nep-fmk New Economics Papers
on Financial Markets
Issue of 2026–05–11
eight papers chosen by
Kwang Soo Cheong, Johns Hopkins University


  1. A Levered ETF Anomaly Explained By Stephen W. Bianchi; Lisa R. Goldberg
  2. A Review of Large Language Models for Stock Price Forecasting from a Hedge-Fund Perspective By Olivia Zhang; Zhilin Zhang
  3. Bank credit risk and sovereign debt exposure: Moral hazard or hedging? By Laura Baselga-Pascual; Lidia Loban; Emma-Riikka Myllymäki
  4. Gender, Financial Literacy and Active Stock Market Participation By M. Tedde
  5. Hedging Against Inflation: International Evidence on Investor Clientele Effects By Martijn Boermans; Laurens Swinkels
  6. The double-edged mind: How LLMs expand stock market participation yet strengthen confirmation-seeking By Damm, Cara; Bauer, Kevin; Hett, Florian; Pelizzon, Loriana
  7. The green bond premium: Evidence from a multiverse analysis By Bauckloh, Michael Tobias; Kirsch, Paula
  8. Stockholding in Europe: Evidence from the Consumer Expectations Survey By Dimitris Christelis; Dimitris Georgarakos; Tullio Jappelli; Geoff Kenny; Justus Meyer

