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on Financial Markets |
| By: | Davis, Carter (Indiana U Bloomington); Knupfer, Samuli (Aalto U and BI Norwegian Business School); Kvaerner, Jens Soerlie (Tilburg U); Dogan, Bahar Sen (Tilburg U); Vokata, Petra (Ohio State U) |
| Abstract: | Contrary to the common assertion that households have little impact on stock prices, we find their relevance is of first order. We quantify their impact using an assetdemand system applied to the complete ownership data for all Norwegian stocks from 2007 to 2020. Households contribute the most to stock market volatility relative to their market share. Even in absolute terms, they come second, surpassed only by institutional investors. Our granular data on households reveal a strong factor structure in household demand: The demand of the rich is distinct from less affluent investors, accounts for the bulk of volatility attributable to households, tilts away from ESG, and is informative about future firm fundamentals. We conclude by using the demand system to measure the profits one can make from trading on household demand shocks. |
| JEL: | G11 G12 G50 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:ecl:ohidic:2024-23 |
| By: | Toomas Laarits; Jeffrey Wurgler |
| Abstract: | Browser data from an approximately representative sample of individual investors offers a detailed account of their search for information, including how much time they spend on stock research, which stocks they research, what categories of information they seek, and when they gather information relative to events and trades. The median individual investor spends approximately six minutes on research per trade on traded tickers, mostly just before the trade; the mean spends around half an hour. Individual investors spend the most time reviewing price charts, followed by analyst opinions, and exhibit little interest in traditional risk statistics. Aggregate research interest is highly correlated with stock size, and salient news and earnings announcements draw more attention. Individual investors have different research styles, and those that focus on short-term information are more likely to trade more speculative stocks. |
| JEL: | G02 G11 G12 G4 G40 G41 G5 G50 G53 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33625 |
| By: | Xavier Gabaix; Ralph S. J. Koijen; Robert J. Richmond; Motohiro Yogo |
| Abstract: | Firm characteristics, based on accounting and financial market data, are commonly used to represent firms in economics and finance. However, investors collectively use a much richer information set beyond firm characteristics, including sources of information that are not readily available to researchers. We show theoretically that portfolio holdings contain all relevant information for asset pricing, which can be recovered under empirically realistic conditions. Such guarantees do not exist for other data sources, such as accounting or text data. We build on recent advances in artificial intelligence (AI) and machine learning (ML) that represent unstructured data (e.g., text, audio, and images) by high-dimensional latent vectors called embeddings. Just as word embeddings leverage the document structure to represent words, asset embeddings leverage portfolio holdings to represent firms. Thus, this paper is a bridge from recent advances in AI and ML to economics and finance. We explore various methods to estimate asset embeddings, including recommender systems, shallow neural network models such as Word2Vec, and transformer models such as BERT. We evaluate the performance of these models on three benchmarks that can be evaluated using a single quarter of data: predicting relative valuations, explaining the comovement of stock returns, and predicting institutional portfolio decisions. We also estimate investor embeddings (i.e., representations of investors and their strategies), which are useful for investor classification, performance evaluation, and detecting crowded trades. We discuss other applications of asset embeddings, including generative portfolios, risk management, and stress testing. Finally, we develop a framework to give an economic narrative to a group of similar firms, by applying large language models to firm-level text data. |
| JEL: | C53 G12 G23 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33651 |
| By: | Antonio Ciccone; Felix Rusche |
