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 examines how market dynamics affect emissions trading prices and abatement efforts.
Using the Minority Game model we study a broad spectrum of problems of market mechanism. We study the role of different types of agents: producers, speculators as well as noise traders. The central issue here is the information flow : producers feed in the information whereas speculators make it away. How well each age…
We study investment strategy in different models of financial markets, where the investors cannot reach a perfect knowledge about available assets. The investor spends a certain effort to get information; this allows him to better choose the investment strategy, and puts a selective pressure upon assets. The best strat…
Cryptos remained resilient after SVB's collapse, contrary to expectations.
Nowadays, when crashes and crises are rather frequent events, an effective monitoring system for the international financial market is needed. Modern nonlinear methods, such as Recurrence Quantification Analysis (RQA), demonstrate the ability to reveal the regularities of the system behavior. Thus, they can be useful f…
In the last years efforts in econophysics have been shifted to study how network theory can facilitate understanding of complex financial markets. Main part of these efforts is the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financia…
Market Mill is a complex dependence pattern leading to nonlinear correlations and predictability in intraday dynamics of stock prices. The present paper puts together previous efforts to build a dynamical model reflecting the market mill asymmetries. We show that certain properties of the conditional dynamics at a sing…
We document and analyze the empirical facts concerning one of the clearest evidence of speculation in financial trading as observed in the postage collection stamp market. We unravel some of the mechanisms of speculative behavior which emphasize the role of fancy and collective behavior. In our conclusion, we propose a…
Order matching systems form the backbone of modern equity exchanges, used by millions of investors daily. Thus, their operation is strictly controlled through numerous regulatory directives to ensure that markets are fair and transparent. Despite these efforts, market manipulation remains an open problem. In this work,…
Study improves early warning models for currency and stock market crises.
Study uses Open Banking data to estimate customer value, showing potential 21% increase.
We use a control framework to analyze the digital vendor's profit maximization problem. The vendor captures market share by focusing costly effort on post-launch product maintenance, which influences user perception of the product and drives a revenue stream associated with product use. Our theoretical results show nec…
Model predicts sponsorship ROI using renewal probability.
Opponent modeling improves auction market performance.
Ensuring sufficient liquidity is one of the key challenges for designers of prediction markets. Various market making algorithms have been proposed in the literature and deployed in practice, but there has been little effort to evaluate their benefits and disadvantages in a systematic manner. We introduce a novel exper…
Motivated by recent financial crises significant research efforts have been put into studying contagion effects and herding behaviour in financial markets. Much less has been said about influence of financial news on financial markets. We propose a novel measure of collective behaviour in financial news on the Web, New…
Financial global crisis has devastating impacts to economies since early XX century and continues to impose increasing collateral damages for governments, enterprises, and society in general. Up to now, all efforts to obtain efficient methods to predict these events have been disappointing. However, the quest for a rob…
MarS simulates financial markets using generative models.
Loyal buyer-seller relationships can arise by design, e.g. when a seller tailors a product to a specific market niche to accomplish the best possible returns, and buyers respond to the dedicated efforts the seller makes to meet their needs. We ask whether it is possible, instead, for loyalty to arise spontaneously, and…
Framework optimizes battery storage for markets by separating long-term degradation from short-term market dynamics.
Notwithstanding almost forty years of efforts, the market for paintings still lacks a widely accepted price index. In this paper, we introduce a simple and intuitive metric to construct such index. Our metric is based on the price of a painting divided by its area. This formulation rests on a solid mathematical foundat…
The international community was caught by surprise on 5 June 2017 when Saudi Arabia, the United Arab Emirates (UAE), Bahrain and Egypt severed diplomatic ties with Qatar, accusing it of destabilizing the region. More than one year after this diplomatic rift, several questions remain unaddressed. This study focuses on t…
RAGIC predicts stock intervals with risk considerations, improving prediction accuracy and coverage.
New model uses symmetries and scaling laws to predict consumer advertising response.
We propose a continuum model for the description of buyer and seller dynamics in an Internet market. The relevant variables are the research effort of buyers and the sellers' reputation building process. We show that, if a commercial web-site gives consumers the possibility to rate credibly sellers they bargained with,…
A growing body of studies on systemic risk in financial markets has emphasized the key importance of taking into consideration the complex interconnections among financial institutions. Much effort has been put in modeling the contagion dynamics of financial shocks, and to assess the resilience of specific financial ma…
Deep learning predicts customer churn in retail.
This work presents the results of an empirical research with the target of modeling the stylized facts of the daily expost System Marginal Price (SMP) of the Greek wholesale electricity market, using data from January 2004 to December of 2011. SMP is considered here as the footprint of an underline stochastic and nonli…
A spin model relating physical to financial variables is presented. This work is the first to introduce the concept of negative absolute temperature into stock market dynamics by establishing a rigorous formal analogy between physical and financial variables. Based on this model, an algorithm evaluating negative temper…
Economy is demanding new models, able to understand and predict the evolution of markets. To this respect, Econophysics offers models of markets as complex systems, that try to comprehend macro-, system-wide states of the economy from the interaction of many agents at micro-level. One of these models is the gas-like mo…
Survey of EEG market and machine learning applications.
The paper examines how risk reduction and insurance choices interact under convex premium principles.
Develops a new flexible grid trading model using ANN and SSO.
This study enhances sales forecasts by integrating market indicators into forecasting models.
The paper proposes a method to measure fairness through equality of effort using algorithmic recourse.
AI-Trader benchmarks LLMs in live financial markets, revealing poor trading performance.
Method identifies potential customers from limited data.
Review of financial dependencies using econophysics and financial economics.
Deep reinforcement learning improves trading performance in volatile energy markets.
Deep RL for portfolio management shows poor robustness.
We provide direct evidence of market manipulation at the beginning of the financial crisis in November 2007. The type of manipulation, a "bear raid," would have been prevented by a regulation that was repealed by the Securities and Exchange Commission in July 2007. The regulation, the uptick rule, was designed to preve…
Framework detects tipping points in complex systems using ML.
Paper models uncertainty in electricity and gas markets to assess its impact.
This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in trade time. We show that wh…
Study reveals widespread manipulation of meme coins, leading to significant economic losses.
Proposes an end-to-end deep learning framework for active investing.
This paper surveys RL methods for quantitative trading.
IndexGAN predicts stock trends using GAN with expert knowledge and news context.