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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.

168,694 papers · 148 categories

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48 results for Global Markets

Model forecasts global stock market volatility using dynamic graphs and all trading days.

problem Enhance forecasting accuracy and practical utility in global stock market volatility.
method Spatial-temporal graph neural network architecture to capture volatility spillover effect.
result Forecasting performance surpasses baseline models in all scenarios.

We study the effect of globalization on the Korean market, one of the emerging markets. Some characteristics of the Korean market are different from those of the mature market according to the latest market data, and this is due to the influence of foreign markets or investors. We concentrate on the market network stru…

2005-09-13abs ↗pdf ↗

QuantNet learns global market trends to improve trading strategies.

problem Developing global trading strategies from multiple markets' data.
method QuantNet integrates transfer and meta-learning to learn market-agnostic trends and market-specific strategies.
result QuantNet outperformed top baseline strategies by 51% Sharpe and 69% Calmar ratios.

The paper analyzes sterling bills of exchange during the first globalization, revealing their global financial role.

problem Understanding the global financial role of sterling bills of exchange during the first globalization.
method Descriptive statistics and network analysis of a unique data set of 23,493 bills re-discounted by the Bank of England in 1906.
result Sterling bills of exchange had a truly global dimension and were crucial for overcoming information asymmetries.

Analyzes how Trump's tweets impact global stock markets.

problem Understanding the financial impact of presidential tweets on stock markets.
method Examined tweets from Donald Trump's presidency, collected from The Guardian and Bloomberg, and analyzed their effect on equity indices.
result Identified tweets that significantly influenced stock market indices.

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the …

2017-03-26abs ↗pdf ↗

The global financial system is highly complex, with cross-border interconnections and interdependencies. In this highly interconnected environment, local financial shocks and events can be easily amplified and turned into global events. This paper analyzes the dependencies among nearly 4,000 stocks from 15 countries. T…

2017-04-04abs ↗pdf ↗

With the random matrix theory, we study the spatial structure of the Chinese stock market, American stock market and global market indices. After taking into account the signs of the components in the eigenvectors of the cross-correlation matrix, we detect the subsector structure of the financial systems. The positive …

2012-01-31abs ↗pdf ↗

Financial global crisis has devastating impacts to economies since early XX century and continues to impose increasing collateral damages for governments, enterprises, and society in general. Up to now, all efforts to obtain efficient methods to predict these events have been disappointing. However, the quest for a rob…

2017-04-18abs ↗pdf ↗

Study detects anomalies in financial markets using GNN and nonextensive entropy.

problem Detecting anomalies in global financial markets with many correlated assets.
method Used Graph Neural Networks (GNN) with nonextensive entropy to measure uncertainty.
result Anomalies are statistically different for nonextensive entropy parameters before, during, and after a crisis.

The paper analyzes global inflation's systemic nature and its impact on equity markets.

problem Understanding the systemic nature of global inflation and its financial market implications.
method Data-driven study using eigenvalue analysis, inner-product optimization, and time-varying portfolio optimization.
result Countries with high centrality in global inflation are identified, and the robustness of equity indices and sectors during inflationary periods are explored.

Study reveals 2020 stock crashes were mostly endogenous, not exogenous.

problem Identifying the cause of the 2020 global stock market crash.
method Applied log-periodic power law singularity (LPPLS) methodology to analyze stock market indexes.
result The 2020 stock market crashes were mostly endogenous, driven by systemic instability.

Informer improves financial market prediction accuracy with global time stamp features.

problem Intra-day minute-scale financial market prediction challenges.
method Informer network, a novel deep learning model with smaller computational complexity and global time stamp features.
result Informer achieves best performance on MAE, RMSE, and MAPE evaluation criteria across all datasets.

The paper introduces a new financial market for environmental indices to attract investors.

problem Inherent risks and sustainability concerns in environmental investments.
method Quantitative measures, econometric analysis, dynamic asset pricing tools, and financial options.
result Monetization and construction of country-specific environmental indices as dollar-denominated assets.

Investor attention predicts global equity market volatility during Ukraine invasion.

problem Predicting global equity market volatility during geopolitical events.
method Event-specific attention indices based on Google Trends, analyzed across 51 global equity markets.
result Investor attention significantly predicts volatility in countries with higher economic openness to Russia and closer to it.

