Cryptos remained resilient after SVB's collapse, contrary to expectations.
problem Impact of SVB collapse on crypto markets.
method Factual summary, sentiment analysis, and market performance examination.
result Cryptocurrencies showed resilience after SVB's collapse.
Study finds significant price declines and capital reallocation from centralized to decentralized exchanges after FTX collapse.
problem Quantifying trust dynamics and redistribution between centralized and decentralized exchanges.
method Interdisciplinary approach combining causal inference and computational text analysis.
result Significant price declines and capital reallocation from centralized to decentralized exchanges following the FTX collapse.
Modeling speculative markets with varying costs of carrying positions.
problem Analyzing the impact of varying costs of carrying positions on speculative markets.
method Continuous-time model with heterogeneous beliefs, Hamilton-Jacobi-Bellman equation.
result Decreasing shorting costs can lead to market collapse and price collapse.
Model predicts market dynamics from demand uncertainty.
problem Market dynamics under uncertain demand forecasts.
method Simple dynamical model iterated with varying parameters.
result Reproduces equilibria, periodic, chaotic, and collapses.
This article continues our analysis of the gold price dynamics that was published in December 2010 (abs/1012.4118) and forecasted the possibility of the "burst of the gold bubble" in April - June 2011. Our recent analysis suggests the possibility of one more substantial fluctuation before the final collapse in July 201…
This work uses transfer entropy to reconstruct influential network between global stock markets.
problem Noise in network structure due to mismatch of scale between single market and global markets.
method Reconstructing influential network between ten typical stock markets using transfer entropy.
result Before financial crises, connection strength between markets reaches a maximum, acting as an early warning signal.
Stablecoin liquidity was affected by the SVB collapse, with USDC's transparency leading to market reactions.
problem Impact of stablecoin transparency on liquidity during market turmoil.
method Adapted MCI measure to Uniswap, Difference-in-Differences analysis on MCI and TVL, measured liquidity concentration.
result USDC's transparency led to swift market reactions, while USDT's opacity provided a safety net.
Study on financial impacts of zombie outbreak on economy.
problem Financial and economic consequences of a zombie epidemic.
method Epidemiological modeling and financial computation.
result GDP losses of 23.44% and financial market drop of 29.30% in a major industrialized nation.
TRIBE model uses LLMs to simulate human trading behavior in bond markets.
problem Complexities in decentralized bond market transactions.
method Agent-based model augmented with LLMs to simulate human-like decision-making.
result Slight trade aversion in LLMs can lead to complete market collapse.
The study uses Random Matrix Theory to identify structural changes in stock markets during shocks.
problem Understanding structural changes in stock markets during exogenous shocks.
method Random Matrix Theory and complexity gap analysis.
result The complexity gap collapses during shocks, indicating strong synchronization, and widens before shocks, signaling a rich structure.
Investment risk on a regulated market is influenced by gold prices and oil trading.
problem Systematic risk of loss in investment portfolios under sanctions.
method Statistical analysis of tail dependence between oil, gold, and Tehran Stock Exchange Index.
result Tail dependence should be considered for systematic risk, and active bartering of oil can prevent market collapse.
Study uncovers that loan maturity layers in interbank networks are crucial for understanding their structure and functions.
problem Lack of maturity details in interbank lending networks hinders understanding of network structure and functions.
method Used a complete interbank loan contract dataset and applied the layered stochastic block model to investigate multiple maturity layers.
result Optimal maturity granularity reveals specific economic functions, such as liquidity intermediation and financing.
FTX's failure linked to Terra-Luna collapse and Binance's influence.
problem FTX's collapse due to misuse of native token and reliance on leverage.
method Analyzed on-chain data, studied cryptocurrency dependency structures, and examined public trades.
result FTX's downfall was accelerated by Binance's tweets and public reaction.
We analyze the constituents stocks of the Dow Jones Industrial Average (DJIA30) and the Standard & Poor's 100 index (S&P100) of the NYSE stock exchange market. Surprisingly, we discover the data collapse of the histograms of the DJIA30 price fluctuations and of the S&P100 price fluctuations to the universal non-paramet…
Model shows how past consumption affects household confidence, leading to varied economic outcomes.
problem Exploring how past consumption impacts current confidence and economic activity in a multi-household model.
method Developed a DSGE model where past consumption influences individual household confidence and consumption propensity.
result The model demonstrates a range of economic outcomes including high output with no crises, high output with increased volatility, and alternation of high and low output states.
