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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.

168,695 papers · 148 categories

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2457 · Feb 202019922001200920172026
48 results for coupon campaign

Study uses causal machine learning to assess coupon campaign impact on retailer sales.

problem Assessing the causal effect of a coupon campaign on retailer sales.
method Causal machine learning algorithms, subgroup analysis, optimal policy learning.
result Only two coupon categories (drugstore and other food) have a significant positive impact on sales.

We consider the problem of identifying current coupons for Agency backed To-be-Announced (TBA) Mortgage Backed Securities. In a doubly stochastic factor based model which allows for prepayment intensities to depend upon current and origination mortgage rates, as well as underlying investment factors, we identify the cu…

2015-10-07abs ↗pdf ↗

HapNet predicts marketing campaign effects using a hierarchical structure.

problem Complex and challenging effect prediction for marketing campaigns.
method Hierarchical Capsule Prediction Network (HapNet).
result HapNet outperforms state-of-the-art methods in both synthetic and real data.

Pricing formulae for defaultable corporate bonds with discrete coupons under consideration of the government taxes in the united model of structural and reduced form models are provided. The aim of this paper is to generalize the comprehensive structural model for defaultable fixed income bonds (considered in [1]) into…

2013-09-06abs ↗pdf ↗

In the UK betting market, bookmakers often offer a free coupon to new customers. These free coupons allow the customer to place extra bets, at lower risk, in combination with the usual betting odds. We are interested in whether a customer can exploit these free coupons in order to make a sure gain, and if so, how the c…

2019-01-07abs ↗pdf ↗

Paper analyzes pricing model for bonds with early redemption.

problem Analyzing pricing of bonds with early redemption features.
method Structural approach for mathematical modeling of bond prices.
result Existence and uniqueness of default and early redemption boundaries proved.

Study uses VIX for zero-coupon Treasury rates, proving long-term stability and returns.

problem Modeling zero-coupon Treasury rates with VIX for volatility.
method Multivariate autoregressive stochastic volatility model, proving stability and Law of Large Numbers.
result VIX accurately models zero-coupon Treasury rates and returns.

We introduce a bond portfolio management theory based on foundations similar to those of stock portfolio management. A general continuous-time zero-coupon market is considered. The problem of optimal portfolios of zero-coupon bonds is solved for general utility functions, under a condition of no-arbitrage in the zero-c…

2003-01-24abs ↗pdf ↗

Real-Time Bidding is nowadays one of the most promising systems in the online advertising ecosystem. In the presented study, the performance of RTB campaigns is improved by optimising the parameters of the users' profiles and the publishers' websites. Most studies about optimising RTB campaigns are focused on the biddi…

2019-10-29abs ↗pdf ↗

This paper enhances uplift modeling for multi-treatment marketing campaigns.

problem Optimizing marketing strategies by selecting individuals likely to respond to different treatments.
method Leveraging score ranking and calibration techniques.
result Improves overall performance of marketing campaigns.

Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control systems and machinery, these adversarial errors could grow to be a serious problem. Despite numerous studies over the past few years, the field of…

2019-11-19abs ↗pdf ↗

The paper tackles the issue of preferential attachment in targeted display advertising by developing domain-adaptation approaches.

problem Skewed distribution of data leads to preferential attachment towards high-budget partners.
method Develops domain-adaptation approaches to predict interested users for low-budget partners.
result Proposed approaches outperform other domain-adaptation methods across different points of campaigns.

Real time bidding (RTB) enables demand side platforms (bidders) to scale ad campaigns across multiple publishers affiliated to an RTB ad exchange. While driving multiple campaigns for mobile app install ads via RTB, the bidder typically has to: (i) maintain each campaign's efficiency (i.e., meet advertiser's target cos…

2018-11-11abs ↗pdf ↗

Study optimizes classifiers for credit card mail campaigns and default prediction.

problem Optimizing classifiers for credit card mail campaigns and default prediction.
method Three distinct models: response, risk, and response-risk. Optimized various performance metrics.
result Random Forest classifier achieves highest accuracy (83.2%) in multi-class response-risk model.

This paper optimizes ad bids and daily budgets for multiple campaigns in pay-per-click advertising.

problem Optimizing ad bids and daily budgets for multiple campaigns in pay-per-click advertising.
method Formulated as a combinatorial semi-bandit problem, solved using Gaussian Processes and four algorithms.
result Regret upper bounded as O(sqrt{T}), where T is the time horizon.

Study analyzes factors influencing healthcare providers' engagement with SMS campaigns.

problem Understanding what drives healthcare providers to engage with SMS campaigns.
method Used logistic regression, random forest, and neural network models to analyze data.
result Identified key factors influencing engagement with SMS campaigns.

