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.
The paper optimizes DIA purchase policies using lifecycle models and asset allocation.
A framework combining HSMM and survival analysis for lifecycle-oriented mobility analysis.
The results of data mining endeavors are majorly driven by data quality. Throughout these deployments, serious show-stopper problems are still unresolved, such as: data collection ambiguities, data imbalance, hidden biases in data, the lack of domain information, and data incompleteness. This paper is based on the prem…
A dynamic model of the product lifecycle of (nearly) homogeneous durables in polypoly markets is established. It describes the concurrent evolution of the unit sales and price of durable goods. The theory is based on the idea that the sales dynamics is determined by a meeting process of demanded with supplied product u…
We present the "Annotation and Benchmarking on Understanding and Transparency of Machine Learning Lifecycles" (ABOUT ML) project as an initiative to operationalize ML transparency and work towards a standard ML documentation practice. We make the case for the project's relevance and effectiveness in consolidating dispa…
A new microeconomic model is presented that aims at a description of the long-term unit sales and price evolution of homogeneous non-durable goods in polypoly markets. It merges the product lifecycle approach with the price dispersion dynamics of homogeneous goods. The model predicts a minimum critical lifetime of non-…
Machine learning has evolved into an enabling technology for a wide range of highly successful applications. The potential for this success to continue and accelerate has placed machine learning (ML) at the top of research, economic and political agendas. Such unprecedented interest is fuelled by a vision of ML applica…
Improving software quality through effective organizational learning.
Homeownership boosts wealth and welfare compared to renting, according to new research.
RED-2400 is a public benchmark of trading events from a Solana exchange, labeled by algorithmic rejection.
We extend the lifecycle model (LCM) of consumption over a random horizon (a.k.a. the Yaari model) to a world in which (i.) the force of mortality obeys a diffusion process as opposed to being deterministic, and (ii.) a consumer can adapt their consumption strategy to new information about their mortality rate (a.k.a. h…
Focuses on monitoring and explaining models in real-world applications.
A new indicator measures project risk from activity durations.
The process of exploring and exploiting Oil and Gas (O&G) generates a lot of data that can bring more efficiency to the industry. The opportunities for using data mining techniques in the "digital oil-field" remain largely unexplored or uncharted. With the high rate of data expansion, companies are scrambling to develo…
The paper audits trading filters, finding a high save-to-miss ratio.
This paper advances theory on the process of collaboration between entities and its implications on the quality of services, information, and/or products (SIPs) that the collaborating entities provide to each other. It investigates the scenario of outsourced IS projects (such as custom software development) where the e…
Based on interviews with 28 organizations, we found that industry practitioners are not equipped with tactical and strategic tools to protect, detect and respond to attacks on their Machine Learning (ML) systems. We leverage the insights from the interviews and we enumerate the gaps in perspective in securing machine l…
SaML guides ML models to avoid survey biases.
Three methods detect informed trading on prediction markets, each focusing on different aspects.
STAD adapts models to evolving time-based data shifts.
Deployment of machine learning (ML) algorithms in production for extended periods of time has uncovered new challenges such as monitoring and management of real-time prediction quality of a model in the absence of labels. However, such tracking is imperative to prevent catastrophic business outcomes resulting from inco…
PredictionMarketBench benchmarks trading agents on prediction markets.
This study examines non-retail trading on Polymarket, revealing unique behavior patterns and structural limitations.
New attacks improve privacy audits by analyzing model updates.
In a large E-commerce platform, all the participants compete for impressions under the allocation mechanism of the platform. Existing methods mainly focus on the short-term return based on the current observations instead of the long-term return. In this paper, we formally establish the lifecycle model for products, by…
Machine Learning is transitioning from an art and science into a technology available to every developer. In the near future, every application on every platform will incorporate trained models to encode data-based decisions that would be impossible for developers to author. This presents a significant engineering chal…
In life-cycle economics the Samuelson paradigm (Samuelson, 1969) states that the optimal investment is in constant proportions out of lifetime wealth composed of current savings and the present value of future income. It is well known that in the presence of credit constraints this paradigm no longer applies. Instead, …
We solve a lifecycle model in which the consumer's chronological age does not move in lockstep with calendar time. Instead, biological age increases at a stochastic non-linear rate in time like a broken clock that might occasionally move backwards. In other words, biological age could actually decline. Our paper is ins…
Systematic review of ML models for detecting social media deception.
This work introduces a bias-variance decomposition for proper scores, improving uncertainty estimation in predictive models.
Geometric stability predicts steerability and detects drift in language models.
Foundation models alter medical data science workflow, challenging veridical data science principles.
The paper tackles model failure detection and refitting in real-world systems.
The paper proposes a method to identify fair features in ML data integration.
Simplifying machine learning (ML) application development, including distributed computation, programming interface, resource management, model selection, etc, has attracted intensive interests recently. These research efforts have significantly improved the efficiency and the degree of automation of developing ML mode…
The importance of incorporating ethics and legal compliance into machine-assisted decision-making is broadly recognized. Further, several lines of recent work have argued that critical opportunities for improving data quality and representativeness, controlling for bias, and allowing humans to oversee and impact comput…
In recent times, machine learning (ML) and artificial intelligence (AI) based systems have evolved and scaled across different industries such as finance, retail, insurance, energy utilities, etc. Among other things, they have been used to predict patterns of customer behavior, to generate pricing models, and to predic…
The Australian Government uses the means-test as a way of managing the pension budget. Changes in Age Pension policy impose difficulties in retirement modelling due to policy risk, but any major changes tend to be `grandfathered' meaning that current retirees are exempt from the new changes. In 2015, two important chan…
Blockchain helps secure payments between AI agents.
Study finds consumers are more price-sensitive before livestreams than after.
Study identifies NFT whales driving the market with consistent high returns.
Large language models struggle with causal relationships, leading to biases and hallucinations.
This study categorizes RWA tokenization challenges and solutions.
Unified framework explains retirement and annuitization decisions under age-dependent mortality.
ReSkill reconciles RL skill creation with policy optimization.
Stablecoins offer efficient settlement but externalize costs and risks.
Polymarket-v1 Database tracks 1.2B trades across 1.3M markets with 100% ground-truth direction.
The paper introduces BCART models for aggregate claim amount, improving frequency-severity and joint modeling.