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on Financial Markets |
| By: | Adam Epp; Jeffrey Gao |
| Abstract: | This paper studies the rapid increase since 2019 of Government of Canada (GoC) debt issuance alongside greater hedge fund participation at GoC bond auctions. We find a systematic relationship between GoC debt stock and hedge fund bidding shares at auction. We attribute this to hedge funds’ business models, which are based on volume and leverage. We also use bid-level auction data and find that hedge funds are more willing than other investor types to buy bonds at lower auction yields (higher auction prices). These two results i) help explain why GoC auction performance has remained steady despite greater issuance and ii) affirm the importance of hedge funds in supporting Canada’s cost-effective debt distribution in recent years. In addition, we conduct a counterfactual analysis of the exit of hedge funds from auction, which further affirms the importance of hedge funds to GoC auction performance. However, the concentration of hedge funds represents a potential vulnerability because hedge funds have a greater flight risk relative to domestic real money investors and thus contribute to a potentially less stable investor base. |
| Keywords: | Debt management; Financial markets; Financial institutions; Financial stability |
| JEL: | D44 G12 G2 G23 H63 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocadp:25-07 |
| By: | Ørpetveit, Andreas (Dept. of Business and Management Science, Norwegian School of Economics) |
| Abstract: | Research shows that competition negatively impacts fund alpha. I derive that fund managers can counteract this impact by adjusting the level of active management. In an international sample, I find that the impact of competition in funds’ investment universe depends on its source: funds face decreasing returns to the total size of active funds and increasing returns to the total size of passive funds. This implies that managers should increase active management when passive fund competition rises and reduce it when active fund competition increases. Empirical evidence suggests that managers adjust only to changes in competition from passive funds. |
| Keywords: | Mutual funds; Active fund management; Competition; Decreasing returns to scale; Equilibrium |
| JEL: | G11 G20 G23 |
| Date: | 2025–05–08 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nhhfms:2025_014 |
| By: | Ørpetveit, Andreas (Dept. of Business and Management Science, Norwegian School of Economics) |
| Abstract: | Despite extensive evidence of how competition in the mutual fund industry affects fees and performance outcomes, less is known about its effect on the incentives of market participants. This paper examines how competition drives product development in mutual fund families. The results show that greater industry competition encourages fund families to focus more on enhancing product quality than altering the fund base. Quality development increases performance across family-affiliated funds, ultimately benefiting investors. Based on these results, I argue that competition helps mitigate conflicts of interest associated with the family-based structure of the industry. |
| Keywords: | Mutual funds; mutual fund families; competition; product development |
| JEL: | G11 G20 L10 |
| Date: | 2025–05–07 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nhhfms:2025_013 |
| By: | Gr\'egory Bournassenko |
| Abstract: | In recent years, cryptocurrencies have attracted growing attention from both private investors and institutions. Among them, Bitcoin stands out for its impressive volatility and widespread influence. This paper explores the predictability of Bitcoin's price movements, drawing a parallel with traditional financial markets. We examine whether the cryptocurrency market operates under the efficient market hypothesis (EMH) or if inefficiencies still allow opportunities for arbitrage. Our methodology combines theoretical reviews, empirical analyses, machine learning approaches, and time series modeling to assess the extent to which Bitcoin's price can be predicted. We find that while, in general, the Bitcoin market tends toward efficiency, specific conditions, including information asymmetries and behavioral anomalies, occasionally create exploitable inefficiencies. However, these opportunities remain difficult to systematically identify and leverage. Our findings have implications for both investors and policymakers, particularly regarding the regulation of cryptocurrency brokers and derivatives markets. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.18982 |
| By: | Giovanni Ballarin; Jacopo Capra; Petros Dellaportas |
| Abstract: | Stock return prediction is a problem that has received much attention in the finance literature. In recent years, sophisticated machine learning methods have been shown to perform significantly better than ''classical'' prediction techniques. One downside of these approaches is that they are often very expensive to implement, for both training and inference, because of their high complexity. We propose a return prediction framework for intraday returns at multiple horizons based on Echo State Network (ESN) models, wherein a large portion of parameters are drawn at random and never trained. We show that this approach enjoys the benefits of recurrent neural network expressivity, inherently efficient implementation, and strong forecasting performance. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.19623 |
| By: | Kandpal, Vinay; Ozili, Peterson K; Jeyanthi, Mary; Ranjan, Deepak; Chandra, Deep |
