Today's Daily Questions

David writes totally fresh, totally original practice (quiz) questions every week: a fresh set of three (4) from Mon to Thursday = 12 new practice questions per week. A few hungry customers like to follow along, so we post them here.

Paid members please note: you do not need to collect practice questions one at a time! After a chapter (or section of related chapters) is finished, Nicole collects them into a single PDF file and uploads to the Study Planner. Most paid members will want to go straight to the study planner (unless you want to discuss/etc in the forum). Thank you!

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  1. Nicole Seaman

    P2.T8.705. Berkshire Hathaway versus its benchmark (Ang)

    Appreciate the citation, David! Very honoured.
    Appreciate the citation, David! Very honoured.
    Appreciate the citation, David! Very honoured.
    Appreciate the citation, David! Very honoured.
    Replies:
    3
    Views:
    199
  2. Nicole Seaman

    P2.T8.706. Alpha, style analysis and the risk anomaly (Ang)

    Learning objectives: Explain how to measure time-varying factor exposures and their use in style analysis. Describe issues that arise when measuring alphas for nonlinear strategies. Compare the volatility anomaly and beta anomaly, and analyze evidence of each anomaly. Describe potential explanations for the risk anomaly. Questions: 706.1. In order to evaluate the performance of its funds,...
    Learning objectives: Explain how to measure time-varying factor exposures and their use in style analysis. Describe issues that arise when measuring alphas for nonlinear strategies. Compare the volatility anomaly and beta anomaly, and analyze evidence of each anomaly. Describe potential explanations for the risk anomaly. Questions: 706.1. In order to evaluate the performance of its funds,...
    Learning objectives: Explain how to measure time-varying factor exposures and their use in style analysis. Describe issues that arise when measuring alphas for nonlinear strategies. Compare the volatility anomaly and beta anomaly, and analyze evidence of each anomaly. Describe potential...
    Learning objectives: Explain how to measure time-varying factor exposures and their use in style analysis. Describe issues that arise when measuring alphas for nonlinear strategies. Compare the...
    Replies:
    0
    Views:
    129
  3. Nicole Seaman

    P1.T3.701. Basic bank functions and definitions (Hull)

    Learning objectives: Explain how deposit insurance gives rise to a moral hazard problem. Describe investment banking financing arrangements including private placement, public offering, best efforts, firm commitment, and Dutch auction approaches. Describe the potential conflicts of interest among commercial banking, securities services, and investment banking divisions of a bank and recommend...
    Learning objectives: Explain how deposit insurance gives rise to a moral hazard problem. Describe investment banking financing arrangements including private placement, public offering, best efforts, firm commitment, and Dutch auction approaches. Describe the potential conflicts of interest among commercial banking, securities services, and investment banking divisions of a bank and recommend...
    Learning objectives: Explain how deposit insurance gives rise to a moral hazard problem. Describe investment banking financing arrangements including private placement, public offering, best efforts, firm commitment, and Dutch auction approaches. Describe the potential conflicts of interest...
    Learning objectives: Explain how deposit insurance gives rise to a moral hazard problem. Describe investment banking financing arrangements including private placement, public offering, best...
    Replies:
    0
    Views:
    130
  4. Nicole Seaman

    P1.T3.700. Major risks faced by banks (Hull)

    Hello @Elnur1 All of the answers and in-depth explanations to our practice questions are available to our paid customers who purchase a study package. Our study packages are here if you are interested in purchasing to get the answers to our practice questions: . Thank you :) Nicole
    Hello @Elnur1 All of the answers and in-depth explanations to our practice questions are available to our paid customers who purchase a study package. Our study packages are here if you are interested in purchasing to get the answers to our practice questions: . Thank you :) Nicole
    Hello @Elnur1 All of the answers and in-depth explanations to our practice questions are available to our paid customers who purchase a study package. Our study packages are here if you are interested in purchasing to get the answers to our practice questions: . Thank you :) Nicole
    Hello @Elnur1 All of the answers and in-depth explanations to our practice questions are available to our paid customers who purchase a study package. Our study packages are here if you are...
    Replies:
    3
    Views:
    147
  5. Nicole Seaman

