1 - 5 of 5 articles
In the last two decades, the hedge fund sector has experienced a spectacular growth, up to the point that it is currently estimated to move more than 50% of the daily volume of stock markets. In contrast to other financial institutions, hedge funds are subject to less restrictive regulations...
Previous studies have found that one of the main challenges in the area of time-series analysis is the lack of ability to reveal the hidden profiles of observed dynamic systems. Therefore, this study applies an adaptive clustering method named the Localized Trend Model to extract and group...
In this paper we propose stochastic time series prediction by autoregressive Hidden Markov Models (AR-HMM). The model parameter estimation, hence the prediction, is carried out by Markov chain Monte Carlo (MCMC) sampling instead of finding a single maximum likelihood model. Estimating the whole...
In the present study, a deterministic model is introduced to explain the stylized facts of financial data. The adaptation introduced by the labyrinth chaos model can reproduce phenomena such as heavy tails observed in financial returns, volatility clustering and jumps. The model is based on the...
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Sign Up Log In
To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don’t already have one.
To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don’t already have one.