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on Financial Markets |
| By: | Matteo Crosignani; Lina Han; Marco Macchiavelli |
| Abstract: | Geoeconomic risk—the risk that firms incur valuation losses when countries deploy economic, trade, or financial leverage for geopolitical aims—has become a first-order concern for investors. In this post, based on our recent Staff Report, we document that domestic U.S. stocks expose investors to substantial geoeconomic risk through firms’ global supply-chain relationships, affecting investors’ returns and portfolio allocation. We also find that investors are compensated for bearing geoeconomic risk through higher risk premia. |
| Keywords: | mutual funds; Asset allocation; geoeconomic risk; export controls |
| JEL: | G12 F51 F38 |
| Date: | 2026–10–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:103863 |
| By: | Keith Hazen (Federal Reserve Bank of Philadelphia and Rutgers University); Julapa Jagtiani (Federal Reserve Bank of Philadelphia); Loretta J. Mester (Wharton School of Business, University of Pennsylvania and Griswold Center for Economic Policy Studies, Princeton University) |
| Abstract: | Using transaction-level data for Bitcoin (BTC), Ethereum (ETH), and Wrapped Bitcoin (WBTC) matched to public “Whale Alert†signals, we examine how large-scale cryptocurrency trades shape market microstructure. Specifically, we test whether whale transactions alter the composition of active non-whale participants, trigger leader-follower herd behavior, and elevate short-term return volatility. We document a stark divergence between networks: Whale alerts heavily reshape (native) BTC participation by mobilizing previously inactive retail and institutional investors, whereas ETH and WBTC participant profiles remain highly stable on the Ethereum platform. Furthermore, non-whale investors exhibit strong leader-follower behavior in the BTC market — buying and selling in tandem with whale direction. This pattern is largely absent in the Ethereum ecosystem, except among the largest non-whale tranches. These behavioral dynamics directly mirror market stability: Whale alerts induce a brief 24-hour spike in BTC volatility (most acutely following WBTC alerts) but coincide with compressed volatility on the Ethereum platform. Additionally, these asymmetric market responses persisted across Ethereum’s transition from proof-of-work to proof-of-stake. These findings indicate persistent informational and structural asymmetries between large and small digital-asset investors. |
| Keywords: | Cryptocurrency, Ethereum, ETH, Bitcoin, WBTC, crypto whales, DeFi |
| JEL: | G14 G23 G28 G41 |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:pri:cepsud:358 |
| By: | Chaudhary, Manav; Zhiyu Fu, Julie; Li, Jian |
| Abstract: | Many economic questions require estimating the price effect of demand shifts (multipliers) in the bond market. Corporate bonds have salient characteristics that distin guish close versus distant substitutes. We show that accounting for the heterogeneous substitutability between bonds is critical for estimating multipliers correctly. By al lowing for heterogeneous substitution, we find that security-level multipliers are very small—an order of magnitude smaller than the estimate ignoring heterogeneous substi tutability. Nonetheless, portfolio multipliers are substantially larger and monotonically increase with the aggregation level. Furthermore, we find that the multiplier is larger for high-yield bonds, longer-maturity bonds, and bonds with greater arbitrage risks. |
| Keywords: | corporate bonds;inelastic demand;mutual funds;demand-based asset pricing |
| JEL: | G10 G12 G23 |
| Date: | 2026–09–19 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:138916 |
| By: | Beáta Horváth (Magyar Nemzeti Bank (Central Bank of Hungary)); Tamás Berki (Magyar Nemzeti Bank (Central Bank of Hungary)); Lívia Réka Ónozó (Magyar Nemzeti Bank (Central Bank of Hungary)); Csanád Temesvári (Magyar Nemzeti Bank (Central Bank of Hungary)) |
| Abstract: | This paper proposes a sentiment-based financial stress indicator for Hungary based on occurrence of financial crisis related terms and explores its relationship with macrofinancial variables related to financial uncertainty. Sentiment analysis was conducted on textual data from two major Hungarian news portals covering the period from 2005 to 2020. The terms used in the analysis carry negative connotations, making them suitable for capturing financial instability and stress. The index successfully identifies stress periods that are not adequately reflected by other available sentiment indices related to Hungary. Overall, we propose a novel type of index that enables timely, even real-time monitoring of financial stress situation in Hungary across different time frequencies. |
| Keywords: | sentiment; financial stress; text analysis |
| JEL: | C32 E44 G01 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:mnb:wpaper:2026/3 |