Bond Valuation and Analysis in R

Starting at USD 39.00
4 hours duration

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Upon completion of this quantitative finance course with R, participants will gain the skills necessary to effectively utilize R in developing models for valuing fixed interest rate bonds. Additionally, they will acquire the ability to estimate and analyze a bond's yield, which serves as a crucial measure of the opportunity cost for bond investors. Furthermore, participants will learn various modeling techniques that can be employed to safeguard bond portfolios against fluctuations in interest rates. Understanding the importance of valuing bonds is essential due to their significance as securities issued by governments or corporations. These securities provide regular interest payments according to a predetermined schedule and are widely recognized as the most prominent type of fixed income securities. In fact, the US fixed income market surpasses the US stock market by 1.5 times in terms of size. However, unlike stocks, fixed income instruments, including bonds, are traded infrequently. Consequently, relying solely on a bond's price as an indicator of its value may prove unreliable. Therefore, the utilization of analytical techniques becomes imperative when analyzing and valuing bonds.

About Provider

DataCamp
DataCamp
Online Education Provider ยท 410 courses
Description
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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