    P2.T8.704. Alpha and effective benchmarks (Andrew Ang)

    Learning objectives: Describe and evaluate the low-risk anomaly of asset returns. Define and calculate alpha, tracking error, the information ratio, and the Sharpe ratio. Explain the impact of benchmark choice on alpha, and describe characteristics of an effective benchmark to measure alpha. Questions: 704.1. Below is the regression output of a portfolio's excess returns against its...
    Learning objectives: Describe and evaluate the low-risk anomaly of asset returns. Define and calculate alpha, tracking error, the information ratio, and the Sharpe ratio. Explain the impact of benchmark choice on alpha, and describe characteristics of an effective benchmark to measure alpha. Questions: 704.1. Below is the regression output of a portfolio's excess returns against its...
    Learning objectives: Describe and evaluate the low-risk anomaly of asset returns. Define and calculate alpha, tracking error, the information ratio, and the Sharpe ratio. Explain the impact of benchmark choice on alpha, and describe characteristics of an effective benchmark to measure...
    Learning objectives: Describe and evaluate the low-risk anomaly of asset returns. Define and calculate alpha, tracking error, the information ratio, and the Sharpe ratio. Explain the impact of...
    Replies:
    0
    Views:
    154
  6. Nicole Seaman

    P1.T2.707. Gaussian Copula (Hull)

    Learning objectives: Define copula and describe the key properties of copulas and copula correlation. Explain tail dependence. Describe the Gaussian copula, Student’s t-copula, multivariate copula, and one-factor copula. Questions: 707.1. Below are the joint probabilities for a cumulative bivariate normal distribution with a correlation parameter, ρ, of 0.30. If V(1) and V(2) are each...
    Learning objectives: Define copula and describe the key properties of copulas and copula correlation. Explain tail dependence. Describe the Gaussian copula, Student’s t-copula, multivariate copula, and one-factor copula. Questions: 707.1. Below are the joint probabilities for a cumulative bivariate normal distribution with a correlation parameter, ρ, of 0.30. If V(1) and V(2) are each...
    Learning objectives: Define copula and describe the key properties of copulas and copula correlation. Explain tail dependence. Describe the Gaussian copula, Student’s t-copula, multivariate copula, and one-factor copula. Questions: 707.1. Below are the joint probabilities for a cumulative...
    Learning objectives: Define copula and describe the key properties of copulas and copula correlation. Explain tail dependence. Describe the Gaussian copula, Student’s t-copula, multivariate...
    Replies:
    0
    Views:
    192
  7. Nicole Seaman

    P2.T8.703. Value, size and momentum investing (Andrew Ang)

    Learning objectives: Assess methods of mitigating volatility risk in a portfolio, and describe challenges that arise when managing volatility risk. Explain how dynamic risk factors can be used in a multifactor model of asset returns, using the Fama-French model as an example. Compare value and momentum investment strategies, including their risk and return profiles. Questions: 703.1. Andrew...
    Learning objectives: Assess methods of mitigating volatility risk in a portfolio, and describe challenges that arise when managing volatility risk. Explain how dynamic risk factors can be used in a multifactor model of asset returns, using the Fama-French model as an example. Compare value and momentum investment strategies, including their risk and return profiles. Questions: 703.1. Andrew...
    Learning objectives: Assess methods of mitigating volatility risk in a portfolio, and describe challenges that arise when managing volatility risk. Explain how dynamic risk factors can be used in a multifactor model of asset returns, using the Fama-French model as an example. Compare value and...
    Learning objectives: Assess methods of mitigating volatility risk in a portfolio, and describe challenges that arise when managing volatility risk. Explain how dynamic risk factors can be used in...
    Replies:
    0
    Views:
    108
  8. Nicole Seaman

    P1.T2.706. Bivariate normal distribution (Hull)

