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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.

168,657 papers · 148 categories

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1122 · Mar 201719922001200920172026
29 results for Switzerland

An empirical model is presented linking inflation and unemployment rate to the change in the level of labour force in Switzerland. The involved variables are found to be cointegrated and we estimate lagged linear deterministic relationships using the method of cumulative curves, a simplified version of the 1D Boundary …

2011-02-26abs ↗pdf ↗

Labor productivity in Turkey, Spain, Belgium, Austria, Switzerland, and New Zealand has been analyzed and modeled. These counties extend the previously analyzed set of the US, UK, Japan, France, Italy, and Canada. Modelling is based on the link between the rate of labor participation and real GDP per capita. New result…

2010-01-27abs ↗pdf ↗

Study analyzes how discounts affect train ticket purchases and rescheduling in Switzerland.

problem Understanding how discounts influence train ticket buying and rescheduling behavior.
method Machine learning techniques, including causal machine learning, to analyze survey data.
result Increasing a discount rate by 1% increases the rescheduled trip share by 0.16% among always buyers.

We have analyzed the risks of possible development of bubbles in the Swiss residential real estate market. The data employed in this work has been collected by comparis.ch, and carefully cleaned from duplicate records through a procedure based on supervised machine learning methods. The study uses the log periodic powe…

2013-03-19abs ↗pdf ↗

Model analyzes debt recycling strategies under various fiscal regimes and jurisdictions.

problem Understanding debt recycling dynamics and their impact on repayment times and equity growth.
method Developed a calibrated model incorporating mortgage interest rates, borrowing costs, and tax shields.
result Introducing positive interest rates without tax shields contracts success regions and lengthens repayment times, but tax shields partially reverse these effects.

Simple models are preferred over complex models, but over-simplistic models could lead to erroneous interpretations. The classical approach is to start with a simple model, whose shortcomings are assessed in residual-based model diagnostics. Eventually, one increases the complexity of this initial overly simple model a…

2017-06-26abs ↗pdf ↗

New method combines regional HIV prevention trial data without sharing individual patient info.

problem Regional differences in HIV prevention efficacy, privacy concerns, and data sharing limitations.
method Federated learning approach that combines site-specific estimators via L1-regularization.
result Improved precision in estimating region-specific survival curves.

Modeling infection hotspots to quantify effects of contact tracing and testing.

problem Capturing the role of infection hotspots in disease transmission.
method Temporal point process modeling framework to represent visits and disease transmission.
result Estimation of transmission rates at sites and households using Bayesian optimization.

PeakWeather provides Swiss weather station data for machine learning.

problem Accurate weather forecasting for various activities and decision-making.
method High-quality dataset of surface weather observations from 8 years of Swiss stations.
result Dataset supports a wide range of spatiotemporal tasks.

New method reconstructs past foehn occurrences using unsupervised and supervised learning.

problem Reconstructing past foehn occurrences due to lack of direct measurement.
method Combining unsupervised and supervised learning methods to infer foehn occurrences from reanalysis data.
result Accurate hourly reconstructions of past foehn occurrences for 83 years.

Machine learning models predict housing prices using macroeconomic factors.

problem Predicting housing prices using macroeconomic data.
method Used machine learning (kNN and tree-bagging) on a dataset of macroeconomic factors.
result Machine learning models can predict housing prices with uncertainties better than existing index uncertainties.

Abstract: Study of geometric structures on surfaces using various tools.

problem Understanding geometric structures on surfaces.
method Use of volume, contact, symplectic, complex, and almost complex structures; local rigidity results; higher-dimensional analogues; constructions with Riemann surfaces; definitions using surjective homomorphisms; models of hyperbolic plane and 3-space; conformal structures.
result Introduction of new models and constructions for hyperbolic plane and 3-space.

New findings challenge the importance of forecast accuracy in battery storage optimization, highlighting the role of rank correlation instead.

problem The challenge of optimizing battery storage dispatch decisions in multi-market electricity trading using forecast accuracy metrics.
method A hierarchical three-layer optimization system trading in multiple markets (FCR, aFRR, day-ahead, intraday) with real market data.
result Rank correlation (Kendall tau) is a better predictor of intraday dispatch value than forecast accuracy (MAE), with a threshold of tau around 0.85-0.95 capturing up to 97-100% of perfect-foresight revenue.

The growth rate of real GDP per capita in the biggest OECD countries is represented as a sum of two components - a steadily decreasing trend and fluctuations related to the change in some specific age population. The long term trend in the growth rate is modelled by an inverse function of real GDP per capita with a con…

2012-05-25abs ↗pdf ↗

Generative adversarial networks generate realistic, time-evolving high-resolution atmospheric fields.

problem Improving spatial resolution of low-resolution atmospheric images.
method Recurrent, stochastic super-resolution GAN for generating ensembles of time-evolving high-resolution atmospheric fields.
result The GAN produces realistic, temporally consistent super-resolution sequences for radar-measured precipitation and cloud optical thickness.

The M and A transactions represent a wide range of unique business optimization opportunities in the corporate transformation deals, which are usually characterized by the high level of total risk. The M and A transactions can be successfully implemented by taking to an account the size of investments, purchase price, …

2015-02-06abs ↗pdf ↗

Study assesses risk of upward lightning at wind turbines using direct measurements and machine learning.

problem Risk underestimation of upward lightning at wind turbines due to limited detection by current standards.
method Direct UL measurements linked to meteorological reanalysis data using random forests.
result Risk maps based on case study events show high probabilities coincide with actual UL events.