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regimes and stock prices. In this paper, we introduce the application ofHMMin trading stocks (with S&P 500 index being an … example) based on the stock price predictions. The procedure starts by using four criteria, including the Akaike information … determine an optimal number of states for the HMM. The selected four-state HMM is then used to predict monthly closing prices of …
Persistent link: https://www.econbiz.de/10011883487
Hidden Markov model (HMM) is a powerful machine-learning method for data regime detection, especially time series data. In this paper, we establish a multi-step procedure for using HMM to select stocks from the global stock market. First, the five important factors of a stock are identified and...
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This paper examines the main drawbacks of technical analysis. Although this is widely used by practitioners, from an academic perspective it can only be seen as a form of "voodoo finance". In particular, it runs into the following pitfalls: Subjectivity; Doubtful assumptions; Unjustified...
Persistent link: https://www.econbiz.de/10013489574
The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...
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