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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.

168,738 papers · 148 categories

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275582109 · Jun 202019922001200920172026
48 results for Geomagnetic Indices

New method uses DTW to evaluate neural network forecasts of geomagnetic indices.

problem Evaluation metrics fail to capture persistence behavior in neural network forecasts.
method Dynamic Time Warping (DTW) to measure time series similarity, training neural networks to remove persistence.
result DTW reveals persistence behavior in neural network forecasts, confirming visual inspection.

Neural Bayes methods simplify fitting complex bivariate extremal models.

problem Inference on complex multivariate extremal dependence models with computationally expensive likelihood functions.
method Use neural networks to approximate Bayes estimators and classifiers for model selection.
result Proposed neural Bayes methods enable routine implementation of complex extreme-value dependence models.

New model predicts particle precipitation from magnetosphere to ionosphere.

problem Improving prediction of electron particle precipitation from magnetosphere to ionosphere.
method Compilation of new database, use of machine learning (ML) tools, neural network (PrecipNet).
result PrecipNet achieves >50% reduction in errors and better captures dynamic changes.

Develops non-parametric tests for group symmetry in data.

problem Lack of statistical tests for group symmetry in data.
method Formulates and implements non-parametric tests for distributional symmetry under specified groups.
result Develops tests for conditional invariance/equivariance and applies them to real-world data.

2L-FUSE enhances feature sparsity through kernel learning.

problem Sparsity and feature selection in regression tasks.
method 2-Layered kernel machines for learning a shape matrix and feature direction identification.
result Minimal yet informative feature sets are identified without losing predictive performance.

We present a novel algorithm that predicts the probability that the time derivative of the horizontal component of the ground magnetic field dB/dtdB/dt exceeds a specified threshold at a given location. This quantity provides important information that is physically relevant to Geomagnetically Induced Currents (GIC), whic…

2019-12-02abs ↗pdf ↗

Machine learning detects and characterizes whistler radio waves for real-time monitoring of the plasmasphere.

problem Detect and characterise whistler radio waves generated by lightning strokes for real-time monitoring of the plasmasphere.
method Developed a machine learning model using image classification and localisation on spectrogram data to identify and localise whistlers.
result The proposed detectors achieve a misdetection and false alarm rate of less than 15% on Marion's dataset.

Composite development indicators used in policy making often subjectively aggregate a restricted set of indicators. We show, using dimensionality reduction techniques, including Principal Component Analysis (PCA) and for the first time information filtering and hierarchical clustering, that these composite indicators m…

2019-11-25abs ↗pdf ↗

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.

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.

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.

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.

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 ↗

Gittins indices provide an optimal solution to the classical multi-armed bandit problem. An obstacle to their use has been the common perception that their computation is very difficult. This paper demonstrates an accessible general methodology for the calculating Gittins indices for the multi-armed bandit with a detai…

2019-09-11abs ↗pdf ↗

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 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.