Financial integration and diversification can lead to instability.
problem Understanding how financial network topology leads to instability.
method Analyzing the effects of market integration and diversification on financial network stability.
result Processes that stabilize financial systems can actually destabilize them.
Modeling financial institution dependence structures for systemic risk.
problem Understanding and measuring systemic risk in financial systems.
method Dynamic model of dependence structure using Markov structures of joint credit migrations.
result Different Markov structures with distinct dependence structures lead to varying systemic instability.
Simple quantifier predicts financial market instability.
problem Predicting financial market instability and risk.
method Combining Information Theory and graph concepts to analyze return rate series.
result Simple quantifier highly correlated with global financial instability periods.
Network geometry measures predict market instability.
problem Predicting financial market instability using network geometry.
method Discrete Ricci curvatures to capture network fragility.
result Different geometric measures distinguish normal and crash periods.
Graph auto-encoders predict stock market instability by measuring graph structure changes.
problem Forecasting stock market instability and volatility.
method Use graph auto-encoders to reconstruct graph structure and measure changes.
result Higher GAE reconstruction error correlates with higher volatility.
Investment strategies in financial markets can lead to instability due to market impacts.
problem Market impacts make it impossible for investors to accurately optimize their strategies.
method Built an agent-based model with technical analysis strategy agents to investigate optimization instability.
result Investment strategies' parameters never converged but continued to change, leading to unstable market price evolution.
New approach uses text analysis to predict financial instability.
problem Improving financial stability monitoring using text data.
method Directed algorithmic text analysis of large text databases.
result Emotion shifts in texts correlate with financial stress indices.
Investment diversification affects financial stability, depending on network connectivity.
problem Analyzing stability of financial networks with diversified portfolios.
method Random matrix dynamical model with portfolio rebalancing, considering heterogeneity and diversification effects.
result Stability/instability transition depends on the largest eigenvalue of the random matrix.
Study compares default models in correlated markets, finds divergence increases during instability.
problem Inconsistent predictions of corporate defaults in highly correlated markets.
method Calculated Jeffreys-Kullback-Leibler divergence between two default models under high and low correlations.
result Divergence between models increases in highly correlated, volatile markets, suggesting inconsistent predictions.
Study reveals signatures of market crashes through eigenvalue analysis of stock return matrices.
problem Understanding the complexity and dynamics of market crashes.
method Cross-correlation structures and eigenspectra of stock return matrices were analyzed over different epochs.
result The smallest eigenvalue can distinguish between internal and external market instabilities.
Temporal network analysis reveals stock market instability and new portfolio optimization tools.
problem Detecting market instability in stock markets using temporal network analysis.
method Utilized temporal network framework to characterize stock market correlation networks and employed temporal centrality as a portfolio selection tool.
result Peripheral stocks with low temporal centrality scores perform better in portfolio optimization under different schemes.
We study the emergence of instabilities in a stylized model of a financial market, when different market actors calculate prices according to different (local) market measures. We derive typical properties for ensembles of large random markets using techniques borrowed from statistical mechanics of disordered systems. …
The paper explores how AI trading agents' similar information representation can cause financial market instability.
problem Systemic instability in AI-dominated financial markets due to similar information representation.
method Structural multi-agent market model with two-layer decision architecture for AI agents.
result Representation homogeneity can lead to systemic instability in financial markets.
Study financial market efficiency using visibility graphs and ARCH models.
problem Estimating market efficiency and predicting financial instability.
method Building visibility graphs from financial time series and validating links against ARCH models.
result Proposed market indicator highly correlated with financial instability periods.
Study uses DNM theory to detect early warning signals of market instability.
problem Detecting early warning signals of financial market instability.
method Applying Dynamical Network Marker (DNM) theory to trading data from the Tokyo Stock Exchange.
result Early warning signals of large price movements can be detected on a daily time scale.
The paper interprets financial markets as crowds during booms and busts.
problem Understanding market irrationality during booms and busts.
method Integrates crowd psychology into behavioural finance.
result Markets behave like psychological crowds during booms and busts.
