Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

Trend · papers per month

13274053 · Oct 202519922001200920172026
48 results for crisis management

Analysis finds no evidence of banks managing deposit run risk prior to 2023 Regional Banking Crisis.

problem Determining factors for deposit run risk management before a regional banking crisis.
method Cross-sectional analysis of interest rate and equity use by banks.
result No evidence of banks managing deposit run risk via their balance sheet.

Research evaluates three risk models for portfolio construction during market downturns.

problem Challenges in constructing quantitative portfolios using statistical risk models.
method Three statistical risk models tested on 1,000 stocks across four periods.
result Models consistently outperform market returns in various crises.

This study examines how economic policy uncertainty impacts commodity prices across different crises.

problem Impact of economic policy uncertainty on commodity prices during various crises.
method Wavelet coherence analysis of time series data.
result Commodity prices are more correlated during global financial and Covid-19 crises.

The paper examines sizing strategies for algorithmic trading in volatile markets.

problem High volatility creates challenges for algorithmic traders.
method Investigates different sizing models and backtesting techniques for financial trading.
result Sizing models can lower Value at Risk (VaR) during crisis events.

Study finds Value Granger-causes Size during crisis regimes but not during normal times.

problem Understanding regime-dependent predictive relationships between equity factors.
method Used 35 years of Fama-French data and a Student-t Hidden Markov Model (HMM) to identify crisis regimes.
result Value Granger-causes Size during crisis regimes but not during normal times, validating across multiple historical events.

Risk management in financial derivative markets requires inevitably the calculation of the different price sensitivities. The literature contains an abundant amount of research works that have studied the computation of these important values. Most of these works consider the well-known Black and Scholes model where th…

2017-05-06abs ↗pdf ↗

Option pricing is an integral part of modern financial risk management. The well-known Black and Scholes (1973) formula is commonly used for this purpose. This paper is an attempt to extend their work to a situation in which the unconditional volatility of the original asset is increasing during a certain period of tim…

2013-04-17abs ↗pdf ↗

Nanotechnology is the first major worldwide research initiative of the 21st century and probably is the solution vector in the economic environment. Also, innovation is widely recognized as a key factor in the economic development of nations, and is essential for the competitiveness of the industrial firms as well. Pol…

2013-03-20abs ↗pdf ↗

This research improves value-at-risk estimation during financial crises using non-extensive statistical methods.

problem Underestimation of value-at-risk during financial crises.
method Non-extensive value-at-risk model based on Tsallis entropy and q-Gaussian probability density function.
result The q-Gaussian model provides better value-at-risk estimation during financial crises.

Although portfolio management didn't change much during the 40 years after the seminal works of Markowitz and Sharpe, the development of risk budgeting techniques marked an important milestone in the deepening of the relationship between risk and asset management. Risk parity then became a popular financial model of in…

2014-03-07abs ↗pdf ↗

Mack-Net model combines Mack's model with RNNs for better insurance liability estimation.

problem Accurate estimation of insurance liabilities for better financial decision-making.
method Integrates Mack's reserving model with Recurrent Neural Networks (RNNs).
result Improves accuracy of general insurance liability assessment.

Geometric framework for portfolio analysis detects financial crises and evaluates performance.

problem Detecting financial crises and evaluating portfolio performance in volatile markets.
method Geometric framework, copula models, statistical computing.
result Automated crisis detection and new portfolio score for performance evaluation.

The paper analyzes XVA reduction strategies in financial crises using Mandatory Breaks, Restructuring, and Resets.

problem Challenges in client XVA management during crises when continuous collateralization is not feasible.
method Compares multiple trade strategies including Mandatory Breaks, Restructuring, and Resets.
result Resets can be twice as effective as Mandatory Breaks/Restructuring if there is no credit recovery. When recovery is at least 1/3, Mandatory Breaks/Restructuring can be more effective.

DARL uses DDPMs to generate synthetic market crash scenarios for robust portfolio optimization.

problem Challenges in capturing complex market dynamics and aligning with diverse investor preferences.
method Synergistic integration of DDPMs and DRL for portfolio management.
result DARL outperforms traditional methods in delivering superior risk-adjusted returns and resilience against crises.

Unified framework maps financial market dynamics using TE and KM, revealing directional information flow.

problem Challenges in traditional correlation analysis of financial markets, especially during crises.
method Combines Transfer Entropy (TE) and Kramers-Moyal (KM) expansion to analyze dynamic interactions among major indices.
result Increased directional information flow during crises, highlighting gold-dollar and oil-equity linkages.