    Learning objectives: Calculate covariance using the EWMA and GARCH(1,1) models. Apply the consistency condition to covariance. Describe the procedure of generating samples from a bivariate normal distribution. Describe properties of correlations between normally distributed variables when using a one-factor model. Questions: 706.1. The data and plot below show a bivariate normal sample...
    Learning objectives: Calculate covariance using the EWMA and GARCH(1,1) models. Apply the consistency condition to covariance. Describe the procedure of generating samples from a bivariate normal distribution. Describe properties of correlations between normally distributed variables when using a one-factor model. Questions: 706.1. The data and plot below show a bivariate normal sample...
    Learning objectives: Calculate covariance using the EWMA and GARCH(1,1) models. Apply the consistency condition to covariance. Describe the procedure of generating samples from a bivariate normal distribution. Describe properties of correlations between normally distributed variables when using...
    Learning objectives: Calculate covariance using the EWMA and GARCH(1,1) models. Apply the consistency condition to covariance. Describe the procedure of generating samples from a bivariate normal...
    Replies:
    0
    Views:
    168
  9. Nicole Seaman

    P2.T8.702. Macroeconomic risk factors including growth, inflation and volatility (Andrew Ang)

    Learning objectives: Describe the process of value investing, and explain reasons why a value premium may exist [BT note: this objective is somewhat out of sequence; the next practice question will review the value premium ]. Explain how different macroeconomic risk factors, including economic growth, inflation, and volatility affect risk premiums and asset returns. Questions: 702.1. Andrew...
    Learning objectives: Describe the process of value investing, and explain reasons why a value premium may exist [BT note: this objective is somewhat out of sequence; the next practice question will review the value premium ]. Explain how different macroeconomic risk factors, including economic growth, inflation, and volatility affect risk premiums and asset returns. Questions: 702.1. Andrew...
    Learning objectives: Describe the process of value investing, and explain reasons why a value premium may exist [BT note: this objective is somewhat out of sequence; the next practice question will review the value premium ]. Explain how different macroeconomic risk factors, including economic...
    Learning objectives: Describe the process of value investing, and explain reasons why a value premium may exist [BT note: this objective is somewhat out of sequence; the next practice question...
    Replies:
    0
    Views:
    182
  10. Nicole Seaman

    P1.T2.705. Correlation (Hull)

    Learning objective: Define correlation and covariance and differentiate between correlation and dependence. Questions: 705.1. In order to evaluate the the potential of a linear relationship between portfolio returns and a benchmark index, your colleague Richard conducted a univariate regression analysis. He regressed the benchmark index returns, B(i), as the dependent (aka, response)...
    Learning objective: Define correlation and covariance and differentiate between correlation and dependence. Questions: 705.1. In order to evaluate the the potential of a linear relationship between portfolio returns and a benchmark index, your colleague Richard conducted a univariate regression analysis. He regressed the benchmark index returns, B(i), as the dependent (aka, response)...
    Learning objective: Define correlation and covariance and differentiate between correlation and dependence. Questions: 705.1. In order to evaluate the the potential of a linear relationship between portfolio returns and a benchmark index, your colleague Richard conducted a univariate...
    Learning objective: Define correlation and covariance and differentiate between correlation and dependence. Questions: 705.1. In order to evaluate the the potential of a linear relationship...
    Replies:
    0
    Views:
    198
  11. Nicole Seaman

    P2.T8.701. Multifactor models (Andrew Ang)

    Learning objectives: Describe multifactor models, and compare and contrast multifactor models to the CAPM. Explain how stochastic discount factors are created and apply them in the valuation of assets. Describe efficient market theory and explain how markets can be inefficient. Questions: 701.1. In introducing multifactor models, Andrew Ang explains that "to capture the composite bad times...
    Learning objectives: Describe multifactor models, and compare and contrast multifactor models to the CAPM. Explain how stochastic discount factors are created and apply them in the valuation of assets. Describe efficient market theory and explain how markets can be inefficient. Questions: 701.1. In introducing multifactor models, Andrew Ang explains that "to capture the composite bad times...
    Learning objectives: Describe multifactor models, and compare and contrast multifactor models to the CAPM. Explain how stochastic discount factors are created and apply them in the valuation of assets. Describe efficient market theory and explain how markets can be...
    Learning objectives: Describe multifactor models, and compare and contrast multifactor models to the CAPM. Explain how stochastic discount factors are created and apply them in the valuation of...
    Replies:
    0
    Views:
    161
  12. Nicole Seaman

