arXiv · arXiv q-fin · 2021
We introduce three adaptive time series learning methods, called Dynamic Model Selection (DMS), Adaptive Ensemble (AE), and Dynamic Asset Allocation (DAA). The methods respectively handle model selection, ensembling, and contextual evaluation in financial time series. Empirically, we use the methods to forecast the returns of four key indices in the US market, incorporating information from the VIX and Yield curves. …
Parley Ruogu Yang, Ryan Lucas
arXiv · arXiv q-fin · 2026
We introduce a structural framework for the geometry of financial order books in which liquidity, supply, and demand are treated as emergent observables rather than primitive market variables. The market is modeled as a relational substrate without assumed metric, temporal, or price coordinates. Observable quantities arise only through observation, implemented here as a reduction of relational degrees of freedom foll…
João P. da Cruz
arXiv · arXiv q-fin · 2026
We propose a structural framework for the geometry of financial order books in which liquidity, supply, and demand are treated as emergent observables rather than primitive economic variables. The market is modeled as an inflationary relational system without assumed metric, temporal, or price coordinates. Observable quantities arise only through projection, implemented here via spectral embeddings of the graph Lapla…
João P. da Cruz
arXiv · arXiv q-fin · 2013
We give a detailed account of correlations between credit sector/quality and treasury curve factors, using the robust framework of the Barclays POINT Global Risk Model. Consistent with earlier studies, we find a strong negative correlation between sector spreads and rate shifts. However, we also observe that the correlations between spreads and Treasury twists reversed recently, which is likely attributable to the Fe…
Arthur M. Berd, Elena Ranguelova, Antonio Baldaque da Silva
arXiv · arXiv q-fin · 2024
This project is a collaboration between industry and academia to delve into Finance Social Networks, specifically the Board of Directors of public companies. Knowing the connections between Directors and Executives in different companies can generate powerful stories and meaningful insights on investments. A proof of concept in the form of a Data Visualization tool reveals its strength in investigating corporate gove…
Alice Da Fonseca, Peter Lake, Ariana Barrenechea
arXiv · arXiv q-fin · 2023
Risk budgeting is a portfolio strategy where each asset contributes a prespecified amount to the aggregate risk of the portfolio. In this work, we propose an efficient numerical framework that uses only simulations of returns for estimating risk budgeting portfolios. Besides a general cutting planes algorithm for determining the weights of risk budgeting portfolios for arbitrary coherent distortion risk measures, we …
Bernardo Freitas Paulo da Costa, Silvana M. Pesenti, Rodrigo S. Targino
arXiv · arXiv q-fin · 2023
Anomaly detection is a challenging task, particularly in systems with many variables. Anomalies are outliers that statistically differ from the analyzed data and can arise from rare events, malfunctions, or system misuse. This study investigated the ability to detect anomalies in global financial markets through Graph Neural Networks (GNN) considering an uncertainty scenario measured by a nonextensive entropy. The ma…
Kleyton da Costa
arXiv · arXiv q-fin · 2022
We investigate the financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize the individuals in a financial market by their trading strategy, namely noise traders and fundamentalists. The opinion of a local majority compels the market exchanging behavior of noise traders, whereas the global behavior of the market influences the fundamentalist agents' decis…
Mateus F. B. Granha, André L. M. Vilela, Chao Wang, Kenric P. Nelson, H. Eugene Stanley
arXiv · arXiv q-fin · 2022
In this paper is proposed a 2 factor structural PDE model of pricing puttable bond with credit risk and derived the analytical pricing formula. To this end, first, a 2 factor structural (PDE) model of pricing zero coupon bond with credit risk is provided, the analytical pricing formula is derived under some conditions for default boundary and default recovery, and the strict monotonicity of the bond price function wi…
Hyong Chol O, Dae Song Choe, Gyong-Dok Rim
arXiv · arXiv q-fin · 2021
The feasibility of making profitable trades on a single asset on stock exchanges based on patterns identification has long attracted researchers. Reinforcement Learning (RL) and Natural Language Processing have gained notoriety in these single-asset trading tasks, but only a few works have explored their combination. Moreover, some issues are still not addressed, such as extracting market sentiment momentum through t…
Francisco Caio Lima Paiva, Leonardo Kanashiro Felizardo, Reinaldo Augusto da Costa Bianchi, Anna Helena Reali Costa
arXiv · arXiv q-fin · 2020
We consider the viability of a modularised mechanistic online machine learning framework to learn signals in low-frequency financial time series data. The framework is proved on daily sampled closing time-series data from JSE equity markets. The input patterns are vectors of pre-processed sequences of daily, weekly and monthly or quarterly sampled feature changes. The data processing is split into a batch processed s…
Joel da Costa, Tim Gebbie
arXiv · arXiv q-fin · 2019
We propose a three-state microscopic opinion formation model for the purpose of simulating the dynamics of financial markets. In order to mimic the heterogeneous composition of the mass of investors in a market, the agent-based model considers two different types of traders: noise traders and contrarians. Agents are represented as nodes in a network of interactions and they can assume any of three distinct possible s…
Bernardo J. Zubillaga, André L. M. Vilela, Chao Wang, Kenric P. Nelson, H. Eugene Stanley
arXiv · arXiv q-fin · 2016
The performance of trend following strategies can be ascribed to the difference between long-term and short-term realized variance. We revisit this general result and show that it holds for various definitions of trend strategies. This explains the positive convexity of the aggregate performance of Commodity Trading Advisors (CTAs) which -- when adequately measured -- turns out to be much stronger than anticipated. W…
Tung-Lam Dao, Trung-Tu Nguyen, Cyril Deremble, Yves Lempérière, Jean-Philippe Bouchaud
arXiv · arXiv q-fin · 2015
We run experimental asset markets to investigate the emergence of excess trading and the occurrence of synchronised trading activity leading to crashes in the artificial markets. The market environment favours early investment in the risky asset and no posterior trading, i.e. a buy-and-hold strategy with a most probable return of over 600%. We observe that subjects trade too much, and due to the market impact that we…
Joao da Gama Batista, Domenico Massaro, Jean-Philippe Bouchaud, Damien Challet, Cars Hommes
arXiv · arXiv q-fin · 2015
The financial market is a complex dynamical system composed of a large variety of intricate relationships between several entities, such as banks, corporations and institutions. At the heart of the system lies the stock exchange mechanism, which establishes a time-evolving network of trades among companies and individuals. Such network can be inferred through correlations between time series of companies stock prices…
Filipi N. Silva, Cesar H. Comin, Thomas K. DM. Peron, Francisco A. Rodrigues, Cheng Ye
arXiv · arXiv q-fin · 2014
The aim of this work is to introduce a new stochastic volatility model for equity derivatives. To overcome some of the well-known problems of the Heston model, and more generally of the affine models, we define a new specification for the dynamics of the stock and its volatility. Within this framework we develop all the key elements to perform the pricing of vanilla European options as well as of volatility derivativ…
José Da Fonseca, Claude Martini
arXiv · arXiv q-fin · 2014
Using available data from the New York stock market (NYSM) we test four different bi-parametric models to fit the correspondent volume-price distributions at each $10$-minute lag: the Gamma distribution, the inverse Gamma distribution, the Weibull distribution and the log-normal distribution. The volume-price data, which measures market capitalization, appears to follow a specific statistical pattern, other than the …
Paulo Rocha, Frank Raischel, João P. da Cruz, Pedro G. Lind