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environment. These ML systems provide realistic support for financial decision-making and risk management in the face of …
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We give explicit algorithms and source code for extracting factors underlying Treasury yields using (unsupervised) machine learning (ML) techniques, such as nonnegative matrix factorization (NMF) and (statistically deterministic) clustering. NMF is a popular ML algorithm (used in computer...
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of the yield curve factor model by analyzing the Bootstrap, DNS, AFNS model of yield curve. Then based on the factor … construction, construct the yield curve factor. In order to make the interest rate forecast, constructed 182 features and mined the … features affecting the yield curves from multiple dimensions. Then used the traditional statistical models and machine learning …
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Corporate misconduct is a huge and widespread problem in the economy. Many companies make mistakes that result in them having to pay penalties or compensation to other businesses. Some of these cases are so serious that they take a toll on a company’s financial condition. The purpose of this...
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finance in real world context. These computational techniques are particularly useful in financial risk management, corporate … bankruptcy prediction, stock price prediction and portfolio management. The book also offers practical and managerial … use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio …
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