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on Financial Markets |
| By: | Kirilenko, A.; Kraus, W.; Linton, O. B.; Xiao, M. |
| Abstract: | Authorised Participants (APs), primarily market makers, possess the right to create and redeem Exchange Traded Funds (ETF) shares based on market demand. The important role they play in facilitating liquidity provision and eliminating ETF mispricing makes their behaviour crucial to the well-functioning of the ETF market. Using a novel regulatory dataset that covers the primary and secondary market transactions of 128 ETFs from 2018 to 2022, we identify a connection between mispricing (the difference between ETF prices and the Net Asset Value (NAV) of their underlying baskets) and AP's inventory. We found that the skill of specialized traders (APs) in managing inventory and the overall demand for an ETF are important reasons why its price might temporarily be "wrong." Our model predicted this, and our real-world data backs it up, showing these factors add explanatory power on top of standard economic or fundamental influences. Further, our model is helpful for understanding the incentive structure of APs’ market makingand arbitraging, as well as the mechanisms behind the significant mispricing observed in March 2020 across various ETF classes. |
| Date: | 2025–05–30 |
| URL: | https://d.repec.org/n?u=RePEc:cam:camdae:2537 |
| By: | Daniel Barth; Stacey L. Schreft |
| Abstract: | This article refines the concept of black swans, typically described as highly unlikely and catastrophic events, by clearly distinguishing between knowable and unknowable events. By emphasizing that black swans are “unknown unknowns, ” the article highlights that the realization of new black swans cannot be prevented and motivates a need for policies that build the financial system's resilience to unforeseeable crises. The article introduces a "resilience principle" that calls for policies that are adaptable, universal, and systemic. Examples are provided of policies with these features, none of which relies on the official sector being better positioned than the private sector to anticipate the unknown. |
| Keywords: | Black Swans; Systemic Risk; Uncertainty; Financial Stability |
| JEL: | G01 G10 E44 D80 H41 |
| Date: | 2025–06–06 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-43 |
| By: | Sukru Selim Calik; Andac Akyuz; Zeynep Hilal Kilimci; Kerem Colak |
| Abstract: | Financial literacy is increasingly dependent on the ability to interpret complex financial data and utilize advanced forecasting tools. In this context, this study proposes a novel approach that combines transformer-based time series models with explainable artificial intelligence (XAI) to enhance the interpretability and accuracy of stock price predictions. The analysis focuses on the daily stock prices of the five highest-volume banks listed in the BIST100 index, along with XBANK and XU100 indices, covering the period from January 2015 to March 2025. Models including DLinear, LTSNet, Vanilla Transformer, and Time Series Transformer are employed, with input features enriched by technical indicators. SHAP and LIME techniques are used to provide transparency into the influence of individual features on model outputs. The results demonstrate the strong predictive capabilities of transformer models and highlight the potential of interpretable machine learning to empower individuals in making informed investment decisions and actively engaging in financial markets. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.06345 |
| By: | Dangxing Chen |
| Abstract: | In recent years, machine learning models have achieved great success at the expense of highly complex black-box structures. By using axiomatic attribution methods, we can fairly allocate the contributions of each feature, thus allowing us to interpret the model predictions. In high-risk sectors such as finance, risk is just as important as mean predictions. Throughout this work, we address the following risk attribution problem: how to fairly allocate the risk given a model with data? We demonstrate with analysis and empirical examples that risk can be well allocated by extending the Shapley value framework. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.06653 |
| By: | Comerton-Forde, Carole (University of Melbourne); Ford, Billy (None); Foucault, Thierry (HEC Paris); Jurkatis, Simon (Bank of England) |
| Abstract: | Investors act as a liquidity backstop in the corporate bond market. By providing liquidity, investors help ease dealers’ balance sheet constraints, especially during market stress. During the March 2020 Dash-for-Cash, in bonds where investors stopped providing liquidity, transaction costs rose by 38%. We find the composition of types of liquidity providers – rather than just their presence – shapes trading costs. Dealers relying on flexible-mandate investors, such as hedge funds, are more resilient to liquidity shocks. Dealers offer discounts to investors for past liquidity services to maintain liquidity provider networks. These discounts represent two thirds of relationship discounts. |