We derive a closed-form formula for computing bond prices between coupon payments. Our results cover both the `Treasury' and the `Street' pricing methods used by sovereign and corporate issuers. We apply our formulas to two UK gilts, the 8% Treasury Gilt 2015, and the 0.5% Treasury Gilt 2022, and show that we can obtai…

2018-01-18abs ↗pdf ↗

In this paper we show how to hedge a zero coupon bond with a smaller amount of initial capital than required by the classical risk neutral paradigm, whose (trivial) hedging strategy does not suggest to invest in the risky assets. Long dated zero coupon bonds we derive, invest first primarily in risky securities and whe…

2016-08-16abs ↗pdf ↗

The paper tackles budget allocation for multiple campaigns using a novel combinatorial bandit approach.

problem Maximizing cumulative returns with limited budgets across various ad lines.
method Formulated as a multi-task combinatorial bandit problem, integrates Bayesian hierarchical models, and uses Thompson sampling.
result Demonstrates robustness and adaptability in maximizing overall cumulative returns.

PolicySynth improves synthetic data alignment with real data for better campaign decisions.

problem Synthetic data used in decision support systems often leads to incorrect decisions.
method PolicySynth framework that conditions synthetic data on churn scorer to align with real data decisions.
result PolicySynth achieves high strategy simulation fidelity (0.923-0.960) on churn and acquisition datasets.

Paper proposes an analytical pricing model for puttable bonds with credit risk.

problem Analytical pricing of puttable bonds with credit risk.
method Developed a 2-factor structural PDE model and derived analytical pricing formula under specific conditions.
result Derived analytical pricing formula for puttable bonds with credit risk.

Paper addresses CPA line forecasting in online advertising mid-flight.

problem Forecasting ad campaign performance mid-flight considering bidding mechanisms.
method Generates relationships between metrics and optimization signals, estimates sensitivity, and characterizes advertiser spends vs. eCPA.
result Demonstrates promising accuracy in forecasting against actual deliveries.

The aim of this paper is to present a dual-term structure model of interest rate derivatives in order to solve the two hardest problems in financial modeling: the exact volatility calibration of the entire swaption matrix, and the calculation of bucket vegas for structured products. The model takes a series of long-ter…

2016-06-04abs ↗pdf ↗

Optimizes user marketing campaigns to balance cost and effectiveness.

problem Lack of methods to optimize marketing campaigns considering cost and effectiveness.
method Proposes a treatment effect optimization algorithm using deep learning to balance cost and effectiveness.
result Demonstrates superior performance in cost-efficiency and real-world business value.

The study uses machine learning to predict CAT bond coupons based on climate data.

problem Predicting CAT bond coupons using climate data.
method Combining climate indicators with machine learning models (random forest, gradient boosting, etc.).
result Extremely randomized trees achieved the lowest RMSE in predicting CAT bond coupons.

The paper tackles decision making problems with funnel structure in email marketing campaigns.

problem Decision making challenges in systems with funnel structure, where fewer observations are received from deeper layers.
method Formulated as a contextual bandit with funnel structure and developed a multi-task learning algorithm.
result Our algorithms offer significant improvement over previous methods in email marketing campaigns.

This paper addresses the problem of inferring a regular expression from a given set of strings that resembles, as closely as possible, the regular expression that a human expert would have written to identify the language. This is motivated by our goal of automating the task of postmasters of an email service who use r…

2012-06-18abs ↗pdf ↗

Chagas disease is a neglected disease, and information about its geographical spread is very scarse. We analyze here mobility and calling patterns in order to identify potential risk zones for the disease, by using public health information and mobile phone records. Geolocalized call records are rich in social and mobi…

2018-08-09abs ↗pdf ↗

Uplift models provide a solution to the problem of isolating the marketing effect of a campaign. For customer churn reduction, uplift models are used to identify the customers who are likely to respond positively to a retention activity only if targeted, and to avoid wasting resources on customers that are very likely …

2019-11-28abs ↗pdf ↗

Study uses time series analysis to predict player churn and conversion in games.

problem Predicting player churn and conversion in free-to-play games.
method State Space time series approach with Autoregressive Integrated Moving Average and Unobserved Components models.
result Unobserved Components approach fails to detect marketing campaigns and predicts abandonment poorly.

Study optimal bidding strategies for digital ads targeting purchases and health campaigns.

problem Optimizing advertising strategies in digital channels.
method Continuous-time models encoding user behavior and auction mechanisms, semi-explicit formulas for optimal bidding.
result Semi-explicit formulas for optimal value and bidding policy for different types of advertising.