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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.

169,181 papers · 148 categories

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275582109 · Jun 202019922001200920182026
48 results for Sutte Indicator

New composite indicators reveal hidden relationships between indicators.

problem Subjective aggregation of indicators leads to missed information.
method Used dimensionality reduction techniques (PCA, filtering, clustering) to reveal hidden relationships.
result Cluster-driven composite indicators outperform traditional ones in data reconstruction.

This study examined how the correlation and network structure of 30 global indices and 145 local Korean indices belonging to the KOSPI 200 have changed during the 13-year period, 2000-2012. The correlations among the indices were calculated. The results showed that although the average correlations of the global indice…

2014-02-07abs ↗pdf ↗

Financial market created for wellbeing indices to mitigate socioeconomic risks.

problem Risk mitigation in financial indices of socioeconomic wellbeing.
method Developed new quantitative measure, created financial market, and implemented insurance instruments.
result Optimal portfolio weights and efficient frontiers for wellbeing indices.

The paper analyzes indices based on counting object pairs for assessing partition agreement in unsupervised learning.

problem The difficulty in interpreting overall indices like Rand and adjusted Rand indices.
method Analysis of three families of indices based on counting object pairs, decomposing overall indices into cluster-level indices.
result Overall indices based on pair-counting approach are sensitive to cluster size imbalance and provide limited information on smaller clusters.

Ranking stock indices based on causal influence using directed information graphs.

problem Identifying which countries exert the most economic influence in a subset of the global economy.
method Representing indices as nodes in a directed graph, estimating causal influences using directed information functional, ranking indices based on net-flow.
result Indices representing smaller economies can exert significant influence on larger economies.

Investigates local indicability of groups with circle homology presentations.

problem Conditions for local indicability in groups with circle homology presentations.
method Generalizes results for two-relator presentations to circle homology presentations.
result Extends results on local indicability to LOT groups and non-cycle-free Adian presentations.

The paper studies topological indices of geometric operators on manifolds with fibered boundaries.

problem Investigating indices of geometric operators on manifolds with fibered boundaries.
method Defining K-groups relative to pushforward for boundary fibration, using groupoid deformation techniques to prove properties of indices.
result Indices of twisted geometric operators can be understood as index pairings over K-groups.

We define analytic indices which involve the eta form and the analytic torsion form. We show that these indices are independent of the geometric choices made in their definitions, and hence are topological in nature.

1995-03-13abs ↗pdf ↗

This research simplifies computation of feature attribution methods under certain conditions.

problem Computational complexity of feature attribution methods, especially power indices.
method Identifying conditions for polynomial computation and introducing new indices.
result Conditions for efficient computation of feature attribution methods are identified.

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.

The study analyzes performance indices for class-imbalanced data and identifies conditions they must meet.

problem Distortions in performance indices under class imbalance.
method Identified two conditions for performance indices and analyzed four binary and five multi-class indices.
result Recommended appropriate indices for evaluating classifiers in class-imbalanced scenarios.

Improved MACD trading strategies with other indicators for better performance.

problem Evaluating the effectiveness of MACD-based trading strategies in the US stock market.
method Backtested various MACD-based trading strategies on US stock indices using Python.
result Win-rate of MACD strategies improved with other momentum indicators, leading to a new VPVMA indicator.

Strategic traders adjust indicative prices near auctions to achieve nearly diffusive outcomes.

problem Achieving diffusive price behavior in Paris Stock Exchange auctions.
method Analyzing the diffusive properties of indicative auction prices and the strategic behavior of traders.
result Strategic traders adjust their order submission times to achieve nearly diffusive price behavior.

Study finds traditional technical indicators underperform in high-frequency trading, suggesting risk management over prediction.

problem Inadequately explored effectiveness of technical indicators in high-frequency trading, particularly at minute-level frequency.
method Evaluation of random forest models with traditional technical indicators on minute-level SPY data.
result In-sample performance is superior to out-of-sample, with risk-adjusted metrics not outperforming a simple buy-and-hold strategy.

New method ranks European countries' innovation performance considering criterion interactions.

problem Lack of consensus on weighting composite innovation indicators.
method Hierarchical-SMAA-Choquet integral approach to rank and benchmark innovation performance.
result Robust measurement of innovation performances in Europe with a hierarchy of interacting composite indicators.

This paper provides a unified framework, which allows, in particular, to study the structure of dynamic monetary risk measures and dynamic acceptability indices. The main mathematical tool, which we use here, and which allows us to significantly generalize existing results is the theory of L0L^0-modules. In the first p…

2013-06-21abs ↗pdf ↗

Study shows news influences world markets, revealing correlations between The New York Times and financial indices.

problem Understanding the relationship between news and financial markets.
method Used Random Matrix Theory and information theory on news and financial indices.
result News drives world market movements, showing correlations preserved even with noise.

Study shows diverse data sources improve cryptocurrency forecasting models.

problem Improving cryptocurrency market forecasting accuracy.
method Integrating various data types, including on-chain metrics, traditional indices, and macroeconomic indicators.
result Data source diversity significantly enhances forecasting model performance.

This paper simplifies conditional Sobol' indices calculation using PCE bases.

problem Computational inefficiency and lack of consistency in evaluating conditional Sobol' indices.
method Analytical extraction of conditional Sobol' indices via basis decomposition of PCE expansions.
result Derives closed-form expressions for conditional Sobol' indices.

This paper reviews and proposes a new approach for evaluating internal cluster validation indices.

problem Selecting the best-performing unsupervised classification algorithm without external information.
method Examines and proposes a new evaluation approach for internal validation indices.
result Suggests a new evaluation approach for internal validation indices.

We propose a new class of mappings, called Dynamic Limit Growth Indices, that are designed to measure the long-run performance of a financial portfolio in discrete time setup. We study various important properties for this new class of measures, and in particular, we provide necessary and sufficient condition for a Dyn…

2013-12-04abs ↗pdf ↗

TINs use neural networks to interpret technical indicators for trading.

problem Lack of interpretable neural architectures for technical indicators in trading.
method Introduced TINs, a neural architecture that reformulates technical indicators into trainable modules.
result Improved risk-adjusted performance compared to traditional indicator-based strategies.