    P1.T2.704. Forecasting volatility with GARCH (Hull)

    Learning objectives: Explain mean reversion and how it is captured in the GARCH(1,1) model. Explain the weights in the EWMA and GARCH(1,1) models. Explain how GARCH models perform in volatility forecasting. Describe the volatility term structure and the impact of volatility changes. Questions: 704.1. The most recent estimate of the daily volatility of an asset, σ(n-1), is 3.0% and the price...
    Learning objectives: Explain mean reversion and how it is captured in the GARCH(1,1) model. Explain the weights in the EWMA and GARCH(1,1) models. Explain how GARCH models perform in volatility forecasting. Describe the volatility term structure and the impact of volatility changes. Questions: 704.1. The most recent estimate of the daily volatility of an asset, σ(n-1), is 3.0% and the price...
    Learning objectives: Explain mean reversion and how it is captured in the GARCH(1,1) model. Explain the weights in the EWMA and GARCH(1,1) models. Explain how GARCH models perform in volatility forecasting. Describe the volatility term structure and the impact of volatility...
    Learning objectives: Explain mean reversion and how it is captured in the GARCH(1,1) model. Explain the weights in the EWMA and GARCH(1,1) models. Explain how GARCH models perform in volatility...
    Replies:
    0
    Views:
    171
  13. Nicole Seaman

    P2.T8.700. Theory of factor risk premiums (Andrew Ang)

    Learning objectives: Provide examples of factors that impact asset prices, and explain the theory of factor risk premiums. Describe the capital asset pricing model (CAPM) including its assumptions, and explain how factor risk is addressed in the CAPM. Explain implications of using the CAPM to value assets, including equilibrium and optimal holdings, exposure to factor risk, its treatment of...
    Learning objectives: Provide examples of factors that impact asset prices, and explain the theory of factor risk premiums. Describe the capital asset pricing model (CAPM) including its assumptions, and explain how factor risk is addressed in the CAPM. Explain implications of using the CAPM to value assets, including equilibrium and optimal holdings, exposure to factor risk, its treatment of...
    Learning objectives: Provide examples of factors that impact asset prices, and explain the theory of factor risk premiums. Describe the capital asset pricing model (CAPM) including its assumptions, and explain how factor risk is addressed in the CAPM. Explain implications of using the CAPM to...
    Learning objectives: Provide examples of factors that impact asset prices, and explain the theory of factor risk premiums. Describe the capital asset pricing model (CAPM) including its...
    Replies:
    0
    Views:
    217
  14. Nicole Seaman

    P1.T2.699. Linear and nonlinear trends (Diebold)

    This question is oddly numbered T2.699 because, as I just finished writing fresh Diebold time series questions, Nicole spotted that I overlooked GARP's two new LOs which appear at the start of the Diebold readings ("Describe linear and nonlinear trends. Describe trend models to estimate and forecast trends";) . I did not want to confuse the continuity of our 7XX series, so this is meant to...
    This question is oddly numbered T2.699 because, as I just finished writing fresh Diebold time series questions, Nicole spotted that I overlooked GARP's two new LOs which appear at the start of the Diebold readings ("Describe linear and nonlinear trends. Describe trend models to estimate and forecast trends";) . I did not want to confuse the continuity of our 7XX series, so this is meant to...
    This question is oddly numbered T2.699 because, as I just finished writing fresh Diebold time series questions, Nicole spotted that I overlooked GARP's two new LOs which appear at the start of the Diebold readings ("Describe linear and nonlinear trends. Describe trend models to estimate and...
    This question is oddly numbered T2.699 because, as I just finished writing fresh Diebold time series questions, Nicole spotted that I overlooked GARP's two new LOs which appear at the start of the...
    Replies:
    1
    Views:
    108
  15. Nicole Seaman

    P1.T2.703. EWMA versus GARCH volatility (Hull)

