakdowns are available in the primary publication.

1. Continuous-Time Cost-of-Carry Fair Value Pricing

Exchange-traded equity index futures (/ES, /NQ, /RTY) cleared on electronic central limit order books (CLOBs) are tethered to the underlying spot index ($S_t$) via continuous-time financing ($r_{\text{SOFR}}$) and constituent dividend yield ($q$) arbitrage bounds:

$$F_{t,T}^{*} = S_t \cdot e^{(r_{\text{SOFR}} - q)\tau}$$

Whenever pre-market macroeconomic releases drive the live futures price ($F_{\text{mkt}}$) outside the transaction-cost no-arbitrage band ($C_{\text{arb}}$), quantitative index arbitrage desks execute simultaneous Cash-and-Carry baskets at the 9:30 AM ET opening cross.

2. Python Reference Implementation: Implied Repo Rate & Basis Engine

From our open-source repository (abmughl/institutional-systems-and-quant-research):


python
import math
from dataclasses import dataclass

@dataclass
class IndexFuturesContract:
    symbol: str
    spot_index: float
    sofr_rate: float
    dividend_yield: float
    days_to_expiry: int
    market_futures_price: float

def compute_futures_fair_value(contract: IndexFuturesContract) -> dict:
    tau = contract.days_to_expiry / 360.0
    fair_value = contract.spot_index * math.exp(
        (contract.sofr_rate - contract.dividend_yield) * tau
    )
    basis_spread = contract.market_futures_price - fair_value
    forward_dividends = contract.spot_index * contract.dividend_yield * tau
    implied_repo = (
        (contract.market_futures_price + forward_dividends - contract.spot_index)
        / contract.spot_index
    ) * (360.0 / contract.days_to_expiry)

    return {
        "symbol": contract.symbol,
        "theoretical_fair_value": round(fair_value, 2),
        "basis_spread_pts": round(basis_spread, 2),
        "implied_repo_rate_pct": round(implied_repo * 100, 4),
        "irc_1256_blended_tax_rate_pct": round((0.60 * 20.0) + (0.40 * 37.0), 2),
    }