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on Financial Markets |
| By: | Andrew Atkeson; Fabrizio Perri; Jonathan Heathcote |
| Abstract: | We show that, to a first-order approximation, estimates of fluctuations in Shiller’s fundamental price relative to observed price depend primarily on forecasts of long-horizon expected returns. Researchers using different measures of cash flow and valuation may reach different conclusions about the extent to which values fluctuate excessively relative to fundamentals, but that is only because return forecasts based on different cash-flow-to-value measures will be different. Using U.S. equity data, we demonstrate that the amount of persistence in expected returns, rather than the amount of short-run return predictability, is the key determinant of implied excess volatility. Disagreements about stock market valuation therefore reduce to disagreements about long-run expected returns. |
| JEL: | E0 G12 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34923 |
| By: | Itzhak Ben-David; Alex Chinco |
| Abstract: | There are three classic problems in corporate finance: capital structure, real investment, and payout policy. In three companion papers, we characterize the max EPS solution to each one. The max EPS approach delivers an optimal leverage ratio even in the absence of frictions, an investment rule based on comparing yields rather than using a risk-adjusted discount rate, and a payout policy where accretive buybacks are preferred to neutral dividends. Our max EPS model draws a bright line between growth and value. Growth stocks have earnings yields below the riskfree rate; value stocks have earnings yields above it. This single comparison leads the two kinds of firms to pursue different constellations of EPS-maximizing policies. The model also produces easy-to-follow calculations that closely mirror what practitioners actually do. This review article ties together these results to form a new max EPS paradigm for corporate-finance research. |
| JEL: | G12 G31 G32 G35 M41 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34971 |
| By: | Antonio Ciccone (Univerity of Mannheim); Felix Rusche (Max Planck Institute for Behavioral Economics) |
| Abstract: | Despite rising stock markets in the United States and Europe from 2017 to 2024, we document that average daily stock market performance becomes negative when weighted by the amount of media coverage. We propose an explanation for this media negativity bias that does not rely on a bad-news bias in news selection. Instead, it rests on two observations: the media prioritize large market movements, positive or negative, and average daily stock market performance conditional on absolute changes above a threshold becomes negative as the threshold increases. We quantify the explanatory power of the proposed mechanism using data from Germany’s most-watched nightly news, which reports on the country's main stock index in a standardized format. Our analysis shows that selective reporting of large market movements accounts for about half the gap in average daily stock market performance between days with and without news coverage. We explain and quantify the link between media negativity bias and the negative skewness of aggregate stock returns. |
| Keywords: | Media Negativity, Financial Markets, Financial Journalism |
| JEL: | L82 G10 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkdps:395 |
| By: | Mengzhong Ma; Te Bao; Yonggang Wen |
| Abstract: | We document the first systematic evidence of negative spillover effects in crypto asset returns across blockchains. Using on-chain data from Ethereum, Solana, Binance Smart Chain, Arbitrum, and Avalanche (2022-2025), we show that surges on one chain often coincide with declines on others, in contrast to the positive co-movements typical of equity markets. These spillovers intensify during attention shocks, proxied by chain activity and extreme return events, and persist after controlling for global equity returns, interest rates, and Bitcoin. Nonlinear factor models reveal that attention-driven capital reallocation, rather than common information, underlies these dynamics. Our findings introduce a new form of cross-market linkage, attention-induced substitution, that shapes risk transmission in crypto markets. The results carry implications for portfolio diversification, systemic risk measurement, and regulation of token launches that may trigger cross-chain capital flight. |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2602.23762 |
| By: | R. Benkraiem (Audencia Business School); N. Dimic; V. Piljak; L. Swinkels |
| Abstract: | We examine the impact of the media-based climate risks, grouped into physical and transition risk categories, on the international corporate bond market in the period from 2012 to 2022. We analyze the following aspects: (i) market development (developed versus emerging markets); (ii) credit quality (investment grade versus high yield bonds), (iii) industry (climate-sensitive versus non-sensitive industries), and (iv) maturity (short versus long term bonds). We find that transition risk is reflected in the global corporate bond market, but not in the emerging corporate bond market segment. Furthermore, transition risk has a material impact only on the investment grade bonds in the global corporate bond market. The industry analysis reveals that there are no consistent significant differences between climate-sensitive and climate-insensitive industries. Maturity analysis indicates that transition risk is reflected in global corporate bond market returns for both short and long terms, but this effect is less pronounced in emerging markets. Physical risk is not systematically reflected in international corporate bond returns. The subsample analysis shows higher importance of transition climate risk following the Paris Agreement in December 2015. |
| Keywords: | Climate risk, Corporate bonds, Debt, Emerging markets, Physical risk, Transition risk |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05535568 |
| By: | Mohammad Al Ridhawi; Mahtab Haj Ali; Hussein Al Osman |