Benchmarking recursive collapse claims with a new framework under false-positive control.
problem Evaluating recursive systems for failure patterns and warning claims.
method Developed Loopzero framework for testing recursive failures, specified claim boundaries in Lean, evaluated under FP constraint, and compared with standard detectors.
result No standard detectors or Loopzero's pre-registered quantile detector achieved the required operating point under the false-positive contract.
Study predicts crypto-currency price collapses using standard deviation.
problem Detecting price collapses in crypto-currencies.
method Phenomenological model and analysis of standard deviation.
result Standard deviation can predict crypto-currency price collapses.
We implement a market microstructure model including informed, uninformed and heuristic-driven investors, which latter behave in line with loss-aversion and mental accounting. We show that the probability of informed trading (PIN) varies significantly during 2008. In contrast, the probability of heuristic-driven tradin…
Data analysis with log-periodical parametrization of the Brent oil price dynamics has allowed to estimate (very approximately) the date when the dashing collapse of the Brent oil price will achieve the absolute minimum level (corresponding to the so-called singularity point), after which there will occur a rather rapid…
The paper proposes a new framework to generate synthetic data with human-like imperfections to prevent model collapse.
problem Model collapse due to statistical optimization of synthetic data.
method Introduces Prompt-driven Cognitive Computing Framework (PMCSF) with Cognitive State Decoder (CSD) and Cognitive Text Encoder (CTE).
result The framework generates text with cognitive imperfections, reducing maximum drawdown and delivering defensive alpha.
Market opening affects bid-ask spread stability.
problem Understanding how market opening affects financial stability.
method Analyzing bid-ask spread data for NASDAQ stocks.
result Market opening affects the stability of bid-ask spread.
Small stocks drive market crashes by suppressing resilience.
problem The single-security price limit exacerbates market panic during crashes.
method Simplified dynamic model on networks of investors and stocks, empirical verification.
result Unexpected linear association between price limit and critical market confidence.
We argue that the word ``critical'' in the title is not purely literary. Based on our and other previous work on nonlinear complex dynamical systems, we summarize present evidence, on the Oct. 1929, Oct. 1987, Oct. 1987 Hong-Kong, Aug. 1998 global market events and on the 1985 Forex event, for the hypothesis advanced f…
Financial markets provide an ideal frame for the study of crossing or first-passage time events of non-Gaussian correlated dynamics mainly because large data sets are available. Tick-by-tick data of six futures markets are herein considered resulting in fat tailed first-passage time probabilities. The scaling of the re…
Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT)…
Study examines Trump's crypto influence on markets, revealing conflicts and vulnerabilities.
problem Presidential power and cryptocurrency markets during Trump's second term.
method Mixed-methods approach combining quantitative and qualitative data.
result Political-linked digital assets became a distinct class with systemic vulnerabilities.
QGMS framework detects market endpoints using geometric patterns.
problem Identifying market endpoints in large-scale movements.
method Hybrid of geometric pattern recognition and quantitative modeling.
result Consistently identifies market endpoints before major reversals.
The study highlights the importance of Wrong-Way Risk in FVA calculations during financial market turmoil.
problem The relevance of Wrong-Way Risk in Funding Valuation Adjustments (FVA) during financial market uncertainty.
method The study examines the impact of various modelling choices, including default times and stochastic/deterministic funding spreads, on FVA calculations.
result WWR effects are non-negligible in FVA modelling from a risk-management perspective.
Develops portfolio theory without probabilistic analysis, focusing on pathwise decomposition.
problem Ensuring market viability without probabilistic assumptions.
method Uses pathwise decomposition and trend extractors to replace semimartingale decomposition.
result Growth-numéraire and viability equivalences are similar but not identical in pathwise setting.
Modeling financial bubbles and crashes with a cubic momentum function.
problem Capturing the micro-level dynamics of investor behavior and panic selling.
method Introducing a cubic function of market momentum to model trend-following and sudden crashes.
result The model successfully replicates complex, nonlinear bubble dynamics.
Investor expectations shifted pessimistically during the 2020 stock market crash and recovery.
problem Analyzing changes in investor expectations during the 2020 stock market crash and recovery.
method Surveying Vanguard clients at three points: before, during, and after the crash.
result Investor pessimism increased following the crash, with significant disagreement about future outcomes.
Bayesian deep learning faces posterior collapse due to likelihood vs. prior competition.
problem Posterior collapse in Bayesian deep learning models.
method Identified competition between likelihood and prior regularization in a linear latent variable model.
result Posterior collapse is related to neural and dimensional collapse, suggesting a broader learning issue.
