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Results for “GAN” · papers 18 · wiki 7
Academic Papers · 18arXiv q-fin live 8 · desk corpus 42
arXiv · arXiv q-fin · 2023

Market-GAN: Adding Control to Financial Market Data Generation with Semantic Context

Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financial market simulation methodologies, existing frameworks often struggle with adapting to specialized simulation context. We pinpoint the challenges as i) current financial datasets do not contain context labels; ii) current techniques are no

Haochong Xia, Shuo Sun, Xinrun Wang, Bo An
arXiv · arXiv q-fin · 2022

Autoencoding Conditional GAN for Portfolio Allocation Diversification

Over the decades, the Markowitz framework has been used extensively in portfolio analysis though it puts too much emphasis on the analysis of the market uncertainty rather than on the trend prediction. While generative adversarial network (GAN) and conditional GAN (CGAN) have been explored to generate financial time series and extract features that can help portfolio analysis. The limitation of the CGAN framework sta

Jun Lu, Shao Yi
arXiv · arXiv q-fin · 2022

A Hybrid Approach on Conditional GAN for Portfolio Analysis

Over the decades, the Markowitz framework has been used extensively in portfolio analysis though it puts too much emphasis on the analysis of the market uncertainty rather than on the trend prediction. While generative adversarial network (GAN), conditional GAN (CGAN), and autoencoding CGAN (ACGAN) have been explored to generate financial time series and extract features that can help portfolio analysis. The limitati

Jun Lu, Danny Ding
arXiv · arXiv q-fin · 2019

Quant GANs: Deep Generation of Financial Time Series

Modeling financial time series by stochastic processes is a challenging task and a central area of research in financial mathematics. As an alternative, we introduce Quant GANs, a data-driven model which is inspired by the recent success of generative adversarial networks (GANs). Quant GANs consist of a generator and discriminator function, which utilize temporal convolutional networks (TCNs) and thereby achieve to c

Magnus Wiese, Robert Knobloch, Ralf Korn, Peter Kretschmer
arXiv · arXiv · 2010

Testing the Capital Asset Pricing Model (CAPM) on the Uganda Stock Exchange

This paper examines the validity of the Capital Asset Pricing Model (CAPM) on the Ugandan stock market using monthly stock returns from 10 of the 11 companies listed on the Uganda Stock Exchange (USE), for the period 1st March 2007 to 10th November 2009. Due to the absence of readily available Uganda Stock Exchange(USE) data, and the placement of daily price lists in pdf only, on the USE website: http://www.use.or.ug

David Wakyiku
arXiv · arXiv · 2025

Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation

Financial bond yield forecasting is challenging due to data scarcity, nonlinear macroeconomic dependencies, and evolving market conditions. In this paper, we propose a novel framework that leverages Causal Generative Adversarial Networks (CausalGANs) and Soft Actor-Critic (SAC) reinforcement learning (RL) to generate high-fidelity synthetic bond yield data for four major bond categories (AAA, BAA, US10Y, Junk). By in

Jaskaran Singh Walia, Aarush Sinha, Naman Saraswat, Srinitish Srinivasan, Srihari Unnikrishnan
arXiv · arXiv · 2013

Polish and Silesian Non-Profit Organizations Liquidity Strategies

The kind of realized mission inflows the sensitivity to risk. Among other factors, the risk results from decision about liquid assets investment level and liquid assets financing. The higher the risk exposure, the higher the level of liquid assets. If the specific risk exposure is smaller, the more aggressive could be the net liquid assets strategy. The organization choosing between various solutions in liquid assets

Grzegorz Michalski, Aleksander Mercik
arXiv · arXiv · 2021

Self-organised criticality in high frequency finance: the case of flash crashes

With the rise of computing and artificial intelligence, advanced modeling and forecasting has been applied to High Frequency markets. A crucial element of solid production modeling though relies on the investigation of data distributions and how they relate to modeling assumptions. In this work we investigate volume distributions during anomalous price events and show how their tail exponents < 2 indicate a diverging

Jeremy D. Turiel, Tomaso Aste
arXiv · arXiv · 2026

Recovering Structural Organization in Noisy Correlation Networks Using Financial Systems as a Testbed

Empirical correlation matrices estimated from financial return time series are contaminated by statistical noise arising from finite sample size, obscuring genuine interactions among assets. We apply spectral decomposition to separate the empirical correlation matrix into a structured component associated with eigenvalues exceeding the Marchenko-Pastur bounds and a random component representing statistical noise. Usi

