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on Financial Markets |
| By: | Fekria Belhouichet; Guglielmo Maria Caporale; Luis Alberiko Gil-Alana |
| Abstract: | This paper examines the long-memory properties of returns of exchange-traded funds (ETFs) specializing in robotics and artificial intelligence (AI) listed on the US market, as well as those of other assets such as the WTI crude oil price (West Texas Intermediate), Bitcoin, the S&P 500 index, 10-year US Treasury bonds, and the VIX volatility index. The frequency is daily and the sample period goes from 1 January 2023 to 23 June 2025. The adopted fractional integration framework is more general and flexible than those previously used in related studies, and sheds light on the degree of persistence of returns. The evidence suggests that all returns series examined are highly persistent, regardless of the error structure assumed, and that in general a linear model is appropriate to capture their evolution over time. The implications are that that the newly developed assets do not offer to investors additional hedging and diversification opportunities compared to more traditional ones, and that the creation of these additional financial instruments does not pose fresh challenges to policy makers tasked with financial stability. |
| Keywords: | persistence, fractional integration, long memory, trends, robotics ETFs, AI ETFs |
| JEL: | C22 G11 G12 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12171 |
| By: | Wiechers, Lukas |
| JEL: | C14 C22 G01 G12 G14 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:vfsc25:325420 |
| By: | Masyayuki Okada (Institute for Monetary and Economic Studies, Bank of Japan (E-mail: masayuki.okada@boj.or.jp)); Kazuhiro Teramoto (Graduate School of Economics, Hitotsubashi University, 2-1 Naka, Kunitachi, Tokyo, Japan. 186-8603. (Email: k.teramoto@r.hit-u.ac.jp)) |
| Abstract: | This paper proposes a novel mechanism explaining why large firms exhibit stronger stock price responses to monetary policy surprises. Empirically, we show that endogeneity arising from the ex-post predictability of these surprises disproportionately affects large firms, leading to overestimated stock return responses. We develop an asset pricing model with granular-origin aggregate fluctuations and investors' imperfect knowledge of monetary policy rule parameters. The model demonstrates that belief revisions about the policy stance drive both monetary policy surprises and heterogeneous stock price responses through changes in the risk premium - even without investor heterogeneity or differential effects of policy shocks on firm fundamentals. |
| Keywords: | monetary policy surprises, stock returns, high-frequency identification, partial information, learning, granular-origin aggregate fluctuations |
| JEL: | E43 E44 E52 E58 G12 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:ime:imedps:25-e-06 |
| By: | Charles Taragin; Benjamin Wallace; Eddie Watkins |
| Abstract: | We study how corporate debt influences the competitive outcomes of horizontal and conglomerate mergers. In contrast to standard models where debt does not affect pricing, our framework shows that mergers can spread fixed debt obligations across a broader product portfolio, creating an "insurance effect" against adverse demand shocks. This effect interacts with the traditional recapture effect from reduced competition. Using numerical simulations and a case study of a major casino merger, we find that debt can either dampen or amplify post-merger price increases, depending on the merger's structure and the market environment. |
| Keywords: | Financial structure; Merger simulation; Horizontal markets |
| JEL: | L41 L13 K21 G32 G34 |
| Date: | 2025–09–19 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-80 |