The paper applies information theory to financial markets, improving risk management and asset allocation.

problem Improving risk management and asset allocation in financial markets.
method Information-theoretic measures (entropy, mutual information, etc.) applied to financial time series.
result Normalized mutual information (NMI) is a powerful measure of temporal dependence in financial markets.

DeepPocket uses graph convolutional reinforcement learning for better financial portfolio management.

problem Maximizing return on investment while managing risk in correlated financial assets.
method Graph convolutional reinforcement learning framework with feature extraction, local information collection, and actor-critic reinforcement learning.
result DeepPocket outperformed market indexes on five real-life datasets over three investment periods, including during the Covid-19 crisis.

Portfolio diversification and active risk management are essential parts of financial analysis which became even more crucial (and questioned) during and after the years of the Global Financial Crisis. We propose a novel approach to portfolio diversification using the information of searched items on Google Trends. The…

2013-10-05abs ↗pdf ↗

Our analysis of financial data, in terms of super-exponential growth, suggests that the seed of the 2002/03 crisis of the Dutch supermarket giant AHOLD was planted in 1996. It became quite visible in 1999 when the post-bubble destabilization regime was well-developed and acted as the precursor of an inevitable collapse…

2004-03-22abs ↗pdf ↗

The paper uses machine learning to predict the impact of the Ukraine crisis on financial markets.

problem Quantifying the impact of the Ukraine crisis on financial markets.
method Selected economic indexes, created datasets, and used machine learning (Linear Regression) for forecasting.
result The model accurately predicted the effects of the Ukraine crisis on financial markets.

Our study shows that many firms would accumulate at zero output level (namely, Bankruptcy status) if a perfectly competitive market reaches full employment (namely, those people who should obtain employment have obtained employment). As a result, appearance of economic crisis is determined by two points; that is, (a). …

2010-10-22abs ↗pdf ↗

Proposes second-order Esscher transform for Lévy models in financial markets.

problem Risk management and quantification in markets with jumps and Lévy dynamics.
method Derives densities, equivalent measures, and pricing formulas for European call options.
result Option prices are bounded and monotonic with the second-order Esscher parameter.

We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an \textit{on-off} phase transition governed by a bankruptcy threshold κκ related to the trade balance of the countries. …

2020-02-17abs ↗pdf ↗

The study examines cross-border lending behavior from G7 countries, showing changes in driving factors after the 2008 financial crisis.

problem Understanding the factors affecting cross-border lending behavior among G7 countries.
method Employed a gravity model to analyze bilateral and global factors influencing cross-border lending.
result Driving factors for cross-border lending have changed since the 2008 financial crisis, with continent variable becoming more significant.

New hybrid model combines GARCH and reinforcement learning for improved VaR estimation.

problem Inaccurate VaR estimation in volatile financial markets.
method Combines GARCH volatility models with DDQN reinforcement learning for dynamic risk forecasting.
result Significant improvement in VaR accuracy and reduction in breaches.

In the aftermath of the 2007 global financial crisis, banks started reflecting into derivative pricing the cost of capital and collateral funding through XVA metrics. Here XVA is a catch-all acronym whereby X is replaced by a letter such as C for credit, D for debt, F for funding, K for capital and so on, and VA stands…

2016-03-09abs ↗pdf ↗

Study improves early warning models for currency and stock market crises.

problem Predicting currency and stock market crises.
method Synthetic review and comparison of early warning models, focusing on crisis identifications and predictive models.
result SWARCH model with elastic thresholding methodology most accurately classifies crisis observations.

This paper calculates risk-dependent centrality of Brazilian stocks, showing rankings vary with external risk and crisis events.

problem Understanding asset rankings in the Brazilian stock market under varying external risks.
method Computed risk-dependent centrality (RDC) for Brazilian stocks traded from 2008 to 2020, analyzing volatility and returns.
result Asset rankings based on RDC vary with external risk and crisis events, with higher volatility in crisis periods.

Study reveals structural differences in financial networks near and far from crises using balance theory.

problem Understanding the complex behavior of stocks and their collective behavior in financial crises.
method Investigates financial networks by triplet interaction in the framework of balance theory, focusing on higher-order interactions.
result Formation of an ordered structure in crisis networks makes them resistant to disorder, with a critical temperature measuring crisis strength.

Paper proposes Multi-Transformer for more accurate stock volatility forecasts.

problem Accurate equity risk models needed for effective risk management.
method Introduces Multi-Transformer neural network architecture, adapted from Transformer models.
result Empirical results show Multi-Transformer leads to more accurate risk measures.