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.
Bounds on long-term returns of leveraged ETFs are given.
This study was conducted to find an appropriate statistical model to forecast the volatilities of PSEi using the model Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Using the R software, the log returns of PSEi is modeled using various ARIMA models and with the presence of heteroskedasticity, the l…
Study optimal portfolio choice with risk control for log-returns.
XGBoost predicts NEPSE Index log returns with low error and high directional accuracy.
This paper is intended as an investigation of the statistical properties of {\it absolute log-returns}, defined as the absolute value of the logarithmic price change, for the Nikkei 225 index in the 28-year period from January 4, 1975 to December 30, 2002. We divided the time series of the Nikkei 225 index into two per…
In an efficient stock market, the log-returns and their time-dependent variances are often jointly modelled by stochastic volatility models (SVMs). Many SVMs assume that errors in log-return and latent volatility process are uncorrelated, which is unrealistic. It turns out that if a non-zero correlation is included in …
Model approximates market prices and returns without prior market dynamics.
Bayesian inference and superstatistics model financial volatility dynamics across different timescales.
The S&P500 daily values and log-returns fail to conform to Benford's laws, revealing underlying trends.
Study compares Bitcoin, gold, and gas price complexity using multifractal and multiscale entropy methods.
A3T-GCN model forecasts FTSE100 stock prices using technical indicators and financial ratios.
The paper examines non-Gaussian models for financial data.
This paper forecasts cryptocurrency log-returns using LASSO-VAR and sentiment analysis.
We introduce performance-based regularization (PBR), a new approach to addressing estimation risk in data-driven optimization, to mean-CVaR portfolio optimization. We assume the available log-return data is iid, and detail the approach for two cases: nonparametric and parametric (the log-return distribution belongs in …
The dynamics of a stock market with heterogeneous agents is discussed in the framework of a recently proposed spin model for the emergence of bubbles and crashes. We relate the log returns of stock prices to magnetization in the model and find that it is closely related to trading volume as observed in real markets. Th…
Improved Hawkes model forecasts extreme financial returns more accurately.
Extends option pricing model to incorporate market factor dynamics.
Continuous time random walks (CTRWs) are used in physics to model anomalous diffusion, by incorporating a random waiting time between particle jumps. In finance, the particle jumps are log-returns and the waiting times measure delay between transactions. These two random variables (log-return and waiting time) are typi…
This paper outlines an agent-based model of a simple financial market in which a single asset is available for trade by three different types of traders. The model was first introduced in the PhD thesis of one of the authors, see reference [1]. The simulated log returns are examined for the presence of the stylised fac…
Proposes a simple algorithm to generate data similar to real series.
Optimizes portfolios with costs, showing existence of optimal strategies.
The paper solves a portfolio selection problem in incomplete markets by balancing utility and risk.
In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumptio…
The three-state agent-based 2D model of financial markets in the version proposed by Giulia Iori in 2002 has been herein extended. We have introduced the increase of herding behaviour by modelling the altering trust of an agent in his nearest neighbours. The trust increases if the neighbour has foreseen the price chang…
This paper clarifies Bitcoin's volatility and predictability across daily, weekly, and monthly scales.
Generative model simulates financial market price variations from order flow.
Detects jumps in financial asset prices with U-shape volatility.
We show that in a large class of stochastic volatility models with additional skew-functions (local-stochastic volatility models) the tails of the cumulative distribution of the log-returns behave as exp(-c|y|), where c is a positive constant depending on time and on model parameters. We obtain this estimate proving a …
Stylized facts of empirical assets log-returns include the existence of (semi) heavy tailed distributions and a non-linear spectrum of Hurst exponents . Empirical data considered are daily prices of 10 large indices from 01/01/1990 to 12/31/2004. We propose a stylized model of price dynamics which is…
We present an empirical study of the subordination hypothesis for a stochastic time series of a stock price. The fluctuating rate of trading is identified with the stochastic variance of the stock price, as in the continuous-time random walk (CTRW) framework. The probability distribution of the stock price changes (log…
The paper assesses dimensionality reduction for cryptocurrency link prediction.
In this paper, we are interested in continuous time models in which the index level induces some feedback on the dynamics of its composing stocks. More precisely, we propose a model in which the log-returns of each stock may be decomposed into a systemic part proportional to the log-returns of the index plus an idiosyn…
HFformer outperforms LSTM in high-frequency trading with multiple signals.
In this study we suggest a portfolio selection framework based on option-implied information and multivariate non-Gaussian models. The proposed models incorporate skewness, kurtosis and more complex dependence structures among stocks log-returns than the simple correlation matrix. The two models considered are a multiv…
Two new models for volatility in Markov-switching environments capture financial time-series properties.
Suppose that are continuous semimartingales that are reversible and have nondegenerate crossings. Then the corresponding rank processes can be represented by generalized Stratonovich integrals, and this representation can be used to decompose the relative log-return of portfolios generated by functi…
Study measures irreversibility in crypto trends using Kullback-Leibler divergence.
Model captures asymmetric extreme events in financial returns.
In this paper we analyse the structure of Warsaw's stock market using complex systems methodology together with network science and information theory. We find minimal spanning trees for log returns on Warsaw's stock exchange for yearly times series between 2000 and 2013. For each stock in those trees we calculate its …
Develops a novel framework for pricing variance swaps in multi-asset stochastic volatility models.
Fractal analysis is carried out on the stock market indices of seven European countries and the US. We find evidence of long range dependence in the log return series of the Mibtel (Italy) and the PX Glob (Czech Republic). Long range dependence implies that predictable patterns in the log returns do not dissipate quick…
Analyzes first exit times in a modified Barndorff-Nielsen and Shephard model.
Generative model prices options and extracts risk-neutral densities.
Study examines USD exchange rate dynamics using Kramers-Moyal expansion.
A growing body of literature suggests that heavy tailed distributions represent an adequate model for the observations of log returns of stocks. Motivated by these findings, here we develop a discrete time framework for pricing of European options. Probability density functions of log returns for different periods are …
The paper models financial returns data with measurement error.
Investment strategy using fractional Kelly portfolios for better growth expectations.
The COS method for European options pricing is improved with a new bound for the number of terms.