| Abstract: | Digital finance is revolutionizing the financial sector in significant ways. Its role in shaping the future of banks and financial services is a topic of widespread interest in the policy and academic literature. This study examines the role of digital finance in shaping the future of banks and financial services. The study shows that digital finance innovations are disrupting banking and the nature of financial services. Financial institutions that will survive in the future must undertake digital transformation to compete for market share in new customer segments and to meet the changing needs and preferences of customers. While nobody knows for sure what the future of banking and financial services will be in the distant future, it is certain that the digital finance revolution would change the face of banking and financial services in the future. Regulation, technology, and geopolitical factors could alter the future of banking and financial services. |
| Keywords: | digital finance, banks, financial services, future. |
| JEL: | G21 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:124267 |
| By: | Masoud Ataei |
| Abstract: | This paper investigates the structural dynamics of stock market volatility through the Financial Chaos Index, a tensor- and eigenvalue-based measure designed to capture realized volatility via mutual fluctuations among asset prices. Motivated by empirical evidence of regime-dependent volatility behavior and perceptual time dilation during financial crises, we develop a regime-switching framework based on the Modified Lognormal Power-Law distribution. Analysis of the FCIX from January 1990 to December 2023 identifies three distinct market regimes, low-chaos, intermediate-chaos, and high-chaos, each characterized by differing levels of systemic stress, statistical dispersion and persistence characteristics. Building upon the segmented regime structure, we further examine the informational forces that shape forward-looking market expectations. Using sentiment-based predictors derived from the Equity Market Volatility tracker, we employ an elastic net regression model to forecast implied volatility, as proxied by the VIX index. Our findings indicate that shifts in macroeconomic, financial, policy, and geopolitical uncertainty exhibit strong predictive power for volatility dynamics across regimes. Together, these results offer a unified empirical perspective on how systemic uncertainty governs both the realized evolution of financial markets and the anticipatory behavior embedded in implied volatility measures. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.18958 |
| By: | Ambedkar Dukkipati; Kawin Mayilvaghanan; Naveen Kumar Pallekonda; Sai Prakash Hadnoor; Ranga Shaarad Ayyagari |
| Abstract: | Fluctuations in stock prices are influenced by a complex interplay of factors that go beyond mere historical data. These factors, themselves influenced by external forces, encompass inter-stock dynamics, broader economic factors, various government policy decisions, outbreaks of wars, etc. Furthermore, all of these factors are dynamic and exhibit changes over time. In this paper, for the first time, we tackle the forecasting problem under external influence by proposing learning mechanisms that not only learn from historical trends but also incorporate external knowledge from temporal knowledge graphs. Since there are no such datasets or temporal knowledge graphs available, we study this problem with stock market data, and we construct comprehensive temporal knowledge graph datasets. In our proposed approach, we model relations on external temporal knowledge graphs as events of a Hawkes process on graphs. With extensive experiments, we show that learned dynamic representations effectively rank stocks based on returns across multiple holding periods, outperforming related baselines on relevant metrics. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.20058 |
| By: | Andrian, Leandro Gaston; Leon-Diaz, John; Rojas, Eugenio |
| Abstract: | We examine hedging as a macroprudential tool in a Sudden Stops model of an economy exposed to commodity price fluctuations. We find that hedging commodity revenues yields significant welfare gains by stabilizing public expenditure, which heavily depends on these revenues. However, this added stability weakens precautionary motives and exacerbates the pecuniary externality that drives overborrowing in such models. As a result, hedging and traditional macroprudential policy act as complements rather than substitutes, with more ag- gressive hedging inducing a stronger macroprudential response. Our findings suggest that while hedging enhances stability and improves welfare, it does not eliminate the need for macroprudential regulation. |
| Keywords: | Hedging;Sudden stops;Financial Crises;Macroprudential policy |
| JEL: | F32 F41 G13 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14083 |
| By: | Latino, Carmelo; Pelizzon, Loriana; Riedel, Max; Wang, Yue |
| Abstract: | Using hand-collected data on European auto asset-backed securities (Auto ABS), we examine the role of mutual funds in financing the transition to zero-emission mobility. Mutual funds, particularly those with a green mandate, tend to have a higher exposure to sustainability-transparent Auto ABS and tend to allocate more capital to deals with a higher proportion of electric vehicles. However, we find no clear preference for portfolios with lower average CO2 emissions. This behaviour suggests that, in the absence of a globally recognized framework for green securitizations, asset managers rely on sustainability proxies that are associated with the lowest disclosure processing costs. Our analysis provides important new evidence on how standardized sustainability disclosures at both the prospectus and loan levels could influence asset allocation. |
| Keywords: | Auto ABS, Car Loans, Zero- or low-emission vehicles, Mutual funds, Securitization, Sustainable Finance |
| JEL: | G11 G18 G20 Q56 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:safewp:316445 |