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…
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48 results for “ad exchanges”
Regional Inequality Simulations Based on Asset Exchange Models with Exchange Range and Local Support Biasphysics.soc-ph
New models reduce regional inequality by adjusting exchange range and asset distribution bias.
problem Reduction of regional inequality in economic systems.
method Proposed new asset exchange models with spatial exchange range and local support bias to adjust asset distribution and circulation rates.
result Achieved asset distribution from over-concentration to exponential and eventually normal, reducing Gini coefficient.
This paper investigates the impact of dark pools on price discovery (the efficiency of prices on stock exchanges to aggregate information). Assets are traded in either an exchange or a dark pool, with the dark pool offering better prices but lower execution rates. Informed traders receive noisy and heterogeneous signal…
Kinetic exchange models have been successful in explaining the shape of the income/wealth distribution in the economies. However, such models usually make some ad-hoc assumptions when it comes to determining the savings factor. Here, we examine a few models in and out of the domain of standard neo-classical economics t…
Many popular network models rely on the assumption of (vertex) exchangeability, in which the distribution of the graph is invariant to relabelings of the vertices. However, the Aldous-Hoover theorem guarantees that these graphs are dense or empty with probability one, whereas many real-world graphs are sparse. We prese…
Ad exchanges use CORP to set reserve prices against strategic buyers.
problem Setting optimal reserve prices in ad exchanges with strategic buyers.
method Proposes CORP policy to learn and set reserve prices robustly.
result Achieves sublinear regret in unknown noise distribution.
We introduce a formal framework for analyzing trades in financial markets. An exchange is where multiple buyers and sellers participate to trade. These days, all big exchanges use computer algorithms that implement double sided auctions to match buy and sell requests and these algorithms must abide by certain regulator…
New neural processes use stacked Markov operators to improve flexibility.
problem Improving flexibility in neural processes.
method Stacking neural parameterized Markov transition operators in function space.
result MNPs outperform baseline models on various tasks.
Machine learning and deep learning infer surface/groundwater exchange from temperature data.
problem Inferring surface/groundwater exchange from temperature data with high temporal resolution.
method Application of machine learning and deep learning algorithms to infer surface/groundwater exchange flux from subsurface temperature observations.
result DL methods outperform ML methods in interpreting noisy temperature data, especially with a smoothing filter.
Monotone adversarial corruptions degrade optimal learning algorithms.
problem Optimal learning algorithms' reliance on exchangeability and independence is challenged.
method Introduces a monotone adversarial corruption model where an adversary adds monotone corruptions to a clean dataset.
result Optimal learning algorithms achieve suboptimal expected error on new test points.
Paper proposes a new algorithm combining gradient descent and Langevin dynamics.
problem Gradient descent can get stuck in local minima, while Langevin dynamics can explore but is slow.
method Replica exchange mechanism swaps positions if Langevin yields a lower objective function.
result New algorithm converges to global minimum linearly with high probability.
Formally verifies fairness and uniformity in financial market trades.
problem Ensuring fairness and uniformity in automated trading systems.
method Formal definition and verification in Coq proof assistant.
result Properties of double-sided auction mechanisms verified.
Stochastic Maps, Wealth Distribution in Random Asset Exchange Models and the Marginal Utility of Relative Wealthcond-mat.stat-mech
We look at how asset exchange models can be mapped to random iterated function systems (IFS) giving new insights into the dynamics of wealth accumulation in such models. In particular, we focus on the "yard-sale" (winner gets a random fraction of the poorer players wealth) and the "theft-and-fraud" (winner gets a rando…
The problem of market clearing is to set a price for an item such that quantity demanded equals quantity supplied. In this work, we cast the problem of predicting clearing prices into a learning framework and use the resulting models to perform revenue optimization in auctions and markets with contextual information. T…
New L0 norm added to TDA for market analysis.
problem Improving TDA tools for market prediction.
method Defined and applied L0 norm in TDA for four markets.
result Enhanced TDA tools for market analysis.
Optimizes reserve prices for first-price auctions to maximize revenue.
problem Optimizing reserve prices for first-price auctions in display advertising.
method Gradient-based algorithm to adaptively update and optimize reserve prices based on bidder responsiveness to experimental shocks.
result Revenue optimization in first-price auctions can be decomposed into demand and bidding components, and techniques are introduced to reduce variance of each.