Study applies Gai-Kapadia framework to global equity markets to assess systemic risk and default cascades.

problem Assessing systemic risk and default cascades in global equity markets.
method Used Gai-Kapadia framework, 20-asset network, Monte Carlo simulations, and deterministic propagation analysis.
result High clustering among Brazilian assets leads to localized contagion, while developed markets show resilience.

Study extends Gai-Kapadia framework to assess systemic risk in global equity markets.

problem Systemic risk and default cascades in global equity markets.
method Network analysis, threshold filtering, Monte Carlo simulations, tail risk assessment.
result System exhibits strong global resilience with negligible probability of large-scale failure.

The paper challenges the assumption of a unique global time in financial markets, highlighting market incompleteness.

problem The assumption of a unique global time in financial markets is challenged.
method The paper contrasts event-time, renewal, point-process, and order-flow descriptions of financial markets.
result Non-uniqueness of time leads to a more foundational form of market incompleteness.

Study uses RL to optimize global equity portfolios, finds mixed results.

problem Optimizing dynamic portfolio weights across diverse global markets.
method Deep reinforcement learning with Soft Actor-Critic, incorporating various constraints and reward formulations.
result RL strategies achieve competitive performance, but no strategy consistently outperforms Buy and Hold.

Recurring international financial crises have adverse socioeconomic effects and demand novel regulatory instruments or strategies for risk management and market stabilization. However, the complex web of market interactions often impedes rational decisions that would absolutely minimize the risk. Here we show that, for…

2009-08-05abs ↗pdf ↗

Hypothesis of Market Efficiency is an important concept for the investors across the globe holding diversified portfolios. With the world economy getting more integrated day by day, more people are investing in global emerging markets. This means that it is pertinent to understand the efficiency of these markets. This …

2017-09-12abs ↗pdf ↗

Over-the-counter markets are at the center of the postcrisis global reform of the financial system. We show how the size and structure of such markets can undergo rapid and extensive changes when participants engage in portfolio compression, a post-trade netting technology. Tightly-knit and concentrated trading structu…

2017-05-19abs ↗pdf ↗

Russia-Ukraine conflict impacts global agricultural futures and spot markets' extreme risks.

problem Impact of Russia-Ukraine conflict on global agricultural futures and spot markets' extreme risks.
method Analytical framework for tail dependence, Copula-CoVaR method, ARMA-GARCH-skewed Student-t model.
result The outbreak of the conflict intensified risks in the wheat market the most and showed significant asymmetries in extreme risk spillovers.

Myopic investors make suboptimal choices that benefit others, leading to market inefficiencies.

problem Myopic investors make suboptimal decisions that lag the market.
method Constrained optimisation and overlapping examples of different investor types.
result Myopic investors' suboptimal choices lead to market inefficiencies and profit opportunities for others.

This study analyzes the correlation structure of global agricultural futures markets using RMT.

problem Understanding the complex correlation structure of global agricultural futures markets.
method Random Matrix Theory (RMT) applied to analyze correlation coefficients and eigenvalues.
result The correlation structure is asymmetric and right skewed, with significant eigenvalues indicating market effects and commodity groups.

After the shocking series of bankruptcies started in 2008, the public does not trust anymore the classical methods of assessing business risks. The global economic severe downturn caused demand for both developed and emerging economies' exports to drop and the crisis became truly global. However, this current crisis of…

2010-07-12abs ↗pdf ↗

In the current era of worldwide stock market interdependencies, the global financial village has become increasingly vulnerable to systemic collapse. The recent global financial crisis has highlighted the necessity of understanding and quantifying interdependencies among the world's economies, developing new effective …

2014-08-03abs ↗pdf ↗

A major impact of globalization has been the information flow across the financial markets rendering them vulnerable to financial contagion. Research has focused on network analysis techniques to understand the extent and nature of such information flow. It is now an established fact that a stock market crash in one co…

2019-11-14abs ↗pdf ↗

Develops a new framework to measure network connectedness across and within markets.

problem Lack of flexible methods to measure network connectedness and its evolution.
method Allows network nodes to be connected in clusters, with shocks orthogonal across clusters and correlated within clusters.
result Demonstrates the effectiveness of the new framework in a detailed empirical analysis of equity markets.

Study examines cross-training neural networks for financial index prediction.

problem Predicting financial indexes from different markets using machine learning.
method Investigated various neural network architectures and trained them on one market index to predict another.
result Cross-training models on one market index improved prediction accuracy for another market index.