Imran Ansari, Shashi Jain, Srikanth K. Iyer
arXiv · arXiv · 2026

A Geometry-Aware Residual Correction of Hagan's SABR Implied Volatility Formula

This paper proposes a hybrid methodology to improve the approximation of SABR (Stochastic Alpha Beta Rho) implied volatility by combining analytical structure with machine learning. The approach augments the neural-network input representation with geometric features derived from the stochastic differential equations of the SABR model. Unlike approaches that fully replace analytical formulas with black-box models, th

Adil Reghai, Lama Tarsissi, Gérard Biau, Alex Lipton
arXiv · arXiv · 2025

Modeling for the Growth of Unorganized Retailing in the Presence of Organized and E-Retailing in Indian Pharmaceutical Industry

The present study considers the rural pharmaceutical retail sector in India, where the arrival of organized retailers and e-retailers is testing the survival strategies of unorganized retailers. Grounded in a field investigation of the Indian pharmaceutical retail sector, this study integrates primary data collection, consumer conjoint analysis and design of experiments to develop an empirically grounded agent-based

Koushik Mondal, Balagopal G Menon, Sunil Sahadev
arXiv · arXiv · 2022

Barcelona in the face of globalization, how to think of the city through the organization and evaluation of major events?

The event questions men whether it is political, cultural or touristic. It has its own meaning as it starts something while showing a will, a new possibility to create, to meet and to surprise. The event is in fact an "advent that reaches everything" generally integrating itself into a long process or phase of the evolution of societies in terms of its societal structure. However, if the event exists, it is significa

Patrice Ballester
arXiv · arXiv · 2022

Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets

This study proposes a new generative adversarial network (GAN) for generating realistic orders in financial markets. In some previous works, GANs for financial markets generated fake orders in continuous spaces because of GAN architectures' learning limitations. However, in reality, the orders are discrete, such as order prices, which has minimum order price unit, or order types. Thus, we change the generation method

Masanori Hirano, Hiroki Sakaji, Kiyoshi Izumi
arXiv · arXiv · 2012

Cross comparison and modelling of Goldman Sachs, Morgan Stanley, JPMorgan Chase, Bank of America, and Franklin Resources

We have studied statistical characteristics of five share price time series. For each stock price, we estimated a best fit quantitative model for the monthly closing price as based on the decomposition into two defining consumer price indices selected from a large set of CPIs. It was found that there are two pairs of similar models (Bank of America/Morgan Stanley and Goldman Sachs/JPMorgan Chase) with a standalone mo

Ivan Kitov
arXiv · arXiv · 2012

Triadic motifs and dyadic self-organization in the World Trade Network

In self-organizing networks, topology and dynamics coevolve in a continuous feedback, without exogenous driving. The World Trade Network (WTN) is one of the few empirically well documented examples of self-organizing networks: its topology strongly depends on the GDP of world countries, which in turn depends on the structure of trade. Therefore, understanding which are the key topological properties of the WTN that d

Tiziano Squartini, Diego Garlaschelli
arXiv · arXiv · 2010

Fairness Is an Emergent Self-Organized Property of the Free Market for Labor

The excessive compensation packages of CEOs of U.S. corporations in recent years have brought to the foreground the issue of fairness in economics. The conventional wisdom is that the free market for labor, which determines the pay packages, cares only about efficiency and not fairness. We present an alternative theory that shows that an ideal free market environment also promotes fairness, as an emergent property re

Venkat Venkatasubramanian
arXiv · arXiv · 2009

Trading leads to scale-free self-organization

Financial markets display scale-free behavior in many different aspects. The power-law behavior of part of the distribution of individual wealth has been recognized by Pareto as early as the nineteenth century. Heavy-tailed and scale-free behavior of the distribution of returns of different financial assets have been confirmed in a series of works. The existence of a Pareto-like distribution of the wealth of market p

M. Ebert, W. Paul
arXiv · arXiv · 2009

La Loi organique relative aux lois de finances (LOLF) dans les institutions culturelles publiques du spectacle vivant en France

In a crisis of public finances, France bases all its hopes on the "evaluation of performance" to moderate the effects of a complex crisis. Under the banner of "modernization of the State", a new "financial constitution" called the Organic Law on finance laws (LOLF) became the main lever of reform of public management. Fully applied to the Cultural Affairs since 2006, the LOLF is based on a set of performance indicato

Ammar Kessab
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