  1. By: Stephen W. Bianchi; Lisa R. Goldberg
    Abstract: Counterintuitively, the S&P 500 Index rose between January 1, 2022, and December 29, 2023, while exchange-traded funds (ETFs) seeking to deliver 2x and 3x daily returns of the index delivered substantially negative returns. Roughly two-thirds of the difference between the returns of the index and the levered ETFs can be attributed to compounding and volatility. The remaining difference is explained by the covariance between the ETFs' deviations from constant leverage and the index's return.
    Date: 2026–04
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2604.27287
  2. By: Olivia Zhang; Zhilin Zhang
    Abstract: Large language models (LLMs) are increasingly deployed in quantitative finance for stock price forecasting. This review synthesizes recent applications of LLMs in this domain, including extracting sentiment from financial news and social media, analyzing financial reports and earnings-call transcripts, tokenizing or symbolizing stock price series, and constructing multi-agent trading systems. Particular attention is paid to practical pitfalls that are often understated in the literature, such as fragility in sentiment analysis, dataset and horizon design, performance evaluation metrics, data leakage, illiquidity premia, and limits of stock price predictability. Organized from a hedge-fund perspective, the review is intended to guide both academic researchers and hedge fund managers in integrating LLMs into real-world trading pipelines and in stress-testing their robustness under realistic market frictions.
    Date: 2026–04
    URL: https://d.repec.org/n?u=RePEc:arx:papers:2605.05211
  3. By: Laura Baselga-Pascual; Lidia Loban; Emma-Riikka Myllymäki (Audencia Business School)
    Abstract: This study investigates the relationship between credit risk and bank exposure to sovereign debt. Using an international dataset of commercial banks from 2002 to 2022, we apply various regressions and panel data models to address potential endogeneity issues. Our results reveal that banks with higher levels of impaired loans tend to hold more sovereign debt. Furthermore, we observe that this relationship is stronger in countries with high sovereign credit ratings. This suggests that banks, when confronted with elevated credit risk from impaired loans, may seek safety in sovereign debt as a seemingly secure investment.
    Keywords: Financial institutions, Bank risk, Sovereign debt nexus, Credit risk
    Date: 2025–01
    URL: https://d.repec.org/n?u=RePEc:hal:journl:hal-05585256
  4. By: M. Tedde
    Abstract: Women are less financially literate than men and participate less to stock market. However, using a unique brokerage dataset and controlling for different levels of financial literacy, we find that women achieve lower scores in the MiFID questionnaire not because of lack of knowledge but because of lack of confidence in their knowledge. Nonetheless, female participation in stock market is still lower than male investors.
    Keywords: financial literacy;Confidence;MiFID Directive;gender gap;Stock market participation
    Date: 2026
    URL: https://d.repec.org/n?u=RePEc:cns:cnscwp:202603
  5. By: Martijn Boermans; Laurens Swinkels
    Abstract: Governments across the world have issued inflation-linked debt to finance their deficits. Recent advances in asset pricing models recognize that there may be clientele effects that affect relative prices, especially in bond markets. We study investor demand for inflation-linked bonds using detailed bond portfolio data. Our analysis reveals pronounced market segmentation: insurance companies, with predominantly nominal liabilities, underinvest in inflation-linked securities, while pension funds overinvest. Investors hedging inflation risk exhibit a strong preference for bonds indexed to domestic rather than foreign inflation. A regulatory reform announcement provides quasi-experimental evidence that the demand for inflation-linked bonds may be shaped by regulatory requirements.
    Keywords: Inflation-linked bonds, investor clientele, securities holdings, sovereign bonds, TIPS
    JEL: F21 G11 G15 G22 G23
    Date: 2026–04
    URL: https://d.repec.org/n?u=RePEc:cnb:wpaper:2026/08
  6. By: Damm, Cara; Bauer, Kevin; Hett, Florian; Pelizzon, Loriana
    Abstract: The shift from information retrieval (keyword-based search engines) to information synthesis (generative AI) constitutes a fundamental change in how people inform themselves online. We investigate how this shift impacts investment behavior using an incentivized online experiment (N = 374), in which we vary whether participants have access to keyword-based search engines, an LLM-based chatbot, or no additional information source. We find that LLMs facilitate participation in the stock market. Participants with access to an LLM when making investment decisions are significantly more likely to enter the stock market and to remain invested compared to those with access to keyword-based search engines or no further information. Our experiment suggests that perceived difficulty of stock market participation decreases and confidence in these choices increases when using an LLM. However, we also document a substantial risk. Access to LLMs enables individuals to confirm and strengthen experimentally induced beliefs. Even when the chatbot itself is not biased, users can prompt the model to validate beliefs they want to hold. Overall, our findings suggest that while LLMs can reduce participation frictions and encourage stock market investments, their effectiveness in confirmation-seeking can also have detrimental consequences. Consequently, these results highlight the critical need for consumer protection frameworks and financial literacy programs that specifically address the unique dynamics of human-AI interaction in modern retail investing.
    Keywords: Large Language Models, Belief Formation, Motivated Reasoning, Financial Decision Making, Robo-Advisors, Stock Market Participation
    Date: 2026
    URL: https://d.repec.org/n?u=RePEc:zbw:safewp:340833
  7. By: Bauckloh, Michael Tobias; Kirsch, Paula
    Abstract: We study the green bond premium, defined as the yield differential between green and matched conventional bonds in the secondary market. Existing estimates vary widely, raising questions about their robustness. We address this by estimating the premium across more than 500, 000 empirical designs spanning common sample and methodological choices. In this multiverse setting, the average premium is -2.59 basis points. It varies systematically with sample composition, with more negative values for municipal bonds, and becomes more negative during periods of heightened climate attention. Finally, we investigate which choices drive variation in premium estimates. We find that it is driven primarily by issuer type and matching choices, while other choices, such as liquidity adjustment, contribute little to overall variation.
    JEL: C52 G11 G12 Q54
    Date: 2026
    URL: https://d.repec.org/n?u=RePEc:zbw:cfrwps:340841
  8. By: Dimitris Christelis (University of Glasgow, CSEF, and CFS); Dimitris Georgarakos (European Central Bank, University of Glasgow and CEPR); Tullio Jappelli (University of Naples Federico II, CSEF, and CEPR); Geoff Kenny (European Central Bank); Justus Meyer (European Central Bank, University of Glasgow)
    Abstract: We examine recent changes in stock market participation using newly available survey data from eleven euro area countries over the period 2020–2024. The evidence points to substantial turnover, with around10% of non-stockholders entering the market each year, and more than 20% of stockholders exiting. New entrants tend to have lower education, income, financial literacy, and risk tolerance than established investors, indicating a shift in the composition of market participants. We also highlight the growing importance of cryptocurrency investments among retail investors. Overall, these findings shed new light on evolving household financial behavior and its implications for market participation and financial stability.
    Keywords: Stocks, Mutual Funds, Crypto Assets, Household Finance, Consumer Expectations Survey
    JEL: D14 E21 G51
    Date: 2026–04–28
    URL: https://d.repec.org/n?u=RePEc:sef:csefwp:780

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