The instability of the financial system as experienced in recent years and in previous periods is often linked to credit defaults, i.e., to the failure of obligors to make promised payments. Given the large number of credit contracts, this problem is amenable to be treated with approaches developed in statistical physi…
We describe the innovations in finances, introduced over the recent decades, and analyze most of the business and regulatory challenges, faced by the financial industry, because of the present disruptive changes in the global capital markets. We use the integrative thinking approach to formulate the new central bank st…
Interbank credit can create money, leading to financial instability.
problem Systemic instability caused by coordination failures in interbank credit.
method Developed a model of interbank credit coordination under minimal institutions, analyzed through simulation.
result Interbank credit can lead to unbound monetary systems and financial instability.
Financial network instability can be highly sensitive to small changes and hard to predict.
problem Understanding and predicting financial network instability and contagion.
method Simple model of financial network dynamics with cross-holdings and failure costs.
result Small changes in investments can have large impacts on financial network stability, and estimating network failures is computationally intractable.
New analysis shows low volatility can be unstable in financial markets.
problem Understanding the relationship between volatility and market stability.
method Using mean first hitting time as a stability indicator and comparing to standard volatility measures.
result Low volatility can be associated with higher instability in financial markets.
We show that financial correlations exhibit a non-trivial dynamic behavior. We introduce a simple phenomenological model of a multi-asset financial market, which takes into account the impact of portfolio investment on price dynamics. This captures the fact that correlations determine the optimal portfolio but are affe…
AlphaForgeBench evaluates LLMs as quantitative researchers, not trading agents, to address instability in financial decision-making.
problem Behavioral instability of LLMs in sequential decision-making under financial uncertainty.
method Proposes AlphaForgeBench, a framework that requires LLMs to generate executable alpha factors and compose factor-based trading strategies.
result Eliminates execution-induced instability and provides a rigorous benchmark for evaluating financial reasoning.
Study examines USD exchange rate dynamics using Kramers-Moyal expansion.
problem Understanding and predicting exchange rate instability.
method Kramers-Moyal expansion and Fokker-Planck formalism applied to log-return data.
result Identifies a stabilizing linear drift and nonlinear diffusion term in exchange rate fluctuations.
We investigate the possible drawbacks of employing the standard Pearson estimator to measure correlation coefficients between financial stocks in the presence of non-stationary behavior, and we provide empirical evidence against the well-established common knowledge that using longer price time series provides better, …
Persistence norms explain financial uncertainty better than volatility.
problem Capturing financial instability and predictability.
method Applied topological data analysis to financial markets.
result Persistence norms are significant in explaining financial uncertainty, while volatility is less effective.
The paper uses a model to predict financial instability by analyzing interest rates and firm resilience.
problem Financial instability and the number of Ponzi firms during economic crises.
method An autocatalytic feedback model that combines interest rates, firm resilience, and network effects.
result The model successfully predicts the number of Ponzi firms and explains the dynamics of financial crises.
Study shows feedback effect between capital flows volatility and financial stability in DRC.
problem Volatility of capital flows can undermine financial stability in DRC.
method Dynamic regression model and vector autoregressive (VAR) model to analyze feedback effects and policy impacts.
result Feedback effect between capital flows volatility and financial stability exists in DRC, but policies do not effectively mitigate volatility.
Study finds short-term instability in financial ARCH models.
problem Short-term stability of financial ARCH models.
method Analyzes quadratic ARCH processes using historical data and empirical innovations.
result Empirical innovations have variance significantly above 1, indicating short-term instability.
Study finds ESG investments more resilient than traditional equity indices during market turmoil.
problem Resilience of ESG investments during financial instability.
method Daily returns analysis using MGND and EGARCH-in-mean models.
result ESG investments show higher resilience compared to traditional equity indices during crises.
In an informal way, a number of thoughts on the financial crisis 2008 are presented from a physicist's viewpoint, considering the problem as a nonergodicity transition of a spin-glass type of system. Some tentative suggestions concerning the way out of the crisis are also discussed, concerning Keynesian "deficit spendi…
DoubleEnsemble improves financial predictions by selecting key features and reweighting samples.
problem Overfitting and instability in financial data analysis.
method Sample reweighting and feature selection using learning trajectory and shuffling.
result DoubleEnsemble outperforms baseline methods in financial prediction tasks.
