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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.

168,742 papers · 148 categories

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295886115 · Jan 202619922001200920172026
48 results for Dutch housing market

Study on efficiency of Dutch auctions on blockchains considering various parameters.

problem Efficiency and fairness in Dutch auctions on blockchains.
method Modeling Dutch auctions with Poisson process and geometric Brownian motion, computing expected losses and time-to-fill.
result Tradeoff between speed and quality in Dutch auctions, useful for setting parameters.

This paper explores integration and contagion among US metropolitan housing markets. The analysis applies Federal Housing Finance Agency (FHFA) house price repeat sales indexes from 384 metropolitan areas to estimate a multi-factor model of U.S. housing market integration. It then identifies statistical jumps in metrop…

2011-10-18abs ↗pdf ↗

The study models mortgage prepayment risk using stochastic housing market activity.

problem Modeling prepayment risk in mortgages under varying housing market conditions.
method Developed a stochastic model for prepayment option value, using swaption pricing formulas and non-standard actuarial hedging.
result Housing market covariance significantly impacts prepayment option prices.

This paper investigates the risk-return relationship in determination of housing asset pricing. In so doing, the paper evaluates behavioral hypotheses advanced by Case and Shiller (1988, 2002, 2009) in studies of boom and post-boom housing markets. The paper specifies and tests a multi-factor housing asset pricing mode…

2011-03-30abs ↗pdf ↗

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a markedly fall during the global financial tsunami and China's economy has also slowed down by about 2\%-3\% when m…

2015-03-18abs ↗pdf ↗

Housing markets play a crucial role in economies and the collapse of a real-estate bubble usually destabilizes the financial system and causes economic recessions. We investigate the systemic risk and spatiotemporal dynamics of the US housing market (1975-2011) at the state level based on the Random Matrix Theory (RMT)…

2013-06-12abs ↗pdf ↗

Study shows how algorithmic prediction affects US housing market, reducing racial wealth disparities.

problem Impact of algorithmic prediction on housing market and racial wealth disparities.
method Natural experiment using digitization of housing records to study entry, allocation, and prices.
result Digitization leads to increased sale prices for minority-owned homes, reducing racial wealth disparities.

Spatial ABM predicts housing market trends in Sydney.

problem Inadequate spatial modeling in housing market forecasts.
method Graph-based spatial agent-based model incorporating social and economic factors.
result Model accurately predicts market trends and local area-specific forecasts.

Spatially weighted conformal prediction improves uncertainty quantification in house price models.

problem Uncertainty quantification in automated valuation models with spatial dependencies.
method Survey and demonstration of various spatially weighted approaches to adjust conformal prediction confidence sets.
result Spatially weighted CP makes confidence sets more consistently calibrated across geographical regions.

The real estate market is exposed to many fluctuations in prices because of existing correlations with many variables, some of which cannot be controlled or might even be unknown. Housing prices can increase rapidly (or in some cases, also drop very fast), yet the numerous listings available online where houses are sol…

2018-09-13abs ↗pdf ↗

Model explains herding and volatility in urban housing prices.

problem Understanding non-linear price dynamics in urban housing markets.
method Agent-based model with rational households and trend-following behavior.
result Model accurately predicts price variability and herding behavior.

Modeling house prices in Australia reveals supply limitations as the primary driver of extreme trends.

problem Understanding the resilience of Australia's housing prices despite changes in mortgage rates.
method Developed a differential equation model and used modern extreme value techniques on real-world data.
result Without supply increases, a 11% mortgage rate hike is needed to moderate extreme housing costs.

The paper introduces mortgage-rate-adjusted home prices to help buyers and adjust housing indices.

problem Impact of mortgage rates on home prices and property purchase decisions.
method Derives mortgage-rate-adjusted 'effective price' and constructs a price-mortgage rate neutrality line.
result Mortgage rates significantly affect home prices over long periods but not during the pandemic.

In this article, we develop a model for the evolution of real estate prices. A wide range of inputs, including stochastic interest rates and changing demands for the asset, are considered. Maximizing their expected utility, home owners make optimal sale decisions given these changing market conditions. Using these opti…

2009-07-10abs ↗pdf ↗

Study shows houses appreciated more during pandemic due to speculation, not just price uncertainty.

problem Impact of COVID-19 on house prices and speculation.
method Quasi-experimental design, unit-level matching, multivariate difference-in-difference regression.
result Properties listed for sale appreciated an additional 1% per month after pandemic onset, with an excess annual growth of 12.7 percentage points.

