arXiv · arXiv q-fin · 2025
We investigate the application of quantum cognition machine learning (QCML), a novel paradigm for both supervised and unsupervised learning tasks rooted in the mathematical formalism of quantum theory, to distance metric learning in corporate bond markets. Compared to equities, corporate bonds are relatively illiquid and both trade and quote data in these securities are relatively sparse. Thus, a measure of distance/…
Joshua Rosaler, Luca Candelori, Vahagn Kirakosyan, Kharen Musaelian, Ryan Samson
arXiv · arXiv · 2026
Automated Market Makers based on concentrated liquidity, such as Uniswap v3, significantly improve capital efficiency but expose Liquidity Providers (LPs) to adverse selection costs, formalized as Loss-Versus-Rebalancing (LVR). While theoretical literature quantifies these costs, the interplay between realistic blockchain microstructure and endogenous pricing mechanisms remains under-explored. This paper develops a g…
Daniele Maria Di Nosse, Fabrizio Lillo
arXiv · arXiv · 2026
This paper proposes an Extended State-Dependent Hawkes Process (ExsdHawkes) to model the intricate dynamics of Limit Order Books (LOBs). Our theoretical contribution lies in relaxing traditional constraints by allowing for state disappearances -- a phenomenon frequently observed in high-frequency trading. We mathematically prove, using Karush--Kuhn--Tucker (KKT) conditions, that the maximum likelihood estimation rema…
Akitoshi Kimura
arXiv · arXiv · 2026
This paper presents a method for forecasting limit order book durations using a self-exciting flexible residual point process. High-frequency events in modern exchanges exhibit heavy-tailed interarrival times, posing a significant challenge for accurate prediction. The proposed approach incorporates the empirical distributional features of interarrival times while preserving the self-exciting and decay structure. Thi…
Kyungsub Lee
arXiv · arXiv · 2026
High-Frequency trading (HFT) environments are characterised by large volumes of limit order book (LOB) data, which is notoriously noisy and non-linear. Alpha decay represents a significant challenge, with traditional models such as DeepLOB losing predictive power as the time horizon (k) increases. In this paper, using data from the FI-2010 dataset, we introduce Temporal Kolmogorov-Arnold Networks (T-KAN) to replace t…
Ahmad Makinde
arXiv · arXiv · 2025
The integration of Deep Reinforcement Learning (DRL) and Evolutionary Computation (EC) is frequently hypothesized to be the "Holy Grail" of algorithmic trading, promising systems that adapt autonomously to non-stationary market regimes. This paper presents a rigorous post-mortem analysis of "Galaxy Empire," a hybrid framework coupling LSTM/Transformer-based perception with a genetic "Time-is-Life" survival mechanism.…
Yijia Chen
arXiv · arXiv · 2025
Modern high-frequency trading (HFT) environments are characterized by sudden price spikes that present both risk and opportunity, but conventional financial models often fail to capture the required fine temporal structure. Spiking Neural Networks (SNNs) offer a biologically inspired framework well-suited to these challenges due to their natural ability to process discrete events and preserve millisecond-scale timing…
Brian Ezinwoke, Oliver Rhodes
OpenAlex · Review of Financial Studies · 2012 · cites 548
Order flow is toxic when it adversely selects market makers, who may be unaware they are providing liquidity at a loss. We present a new procedure to estimate flow toxicity based on volume imbalance and trade intensity (the VPIN toxicity metric). VPIN is updated in volume time, making it applicable to the high-frequency world, and it does not require the intermediate estimation of non-observable parameters or the app…
David Easley, Marcos López de Prado, Maureen O’Hara
OpenAlex · Review of Financial Studies · 2022 · cites 198
Abstract We identify fixed-income mutual funds as an important contributor to the unusually high selling pressure in liquid asset markets during the COVID-19 crisis. We show that mutual funds experienced pronounced investor outflows amplified by their liquidity transformation. In meeting redemptions, funds followed a pecking order by first selling their liquid assets, including Treasuries and high-quality corporate b…
