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Results for “pyramid” · papers 8 · wiki 2
Academic Papers · 8arXiv q-fin live 8 · desk corpus 3
arXiv · arXiv q-fin · 2025

PyFi: Toward Pyramid-like Financial Image Understanding for VLMs via Adversarial Agents

This paper proposes PyFi, a novel framework for pyramid-like financial image understanding that enables vision language models (VLMs) to reason through question chains in a progressive, simple-to-complex manner. At the core of PyFi is PyFi-600K, a dataset comprising 600K financial question-answer pairs organized into a reasoning pyramid: questions at the base require only basic perception, while those toward the apex

Yuqun Zhang, Yuxuan Zhao, Sijia Chen
arXiv · arXiv q-fin · 2021

Pyramid scheme in stock market: a kind of financial market simulation

Artificial stock market simulation based on agent is an important means to study financial market. Based on the assumption that the investors are composed of a main fund, small trend and contrarian investors characterized by four parameters, we simulate and research a kind of financial phenomenon with the characteristics of pyramid schemes. Our simulation results and theoretical analysis reveal the relationships betw

Yong Shi, Bo Li, Guangle Du
arXiv · arXiv q-fin · 2025

Multilayer Perceptron Neural Network Models in Asset Pricing: An Empirical Study on Large-Cap US Stocks

In this study, MLP models with dynamic structure are applied to factor models for asset pricing tasks. Concretely, the MLP pyramid model structure was employed on firm characteristic-sorted portfolio factors for modelling the large-cap US stocks. It was further developed as a practical factor investing strategy based on the predictions. The main findings were evaluated from 2 angles: model predictive power and backte

Shanyan Lai
arXiv · arXiv q-fin · 2023

Stock Trend Prediction: A Semantic Segmentation Approach

Market financial forecasting is a trending area in deep learning. Deep learning models are capable of tackling the classic challenges in stock market data, such as its extremely complicated dynamics as well as long-term temporal correlation. To capture the temporal relationship among these time series, recurrent neural networks are employed. However, it is difficult for recurrent models to learn to keep track of long

Shima Nabiee, Nader Bagherzadeh
arXiv · arXiv q-fin · 2015

Population viewpoint on Hawkes processes

This paper focuses on a class of linear Hawkes processes with general immigrants. These are counting processes with shot noise intensity, including self-excited and externally excited patterns. For such processes, we introduce the concept of age pyramid which evolves according to immigration and births. The virtue if this approach that combines an intensity process definition and a branching representation is that th

Alexandre Boumezoued
arXiv · arXiv q-fin · 2010

S&P 500 returns revisited

The predictions of the S&P 500 returns made in 2007 have been tested and the underlying models amended. The period between 2003 and 2008 should be described by the dependence of the S&P 500 stock market index on real GDP because the population pyramid was highly inaccurate. The 2008 trough and 2009 rally are well predicted by the original model, however. The rally will end in March/April 2010 and the S&P 500 level wi

Ivan O. Kitov, Oleg I. Kitov
arXiv · arXiv q-fin · 2008

Economic law of increase of Kolmogorov complexity. Transition from financial crisis 2008 to the zero-order phase transition (social explosion)

In Maslov (2003), a two level model of the occurrence of financial pyramid (bubbles) has been considered. We also considered the mathematical analogy of this model to Bose condensation. In the present paper, we explain why Ponzi schemes and bubbles result in a crisis in real economics. In Maslov (2005), the law of increase of entropy in financial systems, and consequently increase of Kolmogorov complexity, is formula

V. P. Maslov
arXiv · arXiv q-fin · 2007

Estimating the Fractal Dimension of the S&P 500 Index using Wavelet Analysis

S&P 500 index data sampled at one-minute intervals over the course of 11.5 years (January 1989- May 2000) is analyzed, and in particular the Hurst parameter over segments of stationarity (the time period over which the Hurst parameter is almost constant) is estimated. An asymptotically unbiased and efficient estimator using the log-scale spectrum is employed. The estimator is asymptotically Gaussian and the variance

Erhan Bayraktar, H. Vincent Poor, Ronnie Sircar
Wiki Entities · 2
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