Foreign Exchange Markets
After completing this reading, you should be able to: Explain and describe the mechanics of spot quotes, forward quotes, and future quotes in the foreign exchange market and distinguish between the bid and ask exchange rates. Calculate bid-ask spread and…
Regression Diagnostics
After completing this reading, you should be able to: Explain how to test whether regression is affected by heteroskedasticity. Describe approaches to using heteroskedastic data. Characterize multicollinearity and its consequences; distinguish between multicollinearity and perfect collinearity. Describe the consequences of…
Capital Structure in Banks
After completing this reading, you should be able to: Evaluate a bank’s economic capital relative to its level of credit risk. Identify and describe important factors used to calculate economic capital for credit risk: the probability of default, exposure, and…
What is ERM?
After completing this reading, you should be able to: Describe enterprise risk management (ERM) and compare and contrast differing definitions of ERM. Compare the benefits and costs of ERM and describe the motivations for a firm to adopt an ERM…
Sample Moments
After completing this reading, you should be able to: Estimate the mean, variance, and standard deviation using sample data. Explain the difference between a population moment and a sample moment. Distinguish between an estimator and an estimate. Describe the bias…
Nonstationary Time Series
After completing this reading, you should be able to: Describe linear and nonlinear time trends. Explain how to use regression analysis to model seasonality. Describe a random walk and a unit root. Explain the challenges of modeling time series containing…
Stationary Time Series
After completing this reading, you should be able to: Describe the requirements for a series to be covariance stationary. Define the autocovariance function and the autocorrelation function. Define white noise; describe independent white noise and normal (Gaussian) white noise. Define…
Multivariate Random Variables
After completing this reading, you should be able to: Explain how a probability matrix can be used to express a probability mass function (PMF). Compute the marginal and conditional distributions of a discrete bivariate random variable. Explain how the expectation…
Random Variables
After completing this reading, you should be able to: Describe and distinguish a probability mass function from a cumulative distribution function and explain the relationship between these two. Understand and apply the concept of a mathematical expectation of a random…
FRM Part 1 Study Notes
FRM Part I Foundations of Risk Management 1. The Building Blocks of Risk Management 2. How Do Firms Manage Financial Risk? 3. The Governance of Risk Management 4. Credit Risk Transfer Mechanisms 5. Modern Portfolio Theory (MPT) and the Capital Asset…
