Quantitative Risk Management in R

Starting at USD 39.00
5 hours duration

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.

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DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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