1. Market Regime Snapshot

VIX Term Structure

Tenor Level vs. Spot
VIX Spot 15.0 —
VIX 3M 18.6 +3.5 (Contango)

Realized vs. Implied Vol: SPY 20D RV = 14.8%, VIX = 15.0. Spread = -0.3pp (realized vol below implied — calmer than feared).

Cross-Asset Momentum (1-Month)

Asset 1M Return Signal
SPY (Equity) +4.3% 📈 Positive
TLT (Bonds) -0.1% 📉 Negative
GLD (Gold) +0.6% 📈 Positive
UUP (US Dollar) +1.2% 📈 Positive

Regime: Mixed/transitional regime

Last updated: 2026-07-12 10:27 UTC

2. Factor Performance Dashboard

Source: ETF Proxies (MTUM, VLUE, QUAL, USMV, IWM vs SPY)

Note: ETF proxy returns include market beta and are not directly comparable to factor-neutral French library returns.

Factor Weekly 1M 3M Mean (52W wkly) Std (52W wkly) Z
Momentum +1.66% +3.37% +22.76% +0.62% 2.56% +0.41
Value +1.24% +0.64% +28.29% +1.07% 2.51% +0.07
Quality +0.58% +2.78% +9.90% +0.35% 1.55% +0.14
Low Volatility -0.13% +2.60% +4.48% +0.11% 1.16% -0.21
Size -1.87% +1.32% +1.80% +0.19% 1.57% -1.31

No factor stress signals this week (all within ±2σ).

Last updated: 2026-07-12 10:27 UTC

3. Macro Signal Tracker

Indicator Current 1W Change Signal
HY Spread (OAS) 270bps -5bps ✅ Tightening
IG Spread (OAS) 76bps +1bps ⚠️ Widening
2s10s Yield Curve 0.35% +0.00% Normal
3M10Y Yield Curve 0.71% +0.04% Normal
Fed Funds Rate 3.63% N/A →
HY − IG Spread 194bps — Risk sentiment proxy

Macro Summary: Risk-on macro backdrop

Last updated: 2026-07-12 10:27 UTC

4. Quant Research Digest

Three papers I found worth reading this week:

Estimating the Stochastic Discount Factor from Option Prices and Predicting the Equity Premium — Kenichiro Shiraya et al. arXiv

The authors use S&P 500 option data to isolate a stable, time-varying volatility scaled Stochastic Discount Factor (SDF) that smooths out observation noise. It is a really clean mathematical approach to recovering forward-looking expectations without letting empirical market noise mess up the core asset pricing signal.

Iterative detection of global factors near the BBP phase transition — Andrés García-Medina arXiv

This paper deals with the classic issue of signal-to-noise separation in high-dimensional correlation matrices when you have limited data observations. It offers a solid random matrix theory perspective on trying to spot weak global factors right near the Marčenko–Pastur spectral edge where they usually get hidden by random noise.

tsbootstrap: Distribution-Free Uncertainty Quantification and Conformal Prediction for Time Series — Sankalp Gilda arXiv

This introduces an open-source library that combines time-series resampling methods (like block and sieve bootstrapping) with adaptive conformal prediction. It is a highly practical coding resource for anyone trying to build distribution-free confidence intervals for non-stationary, dependent data streams.

Last updated: 2026-07-12 10:27 UTC

5. Stat of the Week

Stat Value Context
CBOE Skew Index 144 Elevated tail risk (>130)

The Skew Index is still lingering up around 144, but the VIX dropped down to 15.0 and the 20-day realized volatility is sitting calm at 14.8%. We are looking at a classic data divergence where day-to-day fluctuations look totally flat, but out-of-the-money options pricing reveals that people are still paying a hefty premium to cover against a severe market drop. It is a good example of why looking at a single average volatility metric can result in completely missing the actual tail behavior of the distribution.

Last updated: 2026-07-12 10:27 UTC

Generated: 2026-07-12 10:27 UTC