    Learning objectives: Apply the exponentially weighted moving average (EWMA) model to estimate volatility. Describe the generalized autoregressive conditional heteroskedasticity (GARCH(p,q)) model for estimating volatility and its properties. Calculate volatility using the GARCH(1,1) model. Questions: 703.1. The most recent estimate of the daily volatility of an asset is 4.0% and the price...
    Learning objectives: Apply the exponentially weighted moving average (EWMA) model to estimate volatility. Describe the generalized autoregressive conditional heteroskedasticity (GARCH(p,q)) model for estimating volatility and its properties. Calculate volatility using the GARCH(1,1) model. Questions: 703.1. The most recent estimate of the daily volatility of an asset is 4.0% and the price...
    Learning objectives: Apply the exponentially weighted moving average (EWMA) model to estimate volatility. Describe the generalized autoregressive conditional heteroskedasticity (GARCH(p,q)) model for estimating volatility and its properties. Calculate volatility using the GARCH(1,1) model....
    Learning objectives: Apply the exponentially weighted moving average (EWMA) model to estimate volatility. Describe the generalized autoregressive conditional heteroskedasticity (GARCH(p,q)) model...
    Replies:
    0
    Views:
    71
  16. Nicole Seaman

    P2.T6.708. Stress testing the credit value adjustment (CVA)

    Learning objectives: Describe a stress test that can be performed on CVA. Calculate the stressed CVA and the stress loss on CVA. Calculate the debt value adjustment (DVA) and explain how stressing DVA enters into aggregating stress tests of CCR. Describe the common pitfalls in stress testing CCR. Questions: 708.1. Thomas is your firm's Counterparty Credit Risk (CCR) Manager and he is...
    Learning objectives: Describe a stress test that can be performed on CVA. Calculate the stressed CVA and the stress loss on CVA. Calculate the debt value adjustment (DVA) and explain how stressing DVA enters into aggregating stress tests of CCR. Describe the common pitfalls in stress testing CCR. Questions: 708.1. Thomas is your firm's Counterparty Credit Risk (CCR) Manager and he is...
    Learning objectives: Describe a stress test that can be performed on CVA. Calculate the stressed CVA and the stress loss on CVA. Calculate the debt value adjustment (DVA) and explain how stressing DVA enters into aggregating stress tests of CCR. Describe the common pitfalls in stress testing...
    Learning objectives: Describe a stress test that can be performed on CVA. Calculate the stressed CVA and the stress loss on CVA. Calculate the debt value adjustment (DVA) and explain how stressing...
    Replies:
    0
    Views:
    152
  17. Nicole Seaman

    P1.T2.702. Simple (equally weighted) historical volatility (Hull)

    Learning objectives: Define and distinguish between volatility, variance rate, and implied volatility. Describe the power law. Explain how various weighting schemes can be used in estimating volatility. Questions 702.1. Consider the following series of closing stock prices over the tend most recent trading day (this is similar to Hull's Table 10.3) along with daily log returns, squared...
    Learning objectives: Define and distinguish between volatility, variance rate, and implied volatility. Describe the power law. Explain how various weighting schemes can be used in estimating volatility. Questions 702.1. Consider the following series of closing stock prices over the tend most recent trading day (this is similar to Hull's Table 10.3) along with daily log returns, squared...
    Learning objectives: Define and distinguish between volatility, variance rate, and implied volatility. Describe the power law. Explain how various weighting schemes can be used in estimating volatility. Questions 702.1. Consider the following series of closing stock prices over the tend most...
    Learning objectives: Define and distinguish between volatility, variance rate, and implied volatility. Describe the power law. Explain how various weighting schemes can be used in estimating...
    Replies:
    0
    Views:
    239
  18. David Harper CFA FRM

    P2.T5.108. Mortgage payment factor

    hi sir i am very thankful to you to give your valuable time for us
    hi sir i am very thankful to you to give your valuable time for us
    hi sir i am very thankful to you to give your valuable time for us
    hi sir i am very thankful to you to give your valuable time for us
    Replies:
    4
    Views:
    2,857
  19. Nicole Seaman