| Abstract: | Between 2017 and 2024, the main national stock market indices rose in the US and the five largest European economies. However, the average daily performance of all six indices turns from positive to negative when weighted by daily media coverage. A case in point is the average daily performance of Germany’s DAX index on days it was reported on the country’s most-watched nightly news. While the DAX increased by more than 4 index points per day over the period, the index dropped by more than 10 points on days it was reported – news was bad news. On days the DAX wasn’t covered on the nightly news, the index rose by around 10 points – no news was good news. About half of the worse daily performance when the DAX was covered is accounted for by a greater focus on negative news. The other half stems from a novel big news bias: a greater focus on large index changes, whether positive or negative, combined with a negative skew in the daily performance of the index. We show that the big news bias extends to other national stock market indices. |
| Keywords: | Media Bias, Financial Markets |
| JEL: | L82 G10 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_682 |
| By: | Pablo D. Azar; Adrian Casillas; Maryam Farboodi |
| Abstract: | In our previous Liberty Street Economics post, we introduced the decentralized finance (DeFi) intermediation chain and explained how various players have emerged as key intermediaries in the Ethereum ecosystem. In this post, we summarize the empirical results in our new Staff Report that explains how the need for transaction privacy across the DeFi intermediation chain gives rise to intermediaries’ market power. |
| Keywords: | financial intermediation; market power; decentralized finance |
| JEL: | G23 D82 L14 L22 G14 D43 |
| Date: | 2025–04–21 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:99874 |
| By: | Martín Sola; Fabio Spagnolo; Francisco Terfi |
| Abstract: | Stock markets experience periods where stocks or market returns are consistently higher than their mean and other periods where the individual stocks and markets’ volatility fluctuates from high to low. Since these periods do not necessarily coincide, a related question is whether periods where individual stock markets are higher than their mean, usually identified as αs different from zero in the conditional regressions, disappear once the researcher accounts for changing states of the economy. In this spirit, we develop and estimate a state-dependent version of the CAPM pricing model that accounts for considerable swings in the data. We use U.S. financial data to assess the model’s validity and find support for a state-dependent version of the CAPM for the data under consideration. We show how important it is to consider changes in stock and market returns and changes in their variance-covariances, and that, when not accounting for changes in market conditions, may spuriously yield significant α values. We stress that to assess changes in the risk premium, we should not only focus on βs but also allow for changes in the market premium; otherwise, changes in risk premia may be over- or underestimated. In addition, the classification between investment opportunities may be mistaken for a single regime model, even when rolling regressions are used. |
| Keywords: | Non-diversifiable Risk Premium; Markov Chain; Structural Breaks. |
| JEL: | G00 G12 E44 C32 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:udt:wpecon:2025_02 |
| By: | Romulo Alves (SKEMA Business School); Philipp Krueger (University of Geneva - Geneva Finance Research Institute (GFRI); Swiss Finance Institute; European Corporate Governance Institute (ECGI); University of Geneva - Geneva School of Economics and Management); Mathijs A. van Dijk (Erasmus University Rotterdam (EUR)) |
| Abstract: | We provide the most comprehensive analysis to date of the relation between ESG ratings and stock returns, using 16, 000+ stocks in 48 countries and seven different ESG rating providers. We find very little evidence that ESG ratings are related to global stock returns between 2001 and 2020. This finding obtains across different regions, time periods, ESG (sub)ratings, ESG momentum, ESG downgrades and upgrades, and best-in-class strategies. We further find little empirical support for prominent hypotheses from the literature on the role of ESG uncertainty and of country-level ESG social norms, ESG disclosure standards, and ESG regulations in shaping the relation between ESG and global stock returns. Overall, our results suggest that ESG investing did not systematically affect investment performance during the past two decades. |
| Keywords: | ESG investing, Environmental, Social & Governance, Global stock returns, ESG uncertainty, Country characteristics |
| JEL: | G11 G12 G15 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:chf:rpseri:rp2541 |
| By: | Fangfang Wang (Autonomous University of Barcelona); Florina Silaghi (Autonomous University of Barcelona); Steven Ongena (University of Zurich - Department Finance; Swiss Finance Institute; KU Leuven; NTNU Business School; Centre for Economic Policy Research (CEPR)); Miguel García-Cestona (Autonomous University of Barcelona) |