| Keywords: | Bond markets; liquidity; client-sourced liquidity; balance sheet cost |
| JEL: | G10 G14 G23 |
| Date: | 2025–05–16 |
| URL: | https://d.repec.org/n?u=RePEc:boe:boeewp:1126 |
| By: | Cascino, Stefano; Széles, Máté; Veenman, David |
| Abstract: | Recent studies conclude that CEO debt-like incentives, such as defined benefit pensions and deferred compensation (“inside debt”), improve financial reporting quality. We challenge this result on conceptual grounds and evaluate its sensitivity to empirical specification. We reexamine the relation between accrual-based measures of financial reporting quality and CEO inside debt variables and find that it is an artifact of correlated omitted factors that prior studies do not effectively control for. Specifically, we show that the relation disappears when we control for factors related to the volatility and uncertainty of firms’ operating environments. Using a two-step approach, we illustrate how the relation between inside debt and accrual-based financial reporting quality measures is driven entirely by the portion of inside debt that is correlated with these factors, rather than a direct effect of inside debt itself. Our findings challenge the prevailing consensus on the incentive effects of inside debt and suggest that prior evidence is likely confounded by omitted variable bias. |
| Keywords: | inside debt; pensions; deferred compensation; executive compensation; incentives; financial reporting quality; accrurals; earnings management; reexamination; replication |
| JEL: | M41 G32 G33 |
| Date: | 2025–05–28 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:128078 |
| By: | Martijn Boermans |
| Abstract: | Governments across the world have issued inflation-linked debt to finance their deficits. Recent advances in asset pricing models recognize that there may be clientele effects that affect relative prices, especially in bond markets. We study investor demand for inflation-linked bonds using detailed bond portfolio data. Our analysis reveals pronounced market segmentation: insurance companies, with predominantly nominal liabilities, underinvest in inflation-linked securities, while pension funds overinvest. Investors hedging inflation risk exhibit a strong preference for bonds indexed to domestic rather than foreign inflation. A regulatory reform announcement provides quasi-experimental evidence that the demand for inflation-linked bonds may be shaped by regulatory requirements. |
| Keywords: | sovereign bonds; inflation-linked bonds; TIPS; investor clientele; securities holdings |
| JEL: | F21 G11 G15 G22 G23 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:dnb:dnbwpp:838 |
| By: | Zheng Cao; Wanchaloem Wunkaew; Helyette Geman |
| Abstract: | This paper introduces the Hype Index as a novel metric to quantify media attention toward large-cap equities, leveraging advances in Natural Language Processing (NLP) for extracting predictive signals from financial news. Using the S&P 100 as the focus universe, we first construct a News Count-Based Hype Index, which measures relative media exposure by computing the share of news articles referencing each stock or sector. We then extend it to the Capitalization Adjusted Hype Index, adjusts for economic size by taking the ratio of a stock's or sector's media weight to its market capitalization weight within its industry or sector. We compute both versions of the Hype Index at the stock and sector levels, and evaluate them through multiple lenses: (1) their classification into different hype groups, (2) their associations with returns, volatility, and VIX index at various lags, (3) their signaling power for short-term market movements, and (4) their empirical properties including correlations, samplings, and trends. Our findings suggest that the Hype Index family provides a valuable set of tools for stock volatility analysis, market signaling, and NLP extensions in Finance. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.06329 |
| By: | Mihai Cucuringu; Kang Li; Chao Zhang |
| Abstract: | This study focuses on forecasting intraday trading volumes, a crucial component for portfolio implementation, especially in high-frequency (HF) trading environments. Given the current scarcity of flexible methods in this area, we employ a suite of machine learning (ML) models enriched with numerous HF predictors to enhance the predictability of intraday trading volumes. Our findings reveal that intraday stock trading volume is highly predictable, especially with ML and considering commonality. Additionally, we assess the economic benefits of accurate volume forecasting through Volume Weighted Average Price (VWAP) strategies. The results demonstrate that precise intraday forecasting offers substantial advantages, providing valuable insights for traders to optimize their strategies. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.08180 |
| By: | Duy-Minh Dang; Chang Chen |
