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.
Model infers mineral locations from geospatial data, improving predictions with auxiliary data.
Model shows how centralization occurs in cryptocurrency mining.
Game theory shows miners' hardware improvements don't centralize mining.
A new sequencing rule prevents miners from front-running transactions in decentralized exchanges.
The paper analyzes how mutable blockchain protocols affect miner behavior and strategic stability.
Extends PoS proof-of-stake transaction fee mechanism with miner utility model.
Dark blockchain venues increase miners' profits but raise users' execution risk.
Study analyzes market co-movements in critical mineral investments using change point detection and cross-sectional analysis.
Visual Human Activity Recognition (HAR) and data fusion with other sensors can help us at tracking the behavior and activity of underground miners with little obstruction. Existing models, such as Single Shot Detector (SSD), trained on the Common Objects in Context (COCO) dataset is used in this paper to detect the cur…
Distributed securities exchanges may become de facto fragmented if they span geographical regions with asymmetric computer infrastructure. First, we build an economic model of a decentralized exchange with two miner clusters, standing in for compact areas of economic activity (e.g., cities). "Local" miners in the area …
Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This pa…
We investigate the structure of global inter-firm linkages using a dataset that contains information on business partners for about 400,000 firms worldwide, including all the firms listed on the major stock exchanges. Among the firms, we examine three networks, which are based on customer-supplier, licensee-licensor, a…
Dual random fields improve mineral potential predictions.
Defines cost of MEV and shows its relevance in various settings.
CICLAD efficiently mines frequent closed itemsets from data streams with minimal memory usage.
Style Miner generates stable and significant style factors for time series analysis.
Study on wealth and trading in PoS blockchain.
Ethereum tackles bribery in blockchain transactions with new fee mechanism.
A new algorithm discovers causal factors between T2DM and bone mineral density.
New methods evaluate stock market anomalies for prospect investors.
DisCoveR efficiently discovers declarative process models from event logs.
Quantum Proof-of-Work uses boson sampling to secure blockchain consensus.
Prospective learning improves AI performance in changing conditions.
This paper introduces a simple and efficient density estimator that enables fast systematic search. To show its advantage over commonly used kernel density estimator, we apply it to outlying aspects mining. Outlying aspects mining discovers feature subsets (or subspaces) that describe how a query stand out from a given…
Prospect theory is widely viewed as the best available descriptive model of how people evaluate risk in experimental settings. According to prospect theory, people are risk-averse with respect to gains and risk-seeking with respect to losses, a phenomenon called "loss aversion". Despite of the fact that prospect theory…
Develops a new learning framework for dynamic data.
Retrospective and prospective analysis of Diebold-Yilmaz connectedness research.
We explain the main concepts of Prospect Theory and Cumulative Prospect Theory within the framework of rational dynamic asset pricing theory. We derive option pricing formulas when asset returns are altered with a generalized Prospect Theory value function or a modified Prelec weighting probability function and introdu…
In this paper we build a method to optimize Multi-Year Prospective Budgets. First we present a systemic model of Local Community Finances. Then, from two acceptable Multi-Year Prospective Budgets the method implements a Genetic Algorithm to generate a collection of admissible Multi-Year Prospective Budgets among which …
We study optimal investment problems under the framework of cumulative prospect theory (CPT). A CPT investor makes investment decisions in a single-period financial market with transaction costs. The objective is to seek the optimal investment strategy that maximizes the prospect value of the investor's final wealth. W…
Most cryptocurrencies rely on Proof-of-Work (PoW) "mining" for resistance to Sybil and double-spending attacks, as well as a mechanism for currency issuance. Hashcash PoW has successfully secured the Bitcoin network since its inception, however, as the network has expanded to take on additional value storage and transa…
A microeconomic approach is proposed to derive the fluctuations of risky asset price, where the market participants are modeled as prospect trading agents. As asset price is generated by the temporary equilibrium between demand and supply, the agents' trading behaviors can affect the price process in turn, which is cal…
This paper analyzes the profitability of selfish mining on blockchain, considering the risk of ruin.
In discrete time markets with proportional transaction costs, Schachermayer (2004) shows that robust no-arbitrage is equivalent to the existence of a strictly consistent price system. In this paper, we introduce the concept of prospective strict no-arbitrage that is a variant of the strict no-arbitrage property from Ka…
Research analyzes ethical concerns around MEV on blockchain and social media.
New method extends supervised learning for non-stationary control problems.
In this article, inspired by Shi, et al. we investigate the optimal portfolio selection with one risk-free asset and one risky asset in a multiple period setting under cumulative prospect theory (CPT). Compared with their study, our novelty is that we consider a stochastic benchmark, and portfolio constraints. We test …
The study compares parametric and nonparametric models for estimating mean-variance mixtures and finds that nonparametric models perform better.
Optimizes portfolios using CPT utility via convex optimization.
Matching Markets meet Cumulative Prospect Theory: Towards Optimal and Adversarially Robust Learning
Life insurance cash flows become reserve dependent when contract conditions are modified during the contract term on condition that actuarial equivalence is maintained. As a result, insurance cash flows and prospective reserves depend on each other in a circular way, and it is a non-trivial problem to solve that circul…
TabSODA improves imputation of surveys with skips and ordinal data.
The prospects of Kahneman and Tversky, Mega Million and Powerball lotteries, St. Petersburg paradox, premature profits and growing losses criticized by Livermore are reviewed under an angle of view comparing mathematical expectations with awards received. Original prospects have been formulated as a one time opportunit…
Study derives new equation for reserves in non-monotone information scenarios.
Prospective display advertising poses a great challenge for large advertising platforms as the strongest predictive signals of users are not eligible to be used in the conversion prediction systems. To that end efforts are made to collect as much information as possible about each user from various data sources and to …
FedAMD framework improves federated learning with partial client participation.
Decision maker's preferences are often captured by some choice functions which are used to rank prospects. In this paper, we consider ambiguity in choice functions over a multi-attribute prospect space. Our main result is a robust preference model where the optimal decision is based on the worst-case choice function fr…
Machine learning methods have found many applications in Raman spectroscopy, especially for the identification of chemical species. However, almost all of these methods require non-trivial preprocessing such as baseline correction and/or PCA as an essential step. Here we describe our unified solution for the identifica…