Predicting Corrections and Economic Slowdowns

In partnership with

Being able to anticipate a market correction or an economic recession is important for managing risk and positioning your portfolio ahead of major shifts. In this issue, we feature two articles: one that analyzes indicators signaling a potential market correction, and another that examines recession forecasting models based on macroeconomic data.

In this issue:

• Latest Posts

• Predicting Recessions Using The Volatility Index A …

  • Findings

• Can We Predict a Market Correction?

  • Findings

• Closing Thoughts

• Educational Video

  • Short selling in the bull market

• Volatility Weekly Recap

• Around the Quantosphere   

Latest Posts

• Rethinking Leveraged ETFs and Their Options (12 min)

• Using Skewness and Kurtosis to Enhance Trading and Risk Management (10 min)

• Gold Ratios as Stock Market Predictors (11 min)

• Volatility of Volatility: Insights from VVIX (11 min)

• Simplicity or Complexity? Rethinking Trading Models in the Age of AI and Machine Learning (10 min)

Predicting Recessions Using The Volatility Index And The Yield Curve

The yield curve is a graphical representation of the relationship between the yields of bonds with different maturities. The yield curve has been inverted before every recession in the United States since 1971, so it is often used as a predictor of recessions.

A study [1] shows that the co-movement between the yield-curve spread and the VIX index, a measure of implied volatility in S&P500 index options, offers improvements in predicting U.S. recessions over the information in the yield-curve spread alone.

Findings

• The VIX index measures implied volatility in S&P 500 index options and reflects investor sentiment and market uncertainty.

• A counterclockwise pattern (cycle) between the VIX index and the yield-curve spread aligns closely with the business cycle.

• A cycle indicator based on the VIX-yield curve co-movement significantly outperforms the yield-curve spread alone in predicting recessions.

• This improved forecasting performance holds true for both in-sample and out-of-sample data using static and dynamic probit models.

• The predictive strength comes from the interaction between monetary policy and financial market corrections, not from economic policy uncertainty.

• Shadow rate analysis confirms the cycle indicator’s effectiveness, even during periods of unconventional monetary policy and flattened yield curves.

• The findings suggest a new framework for macroeconomic forecasting, with the potential to enhance early detection of financial instability.

• The VIX-yield curve cycle adds value beyond existing leading indicators and may help in anticipating major economic disruptions like the subprime crisis.

In short, the study concludes that the co-movement between the yield curve spread and the VIX index, which is a measure of implied volatility in S&P 500 index options, provides an improved prediction for U.S. recessions over any information available from just considering the yield-curve spreads alone.

This research will have implications for how macroeconomists forecast future economic conditions and could even change how we predict periods of high financial instability like the subprime crisis.

Reference

[1] Hansen, Anne Lundgaard, Predicting Recessions Using VIX-Yield-Curve Cycles (2021). SSRN 3943982

Can We Predict a Market Correction?

A correction in the equity market refers to a downward movement in stock prices after a sustained period of growth. Market corrections can be triggered by various factors such as economic conditions, changes in investor sentiment, or geopolitical events. During a correction, stock prices may decline by a certain percentage from their recent peak, signaling a temporary pause or reversal in the upward trend.

Reference [2] examines whether a correction in the equity market can be predicted. It defines a correction as a 4% decrease in the SP500 index. It utilizes logistic regression to examine the predictability of several technical and macroeconomic indicators.

Findings

• Eight technical, macroeconomic, and options-based indicators were selected based on prior research.

• Volatility Smirk (skew), Open Interest Difference, and Bond-Stock Earnings Yield Differential (BSEYD) are statistically significant predictors of market corrections.

• These three predictors were significant at the 1% level, indicating strong reliability in forecasting corrections.

• TED Spread, Bid-Offer Spread, Term Spread, Baltic Dry Index, and S&P GSCI Commodity Index did not show consistent predictive power.

• The best-performing model used a 3% correction threshold and achieved 77% accuracy in in-sample prediction.

• Out-of-sample testing showed 59% precision in identifying correction events, offering an advantage over random prediction.

• The results highlight inefficiencies in the market and support the presence of a lead-lag effect between option and equity markets.

• The research provides valuable tools for risk management and identifying early signs of downturns in equity markets.

In short, the following indicators are good predictors of a market correction,

• Volatility Smirk (i.e. skew),

• Open Interest Difference, and

• Bond-Stock Earnings Yield Differential (BSEYD)

The following indicators are not good predictors,

• The TED Spread,

• Bid-Offer Spread,

• Term Spread,

• Baltic Dry Index, and

• S&P GSCI Commodity Index

This is an important research subject, as it allows investors to manage risks effectively and take advantage of market corrections.

Reference

[2] Elias Keskinen, Predicting a Stock Market Correction, Evidence from the S&P 500 Index, University of VAASA

Closing Thoughts

Educational Video

Short selling in the bull market

In this video, Laurent Bernut provides a theoretical and practical understanding of short selling, especially in bullish markets. It challenges common myths, highlights the importance of risk management, and explains how short selling can reduce volatility and improve overall performance in long-short strategies. The session also breaks down technical approaches, key indicators, and how to avoid traps like chasing overvalued stocks or relying on flawed valuation logic. Overall, viewers will gain a clearer view of how short selling works, when and why to use it, and how to build more balanced, thoughtful trading strategies in both bullish and bearish conditions.

Volatility Weekly Recap

The figure below shows the term structures for the VIX futures (in colour) and the spot VIX (in grey).

Stocks posted a strong performance on Monday, rising just under 1% on optimism that the conflict in the Middle East would be less severe. The market finished the week at an all-time high, gaining additional momentum. Gold declined during the week, while crypto surged alongside equities. The S&P 500 rose 3.44%, and the Nasdaq gained 4.25%.

In the volatility market, both spot and VIX futures remained in contango, and the roll yield increased. This reflects market complacency and the typical tendency for volatility to remain subdued during the summer months. This resulted in returns of -9.71% and -3.07% for VXX and VIXM respectively.

Around the Quantosphere   

• Hedge funds offer bumper pay to lure AI talent: ‘Million-dollar packages are not far’ (Fnlondon)

• This Hedge Fund Legend Made 30% Returns for 30 Years—By Breaking the No. 1 Rule of Investing (Yahoo Finance)

• Why the Best Strategies Don’t Last — A Quant Truth (Tradingview)

• Millennium's $14 Billion Valuation Hinges on Scarcity (Bloomberg)

• Hedge fund strategies in crypto — what transfers, what doesn’t (Pionline)

• Hedge funds scale back steepener positions as risks rise (Risk)

•  Hedge fund leverage reaches five-year high, buying bank stocks, Goldman Sachs says (CA Finance Yahoo)

• Hedge fund technology jobs are a nightmare: "You're better off at a mutual fund" (efinancialcareers)

• "I've also sent hundreds of applications and had no interviews from Workday." (Efinancialcareers)

Disclaimer

This newsletter is not investment advice. It is provided solely for entertainment and educational purposes. Always consult a financial professional before making any investment decisions.

We are not responsible for any outcomes arising from the use of the content and codes provided in the outbound links. By continuing to read this newsletter, you acknowledge and agree to this disclaimer.