| Abstract: | We investigate multi-period mean-risk portfolio optimization for long-horizon Defined Contribution plans, focusing on buffered Probability of Exceedance (bPoE), a more intuitive, dollar-based alternative to Conditional Value-at-Risk (CVaR). We formulate both pre-commitment and time-consistent Mean-bPoE and Mean-CVaR portfolio optimization problems under realistic investment constraints (e.g., no leverage, no short selling) and jump-diffusion dynamics. These formulations are naturally framed as bilevel optimization problems, with an outer search over the shortfall threshold and an inner optimization over rebalancing decisions. We establish an equivalence between the pre-commitment formulations through a one-to-one correspondence of their scalarization optimal sets, while showing that no such equivalence holds in the time-consistent setting. We develop provably convergent numerical schemes for the value functions associated with both pre-commitment and time-consistent formulations of these mean-risk control problems. Using nearly a century of market data, we find that time-consistent Mean-bPoE strategies closely resemble their pre-commitment counterparts. In particular, they maintain alignment with investors' preferences for a minimum acceptable terminal wealth level-unlike time-consistent Mean-CVaR, which often leads to counterintuitive control behavior. We further show that bPoE, as a strictly tail-oriented measure, prioritizes guarding against catastrophic shortfalls while allowing meaningful upside exposure, making it especially appealing for long-horizon wealth security. These findings highlight bPoE's practical advantages for long-horizon retirement planning. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.22121 |
| By: | Cristian Chica; Yinglong Guo; Gilad Lerman |
| Abstract: | We introduce pricing formulas for competition and collusion models of two-sided markets with an outside option. For the competition model, we find conditions under which prices and consumer surplus may increase or decrease if the outside option utility increases. Therefore, neglecting the outside option can lead to either overestimation or underestimation of these equilibrium outputs. Comparing collusion to competition, we find that in cases of small cross-side externalities, collusion results in decreased normalized net deterministic utilities, reduced market participation and increased price, on both sides of the market. Additionally, we observe that as the number of platforms increases in the competition model, market participation rises. Profits, however, decrease when the net normalized deterministic utility is sufficiently low but increase when it is high. Furthermore, we identify specific conditions that quantify the change of price and consumer surplus when the competition increases. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.06109 |
| By: | Tsvetelina Nenova; Andreas Schrimpf; Hyun Song Shin |
| Abstract: | We show that outstanding volumes in FX swaps serve as a good indicator for the hedging activity associated with portfolio positions of advanced economy bond investors. As such, FX swaps serve as a key barometer of risk-taking and global financial conditions. We develop a simple portfolio choice model for international bond investors and use it to estimate the relationship between global FX hedging activity, relative investment opportunities (captured by the yield curve slopes in respective economies), and the hedging costs associated with underlying investments. We find that higher FX hedging activity is closely associated with US portfolio debt inflows and outflows, indicating that FX hedging plays a crucial role in facilitating cross-border bond investments. This connection between FX hedging motives, portfolio bond flows, and the yield curve highlights a mechanism of international financial spillovers - not only from the US but also from advanced economies with significant accumulated wealth flowing into the US. |
| Keywords: | global portfolio investments, FX hedging, financial conditions |
| JEL: | F31 F32 F42 G15 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:bis:biswps:1273 |
| By: | Eleni Gousgounis; Scott Mixon; Tugkan Tuzun; Clara Vega |
| Abstract: | We study the behavior of liquidity providers and liquidity consumers in the 10-year U.S. Treasury futures market during the height of the COVID-19 shock in March 2020, a period of market turmoil when demand for liquidity was high. In March 2020, PTFs reduced their volume of liquidity providing trades as a share of total trading volume. However, they still accounted for the lion share of total liquidity provision and their liquidity provision improved market liquidity. In contrast, dealers (banks and non-banks) increased their volume of liquidity providing trades as a share of total trading volume, but their activity did not have a large effect on overall liquidity. Among the traders that place liquidity consuming trades, asset managers had the largest impact on liquidity by increasing transaction costs. Despite a significant attention to the role of basis traders in the Treasury market disruption of March 2020, we do not find evidence for basis traders being important drivers of disruption in Treasury futures market. |
| Keywords: | PTFs; Basis traders; Treasury futures |
| JEL: | G10 G13 |
| Date: | 2025–05–30 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-38 |