Business and Economics
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Quantitative Risk Management (QRM) involves the development of models to assess the risks associated with financial portfolios, a crucial task within the banking, insurance, and asset management sectors. The initial phase of the model building process entails gathering data on the underlying risk factors that impact portfolio value and conducting a thorough analysis of their behavior. This course will equip you with the skills necessary to effectively handle risk-factor return series, examine the empirical characteristics, commonly referred to as stylized facts, of this data, such as their tendency to deviate from normality and exhibit volatility. Additionally, you will learn how to estimate the value-at-risk for a given portfolio.
by DataCamp
Work with risk-factor return series, study their empirical properties, and make estimates of value-a...
by DataCamp
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Pytho...
by DataCamp
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how t...
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Learn to use Python for financial analysis using basic skills, including lists, data visualization,...
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Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest...
by DataCamp
Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.
by DataCamp
Advance you R finance skills to backtest, analyze, and optimize financial portfolios.