I. Structure:
Module 9-4 is the basic knowledge (quantitative analysis, product knowledge acquisition and valuation method). Only by mastering this knowledge can we enter the remaining risk management modules (market risk, credit risk, operational risk, investment management and current hot topics in financial markets).
For example, applying VaR to estimate the market risk of bonds (market risk management module) will use the basic knowledge of market risk (module 1), normal distribution (module 2) and bond valuation and sensitivity analysis (modules 3 and 4).
Don't spend too much time on some topics, which will affect your study plan. For example, quantitative analysis belongs to the basic knowledge part, but you don't have to master all the exam contents to learn other parts. All you have to master is normal distribution and confidence interval, and regression analysis is also necessary for follow-up study.
It is very important to master the use of special financial calculator. For example, you should be able to use a calculator to calculate the maturity price and yield of bonds. There will be a special part in the e-learning course to explain the use of calculators.
4. Learn step by step. The reason why I will explain the knowledge of the second module in part *9 is because I hope that students can know how to calculate "expected return" and volatility (standard deviation of return) before teaching portfolio theory.
5. Necessary memory. You need to remember the commonly used normal distribution related values (*4 even remembers the T distribution), such as the one-tailed and two-tailed test values with 90%, 95% and 99% confidence intervals.
Second, the proportion and outline of FRM level 1 examination subjects
(1) Risk management basis 20%
The role of risk management
Basic risk types
Measurement and management tools
Create the value of risk management
Modern portfolio theory
Standard and non-standard of capital asset pricing model
exponential model
Risk adjustment performance measurement
Enterprise risk management
Financial disaster and risk management failure
case study
Moral principles and morality as a strategy
(2) Quantitative analysis 20%
Discrete and continuous probability distribution
Population and sample statistics
Statistical inference and hypothesis testing
Parameter estimation of segmentation therapy
Graphical representation of statistical relations
Unit and multivariate linear regression
Monte Carlo method
Correlation estimation and fluctuation using EWMA and GARCH models
Term structure of volatility
(3) Financial market and output 30%
OTC market mechanism
Forward, futures, swaps and options
Interest rate level and interest rate sensitivity index
Fixed income securities derivatives
Interest rates, foreign exchange, stocks
Commodity derivative products
exchange risk
corporate bonds
Credit rating mechanism
(4) Valuation and risk model 30%
Risk grade value
Option valuation
Valuation of fixed income securities
State and Sovereign Risk Model and Management
External and internal credit ratings
Expectations and unexpected losses
operating risk
Stress testing and scenario analysis