Portfolio optimization, hidden Markov models, and technical analysis of P&F–Charts
نویسنده
چکیده
In this work introduce an adaptive method of portfolio optimization. The basic idea is to describe essential movements of the stock price using a hidden Markov model and to calculate the optimal portfolio using a recursive algorithm. The portfolio optimization is adaptive in the sense that the standard EM–algorithm fits the model to historical data, which improves the portfolio performance.
منابع مشابه
Introducing Busy Customer Portfolio Using Hidden Markov Model
Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...
متن کاملActuarial Inference and Applications of Hidden Markov Models
Hidden Markov models have become a popular tool for modeling long-term investment guarantees. Many different variations of hidden Markov models have been proposed over the past decades for modeling indexes such as the S&P 500, and they capture the tail risk inherent in the market to varying degrees. However, goodness-of-fit testing, such as residual-based testing, for hidden Markov models is a ...
متن کاملA method for portfolio choice
This paper shows how one can use the theory of hidden Markov models for portfolio optimization. We illustrate our method by a ball and urn experiment. An application to historical data is examined.
متن کاملRobustness-based portfolio optimization under epistemic uncertainty
In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...
متن کاملUsing MODEA and MODM with Different Risk Measures for Portfolio Optimization
The purpose of this study is to develop portfolio optimization and assets allocation using our proposed models. The study is based on a non-parametric efficiency analysis tool, namely Data Envelopment Analysis (DEA). Conventional DEA models assume non-negative data for inputs and outputs. However, many of these data take the negative value, therefore we propose the MeanSharp-βRisk (MShβR) model...
متن کامل