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.
Method detects multi-timescale consumer spending patterns from receipts.
Study uses EEG and ML to predict movie ratings with 72% accuracy.
Study uses Bayesian regression to analyze consumer behavior changes in restaurants post-COVID-19.
Consumer Demand Response (DR) is an important research and industry problem, which seeks to categorize, predict and modify consumer's energy consumption. Unfortunately, traditional clustering methods have resulted in many hundreds of clusters, with a given consumer often associated with several clusters, making it diff…
Paper uses GANs to simulate consumer transactions with SKU constraints.
This paper takes a deep learning approach to understand consumer credit risk when e-commerce platforms issue unsecured credit to finance customers' purchase. The "NeuCredit" model can capture both serial dependences in multi-dimensional time series data when event frequencies in each dimension differ. It also captures …
This study examines how fashion consumption affects self-confidence and buying behavior in Iranian consumers.
In economics literature, it is accepted that all people are rational and they try to maximize their utilities as possible as they can. In addition, economic theories are formed with the assumptions not suitable to real life. For instance, indifference curves are drawn with the assumptions that there are two goods, peop…
Study on self-consuming generative models with diverse human curation, focusing on convergence and stability.
Study evaluates clustering methods for Google Trends data.
New model uses symmetries and scaling laws to predict consumer advertising response.
Current auto loans converge to super-prime credit despite remaining underwater.
We study the effects of introducing information inefficiency in a model for a random linear economy with a representative consumer. This is done by considering statistical, instead of classical, economic general equilibria. Employing two different approaches we show that inefficiency increases the consumption set of a …
Social interactions and personal tastes shape our consumption behavior of cultural products. In this study, we present a computational model of a cultural market and we aim to analyze the behavior of the consumer population as an emergent phenomena. Our results suggest that the final market shares of cultural products …
There are few papers about the consumption pattern of the Portuguese wine, using econometrics techniques. This work, pretend to analyze the consumers behavior of the wine produced in Portugal, determining the demand equation with panel data methods. There were used statistical data available in the Alentejo Regional Wi…
Understanding consumption dynamics and its impact on the whole economy and welfare within the present economic crisis is not an easy task. Indeed the level of consumer demand for different goods varies with the prices, consumer incomes and demographic factors. Furthermore crisis may trigger different behaviors which re…
Study improves retail demand forecasting by integrating macroeconomic data.
We study here numerically the behavior of an ideal gas like model of markets having only one non-consumable commodity. We investigate the behavior of the steady-state distributions of money, commodity and total wealth, as the dynamics of trading or exchange of money and commodity proceeds, with local (in time) fluctuat…
This paper presents a case study of a recommender system that can be used to save energy in smart homes without lowering the comfort of the inhabitants. We present an algorithm that uses consumer behavior data only and uses machine learning to suggest actions for inhabitants to reduce the energy consumption of their ho…
Proof-of-Stake networks with EIP-1559 exhibit stable token prices and secure network security.
PsychFM predicts individual gambling choices using psychological and machine learning models.
We present a Bayesian framework for estimating the customer lifetime value (CLV) and the customer equity (CE) based on the purchasing behavior deducible from the market surveys on customer purchasing behavior. The proposed framework systematically addresses the challenges faced when the future value of customers is est…
In this paper, we study the assortment optimization problem faced by many online retailers such as Amazon. We develop a \emph{cascade multinomial logit model}, based on the classic multinomial logit model, to capture the consumers' purchasing behavior across multiple stages. Different from existing studies, our model a…
In the last decade, the digital age has sharply redefined the way we study human behavior. With the advancement of data storage and sensing technologies, electronic records now encompass a diverse spectrum of human activity, ranging from location data, phone and email communication to Twitter activity and open-source c…
This study compares logistic regression and XGBoost for predicting credit risk.
Active learning recovers choice model from noisy data.
Recommenders personalize the web content by typically using collaborative filtering to relate users (or items) based on explicit feedback, e.g., ratings. The difficulty of collecting this feedback has recently motivated to consider implicit feedback (e.g., item consumption along with the corresponding time). In this pa…
Model shows PoS networks can be captured by external finance, leading to centralization.
LISBET automates social behavior analysis using machine learning.
This paper introduces TDA and TSI for better business analytics.
Paper predicts recycling bin full events to reduce RVM downtime.
Robinhood users react strongly to overnight price changes and big losers, trading quickly after extreme losses.
Paper characterizes MDM for consumer choice modeling and prediction.
Private equity deals predict public market returns with up to 70% accuracy.
A text mining approach is proposed based on latent Dirichlet allocation (LDA) to analyze the Consumer Financial Protection Bureau (CFPB) consumer complaints. The proposed approach aims to extract latent topics in the CFPB complaint narratives, and explores their associated trends over time. The time trends will then be…
Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis can be highly time consuming. In motor control studies, humans or other …
The study optimizes free trial lengths to boost subscriptions and consumer loyalty.
Study predicts purchasing decisions of online food delivery customers.
A simple model economy with locally interacting producers and consumers is introduced. When driven by extremal dynamics, the model self-organizes {\em not} to an attractor state, but to an asymptote, on which the economy has a constant rate of deflation, is critical, and exhibits avalanches of activity with power-law d…
Analyzes new economic paradigm for non-independent consumer choices.
This paper presents two cases of random banking data generators based on migration matrices and scoring rules. The banking data generator is a new hope in researches of finding the proving method of comparisons of various credit scoring techniques. There is analyzed the influence of one cyclic macro--economic variable …
We determine the optimal amount to invest in a Black-Scholes financial market for an individual who consumes at a rate equal to a constant proportion of her wealth and who wishes to minimize the expected time that her wealth spends in drawdown during her lifetime. Drawdown occurs when wealth is less than some fixed pro…
Detects systematic anomalies in consumer complaints using NLP.
Paper presents a novel time series clustering algorithm for financial inclusion.
New algorithm reduces regret in dynamic assortment selection.
Study finds consumers are more price-sensitive before livestreams than after.
A new ride-hailing subsidy system uses deep causal networks to estimate consumer elasticity.
Most e-commerce product feeds provide blended results of advertised products and recommended products to consumers. The underlying advertising and recommendation platforms share similar if not exactly the same set of candidate products. Consumers' behaviors on the advertised results constitute part of the recommendatio…