FRM Part 1 Exam Preparation Videos - 2019

Define discrete and continuous random variables, and calculate mean, variance, standard deviation, skewness, and kurtosis; analyze joint, marginal, conditional probabilities, normal and multivariate normal distributions, and Bayes' theorem.

Explore normal distribution concepts, confidence intervals, and z-scores; apply standardization to the standard normal, and compare chi-square and F distributions for variance testing, with sampling distribution basics.

Learn hypothesis testing and confidence intervals, including defining null and alternative hypotheses, constructing confidence intervals, and selecting tests such as z, t, chi-square, or F with standard errors and p-values.

Explore regression with a single regressor, interpreting confidence intervals and p-values, performing t-tests, and understanding homoscedasticity and heteroscedasticity, plus the gloss Markle theorem.

Explore multiple linear regression with several predictors, estimate coefficients by least squares, assess fit with R-squared and adjusted R-squared, and examine assumptions, bias from omitted variables, and multicollinearity.

Learn how to compare models using R-squared and unbiased estimators, account for degrees of freedom, and identify the best model for forecasting trends.

Analyze how to characterize cycles in time series by distinguishing stationary processes from white noise, and evaluating lag-based correlations, variance, and finite versus infinite behavior.

This lecture explains modeling cycles with moving averages to forecast GDP trends, highlighting seasonality, seasonal adjustments, and the impact of short-run and long-run shocks on economic data.

Explore volatility estimation using continuously compounded returns, historical data, exponentially weighted moving average and arch models, and understand how correlations and variances drive portfolio risk.

Identify, quantify, accumulate, and mitigate risks through the risk management process; distinguish expected loss from unexpected loss; examine market, liquidity, and operational risk.

Identify how hedging and risk management reduce downside risk while enabling upside potential using instruments such as forwards, futures, swaps, options, and credit default swaps.

Explore corporate governance and risk management through independent boards, align risk appetite with business strategy, and highlight audit and risk management committee roles in ensuring controls and performance.

Applying CAPM to portfolio performance using Treynor, Sharpe, and Jensen's alpha, and assessing tracking error, information ratio, and downside risk under systematic and unsystematic risk.

Evaluate risk-adjusted performance within peer groups using the Morningstar rating system, identifying top performers and measuring risk through value at risk and benchmark consistency.

Explore arbitrage pricing theory and multi-factor risk models, hedging exposure to macro factors like GDP, inflation, and interest rates, and interpret factor loadings via regression to explain systematic risk.

Explore how misreporting and unexpected market moves triggered financial disasters from distrained securities to LTCM, and learn risk management lessons for independent controls and liquidity risk.

Define the role and limits of risk management. Explain how failures occur through mismeasurement and poor communication, and emphasize ongoing monitoring and risk metrics in crisis decision making.

Explore the GARP code of conduct, outlining professional integrity, conflicts of interest, confidentiality, and disclosure standards in risk management.

Quantify volatility in VaR models by examining fat tails, skewness, and conditional versus unconditional distributions, and explore parametric, non-parametric, historical, and implied methods.

Explain value at risk for linear and nonlinear derivatives using delta-normal and Monte Carlo stress testing, highlight limitations, and show how scenario analysis addresses correlation breakdown and worst-case scenarios.

Explore binomial trees for option pricing, focusing on calls, value estimation, and practical decision-making to understand money and strategy in FRM part 1 prep.

Delve into pricing employee stock options using the Black-Scholes-Merton framework, covering strike and exercise prices, stock price dynamics, dividends, and dilution effects on option value.

Explore how excel-based tools compute option greeks—delta, gamma, theta, vega, and rho—using a European Nifty index option, with time to expiry, volatility, and interest rate.

Explore how discount factors determine the present value of future cash flows and how bond pricing uses clean versus dirty prices, accrued interest, and arbitrage concepts.

Analyze how spot, forward, and par rates interact under discrete and continuous compounding, and learn to compute future values, discount factors, and present values for bonds and swaps.

Learn how bond prices are determined by discounting cash flows to present value, reflecting yields, premiums or discounts, and forward rates.

Explore how multi-factor risk metrics assess exposure and hedge strategies for portfolios, detailing sensitivities, basis points, interest-rate moves, and scenario impacts on valuations.

Explore how external rating agencies assess default risk and investment grade, and how banks use internal ratings to influence bond pricing across economic cycles.

Explore how stress testing uses scenario analysis to estimate worst-case losses across risk factors, set economic capital buffers, and assess extreme events on portfolios and liquidity.