?????? (Deep Credit Risk) - ??Python?????? (häftad)

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Format: Häftad (Paperback / softback)
Språk: Kinesiska
Antal sidor: 456
Utgivningsdatum: 2021-07-23
Förlag: Deep Credit Risk
Medarbetare: Rsch, Daniel
Illustrationer: Black & white illustrations
Dimensioner: 235 x 190 x 23 mm
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Antal komponenter: 1
Komponenter: 3:B&W 7.5 x 9.25 in or 235 x 191 mm Perfect Bound on White w/Gloss Lam
ISBN: 9780645245202

?????? (Deep Credit Risk) - ??Python??????

av Harald Scheule, Daniel Roesch

Häftad, Kinesiska, 2021-07-23

872

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- COVID-19

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- Logit;

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- CECLIFRS 9CCAR

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- 1500...

- Understand the role of liquidity, equity and many other key banking features

- Engineer and select features

- Predict defaults, payoffs, loss rates and exposures

- Predict downturn and crisis outcomes using pre-crisis features

- Understand the implications of COVID-19

- Apply innovative sampling techniques for model training and validation

- Deep-learn from Logit Classifiers to Random Forests and Neural Networks

- Do unsupervised Clustering, Principal Components and Bayesian Techniques

- Build multi-period models for CECL, IFRS 9 and CCAR

- Build credit portfolio correlation models for VaR and Expected Shortfal

- Run over 1,500 lines of pandas, statsmodels and scikit-learn Python code

- Access real credit data and much more ...

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