Recent Academic Research
CME FedWatch accuracy, bond short interest and future stock returns, wildfire impact on real estate, new inflation model, and climate affecting commodities
Welcome back to another issue of Recent Academic Research! Thank you all for the support recently. I’m happy to see that others see the value in academic research.
Let’s get into it.
FedWatch Predictions
Paper Title: Watching the FedWatch
Authors & Date: Stefano Bonini, Shengyu Huang, & Majeed Simaan | 1/16/2025
Summary:
This paper evaluates the CME FedWatch Tool, which predicts Federal Reserve rate decisions using probabilities derived from Fed funds futures. It finds that FedWatch has 88% accuracy in forecasting rate decisions 30 days before FOMC meetings, outperforming Fed funds futures alone (75% accuracy). However, accuracy declines for longer-term predictions, dropping to 68% (2 meetings ahead) and 45% (4 meetings ahead).
A trading strategy based on FedWatch predictions improves risk-adjusted returns, doubling the Sharpe Ratio compared to a naïve strategy. The study also finds that FedWatch reduces market uncertainty before FOMC meetings, though its impact on the pre-FOMC drift remains inconclusive.
Thoughts:
I saw this paper, and instantly knew that I had to include it. I use the CME FedWatch tool quite often, and its cool to visualize where the market’s head is at with the Fed Funds rate.
Now, we know that the FedWatch Tool uses the 30-day Fed Funds Futures contracts on CME, so it makes sense that it is more accurate for shorter predictions. But, CME uses some “unconventional” calculations in order to derive probabilities from the underlying futures price. It is unique to see how this paper claims that it is overlooked (yet quickly growing in popularity).
Short Interest and Future Returns
Paper Title: Short Interest in Bonds and Aggregate Stock Returns
Authors & Date: Huu Nhan Duong, Arseny Gorbenko, Petko S. Kalev, & Xiao Tian | 1/16/2025
Summary:
This paper finds that corporate bond short interest—the percentage of bonds being shorted—predicts future stock market declines. A one-standard-deviation increase in bond short interest is associated with a -0.39% drop in the S&P 500’s excess return the following month, with the effect strengthening over longer horizons.
Bond short interest outperforms traditional stock short interest as a predictor, likely because bond traders anticipate deteriorating fundamentals before equity markets react. The study also shows that a trading strategy based on bond short interest achieves Sharpe Ratios between 0.78 and 0.95, highlighting its potential value for investors looking to hedge against market downturns.
Thoughts:
If you're betting against corporate bonds, you likely see some kind of flaw or risk in the broader market. While we don’t know exactly what type of risk is being priced in—whether it’s interest rate risk, credit risk, or something else—we do know that higher bond short interest predicts future economic distress.
But why does this risk show up in the bond market before equities? According to the paper, it comes down to liquidity differences and the type of information bond traders focus on—deteriorating cash flows and widening credit spreads.
Wildfire Smoke and Real Estate
Paper Title: Air Pollution and Rent Prices: Evidence from Wildfire Smoke Plumes
Authors & Date: Luis A. Lopez & Nitzan Tzur-Ilan | 1/10/2025
Summary:
This paper examines how wildfire smoke pollution affects rental prices and home values, using satellite data and air quality readings. It finds that a one standard deviation increase in PM2.5 pollution lowers rents by 2.4% and home prices by 9%, with homeowners reacting more strongly than renters.
Higher pollution also delays rental transactions, increasing days on market by 3.4% and reducing the likelihood of a lease being signed. The study highlights how short-term air quality shocks impact housing markets, with long-term consequences for property values.
Thoughts:
I thought this paper was especially relevant given the California wildfires. Many people in LA will be displaced due to the fires, and they may find a home to buy or rent in a nearby location at an attractive discount due to wildfire smoke.
The one counterargument I see is that prices could drastically increase due to reduced supply and higher demand. This could negate the effects of wildfire smoke unless the smoke spreads far enough to impact surrounding areas.
Predicting U.S. Inflation
Paper Title: Weekly Nowcasting U.S. Inflation with Enhanced Random Forests
Authors & Date: Philipp Wegmueller & Seton Leonard | 1/14/2025
Summary:
This paper develops an enhanced random forest model for weekly nowcasting of U.S. inflation, incorporating mixed-frequency macroeconomic data. The model outperforms traditional inflation forecasts, reducing forecast error by 50% compared to basic models and 10% better than the Cleveland Fed’s nowcast.
By integrating high-frequency indicators like gasoline prices and using regression-based decision nodes, the model adapts more dynamically to inflation shocks. The findings highlight the power of machine learning in improving real-time inflation forecasting.
Thoughts:
This is without a doubt a highly competitive market. If you can forecast inflation more accurately than anyone else, you gain insight into the Fed’s likely future decisions. That means you could take positions ahead of how the market will react to a more dovish or hawkish Fed.
That said, these models are probably just one part of a larger system for investment decisions. Like any model, they shouldn’t be relied on entirely.
Natural Disaster Risk Premium
Paper Title: A Tale of Commodities and Climate-driven Disasters
Authors & Date: Filippo Pellegrino | 1/14/2025
Summary:
This paper examines how climate-driven disasters impact commodity prices, using global production data from the 1970s to today. The study finds that commodity production is increasingly concentrated in high-risk areas, making markets more vulnerable to climate shocks. Agricultural and energy commodities see the strongest price reactions, while commodities produced in safer locations remain more stable.
A long-short strategy (long vulnerable commodities, short resilient commodities) earns a monthly CAPM alpha of 1.10%. The findings highlight how climate risk is becoming a key factor in commodity pricing and offer insights for building climate risk-driven trading strategies.
Thoughts:
It’s fascinating to see how efficiently the market prices in risk and compensates investors for it. While this paper finds "CAPM alpha" in the long-short strategy, that doesn’t necessarily mean there’s free money on the table—it just means the returns aren’t explained by exposure to the overall stock market. Instead, the risk premium is likely coming from other factors, such as exposure to climate-driven supply shocks and commodity-specific risks.
Feedback
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I'd have to read the smoke plumes paper - but it does seem interesting. Based on my understanding of the broad research, housing prices (and rents) are tied to local current+future income. If more particulates in the air reduce wages (both in the short run and long-run via child development), it's not surprising to see house prices fall more.