Study shows how macroprudential policies affect credit growth in Israel, especially in housing and business sectors.

problem Impact of macroprudential policies on credit growth in Israel.
method Bank-level panel data analysis for Israel, 2004-2019; interaction of monetary and macroprudential policies.
result Accommodative monetary policy interacts with macroprudential policies to increase total credit growth.

Study shows house buyers in Christchurch value earthquake risk differently based on time since 2011 quake.

problem Understanding how house buyers' perception of earthquake risk changes over time.
method Used a hedonic price model to analyze house prices in Christchurch over three periods.
result Buyers value earthquake risk differently based on the time since the 2011 Christchurch earthquake.

Improved negation detection in Dutch clinical texts using machine learning.

problem Extracting negation from clinical text for better model development.
method Comparison of rule-based and machine learning methods (biLSTM, RoBERTa).
result BiLSTM and RoBERTa models outperform rule-based method in F1 score, precision, and recall.

We consider a simple stochastic model of a urban rental housing market, in which the interaction of tenants and landlords induces rent fluctuations. We simulate the model numerically and measure the equilibrium rent distribution, which is found to be close to a lognormal law. We also study the influence of the density …

2012-03-23abs ↗pdf ↗

Study finds no consistent return predictability using payout ratios across 16 countries.

problem Return predictability using payout ratios in various markets.
method Analysis of 16 developed countries' bond, equity, and housing markets using payout-price ratios.
result No consistent in-sample and out-of-sample performance with positive utility gain.

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.

The paper analyzes debt recycling strategies for mortgage repayment, revealing complex phases of success and failure.

problem Evaluating the effectiveness of debt recycling strategies compared to standard mortgage repayment.
method Developed a dynamical model to study the time evolution of equity and mortgage balance under various conditions.
result The model identifies four phases: strongly successful, weakly successful, default, and permanent re-mortgaging, with sensitivity to initial conditions.

Inefficient markets allow investors to consistently outperform the market. To demonstrate that inefficiencies exist in sports betting markets, we created a betting algorithm that generates above market returns for the NFL, NBA, NCAAF, NCAAB, and WNBA betting markets. To formulate our betting strategy, we collected and …

2019-10-19abs ↗pdf ↗

This thesis evaluates text-based vs audio-based classification of mental health interviews.

problem Classifying psychiatric illness using text-based methods.
method Design and evaluate a text classification network on mental health interviews, using belabBERT.
result Text-based classification is a strong alternative to audio-based methods.

The paper uses graph learning to detect valid instruments in high-dimensional data for house pricing.

problem Endogeneity bias and invalid instrument validation in high-dimensional data.
method Merge variable selection algorithms and probabilistic graphs to estimate house prices and causal structure.
result Efficient data-driven instrument selection and invalid instrument purge in high-dimensional data.

Examines how extending home loan durations affects French households financially.

problem Financial implications for households with extended home loan durations.
method Analysis of French and international home loan systems, including bullet loans and Japanese home loans.
result Extending home loan durations can reduce monthly payments but raises financial risks.

Spectral analysis detects structural changes in financial networks.

problem Detecting structural transitions in financial networks to assess systemic risk.
method Ensemble properties of spectral radius of random graph models calibrated on real-world evolving networks.
result The spectral deviation captures ongoing topological changes in financial networks.

West Frisian lemmatizer, POS tagger, and parser created.

problem Creating accurate lemmatization, POS tagging, and dependency parsing for West Frisian.
method Using a corpus of 44,714 words annotated according to Universal Dependency version 2. Applying Dutch POS tags and morphological/syntactic annotations to create Frisian translations.
result Significant improvement in lemma accuracy compared to default parameters.

Singapore's cooling measures did not increase housing wealth overall.

problem The impact of cooling measures on housing wealth distribution.
method Examined Singapore's cooling measures over ten rounds, analyzing welfare from housing wealth.
result Welfare from housing wealth in the last round might not be higher than before 2009, depending on the deflator.

HabitatAgent offers a multi-agent system for transparent housing consultation.

problem Opaque reasoning and brittle multi-constraint handling in housing recommendation systems.
method HabitatAgent is a multi-agent architecture with specialized roles for memory, retrieval, generation, and validation.
result HabitatAgent achieves 95% accuracy in real user consultation scenarios, significantly outperforming a strong baseline.

Elevating houses to flood risk increases uncertainty, leading to higher optimal elevations.

problem Deciding how high to elevate houses to manage riverine flood risks is complex due to uncertainties.
method Used a multi-objective robust decision-making framework to analyze uncertainties.
result Optimal house elevation can be significantly higher than FEMA's recommendation due to deep uncertainties.