    P2.T6.707. Stress testing counterparty exposures

    Learning objectives: Differentiate among current exposure, peak exposure, expected exposure, and expected positive exposure. Explain the treatment of counterparty credit risk (CCR) both as a credit risk and as a market risk and describe its implications for trading activities and risk management for a financial institution. Describe a stress test that can be performed on a loan portfolio and...
    Learning objectives: Differentiate among current exposure, peak exposure, expected exposure, and expected positive exposure. Explain the treatment of counterparty credit risk (CCR) both as a credit risk and as a market risk and describe its implications for trading activities and risk management for a financial institution. Describe a stress test that can be performed on a loan portfolio and...
    Learning objectives: Differentiate among current exposure, peak exposure, expected exposure, and expected positive exposure. Explain the treatment of counterparty credit risk (CCR) both as a credit risk and as a market risk and describe its implications for trading activities and risk management...
    Learning objectives: Differentiate among current exposure, peak exposure, expected exposure, and expected positive exposure. Explain the treatment of counterparty credit risk (CCR) both as a...
    Replies:
    0
    Views:
    174
  20. Nicole Seaman

    P1.T2.701. Regression analysis to model seasonality (Diebold)

    I hope you enjoy the new Diebold questions. Just these three required several hours to prepare, believe it or not. Diebold's actual end of chapter questions are more like data science assignments. These questions are not too difficult, but they attempt to really apply the essentials of seasonality (as opposed to cycles and trends) in time series. I am just about to add the underlying XLS to...
    I hope you enjoy the new Diebold questions. Just these three required several hours to prepare, believe it or not. Diebold's actual end of chapter questions are more like data science assignments. These questions are not too difficult, but they attempt to really apply the essentials of seasonality (as opposed to cycles and trends) in time series. I am just about to add the underlying XLS to...
    I hope you enjoy the new Diebold questions. Just these three required several hours to prepare, believe it or not. Diebold's actual end of chapter questions are more like data science assignments. These questions are not too difficult, but they attempt to really apply the essentials of...
    I hope you enjoy the new Diebold questions. Just these three required several hours to prepare, believe it or not. Diebold's actual end of chapter questions are more like data science assignments....
    Replies:
    1
    Views:
    213
  21. Nicole Seaman

    P2.T6.706. Heuristic approach versus neural networks (De Laurentis)

    Learning objectives: Describe the use of a cash flow simulation model in assigning rating and default probability, and explain the limitations of the model. Describe the application of heuristic approaches, numeric approaches, and artificial neural networks in modeling default risk and define their strengths and weaknesses. Describe the role and management of qualitative information in...
    Learning objectives: Describe the use of a cash flow simulation model in assigning rating and default probability, and explain the limitations of the model. Describe the application of heuristic approaches, numeric approaches, and artificial neural networks in modeling default risk and define their strengths and weaknesses. Describe the role and management of qualitative information in...
    Learning objectives: Describe the use of a cash flow simulation model in assigning rating and default probability, and explain the limitations of the model. Describe the application of heuristic approaches, numeric approaches, and artificial neural networks in modeling default risk and define...
    Learning objectives: Describe the use of a cash flow simulation model in assigning rating and default probability, and explain the limitations of the model. Describe the application of heuristic...
    Replies:
    0
    Views:
    251
  22. Nicole Seaman

    P1.T2.700. Seasonality in time series analysis (Diebold)

    Learning objective: Describe the sources of seasonality and how to deal with it in time series analysis. Questions 700.1. Which of the following time series is MOST LIKELY to contain a seasonal pattern? a. Price of solar panels b. Employment participation rate c. Climate data data recorded from a weather station once per year d. Return on average assets (ROA) for the large commercial bank...
    Learning objective: Describe the sources of seasonality and how to deal with it in time series analysis. Questions 700.1. Which of the following time series is MOST LIKELY to contain a seasonal pattern? a. Price of solar panels b. Employment participation rate c. Climate data data recorded from a weather station once per year d. Return on average assets (ROA) for the large commercial bank...
    Learning objective: Describe the sources of seasonality and how to deal with it in time series analysis. Questions 700.1. Which of the following time series is MOST LIKELY to contain a seasonal pattern? a. Price of solar panels b. Employment participation rate c. Climate data data recorded...
    Learning objective: Describe the sources of seasonality and how to deal with it in time series analysis. Questions 700.1. Which of the following time series is MOST LIKELY to contain a seasonal...
    Replies:
    0
    Views:
    288
  23. Nicole Seaman

