We consider the effects of the global financial crisis through a local Korean financial market around the 2008 crisis. We analyze 185 individual stock prices belonging to the KOSPI (Korea Composite Stock Price Index), cosidering three time periods: the time before, during, and after the crisis. The complex networks gen…
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48 results for “crisis times”
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.
In this work, the time chart of Dow Jones Industrial Average (DJIA) index is analyzed and approach of recession time term is predicted, which may be hallmark of a worldwide economic crisis. However, the methods used for the prediction will be disclosed a few years from now. On the other hand, this work will be updated …
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.
In order to figure out and to forecast the emergence phenomena of social systems, we propose several probabilistic models for the analysis of financial markets, especially around a crisis. We first attempt to visualize the collective behaviour of markets during a financial crisis through cross-correlations between typi…
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.
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.
Methods of nonlinear dynamics and the construction of cryptocurrency crisis phenomena precursorsq-fin.ST
This article demonstrates the possibility of constructing indicators of critical and crisis phenomena in the volatile market of cryptocurrency. For this purpose, the methods of the theory of complex systems such as recurrent analysis of dynamic systems and the calculation of permutation entropy are used. It is shown th…
We study the dynamics of correlation and variance in systems under the load of environmental factors. A universal effect in ensembles of similar systems under the load of similar factors is described: in crisis, typically, even before obvious symptoms of crisis appear, correlation increases, and, at the same time, vari…
Python tool detects economic crises from S&P500 correlation data.
problem Identifying economic crises from market correlation data.
method Bayesian multi-trend change point analysis.
result Mean market correlation correlates with major economic events.
The 2008 financial crisis revealed banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.
problem Fundamental vulnerabilities in interconnected banking systems during the 2008 financial crisis were inadequately addressed by existing frameworks.
method Developed a unified spatial-network framework using spectral analysis of network Laplacian operators combined with spatial difference-in-differences identification.
result Banking consolidation paradoxically increased systemic fragility and global financial contagion with negligible spatial decay.
The paper examines how randomness in forex returns increases during financial crises.
problem Measuring randomness in forex returns during financial crises.
method Approximate Entropy and Sample Entropy statistics.
result Randomness in forex returns decreases during financial crises, as evidenced by lower entropy values.
Following the thermodynamic formulation of multifractal measure that was shown to be capable of detecting large fluctuations at an early stage, here we propose a new index which permits us to distinguish events like financial crisis in real time . We calculate the partition function from where we obtain thermodynamic q…
Using the eigenvalues and eigenvectors of correlations matrices of some of the main financial market indices in the world, we show that high volatility of markets is directly linked with strong correlations between them. This means that markets tend to behave as one during great crashes. In order to do so, we investiga…
We analyze whether the prediction of the fractal markets hypothesis about a dominance of specific investment horizons during turbulent times holds. To do so, we utilize the continuous wavelet transform analysis and obtained wavelet power spectra which give the crucial information about the variance distribution across …
The Financial Crisis of 2008 is a worldwide financial crisis causing a worldwide economic decline that is the most severe since the 1930s. According to the International Monetary Fund (IMF), the global financial crisis gave impact on USD 3.4 trillion losses from financial institutions around the world between 2007 and …
Decomposes financial networks to reveal cause-effect hierarchies during crises.
problem Complex financial networks are hard to interpret due to Granger causality.
method Helmholtz-Hodge-Kodaira decomposition to separate networks into rotational and gradient components.
result Precious metals and pharmaceutical products are identified as causal drivers during crises.
OMD monitors stock market dynamics through matrix trajectories, revealing crisis patterns and sector rotations.
problem Understanding and predicting stock market dynamics during crises.
method Applying OMD to S&P 500 returns over three crises, analyzing distance matrices and their spectra.
result Market dynamics show coherent changes during crises, with sector-specific patterns and volatility clustering.
Crisis Propagation in a Heterogeneous Self-Reflexive DSGE Modelcond-mat.stat-mech
Model shows how confidence feedback can lead to different crisis outcomes.
problem Characterizing the impact of economic recessions on different social strata.
method A self-reflexive DSGE model with heterogeneous households, varying parameters to analyze crisis typologies.
result Crisis propagation can be confined to high or low income households, depending on social network structure and income inequality.
The global financial crisis, beginning in 2008, took an historic toll on national economies around the world. Following equity market crashes, unemployment rates rose significantly in many countries: Italy was among those. What will be the impact of such large shocks on Italian healthcare finances? An empirical model f…
This paper analyzes the connection between innovation activities of companies -- implemented before crisis -- and their performance -- measured at time of crisis. The companies listed in the STAR Market Segment of the Italian Stock Exchange are analyzed. Innovation is measured through the level of investments in total …
Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisisphysics.soc-ph
We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of indiv…
Financial Bubbles, Real Estate bubbles, Derivative Bubbles, and the Financial and Economic Crisisq-fin.RM
The financial crisis of 2008, which started with an initially well-defined epicenter focused on mortgage backed securities (MBS), has been cascading into a global economic recession, whose increasing severity and uncertain duration has led and is continuing to lead to massive losses and damage for billions of people. H…
Regime-Dependent Predictive Structure Between Equity Factors: Evidence from Granger Causalityq-fin.RM
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.
