Recent Academic Research
The impact of tariffs on inflation, a corporate bond factor model, sector performance during health crises, forecasting crude oil prices, and trade duration
Welcome back to another issue of Recent Academic Research! For those interested in macro, I highly recommend diving into the first highlighted paper (it’s quite relevant in today’s market).
Once again, thank you for all the support and growth recently. Let’s get into it.
Tariffs and Inflation
Paper Title: The Impact of Tariffs on Inflation
Authors & Date: Omar Barbiero & Hillary Stein | 2/7/2025
Summary:
This paper examines how tariffs impact U.S. inflation, showing that price increases extend beyond imported goods due to supply chain effects and business markups. The study estimates inflationary effects under two scenarios: a 25% tariff on Canada and Mexico combined with a 10% tariff on China, which could add 0.8 percentage points to core inflation, and a 60% tariff on China plus a 10% tariff on all other imports, which could raise inflation by up to 2.2 percentage points.
For comparison, the 2018 tariffs increased core inflation by 0.1–0.2 percentage points, more than previously estimated. The findings highlight that tariffs don’t just impact foreign goods—they raise prices across entire industries by increasing supply chain costs and influencing corporate pricing strategies.
Thoughts:
The rise in inflation from tariffs, as estimated by economists at the Federal Reserve Bank of Boston, could increase pressure on the Fed to delay rate cuts. Additionally, the probability of a rate hike may be higher than what the market currently prices in.
Recently, however, markets have begun to view tariffs as a negotiation tool rather than a purely protectionist measure, particularly in forcing foreign governments to comply with U.S. demands. This shift in perception is reflected in the decline of the U.S. dollar (DXY index). Despite this, uncertainty surrounding Trump’s tariff policies remains high, and this paper underscores how such tariffs can significantly influence future inflation and monetary policy decisions.
Corporate Bond Factor Model
Paper Title: The Cross-Section of Corporate Bond Returns
Authors & Date: Guido Baltussen, Frederik Muskens, & Patrick Verwijmeren | 2/10/2025
Summary:
This paper develops a five-factor model to explain corporate bond returns, improving on traditional credit pricing models. The study finds that shorter-maturity bonds, undervalued bonds (high credit spreads), and bonds from firms with strong equity momentum consistently outperform. Additionally, bonds issued by firms with low accruals (high cash earnings quality) generate higher returns, similar to the accrual anomaly in equities.
The model explains over 70% of cross-sectional return variation, outperforming standard bond pricing approaches. The findings highlight new opportunities for systematic bond investing, showing that corporate bond returns are driven by more than just interest rate and credit risk factors.
Thoughts:
Factor models are widespread in equity markets. However, they are less prevalent in corporate bond markets due to infrequent trading, duration risk, credit risk, and liquidity constraints.
While most other corporate bond research focuses on default risk, it is nice to see more papers on return relationships. It is intuitive that firms with well performing stocks also likely have high performing bonds. Barclay’s Quantitative Portfolio Strategy group actually has written on some corporate bond trading strategies that are similar to these findings, including Excess Spread to Peers and Equity Momentum in Credit.
Sector Performance During Health Crises
Paper Title: Industry return predictability using health policy uncertainty
Authors & Date: Thach Pham, Deepa Bannigidadmath, & Robert Powell | 2/10/2025
Summary:
This paper examines how health policy uncertainty (HU) impacts U.S. industry returns, particularly during health crises like SARS and COVID-19. Using data from 1985 to 2020, the authors find that HU significantly predicts returns in 25 out of 49 industries, with pharmaceuticals, medical equipment, and defense sectors benefiting the most, while industries like aircraft, real estate, and construction suffer.
The study also shows that investors can build profitable trading strategies based on HU, generating annualized returns between 2.99% and 11.44%. These findings highlight the role of policy-driven uncertainty in shaping market behavior and offer new insights for asset pricing and risk management.
Thoughts:
We all know about the impact of COVID-19 on the U.S. equity markets over the last 5 years. However, what’s interesting is that industries seem to perform differently from health crises.
It is intuitive that healthcare companies and sectors (pharmaceuticals and medical equipment) would perform well, as there will be greater demand for their products and services. However, its interesting to see how other industries, like aircraft and construction, suffer during these periods. If the impact of these health crises are large enough, they can reduce the demand for economic expansion.
Forecasting Crude Oil Prices
Paper Title: "One Out of Many" Consolidating a Long-term Trend Forecast for Investing in Energy Commodities
Authors & Date: Fernanda Diaz-Rodriguez & M-Dolores Robles | 2/13/2025
Summary:
This paper explores long-term trend forecasting for crude oil prices, proposing a forecast combination approach to improve prediction accuracy for energy investments and policy decisions. Instead of relying on a single model, the study integrates five trend estimation methods with seven combination techniques, finding that the Multi-Ensemble Time-Scale (METS) algorithm produces the most stable and accurate forecasts.
The results show that trend-based forecasts outperform short-term price predictions, making them more useful for investment strategies and risk management. The findings suggest that investors and policymakers should prioritize trend-following approaches rather than reacting to short-term volatility in energy markets.
Thoughts:
I wanted to include this paper to show the power of aggregating predictions from multiple models. Different models may be able to capture specific information during time periods, and some models may be more accurate during different market regimes due to their predictors.
At the end of the day, it is not just about who has the best model. There is an advantage in having multiple sources of information (from multiple models) and being able to use that to enhance your forecasting abilities.
Trade Frequency and Return Patterns
Paper Title: The Predictive Power of Inter-trade Durations: Return Reversals and Momentum
Authors & Date: Zannatus Saba | 2/12/2025
Summary:
This paper examines how inter-trade durations (the time between consecutive trades) impact short-term price reversals and momentum. Using intraday trading data from 2019 to 2022, the study finds that longer trade durations reduce short-term reversals and strengthen momentum trends, particularly in institutionally owned stocks and bullish market conditions. In contrast, shorter trade durations lead to market overreactions and frequent price corrections.
Granger causality tests confirm that trade duration predicts price behavior, not the other way around. The findings highlight that longer inter-trade durations signal more stable price trends, while shorter durations indicate increased volatility and mean-reversion opportunities.
Thoughts:
The trade duration measure is based on intraday data and captures the time between consecutive trades, rather than the holding period of a position. Longer trade durations means lower trading frequency.
The positive relationship between trade duration and momentum makes sense because longer trade durations indicate fewer opposing orders against the prevailing price trend, allowing momentum to persist for a longer period.
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Well, if we didn’t have a fake fiat monetary system owned and run by a shadowy private entity, much of this wouldn’t apply.
It drives me nuts how people try to analyze the market when it all comes down to “whether or not the Federal Reserve decides to (fill in the blank).”
It pretty much boils down to, “hey, Jerome, should we make any changes?”… Mr. Powell’s response, “naw, let it sit as it is and see how they wrangle with what we’ve done.”