How to Analyze Market Volatility Across Different Asset Classes

Volatility Divergence Between Bonds and Equities, What It Tells Us in Quantitative Finance The market often speaks in signals, and volatility is one of its loudest voices. But not all volatility is created equal. In recent years, a striking divergence has emerged between bond market volatility (MOVE Index) and equity market volatility (VIX Index). This gap is not just statistical noise, it has profound implications for modeling, hedging, and pricing in quantitative finance. 1. What the Chart Shows ➤ The VIX Index reflects expected 30-day equity volatility based on S&P 500 options, while the MOVE Index does the same for Treasury bond yields across multiple tenors, ➤ Historically, the two moved in tandem, both spiking during macro shocks like 2008 or March 2020, ➤ Since early 2022, however, the MOVE Index has remained elevated, while the VIX has normalized to near-historic lows. This signals far more uncertainty in rates than in equity prices, 2. Why the Bond Market is More Volatile Now ➤ Central banks are no longer predictable. After decades of low and stable inflation, the monetary policy regime has become reactive and uncertain, ➤ Duration and convexity risks are back in focus. Fixed income instruments are sensitive to rate changes, even small shifts in forward guidance or CPI prints ripple violently through the curve, ➤ Illiquidity in bond markets and fewer primary dealers post-Volcker Rule have amplified the spikes in MOVE, 3. Why This Matters in Quantitative Finance ➤ Different Models, Different Rules, In equity derivatives, we rely heavily on stochastic volatility models like Heston or local volatility surfaces. In contrast, interest rate modeling demands term structure dynamics, think Hull-White, CIR, or the HJM framework, ➤ Calibration is Not Universal, You can’t plug the same parameters into both markets. Bond models must reflect mean-reversion, yield curve evolution, and policy reaction functions, while equity models capture volatility clustering, skew, and jumps, ➤ Risk Management Diverges, Fixed income desks use DV01, PVBP, and key rate durations to manage exposure. Equity risk is more tied to delta, gamma, and vega. One market reacts to macro, the other to micro and sentiment, 4. A Practical Takeaway for Quants ➤ If you’re building a volatility forecasting model, you cannot assume cross-asset symmetry, ➤ Market-making desks may hedge volatility mismatches using cross-asset volatility spreads, ➤ Portfolio optimization in a multi-asset framework now requires correlation breakdown modeling, the assumption of vol convergence has clearly failed, Volatility is not a monolith. Bond and equity markets reflect risk through very different mechanisms. That’s why quantitative finance has evolved domain-specific models, calibrated to the physics of each asset class. #QuantitativeFinance #Volatility #VIX # #FixedIncome #EquityMarkets #RiskModeling #RatesVolatility

Another look heading into the weekend of #VIX, relative to both MOVE and EVZ. VIX represents expected 30-day volatility in the S&P 500 (US #equities), while MOVE is a bond market #volatility proxy and EVZ is the comparable FX volatility index proxy. Looking at the last 15+ year relationship, there’s no doubt MOVE has been the cheapest in relative terms of the three for the longest duration over this period. VIX seems to be the most expensive, but in any case it’s at least comparable to EVZ. There have been prior times (ex: 2015 debt ceiling standoff), where it made sense for a particular asset classes to have substantively more expected volatility; it was MOVE then. However today, we don’t quite have an environment that would be biased against a particular financial asset. Due to the Fed hiking cycle, naturally we’d expect MOVE to likely be a bit higher. However that’s not only not always true, but even so that doesn’t mean the equity market has any reason to be effectively be front-running pricing in major rate cuts. Additionally, with the recent turbulence in yields, unpredictable global #inflation readings and central #bank responses, it’s appropriate for the FX market to be pricing in some expected volatility through EVZ. It looks like there’s just recently been a large spike upward for EVZ, so that appears to be happening. The bond market - through MOVE - has done a much better job throughout this entire cycle of at least assessing there is market risk and even a very heightened one at times. We see a local peak spiking upward during the most recent debt ceiling standoff. Either way, as there are lingering uncertainties about what the future of the fixed income market holds, MOVE has been fluctuation, which again tells me the bond market is thinking about risk pricing. With VIX this cheap - the lowest of the three indices in the current cycle - market participants are stubbornly insisting on remaining complacent. The equity market has now seen corporate fundamentals in large-caps deteriorate two quarters and on a much larger basis in the second. The labor market is clearly starting to break down, which historically impacts the equity market very negatively after the US #economy is in recession. There has not been a single bull market during a recession and this time won’t be different. In a market with so much capital at stake and the drawdown potentials so extreme, it’s almost irresponsible to neglect downside protection. Reviewing the divergence and considering volatility potential in each market, it does not seem fully understandable why the US equity market effectively abandoned risk pricing in this cycle. VIX should not be this low when the yield curve has been so inverted, #earnings declined consecutive quarters, inflation + US Fed still a problem, etc. VIX will rise, but I'm sure most know the time to capitalize on a bear market thesis is when VIX is low. TradingView #Research #Markets #Finance #Valuation #EquityResearch

Simple macro guardrails for non-macro PMs....... Most equity investors aren't macro experts. But when macro trends dominate the evidence shows that stock picking stops driving returns, and so PMs' bottom-up convictions go frustratingly unrewarded. Measuring their macro vol is one guardrail people build into portfolio risk systems. Quant Insight's model explains: ➡️ How much risk comes from macro vs. non-macro ➡️ Which macro drivers matter (e.g. US$, rates, oil) ➡️ How each asset is exposed It analyzes: 📈 Macro factor volatility (e.g. StDvs in US$) 🔗 Correlations between factors (e.g. USD moves impact rates, commodities) 🧠 Each asset’s exposure in the portfolio Why Care? See chart. Since 2009, as macro's share of forecast volatility in IWM rose (blue), the 6m rolling Sharpe (orange) has come under pressure. IWM bulls now need to believe we've hit peak uncertainty + macro's share will drop. Curious on other ETFs? How is this data actionable? ✅ Track macro's share of your portfolio risk ✅ Identify its key drivers ✅ Adjust exposure or optimize to reduce macro-driven volatility Macro risk is not going away, but it is manageable when measured properly.