Recent Academic Research
Optimal straddles in Bitcoin, CEO earnings call tone, the climate risk in bonds, and how interest rates affect equity values from discounting
Welcome back to another issue of Recent Academic Research! Let’s get into it.
Crypto Straddles
Is at-the-money really the best place to sell crypto volatility?
Most volatility sellers default to at the money strikes because that is where the premium is thickest, but crypto return dynamics (heavy tails and frequent jumps) make this "standard" approach surprisingly suboptimal. By analyzing years of Bitcoin option data, this study finds that the sweet spot for a daily short strangle is actually about 3% out of the money.
The researchers move beyond static rules of thumb by training machine learning models to adjust strikes based on current market states (like implied volatility levels and the shape of the surface). Their smoothed classification model consistently beats the standard benchmark by reducing the impact of daily noise and focusing on persistent regimes.
Wen, Hongzhe and Yu, Xitian, Optimal Strike Distance for Daily Crypto Strangles: Theory and Empirical Analysis (January 26, 2026). Available at SSRN: https://ssrn.com/abstract=6151986
CEO Tone Impacts Returns
Can the nervous tremor in a CEO’s voice tell you more about future stock returns than the actual words in the transcript?
Traditional sentiment analysis focuses on what executives say, but this research suggests that the way they say it is far more predictive of future performance. By isolating earnings calls where the transcript text was entirely neutral, the authors analyzed paralinguistic features like pitch, energy, and vocal tension.
They found that even when the language is devoid of optimism or pessimism, vocal cues of assertiveness or nervousness predict significant stock moves. Specifically, portfolios built on high conviction vocal tones generated alpha between 40 and 70 basis points over the following month.
This suggests that voice provides an entirely independent channel of information that text based algorithms completely miss. The subtle, nonverbal cues of the CEO and CFO (captured during the heat of the Q&A session) act as a high resolution window into their true confidence level and cognitive load.
Pope, David, Voice Beyond Words: Evidence That Managerial Tone Predicts Returns When Text Does Not (January 26, 2026). Available at SSRN: https://ssrn.com/abstract=6135066
Bonds and Climate Risk
Bond return differs based on the “climate risk” associated with the bond.
This research uncovers a pattern where bonds that are most sensitive to climate policy uncertainty actually yield less than their peers. While we might expect a "risk premium" for holding uncertainty, the reality is that institutional investors view these specific bonds as valuable insurance policies.
Because these assets tend to perform well when climate regulations tighten, risk averse portfolios are willing to pay a premium for them (driving the initial price up and the future return down). This effect is particularly concentrated in high carbon sectors and has intensified significantly since the 2015 Paris Agreement.
This means that policy resilient bonds might be more expensive than they look (offering safety at the cost of yield). This negative premium remains significant even after controlling for traditional macroeconomic factors.
Yang, Wenhan and Wu, Chunchi, Climate Policy Uncertainty and the Cross Section of Corporate Bond Returns. Available at SSRN: https://ssrn.com/abstract=6277839 or http://dx.doi.org/10.2139/ssrn.6277839
Stock Valuation from Interest Rate Discounting
Why have stocks and bonds seemingly broken their historical link, and which part of interest rates actually drives stock prices?
We often assume that falling interest rates should mechanically boost stock valuations (a one for one trade), yet the historical data across major economies shows a muddled relationship.
This paper resolves the confusion by splitting real interest rates into three distinct drivers: expected growth, risk, and “pure discounting.” It turns out that only the pure discounting component (the part of the rate tied to time preference) transmits directly to equity yields. In fact, this single factor explains 80% of cross country valuation changes since 1990.
Meanwhile, about two thirds of the decline in U.S. rates were driven by slowing growth and shifting risk (which often drag stock prices down, cancelling out the benefit of lower rates). This finding matters because it suggests that blindly buying stocks whenever rates fall is a poor decision, and that you have to know why the rates are moving to know if the equity “duration” will actually kick in. Isolating the pure discounting component is the only way to accurately measure how much a change in rates has passed through to equities.
Gormsen, Niels Joachim and Lazarus, Eben, Interest Rates and Equity Valuations (February 02, 2026). Available at SSRN: https://ssrn.com/abstract=6171489
Feedback
Thank you for reading this week’s edition of Recent Academic Research. Remember to fill out the poll to let me know which paper was your favorite and like the post if you enjoyed it.
Feel free to follow up with any questions, comments, or ideas for the future!
Disclaimer
The content provided in this newsletter, "Alpha in Academia," is for informational and educational purposes only. It should not be construed as financial advice, investment recommendations, or an offer or solicitation to buy or sell any securities or financial instruments. Past performance is not indicative of future results. The financial markets involve risks, and readers should conduct their own research and consult with qualified financial advisors before making any investment decisions.
The interpretations, opinions, and analyses presented herein are those of the author and do not necessarily reflect the views of the original researchers, their institutions, or the full implications of the cited academic papers. While every effort is made to accurately represent the research discussed, readers should be aware that the summaries and interpretations may not capture the full scope or nuances of the original studies. The information contained in this newsletter is believed to be accurate and reliable at the time of publication, but accuracy and completeness cannot be guaranteed. The author and publisher accept no liability for any loss or damage resulting from reliance on the information provided.
This newsletter may contain links to external websites or resources. The author is not responsible for the content, accuracy, or reliability of these external sources.
By subscribing to or reading this newsletter, you acknowledge that you have read and understood this disclaimer and agree to hold the author and publisher harmless from any liability that may arise from your use of the information contained herein.