A Python approach minimizes risk in decentralized exchanges.
problem Minimizing risk in decentralized exchanges.
method Three-step approach: Kernel Ridge Regression, function minimization, and algorithmic trick.
result Reduced computational load and increased solution accuracy.
Heterogeneity of economic agents is emphasized in a new trend of macroeconomics. Accordingly the new emerging discipline requires one to replace the production function, one of key ideas in the conventional economics, by an alternative which can take an explicit account of distribution of firms' production activities. …
T-duality acts on circle bundles by exchanging the first Chern class with the fiberwise integral of the H-flux, as we motivate using E_8 and also using S-duality. We present known and new examples including NS5-branes, nilmanifolds, Lens spaces, both circle bundles over RP^n, and the AdS^5 x S^5 to AdS^5 x CP^2 x S^1 w…
This study analyzes factors affecting China's stock market volatility.
problem Investigating factors influencing China's stock market volatility.
method Used ARDL model and principal component analysis on daily data from 2010-2024.
result Exchange rate and bond yields significantly impact stock market volatility.
We examine the relationship between trading volumes, number of transactions, and volatility using daily stock data of the Tokyo Stock Exchange. Following the mixture of distributions hypothesis, we use trading volumes and the number of transactions as proxy for the rate of information arrivals affecting stock volatilit…
NAC-FL optimizes model updates in FL systems by adapting compression to network congestion.
problem Federated Learning systems face congestion and delays in data exchanges.
method NAC-FL dynamically adjusts client compression based on network congestion.
result NAC-FL reduces training time and achieves robust performance improvements.
We consider an ad hoc network where multiple users access the same set of channels. The channel characteristics are unknown and could be different for each user (heterogeneous). No controller is available to coordinate channel selections by the users, and if multiple users select the same channel, they collide and none…
Efficient method defends privacy in federated learning without accuracy loss.
problem Privacy attacks on federated learning by reconstructing and identifying local data.
method Random noise perturbation method that allows recovery of true gradients.
result Strong privacy protection without sacrificing learning accuracy.
A new model adds stochastic spot/volatility correlation to Heston model for better exotic pricing.
problem Improving exotic option pricing in foreign exchange markets.
method Developed a Double Heston model with stochastic spot/volatility correlation, an affine model.
result The new model increases prices of out-of-the-money knockout options and one touch options.
The paper studies how adding an ℓ2 penalty affects network embeddings.
problem The impact of ℓ2 regularization on network embeddings.
method Analyzes the asymptotic behavior of ℓ2 regularized node2vec embeddings under graphon theory.
result The learned embeddings asymptotically form a graphon with a nuclear-norm-type penalty.
A scalable protocol for federated averaging with privacy and correctness guarantees.
problem Privacy and correctness in federated learning from multiple parties.
method Scalable protocol using correlated and independent Gaussian noise, analyzed for differential privacy and graph topology.
result Nearly matches trusted curator model's utility with minimal communication.
Deep network optimizes ad bidding for first-price auctions.
problem Optimizing bid prices for first-price auctions in online advertising.
method Introduced a deep distribution network for optimal bidding.
result Algorithm outperforms previous methods in terms of surplus and eCPX metrics.
Predicting click and conversion probabilities when bidding on ad exchanges is at the core of the programmatic advertising industry. Two separated lines of previous works respectively address i) the prediction of user conversion probability and ii) the attribution of these conversions to advertising events (such as clic…
The exchange algorithm is studied for its convergence and asymptotic variance.
problem Theoretical limitations of the exchange algorithm in sampling from doubly-intractable distributions.
method Theoretical analysis of the exchange algorithm's convergence speed and asymptotic variance.
result The exchange algorithm converges at a geometric rate and satisfies a Central Limit Theorem.
Study on pricing American Exchange options using Lévy processes.
problem Pricing American Exchange options driven by Lévy processes.
method Represented American Exchange options as European options plus early exercise premium; studied properties of free boundary and provided an approximative formula.
result Developed an approximative formula for American Exchange options.
Optimal crypto order execution using cross-exchange signals.
problem Maximizing order execution efficiency in cryptocurrency markets.
method Reinforcement learning applied to cross-exchange data.
result Cross-exchange signals improve optimal execution outcomes.
Study exchange option pricing with stochastic volatility and correlation.
problem Pricing exchange options under stochastic volatility and correlation.
method Approximation using a closed-form solution with Taylor expansion.
result Numerical results show the effectiveness of the proposed method.