The study assesses how financial markets' efficiency changed during the COVID-19 crisis.
problem The impact of COVID-19 on financial market efficiency.
method Dynamic estimation method for Hurst exponent and memory parameter using alpha-stable distribution and dependence structure.
result Financial markets' efficiency varied during the COVID-19 crisis, with some indices showing less impact than others.
After September 2008, the advanced economies severe decline caused demand for emerging economies' exports to drop and the crisis became truly global, much deeper and broader than expected. In these times of global depression, most countries and companies are affected, some more than others. The financial crisis has tur…
OMD monitors stock market dynamics through matrix trajectories and reveals crisis patterns.
problem Understanding and predicting stock market crises and sector rotations.
method Applying OMD to S\&P 500 returns over three crises, analyzing distance matrices and their spectra.
result Market dynamics show coherent changes during crises, with distinct sector leadership.
We investigate the use of the Hurst exponent, dynamically computed over a moving time-window, to evaluate the level of stability/instability of financial firms. Financial firms bailed-out as a consequence of the 2007-2010 credit crisis show a neat increase with time of the generalized Hurst exponent in the period prece…
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.
One of the findings of the recent literature is that the 2008 financial crisis caused reduction in international diversification benefits. To fully understand the possible potential from diversification, we build an empirical model which combines generalised autoregressive score copula functions with high frequency dat…
Model shows worldwide trade crises can be localized or global, depending on trade balance.
problem Understanding and predicting worldwide trade crises.
method Modeling worldwide trade network using Google matrix analysis and bankruptcy threshold.
result Crisis contagion is localized for high trade balance, global for low trade balance.
This paper presents two cases of random banking data generators based on migration matrices and scoring rules. The banking data generator is a new hope in researches of finding the proving method of comparisons of various credit scoring techniques. There is analyzed the influence of one cyclic macro--economic variable …
In this paper, we perform a comparative segmentation and clustering analysis of the time series for the ten Dow Jones US economic sector indices between 14 February 2000 and 31 August 2008. From the temporal distributions of clustered segments, we find that the US economy took one and a half years to recover from the m…
Study examines oil and US stock market interactions during coronavirus crisis.
problem Understanding the impact of coronavirus on oil and stock markets.
method Wavelet analysis of daily data from February 18, 2020 to August 15, 2020.
result Oil prices lead US stock prices at 3-5-day cycles during the first and second parts of March and April 2020.
Defines crisis transitions in pure exchange economies rigorously.
problem Understanding crises in economic equilibrium models.
method Uses mathematical concepts like branching, envelopes, and intrinsic derivative.
result Establishes criteria to distinguish crises from other equilibria.
General Equilibrium Amplification and Crisis Vulnerability: Cross-Crisis Evidence from Global Banksecon.EM
This study quantifies systemic importance in global banks using a continuous framework that amplifies localized shocks.
problem Analyzing financial contagion and systemic risk in global banks.
method Developed a continuous framework incorporating geographic proximity and interbank network linkages, using a master equation and Feynman-Kac representation.
result The amplification factor correctly identifies systemically important institutions and predicts crisis outcomes.
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.
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.
Collective behavior of stock prices in the time of crisis as a response to the external stimulusq-fin.ST
Study shows stock price interactions increase during crises due to external stimulus.
problem Understanding stock price interactions during economic crises.
method Granger Causality and recurrence analysis on stock price series.
result External stimulus drives stock price interactions during crises.
Machine learning predicts US stock market crashes.
problem Early detection of stock market crises.
method Random Forest and Extreme Gradient Boosting models.
result Extreme Gradient Boosting outperforms other models.
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). …
We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest ei…
Fundamental defect of the macroeconomic thinking as one of the main causes of the crisis enduredq-fin.GN
The main points of the first section of the article written by S.I. Chernyshov, A.V. Voronin and S.A. Razumovsky arXiv:1003.4382), which deals with the fundamental bases of the macroeconomic theory, have been analyzed. An incorrectness of the Harrod's model of the economical growth in its generally accepted interpretat…
Macroeconomic theories of growth and wealth distribution have an outsized influence on national and international social and economic policies. Yet, due to a relative lack of reliable, system wide data, many such theories remain, at best, unvalidated and, at worst, misleading. In this paper, we introduce a novel econom…
Financial networks are dynamic. To assess their systemic importance to the world-wide economic network and avert losses we need models that take the time variations of the links and nodes into account. Using the methodology of classical mechanics and Laplacian determinism we develop a model that can predict the respons…
Social media sources can provide crucial information in crisis situations, but discovering relevant messages is not trivial. Methods have so far focused on universal detection models for all kinds of crises or for certain crisis types (e.g. floods). Event-specific models could implement a more focused search area, but …
The study analyzes aftershocks of stock market crashes using statistical methods.
problem Understanding the aftershocks of stock market crashes during crises.
method Structural break analysis and statistical methods applied to 1987 crash, 2008 financial crisis, and 2020 COVID-19 pandemic.
result The recovery of stock price during the COVID-19 pandemic may be faster than the financial crisis of 2008.
Paper presents a DRL framework for detecting and anticipating financial crises.
problem Detecting and adapting to financial crises using deep reinforcement learning.
method Two sub-networks, one for past performances and standard deviations, the other for contextual features. Adversarial training for robustness.
result Framework substantially outperforms traditional methods in detecting and anticipating crises.