    P2.T6.705. Logistic regression and principal component analysis (PCA, De Laurentis)

    Learning objectives: Describe the application of a logistic regression model to estimate default probability. Define and interpret cluster analysis and principal component analysis. Questions: 705.1. Logistic regression is often used to predict whether a loan will default. For example, the logit function can predict conditional default by the estimation of default probability as a function...
    Learning objectives: Describe the application of a logistic regression model to estimate default probability. Define and interpret cluster analysis and principal component analysis. Questions: 705.1. Logistic regression is often used to predict whether a loan will default. For example, the logit function can predict conditional default by the estimation of default probability as a function...
    Learning objectives: Describe the application of a logistic regression model to estimate default probability. Define and interpret cluster analysis and principal component analysis. Questions: 705.1. Logistic regression is often used to predict whether a loan will default. For example, the...
    Learning objectives: Describe the application of a logistic regression model to estimate default probability. Define and interpret cluster analysis and principal component...
    Replies:
    0
    Views:
    358
  24. Nicole Seaman

    P1.T1.705. Fama-French three factor model (Bodie's multifactor models continued)

    Learning objectives: Describe properties of well-diversified portfolios and explain the impact of diversification on the residual risk of a portfolio. Explain how to construct a portfolio to hedge exposure to multiple factors. Describe and apply the Fama-French three factor model in estimating asset returns. Questions: 705.1. In a single-factor economy, each of the following portfolios (A,...
    Learning objectives: Describe properties of well-diversified portfolios and explain the impact of diversification on the residual risk of a portfolio. Explain how to construct a portfolio to hedge exposure to multiple factors. Describe and apply the Fama-French three factor model in estimating asset returns. Questions: 705.1. In a single-factor economy, each of the following portfolios (A,...
    Learning objectives: Describe properties of well-diversified portfolios and explain the impact of diversification on the residual risk of a portfolio. Explain how to construct a portfolio to hedge exposure to multiple factors. Describe and apply the Fama-French three factor model in estimating...
    Learning objectives: Describe properties of well-diversified portfolios and explain the impact of diversification on the residual risk of a portfolio. Explain how to construct a portfolio to hedge...
    Replies:
    0
    Views:
    204
  25. Nicole Seaman

    P2.T6.704 Linear discriminant analysis (LDA according to De Laurentis)

    Learning objectives: Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model. Describe linear discriminant analysis (LDA), define the Z-score and its usage, and apply LDA to classify a sample of firms by credit quality. Questions: 704.1. In the Merton approach to credit risk, default probability is given by...
    Learning objectives: Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model. Describe linear discriminant analysis (LDA), define the Z-score and its usage, and apply LDA to classify a sample of firms by credit quality. Questions: 704.1. In the Merton approach to credit risk, default probability is given by...
    Learning objectives: Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model. Describe linear discriminant analysis (LDA), define the Z-score and its usage, and apply LDA to classify a sample of firms by credit...
    Learning objectives: Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model. Describe linear discriminant...
    Replies:
    0
    Views:
    263
  26. Nicole Seaman

    P1.T1.704. Bodie's multifactor models

    Learning objectives: Describe the inputs, including factor betas, to a multifactor model. Calculate the expected return of an asset using a single-factor and a multifactor model. Questions 704.1. Suppose that three factors have been identified for the U.S. economy: Expected inflation rate (IR) is +2.00% Expected 10-year Treasury yield (T-NOTE) is 2.40% Expected growth in productivity (PROD)...
    Learning objectives: Describe the inputs, including factor betas, to a multifactor model. Calculate the expected return of an asset using a single-factor and a multifactor model. Questions 704.1. Suppose that three factors have been identified for the U.S. economy: Expected inflation rate (IR) is +2.00% Expected 10-year Treasury yield (T-NOTE) is 2.40% Expected growth in productivity (PROD)...
    Learning objectives: Describe the inputs, including factor betas, to a multifactor model. Calculate the expected return of an asset using a single-factor and a multifactor model. Questions 704.1. Suppose that three factors have been identified for the U.S. economy: Expected inflation rate...
    Learning objectives: Describe the inputs, including factor betas, to a multifactor model. Calculate the expected return of an asset using a single-factor and a multifactor...
    Replies:
    0
    Views:
    217
  27. Nicole Seaman