A recent trend observed in traditionally challenging fields such as computer vision and natural language processing has been the significant performance gains shown by deep learning (DL). In many different research fields, DL models have been evolving rapidly and become ubiquitous. Despite researchers' excitement, unfo…
A known failing of many popular random graph models is that the Aldous-Hoover Theorem guarantees these graphs are dense with probability one; that is, the number of edges grows quadratically with the number of nodes. This behavior is considered unrealistic in observed graphs. We define a notion of edge exchangeability …
Wealth Distributions in Asset Exchange Modelsphysics.soc-ph
How do individuals accumulate wealth as they interact economically? We outline the consequences of a simple microscopic model in which repeated pairwise exchanges of assets between individuals build the wealth distribution of a population. This distribution is determined for generic exchange rules --- transactions that…
The team predicts foreign exchange rates using clustering and attention models.
problem Complexity and unexpected events in foreign exchange markets.
method Clustering and attention models applied to historical data.
result Improved event-driven price prediction for oversold scenarios.
Wealth Distributions in Models of Capital Exchangecond-mat.stat-mech
A dynamical model of capital exchange is introduced in which a specified amount of capital is exchanged between two individuals when they meet. The resulting time dependent wealth distributions are determined for a variety of exchange rules. For ``greedy'' exchange, an interaction between a rich and a poor individual r…
Study finds recurring patterns in cryptocurrency volatility and liquidity.
problem Recurring patterns in volatility and liquidity of major cryptocurrencies.
method Data from two centralized exchanges and a decentralized exchange analyzed for patterns.
result Systematic patterns in volatility and liquidity across different timeframes.
Representation of Exchange Option Prices under Stochastic Volatility Jump-Diffusion Dynamicsq-fin.MF
The article provides representations of exchange option prices under SVJD dynamics.
problem Modeling and pricing exchange options under stochastic volatility and jumps.
method Develops representations for European and American exchange options using SVJD dynamics and equivalent martingale measures.
result Derives integro-partial differential equations and representations for exchange option prices.
This paper introduces cluster exchange groupoids for Coxeter-Dynkin diagrams and finds their fundamental groups are braid groups.
problem Understanding the fundamental groups of cluster exchange groupoids for Coxeter-Dynkin diagrams.
method Introduced cluster exchange groupoids for Coxeter-Dynkin diagrams and showed the fundamental group isomorphic to braid groups.
result The fundamental group of the exchange groupoid for a Coxeter-Dynkin diagram is the braid group associated with the diagram.
Kalman Filter in the Problem of the Exchange and the Inflation Rates Adequacy To Determining Factorsq-fin.MF
Study finds relevance of exchange and inflation rates to economic factors.
problem Determining the relevance of exchange and inflation rates to economic factors.
method Introduced concept of adequacy, established positive relation between exchange and inflation rates and other economic factors.
result Close positive relation found between exchange and inflation rates and other economic factors.
The article improves the display of acceptable exchange ratios for merging companies.
problem Determining feasible exchange ratios for merging companies.
method Exploits a diagrammatic approach to display the bargaining region.
result Shares face upper and lower bounds for acceptable exchange ratios.
Framework for systemic risk modeling using jointly exchangeable arrays.
problem Systemic risk in insurance portfolios with interactions.
method Jointly exchangeable arrays, central limit theorems, simulation-based validation.
result Asymptotic approximations for total portfolio losses in large portfolios over long time horizons.
Framework handles both exchangeable and non-exchangeable event sequences without tuning.
problem Handling both exchangeable and non-exchangeable event sequences efficiently.
method Parametric Hawkes-process-inspired conditional probability mass function with variational inference.
result Competitive computational and predictive performance against state-of-the-art methods.
Unified framework for representation and causal structure learning using exchangeable data.
problem Identifying latent representations or causal structures in non-i.i.d. data.
method Identifiable Exchangeable Mechanisms (IEM) framework for representation and structure learning.
result New insights and identifiability results for causal structure and representation learning.
IUS framework predicts EUR/USD exchange rate with improved accuracy.
problem Accurate forecasting of EUR/USD exchange rate.
method Combines large language models for sentiment analysis, deep learning for forecasting, and feature selection.
result Optuna-optimized Bi-LSTM model reduces MAE and RMSE by 10.69% and 9.56% respectively.
The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Featurescs.LG
Nonparametric Bayesian models are often based on the assumption that the objects being modeled are exchangeable. While appropriate in some applications (e.g., bag-of-words models for documents), exchangeability is sometimes assumed simply for computational reasons; non-exchangeable models might be a better choice for a…