The Weekly Print
1. Market Regime Snapshot
VIX Term Structure
| Tenor | Level | vs. Spot |
|---|---|---|
| VIX Spot | 14.2 | — |
| VIX 3M | 18.5 | +4.2 (Contango) |
Realized vs. Implied Vol: SPY 20D RV = 13.4%, VIX = 14.2. Spread = -0.9pp (realized vol below implied — calmer than feared).
Cross-Asset Momentum (1-Month)
| Asset | 1M Return | Signal |
|---|---|---|
| SPY (Equity) | +4.4% | 📈 Positive |
| TLT (Bonds) | -2.5% | 📉 Negative |
| GLD (Gold) | +9.0% | 📈 Positive |
| UUP (US Dollar) | -0.8% | 📉 Negative |
Regime: Mixed/transitional regime
Last updated: 2026-08-16 17:00 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 | +2.55% | -5.76% | +3.11% | +0.45% | 2.74% | +0.77 |
| Value | +3.26% | +1.28% | +13.43% | +1.10% | 2.49% | +0.87 |
| Quality | +0.07% | +2.49% | +7.10% | +0.38% | 1.48% | -0.21 |
| Low Volatility | +0.51% | +3.58% | +7.57% | +0.19% | 1.15% | +0.28 |
| Size | +0.76% | -0.18% | +2.31% | +0.25% | 1.54% | +0.33 |
No factor stress signals this week (all within ±2σ).
Last updated: 2026-08-16 17:00 UTC
3. Macro Signal Tracker
| Indicator | Current | 1W Change | Signal |
|---|---|---|---|
| HY Spread (OAS) | 271bps | +0bps | → Unchanged |
| IG Spread (OAS) | 79bps | +1bps | ⚠️ Widening |
| 2s10s Yield Curve | 0.51% | +0.05% | Normal |
| 3M10Y Yield Curve | 0.82% | +0.04% | Normal |
| Fed Funds Rate | 3.63% | N/A | → |
| HY − IG Spread | 192bps | — | Risk sentiment proxy |
Macro Summary: Neutral macro backdrop
Last updated: 2026-08-16 17:01 UTC
4. Quant Research Digest
Three papers I found worth reading this week:
FlowLOB: Efficient and Controllable Limit Order Book Generation with Flow Matching — Zhuohan Wang et al. arXiv
The authors use flow-matching to generate synthetic limit order book trajectories that can effectively transfer to unseen instruments. Generating realistic market data is a notoriously difficult hurdle for accurate backtesting, so seeing a model successfully reproduce LOB dynamics across different sampling frequencies makes for a great technical reference.
DYSANOS Generative Dynamic Smooth Arbitrage-free Non-parametric Option Surfaces — Hans Buehler et al. arXiv
This paper introduces a generative market model capable of simulating smooth, static-arbitrage-free option surfaces across various strikes and expiries. Many standard volatility models introduce arbitrage opportunities when pushed to generate long-term paths, making this a useful framework for modeling extended option price trajectories without breaking underlying assumptions.
Diffusion Models in Finance: A Survey — Zhuohan Wang et al. arXiv
This is a comprehensive survey on the application of diffusion generative models in financial data, specifically highlighting their alignment with stochastic differential equations. It provides a clean, mathematical overview of why diffusion models are increasingly becoming the standard for complex financial modeling architectures.
Last updated: 2026-08-16 17:01 UTC
5. Stat of the Week
| Stat | Value | Context |
|---|---|---|
| CBOE Skew Index | 138 | Elevated tail risk (>130) |
The Skew Index is sitting at 138 this week while the VIX remains relatively low at 14.2. This divergence between calm realized volatility and an elevated skew is a great structural reminder of why assuming normal distributions in return forecasting can be dangerous. It is exactly the kind of environment where optimizing for CVaR instead of standard mean-variance makes a practical mathematical difference.
Last updated: 2026-08-16 17:01 UTC
Generated: 2026-08-16 17:01 UTC