    P2.T6.703 Structural versus Reduced-form credit risk approaches (DeLaurentis)

    Learning outcomes: Describe rating agencies’ assignment methodologies for issue and issuer ratings. Describe the relationship between borrower rating and probability of default. Compare agencies’ ratings to internal experts-based rating systems. Distinguish between the structural approaches and the reduced-form approaches to predicting default. Questions: 703.1. De Laurentis explains the...
    Learning outcomes: Describe rating agencies’ assignment methodologies for issue and issuer ratings. Describe the relationship between borrower rating and probability of default. Compare agencies’ ratings to internal experts-based rating systems. Distinguish between the structural approaches and the reduced-form approaches to predicting default. Questions: 703.1. De Laurentis explains the...
    Learning outcomes: Describe rating agencies’ assignment methodologies for issue and issuer ratings. Describe the relationship between borrower rating and probability of default. Compare agencies’ ratings to internal experts-based rating systems. Distinguish between the structural approaches and...
    Learning outcomes: Describe rating agencies’ assignment methodologies for issue and issuer ratings. Describe the relationship between borrower rating and probability of default. Compare agencies’...
    Replies:
    0
    Views:
    315
  28. Nicole Seaman

    P1.T1.703. Policy responses and real effects of global financial crisis (Gorton)

    Learning objectives: Describe the historical background leading to the recent financial crisis. Distinguish between the two main panic periods of the financial crisis and describe the state of the markets during each. Assess the governmental policy responses to the financial crisis and review their short-term impact. Describe the global effects of the financial crisis on firms and the real...
    Learning objectives: Describe the historical background leading to the recent financial crisis. Distinguish between the two main panic periods of the financial crisis and describe the state of the markets during each. Assess the governmental policy responses to the financial crisis and review their short-term impact. Describe the global effects of the financial crisis on firms and the real...
    Learning objectives: Describe the historical background leading to the recent financial crisis. Distinguish between the two main panic periods of the financial crisis and describe the state of the markets during each. Assess the governmental policy responses to the financial crisis and review...
    Learning objectives: Describe the historical background leading to the recent financial crisis. Distinguish between the two main panic periods of the financial crisis and describe the state of the...
    Replies:
    0
    Views:
    168
  29. Nicole Seaman

    P2.T6.702. Credit rating assignment methodologies (De Laurentis)

    Learning objectives: Explain the key features of a good rating system. Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default. Describe a rating migration matrix and calculate the probability of default, cumulative probability of default, marginal probability of default, and annualized default rate. Questions: 702.1. Assume the...
    Learning objectives: Explain the key features of a good rating system. Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default. Describe a rating migration matrix and calculate the probability of default, cumulative probability of default, marginal probability of default, and annualized default rate. Questions: 702.1. Assume the...
    Learning objectives: Explain the key features of a good rating system. Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default. Describe a rating migration matrix and calculate the probability of default, cumulative probability of default,...
    Learning objectives: Explain the key features of a good rating system. Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default. Describe a...
    Replies:
    0
    Views:
    292
  30. Nicole Seaman

    P1.T1.700. Key factors that led to the housing bubble (Brunnermeier)

    Hello @kkunderp The reason that the answers are only available to our paid customers is because all of the daily practice questions are part of our PAID study packages, as they are compiled into practice question sets for our customers. We post them in the forum so our paid customers can gain more insight with the in-depth and detailed answers that David provides for each question, and so...
    Hello @kkunderp The reason that the answers are only available to our paid customers is because all of the daily practice questions are part of our PAID study packages, as they are compiled into practice question sets for our customers. We post them in the forum so our paid customers can gain more insight with the in-depth and detailed answers that David provides for each question, and so...
    Hello @kkunderp The reason that the answers are only available to our paid customers is because all of the daily practice questions are part of our PAID study packages, as they are compiled into practice question sets for our customers. We post them in the forum so our paid customers can gain...
    Hello @kkunderp The reason that the answers are only available to our paid customers is because all of the daily practice questions are part of our PAID study packages, as they are compiled into...
    Replies:
    6
    Views:
    416

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