| Abstract: | We investigate the impact of ESG rating changes and daily ESG news sentiment on firm credit risk. We document a significant increase in CDS spreads following ESG rating downgrades, especially for the social pillar, while we find a muted reaction to ESG upgrades. A similar asymmetrical effect is documented for ESG news. We further show that the adverse effect of ESG downgrades on the CDS market is mitigated in the presence of positive ESG sentiment, a transparent information environment and higher rating disagreement. Lastly, the reaction is stronger for firms with lower creditworthiness, higher bankruptcy probability and tighter financial constraints. |
| Keywords: | ESG ratings, Credit default swaps, Event study, ESG news sentiment |
| JEL: | G14 G32 M14 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:chf:rpseri:rp2524 |
| By: | Campbell R. Harvey; Michele G. Mazzoleni; Alessandro Melone |
| Abstract: | Institutional investors engage in trillions of dollars of regular portfolio rebalancing, often based on calendar schedules or deviations from allocation targets. We document that such rebalancing has a market impact and generates predictable price patterns. When stocks are overweight, funds sell stocks and buy bonds, leading to a decrease in equity returns of 17 basis points over the next day. Our results are robust to controls for momentum, reversals, and macroeconomic information. Importantly, we estimate that current rebalancing practices cost investors about $16 billion annually—or $200 per U.S. household. Moreover, the predictability of these trades enables certain market participants to profit by front-running the orders of large institutional funds. While rebalancing remains a fundamental tool for investors, our findings highlight the costs associated with prevailing strategies and emphasize the need for innovative approaches to mitigate these costs. |
| JEL: | G0 G12 G14 G23 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33554 |
| By: | Guglielmo Maria Caporale; Luis Alberiko Gil-Alana; Leyre Muñoz |
| Abstract: | This paper examines the stochastic behaviour of the number of earthquakes (in total and also classified by magnitude) and stock market log prices and returns in the case of Japan over the period from January 2009 to February 2024 using fractional integration methods. Their linkages are then investigated by means of regression analysis. The results indicate that the former variable exhibits short-memory, I(0) behaviour. By contrast, stock market prices appear to be an I(d), fractional integration process, with d less than 1. Since the orders of integration of the two variables are different, we treat seismic events as exogenous in the context of a regression model with stock returns. The findings suggest that earthquakes have a statistically significant, though relatively small, negative impact on the Nikkei 225 index. More specifically, there exists a negative relationship between the magnitude and number of earthquakes and monthly stock returns. This suggests that seismic activity creates uncertainty in the market, which in turn affects its performance. |
| Keywords: | stock market prices, earthquakes, Japan, persistence, fractional integration. |
| JEL: | C22 C58 G14 Q54 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11822 |
| By: | Angie Andrikogiannopoulou (King’s College London); Philipp Krueger (University of Geneva - Geneva Finance Research Institute (GFRI); Swiss Finance Institute; European Corporate Governance Institute (ECGI); University of Geneva - Geneva School of Economics and Management); Shema Frédéric Mitali (SKEMA Business School); Filippos Papakonstantinou (King’s College London) |
| Abstract: | We construct novel measures of mutual funds’ environmental, social, and governance (ESG) commitment by analyzing the discretionary investment-strategy descriptions of their prospectuses. We find that fund flows respond strongly to such text-based ESG measures. Using discrepancies between text- and fundamentals-based ESG measures, we identify greenwashing. We find that greenwashing is more prevalent since ESG issues have started attracting mainstream attention and among funds with lower past flows and weaker oversight. Furthermore, greenwashers attract similar flows but have worse performance than genuinely-green funds, suggesting that investors cannot distinguish them and suffer welfare losses. Our methodology could help regulators combat ESG-related misconduct. |
| Keywords: | ESG, Prospectus, Greenwashing, Text Analysis, Mutual Funds, Fund Flows, Fund Performance |
| JEL: | G11 G23 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:chf:rpseri:rp2543 |