arXiv · arXiv q-fin · 2024
This paper introduces a new risk-on risk-off strategy for the stock market, which combines a financial stress indicator with a sentiment analysis done by ChatGPT reading and interpreting Bloomberg daily market summaries. Forecasts of market stress derived from volatility and credit spreads are enhanced when combined with the financial news sentiment derived from GPT-4. As a result, the strategy shows improved perform…
Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana, David Saltiel, Beatrice Guez
arXiv · arXiv q-fin · 2019
Systemic liquidity risk, defined by the IMF as "the risk of simultaneous liquidity difficulties at multiple financial institutions", is a key topic in macroprudential policy and financial stress analysis. Specialized models to simulate funding liquidity risk and contagion are available but they require not only banks' bilateral exposures data but also balance sheet data with sufficient granularity, which are hardly a…
V. Macchiati, G. Brandi, G. Cimini, G. Caldarelli, D. Paolotti
arXiv · arXiv q-fin · 2025
This paper presents a machine learning driven framework for sectoral stress testing in the Indian financial market, focusing on financial services, information technology, energy, consumer goods, and pharmaceuticals. Initially, we address the limitations observed in conventional stress testing through dimensionality reduction and latent factor modeling via Principal Component Analysis and Autoencoders. Building on th…
Vidya Sagar G, Shifat Ali, Siddhartha P. Chakrabarty
arXiv · arXiv q-fin · 2026
Most currency pairs lack a direct liquid market, so international foreign exchange relies on routing transactions through a dominant vehicle currency. Multi-currency automated market makers (AMMs) offer an alternative by sharing liquidity across many currency pairs, facilitating direct cross-currency trade while exploiting liquidity consolidation. This paper studies a multi-currency pool design that minimizes trading…
Reina Ke Xin Li, Andreas Park, Andreas Veneris, Srisht Fateh Singh
arXiv · arXiv q-fin · 2026
In this work we evaluate the performance of three classes of methods for detecting financial anomalies: topological data analysis (TDA), principal component analyis (PCA), and Neural Network-based approaches. We apply these methods to the TSX-60 data to identify major financial stress events in the Canadian stock market. We show how neural network-based methods (such as GlocalKD and One-Shot GIN(E)) and TDA methods a…
Luigi Caputi, Nicholas Meadows
arXiv · arXiv q-fin · 2025
This study proposes a regime-aware reinforcement learning framework for long-horizon portfolio optimization. Moving beyond traditional feedforward and GARCH-based models, we design realistic environments where agents dynamically reallocate capital in response to latent macroeconomic regime shifts. Agents receive hybrid observations and are trained using constrained reward functions that incorporate volatility penalti…
Gabriel Nixon Raj
arXiv · arXiv q-fin · 2025
Market generators using deep generative models have shown promise for synthetic financial data generation, but existing approaches lack causal reasoning capabilities essential for counterfactual analysis and risk assessment. We propose a Time-series Neural Causal Model VAE (TNCM-VAE) that combines variational autoencoders with structural causal models to generate counterfactual financial time series while preserving …
Dennis Thumm, Luis Ontaneda Mijares
arXiv · arXiv q-fin · 2018
We investigate the performance of dynamic portfolios constructed using more than 21,000 technical trading rules on 12 categorical and country-specific markets over the 2004-2015 study period, on rolling forward structures of different lengths. We also introduce a discrete false discovery rate (DFRD+/-) method for controlling data snooping bias. Compared to the existing methods, DFRD+/- is adaptive and more powerful, …
Georgios Sermpinis, Arman Hassanniakalager, Charalampos Stasinakis, Ioannis Psaradellis
arXiv · arXiv · 2026
We propose an AI economist agent for economic and financial scenario analysis. Scenario design often requires analysts to assess emerging risks with limited historical precedent, combine information from many sources, and translate qualitative mechanisms into internally consistent quantitative paths. Large language models (LLMs) can search and synthesize this information, but fluent narratives alone do not establish …
Masahiro Kato
arXiv · arXiv · 2025
We develop a transparent and fully auditable LLM-based pipeline for macro-financial stress testing, combining structured prompting with optional retrieval of country fundamentals and news. The system generates machine-readable macroeconomic scenarios for the G7, which cover GDP growth, inflation, and policy rates, and are translated into portfolio losses through a factor-based mapping that enables Value-at-Risk and E…
Masoud Soleimani
arXiv · arXiv · 2021
This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers the modeling of the liability liquidity risk (or funding liquidity), the second dimension is dedicated to the modeling of the asset liquidity risk (or market liquidity), whereas the third dimension considers the management of the asset-liability liquidi…
Thierry Roncalli
arXiv · arXiv · 2021
This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers liability liquidity risk (or funding liquidity) modeling, the second dimension focuses on asset liquidity risk (or market liquidity) modeling, and the third dimension considers the asset-liability management of the liquidity gap risk (or asset-liability…
Thierry Roncalli, Amina Cherief, Fatma Karray-Meziou, Margaux Regnault
arXiv · arXiv · 2021
This article is part of a comprehensive research project on liquidity risk in asset management, which can be divided into three dimensions. The first dimension covers liability liquidity risk (or funding liquidity) modeling, the second dimension focuses on asset liquidity risk (or market liquidity) modeling, and the third dimension considers asset-liability liquidity risk management (or asset-liability matching). The…
Thierry Roncalli, Fatma Karray-Meziou, François Pan, Margaux Regnault
OpenAlex · Review of Financial Studies · 2022 · cites 55
Abstract Two intermediary-based factors—a corporate bond dealer inventory measure and a broad intermediary distress measure—explain more than 40$\%$ of the puzzling common variation in credit spread changes beyond canonical structural factors. A simple intermediary-based model with partial market segmentation accounts for intermediary factors’ explanatory power and delivers three further implications with empirical s…
Zhiguo He, Paymon Khorrami, Zhaogang Song
OpenAlex · RePEc: Research Papers in Economics · 2008 · cites 126
As the financial crisis deepened and unsecured interbank markets effectively shut down, repo market activity became increasingly concentrated in the very shortest maturities and against the highest-quality collateral. Repo rates for US Treasury collateral fell relative to overnight index swap rates, while comparable sovereign repo rates in the euro area and the United Kingdom rose. The different dynamics across marke…
Peter Hördahl, Michael R. King
arXiv · arXiv · 2020
It has been decades since the academic world of ruin theory defined the insolvency of an insurance company as the time when its surplus falls below zero. This simplification, however, needs careful adaptions to imitate the real-world liquidation process. Inspired by Broadie et al. (2007) and Li et al. (2020), this paper uses a three-barrier model to describe the financial stress towards bankruptcy of an insurance com…
Aili Zhang, Ping Chen, Shuanming Li, Wenyuan Wang
arXiv · arXiv · 2026
Agent-based models of markets readily produce emergent instabilities, but telling a genuine collective effect apart from a parameter artefact takes discipline. We apply Bouchaud's phase-diagram method to a continuous-double-auction order-book model. The method is to map the full phase diagram, test its robustness to rule changes, and rule out degenerate and numerical origins before we call any feature a tipping point…
Jan Novotny
arXiv · arXiv · 2026
We propose a structural framework for the geometry of financial order books in which liquidity, supply, and demand are treated as emergent observables rather than primitive economic variables. The market is modeled as an inflationary relational system without assumed metric, temporal, or price coordinates. Observable quantities arise only through projection, implemented here via spectral embeddings of the graph Lapla…
João P. da Cruz