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.
Study evaluates sustainability of European banks using a new model.
LemonadeBench evaluates LLMs' economic intuition through a simulated lemonade stand.
Business taxonomies are indispensable tools for investors to do equity research and make professional decisions. However, to identify the structure of industry sectors in an emerging market is challenging for two reasons. First, existing taxonomies are designed for mature markets, which may not be the appropriate class…
Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel m…
ML models predict stock prices poorly during recessions.
We evaluate how modern outlier detection methods perform in identifying outliers in e-commerce conversion rate data. Based on the limitations identified, we then present a novel method to detect outliers in e-commerce conversion rate. This unsupervised method is made more business relevant by letting it automatically a…
Examines international taxation's impact on Georgian businesses.
The aim of process discovery, originating from the area of process mining, is to discover a process model based on business process execution data. A majority of process discovery techniques relies on an event log as an input. An event log is a static source of historical data capturing the execution of a business proc…
Develops a Bayesian model to predict business revenue and demand.
The paper proposes a ML workflow for B2B sales prediction.
CONDA-PM framework helps analyze concept drift in business processes.
GRM uses graph neural networks to score process activity relevance.
Company2Vec creates embeddings from company websites for fine-grained business analytics.
Process mining sheds new light on the relationship between process models and real-life processes. Process discovery can be used to learn process models from event logs. Conformance checking is concerned with quantifying the quality of a business process model in relation to event data that was logged during the execut…
GenéLive! generates rhythm game commands with musical structure.
Large corporate credit models may be adapted for small business risk assessment.
Paper proposes GANs for generating business process suffixes and remaining times.
This study integrates cost-sensitive and causal classification methods.
Business Architecture (BA) plays a significant role in helping organizations understand enterprise structures and processes, and align them with strategic objectives. However, traditional BAs are represented in fixed structure with static model elements and fail to dynamically capture business insights based on interna…
Study evaluates valuation models for UK companies using case studies.
A computational theory reduces agent evaluation errors and speeds up processes.
We introduce a probabilistic model of labor markets for university graduates, in particular, in Japan. To make a model of the market efficiently, we take into account several hypotheses. Namely, each company fixes the (business year independent) number of opening positions for newcomers. The ability of gathering newcom…
Endogenous business cycles explain higher comovement across countries.
Modeling business expansion as a stochastic control problem, the study finds that firms are incentivized to expand but may wait.
Bayesian model uses mobile data to assess business resilience after hurricanes.
A new metric optimizes forecasts for lumpy, intermittent demand.
Probabilistic forecasting, i.e. estimating the probability distribution of a time series' future given its past, is a key enabler for optimizing business processes. In retail businesses, for example, forecasting demand is crucial for having the right inventory available at the right time at the right place. In this pap…
We propose a dynamical model for business cycle based on an optimal DI model. In the model there exists a conserved quantity, which corresponds to the total energy in a dynamical system. We found that the business cycle with the period 6 or 7 years is nicely reproduced, since the model predicts a periodic motion in the…
Understanding large, structured documents like scholarly articles, requests for proposals or business reports is a complex and difficult task. It involves discovering a document's overall purpose and subject(s), understanding the function and meaning of its sections and subsections, and extracting low level entities an…
Development of efficient business process models and determination of their characteristic properties are subject of intense interdisciplinary research. Here, we consider a business process model as a directed graph. Its nodes correspond to the units identified by the modeler and the link direction indicates the causal…
Study examines cyber losses across sectors, finds high severity and frequency.
The general and special repo rates are related with the prices of the European call- and American put-options. The evaluation takes into account specific business models of the parties in the repo agreement and the law restrictions. Using the repo-option relation, an alternative to the Black-Scholes method of option pr…
We aim at developing and improving the imbalanced business risk modeling via jointly using proper evaluation criteria, resampling, cross-validation, classifier regularization, and ensembling techniques. Area Under the Receiver Operating Characteristic Curve (AUC of ROC) is used for model comparison based on 10-fold cro…
Optimizes user marketing campaigns to balance cost and effectiveness.
Paper assesses risks of stablecoins, from lending to business-to-business.
Sales forecasting plays a prominent role in business planning and business strategy. The value and importance of advance information is a cornerstone of planning activity, and a well-set forecast goal can guide sale-force more efficiently. In this paper CPU sales forecasting of Intel Corporation, a multinational semico…
Group Shapley evaluates feature groups in business data, improving explainability in AI.
At the initial stages of this research, the assumption was that the franchised businesses perhaps should not be affected much by recession as there are multiple cash pools available inherent to the franchised business model. However, after analyzing the available data, it indicated otherwise, the stock price performanc…
Study proposes a novel local explanation method for deep learning classifiers in process mining.
Business cycles affect startup valuations, both directly and indirectly.
Machine learning predicts US and EuroZone business cycles with high accuracy.
A microscopic model of aggregation and fragmentation is introduced to investigate the size distribution of businesses. In the model, businesses are constrained to comply with the market price, as expected by the customers, while customers can only buy at the prices offered by the businesses. We show numerically and ana…
We have created a framework for analyzing subscription based businesses in terms of a unified metric which we call SCV (single customer value). The major advance in this paper is to model customer churn as an exponential decay variable, which directly follows from experimental data relating to subscription based busine…
Study shows credit expansion in mortgage markets influenced U.S. business cycle.
New risk theory for 'Pay-for-Performance' models.
Paper proposes transparent insurance models for PBMs.
Facing the FRTB, banks need to allocate their capital to each business units or risk positions to evaluate the capital efficiency of their strategies. This paper proposes two computationally efficient allocation methods which are weighted according to liquidity horizon. Both methods provide more stable and less negativ…
User intended actions are widely seen in many areas. Forecasting these actions and taking proactive measures to optimize business outcome is a crucial step towards sustaining the steady business growth. In this work, we focus on pre- dicting attrition, which is one of typical user intended actions. Conventional attriti…