Two new PCA variants improve financial data analysis.
problem Numerical instability and nonstationarity in PCA for finance.
method Iterated and exponentially weighted moving PCA variants using Ogita-Aishima iteration.
result Improved stability and adaptability in financial data analysis.
Mathematical framework investigates fire sales amplification and stability.
problem Market instability caused by fire sales amplification.
method Developed a mathematical framework to investigate system characteristics and resilience.
result Characterized systems resilient to small shocks for financial stability assessment.
Model quantifies systemic risk in financial networks using PD and contagion mechanisms.
problem Underestimation of capital needed for financial system stability.
method Dynamic PD model combining credit risk techniques and contagion mechanism on network of exposures.
result Systemic risk statistics and node contributions revealed through loss distribution.
Through a long-period analysis of the inter-temporal relations between the French markets for credit default swaps (CDS), shares and bonds between 2001 and 2008, this article shows how a financial innovation like CDS could heighten financial instability. After describing the operating principles of credit derivatives i…
ReGEN-TAD detects anomalies in financial time series with interpretable models.
problem Detecting anomalies in complex financial time series with high-dimensional data.
method Integrates machine learning with econometric diagnostics in a refined convolutional--transformer architecture.
result Unified anomaly score without labeled data, robust to structured deviations.
China's infrastructure investments fail to deliver economic growth, leading to fragility.
problem The myth that infrastructure investment leads to economic growth is debunked.
method Analysis of the largest dataset of infrastructure investment data in China.
result Infrastructure investments in China do not provide a positive risk-adjusted return.
Study of U.S. stock market dynamics using Boltzmann Machine model.
problem Understanding market correlation structure and instabilities.
method Boltzmann Machine model with binary variables, exact and approximate learning algorithms.
result Binarization preserves market correlation structure and heavy positive tail in couplings.
We study analytically and numerically Minsky instability as a combination of top-down, bottom-up and peer-to-peer positive feedback loops. The peer-to-peer interactions are represented by the links of a network formed by the connections between firms, contagion leading to avalanches and percolation phase transitions pr…
Threats on the stability of a financial system may severely affect the functioning of the entire economy, and thus considerable emphasis is placed on the analyzing the cause and effect of such threats. The financial crisis in the current and past decade has shown that one important cause of instability in global market…
New model reveals latent liquidity in financial markets.
problem Understanding the connection between latent and observable order books.
method Suggests a simple mechanism for revealing latent liquidity and quantifies it from real data.
result Existence of a market instability threshold leading to liquidity crises.
A new risk measure (FRM) for EM FI returns helps investors protect against volatility and policy instability.
problem Systemic risk in EM FI returns due to external shocks and domestic policy instability.
method Daily FRM-EM measure applied to 25 largest EM FI returns, incorporating Macro factors.
result FRM-EM captures systemic risk behavior in EM FI returns, reaching maximum during crises.
Stock market price fluctuations follow Lévy's stable distribution over long term.
problem Understanding the stability of stock market price fluctuations over different time scales.
method Estimated Lévy's stable parameters from four stock markets over long and short term.
result Stable parameters from different stock markets showed a unique value over long term, but fluctuated with correlation in short term.
This review is a partial synthesis of the book ``Why stock market crash'' (Princeton University Press, January 2003), which presents a general theory of financial crashes and of stock market instabilities that his co-workers and the author have developed over the past seven years. The study of the frequency distributio…
Survey of determinism issues in financial AI systems.
problem Vulnerabilities in reproducibility of financial AI systems.
method Literature review and first-party experiments on public financial datasets.
result Proposed a layered evaluation framework linking modality-specific metrics to audit readiness.
Propagation of balance-sheet or cash-flow insolvency across financial institutions may be modeled as a cascade process on a network representing their mutual exposures. We derive rigorous asymptotic results for the magnitude of contagion in a large financial network and give an analytical expression for the asymptotic …
I study the limit of a large random economy, where a set of consumers invests in financial instruments engineered by banks, in order to optimize their future consumption. This exercise shows that, even in the ideal case of perfect competition, where full information is available to all market participants, the equilibr…