Agent-based models show how market instability arises from individual uncertainty.
problem Understanding how market instability arises from individual uncertainty.
method Agent-based models and catastrophe theory.
result Changes in uncertainty among agents lead to systemic market risks.
The ultimate value of theories of the fundamental mechanisms comprising the asset price in financial systems will be reflected in the capacity of such theories to understand these systems. Although the models that explain the various states of financial markets offer substantial evidences from the fields of finance, ma…
Proves weakly non-collapsed RCD spaces are strongly non-collapsed.
problem Proving the equivalence of weakly non-collapsed and strongly non-collapsed RCD spaces.
method Analyzes properties of RCD spaces and uses auxiliary results.
result Confirms conjecture about RCD spaces being strongly non-collapsed.
Study on Neural Collapse limits in deep learning.
problem Understanding the limits of Neural Collapse in deep learning.
method Investigated Neural Collapse in the context of generalization and feature learning, refining conjectures and conducting experiments.
result Neural Collapse primarily occurs on the train set and not on the test set, suggesting it is an optimization phenomenon with unclear connections to generalization.
Study reveals how illiquidity network signals Chinese stock market crashes.
problem Understanding and predicting Chinese stock market crashes.
method Established an illiquidity network to model market dynamics.
result Market crashes are preceded by a more densely connected illiquidity network.
Study of collapsed manifolds with bounded Ricci curvature and non-collapsed universal cover.
problem Understanding collapsed manifolds with specific Ricci curvature properties.
method Ricci flow techniques applied to non-collapsed universal cover.
result Partial extension of nilpotent structural results to global Ricci bounded covering geometry.
SR-GANs combat mode collapse in GANs by monitoring and compensating spectral distributions.
problem Mode collapse in GANs.
method Spectral regularization (SR-GANs) to combat spectral collapse.
result SR-GANs prevent mode collapse and outperform SN-GANs in experiments.
Episodes of market crashes have fascinated economists for centuries. Although many academics, practitioners and policy makers have studied questions related to collapsing asset price bubbles, there is little consensus yet about their causes and effects. This review and essay evaluates some of the hypotheses offered to …
StakeBench evaluates language understanding by linking comments to market commitments, improving model alignment with real-world outcomes.
problem Existing financial NLP benchmarks measure perceived language rather than market commitments.
method StakeBench uses observable market behavior to supervise models, testing their ability to detect commitments, identify sides, and project odds.
result Models partially recover position-side signals but struggle with later tasks, highlighting structural failures.
Ricci flow smooths locally collapsing manifolds with controlled curvature.
problem Locally collapsing manifolds with controlled Ricci curvature.
method Ricci flow for a definite period of time, detecting collapsing infranil fiber bundles.
result Topological conditions detect collapsing infranil fiber bundles.
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.
Investigates cryptocurrency maturity through collective dynamics and diversification.
problem Determining if cryptocurrency market exhibits similar mathematical properties to equity market.
method Adjusts focus to retail cryptocurrency investors' behavioral patterns, contrasting with equity market.
result Identifies ideal portfolio size and spread across cryptocurrencies, revealing signatures of maturity.
Study flat manifolds and their collapse using Teichmüller theory.
problem Understanding the collapse of flat manifolds and orbifolds.
method Algebraic description of Teichmüller and moduli spaces, study of boundaries.
result Every closed flat orbifold can be obtained by collapsing closed flat manifolds, and collapsed limits of 3-manifolds are classified.
Mathematical analysis shows annealing prevents mode collapse in Gaussian mixtures.
problem Mode collapse in variational inference for multimodal distributions.
method Analyzed annealing strategies for Gaussian mixtures, derived formulas, and tested on neural networks.
result Appropriately chosen annealing schemes can robustly prevent mode collapse.
Proving NP-completeness of (d,k)-collapsibility for d≥k+2 except (2,0).
problem Determining if a d-dimensional simplicial complex can be collapsed to a k-dimensional subcomplex. method Extending previous works to show NP-completeness for d≥k+2. result NP-completeness of (d,k)-collapsibility for d≥k+2 except (2,0). The study characterizes and rules out collapsing in convex ancient mean curvature flow.
problem Characterizing and ruling out collapsing in convex ancient mean curvature flow.
method Characterization and counterexamples.
result Collapsing occurs if and only if the flow is asymptotic to at least one Grim hyperplane.