Time series analysis for financial market meltdowns
نویسندگان
چکیده
منابع مشابه
a time-series analysis of the demand for life insurance in iran
با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند
Machine learning algorithms for time series in financial markets
This research is related to the usefulness of different machine learning methods in forecasting time series on financial markets. The main issue in this field is that economic managers and scientific society are still longing for more accurate forecasting algorithms. Fulfilling this request leads to an increase in forecasting quality and, therefore, more profitability and efficiency. In this pa...
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The need to assess subtle, potentially exploitable changes in serial structure is paramount in the analysis of financial data. Herein, we demonstrate the utility of approximate entropy (ApEn), a model-independent measure of sequential irregularity, toward this goal, by several distinct applications. We consider both empirical data and models, including composite indices (Standard and Poor's 500...
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We discuss the theoretical machinery involved in predicting financial market movements using an artificial market model which has been trained on real financial data. This approach to market prediction in particular, forecasting financial time-series by training a third-party or ‘black box’ game on the financial data itself – was discussed by Johnson et al. in [10] and [13] and was based on som...
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We discuss the theoretical machinery involved in predicting financial market movements using an artificial market model which has been trained on real financial data. This approach to market prediction in particular, forecasting financial time-series by training a third-party or ‘black box’ game on the financial data itself – was discussed by Johnson et al. 13 and was based on some encouraging ...
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ژورنال
عنوان ژورنال: Journal of Banking & Finance
سال: 2011
ISSN: 0378-4266
DOI: 10.1016/j.jbankfin.2010.12.007