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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.

169,051 papers · 148 categories

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3569104138 · May 202619922001200920172026
48 results for international markets

Study improves stock price prediction by integrating international markets using deep learning.

problem Complex cross-correlation between international stock markets.
method Multimodal deep learning to forecast stock prices.
result Early and intermediate fusion models outperform late fusion and single modality models.

Study uses AI to predict changes in international public finances based on US markets.

problem Understanding correlations between US and international public finances.
method Artificial intelligence and neural networks to model and predict changes.
result Neural network model achieved MSE of 2.79, indicating significant correlation and impact of US market volatility on international markets.

Paper optimizes internal balancing of wind and hydropower to reduce intraday market volatility.

problem Reduction of intraday market volatility for power producers with wind and hydropower assets.
method Internal balancing within the same river system and sales/purchase in a pay-as-bid intraday market.
result Reduction in short-term marginal cost and risk through internal balancing.

The study reveals the hierarchical structure of the international FOREX market using currency fluctuation distribution similarities.

problem Understanding the hierarchical structure of the international FOREX market.
method Using Jensen-Shannon divergence to quantify the similarity between normalized logarithmic return distributions of currencies.
result Clusters of currencies are consistent with the nature of underlying economies but diverge during crises.

Paper uses neural networks to analyze oil price impact on Iranian stock and industry indices.

problem Impact of oil price volatility on Tehran stock and industry indices.
method Feed-forward neural networks analysis of two periods: sanctions and post-sanctions.
result Neural networks predict stock and industry indices well, showing significant oil price volatility impact.

We investigated the network structures of the Japanese stock market through the minimum spanning tree. We defined grouping coefficient to test the validity of conventional grouping by industrial categories, and found a decreasing in trend for the coefficient. This phenomenon supports the increasing external influences …

2007-08-03abs ↗pdf ↗

This paper offers a framework for FX dealers to decide between internalizing and externalizing their market making to balance risk control and costs.

problem FX dealers face risk from flow uncertainty and need to decide on internalization vs. externalization strategies.
method Develops an optimal control framework that balances pricing and hedging strategies.
result Provides insights into the trade-off between risk control and transaction costs in market making.

The paper proposes a new algorithm for dealer markets that incorporates hedging and market impact.

problem How to manage risk and quote prices in dealer markets with limited internalization.
method Develops a mathematical model that allows dealers to hedge part of their inventory and adjust quotes based on inventory size.
result Dealers can internalize risk within a certain inventory range and externalize it outside of that range, optimizing their quoting strategy.

This paper introduces a new process for portfolio rebalancing that is more equitable than existing methods.

problem Improving portfolio rebalancing processes in finance to be more equitable.
method Introduces a new market-invariant process for portfolio rebalancing, proving its superiority over existing methods.
result The market-invariant process is more equitable than the banker and linear processes, as demonstrated by empirical results.

We show that some specific market risk measures implied by current international capital regulation (the Basel Accords and the Capital Adequacy Directive of the European Union) violate the obvious requirement of convexity in some regions in the space of portfolio weights.

2003-07-10abs ↗pdf ↗

Proposes a framework to predict stock movements by integrating multi-order and internal dynamics.

problem Predicting stock movements with multi-order and internal dynamics.
method Temporal generative filters and hypergraph attentions using wavelet basis.
result Framework outperforms state-of-the-art methods in terms of profit and stability.

A novel approach to analyzing time series generated by complex systems, such as markets, is presented. The basic idea of the approach is the {\it Law of Self-Similar Evolution}, according to which any complex system develops self-similarly. There always exist some internal laws governing the evolution of a system, say …

2001-10-15abs ↗pdf ↗

The study reveals asymmetries in US financial shocks' international impacts.

problem Analyzing nonlinearities in international financial spillovers.
method Developed a flexible nonlinear multi-country model to capture asymmetries in responses to financial shocks.
result Adverse shocks trigger stronger declines in output, inflation, and stock markets than benign shocks.

In this study, we establish a network structure of the Korean stock market, one of the emerging markets, with its minimum spanning tree through the correlation matrix. Base on this analysis, it is found that the Korean stock market doesn't form the clusters of the business sectors or of the industry categories. When th…

2005-04-01abs ↗pdf ↗

Hidden Markov model predicts profitable statistical arbitrage in Shanghai crude oil futures.

problem Statistical arbitrage opportunities in international crude oil futures markets.
method Hidden Markov model for cointegration spread, mean-reverting regime-switching process.
result Statistical arbitrage strategies involving Shanghai crude oil futures are profitable.

HybridCGAN improves portfolio analysis by balancing trend prediction and market uncertainty.

problem Markowitz framework's overemphasis on market uncertainty and trend prediction.
method A hybrid approach combining deep generative models to balance trend prediction and market uncertainty.
result HybridCGAN leads to better portfolio allocation compared to existing methods.

It is shown that absence of arbitrage opportunity in financial markets is a particular case of existence of uncertainty in decision system. Absence of arbitrage opportunity is considered in the sense of the Arrow-Debreu model of financial market with a riskless asset, while uncertainty (or ambiguity) is defined on the …

2013-07-22abs ↗pdf ↗

The Basel II Accords have sparked increased interest in the development of approaches based on internal ratings systems and have initiated the elaboration of models for remote ratings forecasts based on external ones as part of Risk Management and Early Warning Systems. This article evaluates the peculiarities of curre…

2016-07-05abs ↗pdf ↗

We address the problem of gauging the influence exerted by a given country on the global trade market from the viewpoint of complex networks. In particular, we apply the PWP method for computing indirect influences on the world trade network.

2014-11-27abs ↗pdf ↗

AMSAs adaptively manage crypto-currency trading by selecting multiple strategies based on market conditions.

problem Maximizing gains in volatile crypto-currency markets with high uncertainty.
method AMSAs use multiple sub-agents with different strategies, dynamically selecting them based on market conditions.
result AMSAs can achieve high positive alpha in long-term crypto-currency trading.

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.

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 ↗

Study examines grain futures connectedness during Russia-Ukraine conflict.

problem Quantile return connectedness of grain futures markets during geopolitical instability.
method Dynamic quantile VAR combined with frequency-domain decomposition.
result Heterogeneous spillovers across quantiles, with strong transmitters and persistent receivers.

The paper limits the profitability of technical trading rules and finds they are not better than random trading.

problem The profitability of technical trading rules in stock markets is controversial.
method Proves the upper bound of cumulative return and investigates the profitability of technical trading rules using bootstrap methodology.
result Technical trading rules are not better than random trading and less profitable than the market.

Informed traders strategically reveal noisier signals, making prices less responsive to public information.

problem How informed traders strategically reveal signals impacts market prices and utility.
method Modeling a market with an informed trader, an uninformed trader, and liquidity providers, proving equilibrium existence.
result In equilibrium, the insider strategically reveals a noisier signal, making prices less responsive to public information.