Yiming Ma, Kairong Xiao, Yao Zeng
OpenAlex · European Finance Review · 2014 · cites 64
Abstract Following the “flash crash” on May 6, 2010, warning signals for impending market stress have been in high demand, yet only the VPIN metric of Easley, López de Prado, and O’Hara (ELO) has claimed success. In addition, ELO find the metric useful in predicting short-term volatility. VPIN involves decomposing volume into active buys and sells. We utilize quotes and trade data to construct an accurate trade class…
Torben G. Andersen, Oleg Bondarenko
arXiv · arXiv · 2025
We explore the interplay between sovereign debt default/renegotiation and environmental factors (e.g., pollution from land use, natural resource exploitation). Pollution contributes to the likelihood of natural disasters and influences economic growth rates. The country can default on its debt at any time while also deciding whether to invest in pollution abatement. The framework provides insights into the credit spr…
Emilio Barucci, Daniele Marazzina, Aldo Nassigh
OpenAlex · The Quarterly Journal of Economics · 2015 · cites 893
Abstract The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed i…
Eric Budish, Peter Cramton, John J. Shim
OpenAlex · The Journal of Finance · 2014 · cites 823
ABSTRACT We model a loop between sovereign and bank credit risk. A distressed financial sector induces government bailouts, whose cost increases sovereign credit risk. Increased sovereign credit risk in turn weakens the financial sector by eroding the value of its government guarantees and bond holdings. Using credit default swap (CDS) rates on European sovereigns and banks, we show that bailouts triggered the rise o…
Viral V. Acharya, Itamar Drechsler, Philipp Schnabl
OpenAlex · Review of Financial Studies · 2014 · cites 1218
We examine the role of high-frequency traders (HFTs) in price discovery and price efficiency. Overall HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors, both on average and on the highest volatility days. This is done through their liquidity demanding orders. In contrast, HFTs' liquidity supplying orders are adversely sel…
Jonathan Brogaard, Terrence Hendershott, Ryan Riordan
OpenAlex · 2009 · cites 353
Acknowledgments. Chapter 1 Introduction. Chapter 2 Evolution of High-Frequency Trading. Financial Markets And Technological Innovation. Evolution Of Trading Methodology. Chapter 3 Overview of the Business of High-Frequency Trading. Comparison With Traditional Approaches to Trading. Market Participants. Operating Model. Economics. Capitalizing a High-Frequency Trading Business. Conclusion. Chapter 4 Financial Markets …
Irene Aldridge
OpenAlex · National Bureau of Economic Research · 2007 · cites 235
We study the nature of sovereign credit risk using an extensive sample of CDS spreads for 26 developed and emerging-market countries. Sovereign credit spreads are surprisingly highly correlated, with just three principal components accounting for more than 50 percent of their variation. Sovereign credit spreads are generally more related to the U.S. stock and high-yield bond markets, global risk premia, and capital f…
Francis A. Longstaff, Jun Pan, Lasse Heje Pedersen, Kenneth J. Singleton
OpenAlex · Journal of Financial and Quantitative Analysis · 2016 · cites 123
Abstract We provide new empirical evidence that U.S. expected growth and consumption volatility are closely related to the strong comovement in sovereign spreads. We rationalize these findings in an equilibrium model with recursive utility for credit default swap (CDS) spreads. The framework links a reduced-form default process with country-specific sensitivity to expected growth and macroeconomic uncertainty. Exploi…
Patrick Augustin, Roméo Tédongap
arXiv · arXiv · 2026
We test whether five widely promoted retail signal families - trend, oscillator, candlestick, volume, and calendar rules - deliver a positive, economically meaningful, net-of-cost, and survivable edge. Practical viability is the conjunction of three predeclared gates: statistical edge after multiplicity correction, economic viability after trading costs, and finite-bankroll survival under leverage. Exposure-matched b…
Adam Darmanin