| Abstract: | Stock market prediction presents considerable challenges for investors, financial institutions, and policymakers operating in complex market environments characterized by noise, non-stationarity, and behavioral dynamics. Traditional forecasting methods often fail to capture the intricate patterns and cross-sectional dependencies inherent in financial markets. This paper presents an integrated framework combining a node transformer architecture with BERT-based sentiment analysis for stock price forecasting. The proposed model represents the stock market as a graph structure where individual stocks form nodes and edges capture relationships including sectoral affiliations, correlated price movements, and supply chain connections. A fine-tuned BERT model extracts sentiment from social media posts and combines it with quantitative market features through attention-based fusion. The node transformer processes historical market data while capturing both temporal evolution and cross-sectional dependencies among stocks. Experiments on 20 S&P 500 stocks spanning January 1982 to March 2025 demonstrate that the integrated model achieves a mean absolute percentage error (MAPE) of 0.80% for one-day-ahead predictions, compared to 1.20% for ARIMA and 1.00% for LSTM. Sentiment analysis reduces prediction error by 10% overall and 25% during earnings announcements, while graph-based modeling contributes an additional 15% improvement by capturing inter-stock dependencies. Directional accuracy reaches 65% for one-day forecasts. Statistical validation through paired t-tests confirms these improvements (p |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2603.05917 |
| By: | Broner, Fernando; Cortina Lorente, Juan Jose; Schmukler, Sergio; Williams, Tomas |
| Abstract: | This paper examines how shifts in investor demand influence firm financing and investment decisions. For identification, the paper exploits a large-scale MSCI methodo logical reform that mechanically redefined the stock weights in major international equity benchmark indexes, changing the portfolio allocation of 2, 508 firms across 49 countries. Because benchmark-tracking investors closely follow these indexes, the rebalancing constituted a clean shock to equity demand. The results show that portfolio rebalancing by benchmark-tracking investors generated significant capital inflows and outflows at the firm level. Firms experiencing larger inflows increased equity issuance, even more so debt financing, and real investment. The paper complements the empirical analysis with a simple model of firm financing in which a decline in the cost of equity increases the value of equity and relaxes borrowing constraints. Higher equity valuations allow firms to expand borrowing even without issuing substantial new equity, so debt financing responds more strongly than equity issuance. |
| Date: | 2026–02–18 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:11315 |
| By: | Marina Emiris (National Bank of Belgium, Research Department); Joanna Harris (Chicago Booth School of Business.); François Koulischer (University of Luxembourg.) |
| Abstract: | We study how sustainability disclosure regulation affects mutual fund flows and portfolio choices, accounting for investor heterogeneity. Guided by a model of ESG investing under uncertainty, we exploit the introduction of the European Sustainable Finance Disclosure Regulation (SFDR) as a natural experiment, using granular fund–investor holdings data. We show that funds subject to higher disclosure requirements attract significantly larger inflows, particularly for funds with higher pre-regulation uncertainty. Institutional investors respond more strongly than retail investors, and investor trust in environmental labels amplifies these effects. We also find evidence that disclosure induces fund managers to increase portfolio greenness. |
| Keywords: | Mutual funds; Disclosure Regulation; Trust; ESG ratings. |
| JEL: | G23 G11 G14 Q56 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:nbb:reswpp:202603-490 |
| By: | Thomas Dulak; Guntram Wolff |
| Abstract: | Since the first green bond was issued in 2007, the market has expanded significantly and now accounts for around 3% of the global bond universe. Westudy the liquidity of green bonds. In particular, we are the first to investigategreen bonds’ daily trading volumes and frequency with a unique dataset fromEuroclear. Studying these dimensions of liquidity is particularly important in relatively small markets. Our dataset, covering the period 2020 to 2025, allows us todirectly compare green bonds with conventional bonds. We find that green bondsdo not suffer from a systematic liquidity disadvantage relative to conventionalbonds. On the contrary, they are traded in higher aggregate volumes, drivenby more frequent trading rather than by larger transaction sizes. These differences persist during periods of heightened market-wide stress. Within the greenbond universe, third-party certification is associated with higher trading volumesthrough more intensive trading when bonds are active, while green bonds funding more common project types are traded more regularly than bonds financingmore niche projects |
| Keywords: | Green bonds; Bond liquidity; Trading activity; Market stress; Certification |
| JEL: | G11 G23 Q56 |
| Date: | 2026–03–01 |
| URL: | https://d.repec.org/n?u=RePEc:eca:wpaper:2013/404323 |
| By: | Michael J. Fleming; Weiling Liu; Giang Nguyen |
| Abstract: | Using thirty-three years of intraday Treasury data, we provide the first high-frequency evidence on auction-day price pressure: yields rise in the hours before auction and reverse afterward. This pressure strengthens when dealers face tighter risk-bearing constraints and weakens when investor demand is stronger or more elastic. More importantly, net order flow dominates in explaining the pressure, providing the first direct evidence that trading transmits dealer constraints into prices. Despite concerns about dealer capacity amid rapid federal debt growth, price pressure has not increased in recent years, partly because non-dealer participants now absorb more auction supply and ease dealers’ intermediation burden. |
| Keywords: | Treasury auctions; dealer intermediation; order flow; Price pressure; Supply effects; risk bearing capacity; returns; demand elasticity; liquidity; frictions |
| JEL: | G12 G14 E43 H63 |
| Date: | 2026–03–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednsr:102915 |