TL;DR: In this article, the authors examined and explained the differences in the rates offered on corporate bonds and those offered on government bonds, and examined whether there is a risk premium in corporate bond spreads and, if so, why it exists.
Abstract: The purpose of this article is to explain the spread between rates on corporate and government bonds. We show that expected default accounts for a surprisingly small fraction of the premium in corporate rates over treasuries. While state taxes explain a substantial portion of the difference, the remaining portion of the spread is closely related to the factors that we commonly accept as explaining risk premiums for common stocks. Both our time series and cross-sectional tests support the existence of a risk premium on corporate bonds. THE PURPOSE OF THIS ARTICLE is to examine and explain the differences in the rates offered on corporate bonds and those offered on government bonds ~spreads!, and, in particular, to examine whether there is a risk premium in corporate bond spreads and, if so, why it exists. Spreads in rates between corporate and government bonds differ across rating classes and should be positive for each rating class for the following reasons: 1. Expected default loss—some corporate bonds will default and investors require a higher promised payment to compensate for the expected loss from defaults. 2. Tax premium—interest payments on corporate bonds are taxed at the state level whereas interest payments on government bonds are not. 3. Risk premium—The return on corporate bonds is riskier than the return on government bonds, and investors should require a premium for the higher risk. As we will show, this occurs because a large part of the risk on corporate bonds is systematic rather than diversifiable. The only controversial part of the above analyses is the third point. Some authors in their analyses assume that the risk premium is zero in the corporate bond market.1
TL;DR: In this article, an economic model that determines the optimal amount to invest to protect a given set of information is presented, taking into account the vulnerability of the information to a security breach and the potential loss should such a breach occur.
Abstract: This article presents an economic model that determines the optimal amount to invest to protect a given set of information. The model takes into account the vulnerability of the information to a security breach and the potential loss should such a breach occur. It is shown that for a given potential loss, a firm should not necessarily focus its investments on information sets with the highest vulnerability. Since extremely vulnerable information sets may be inordinately expensive to protect, a firm may be better off concentrating its efforts on information sets with midrange vulnerabilities. The analysis further suggests that to maximize the expected benefit from investment to protect information, a firm should spend only a small fraction of the expected loss due to a security breach.
TL;DR: An economic model is presented that determines the optimal amount to invest to protect a given set of information and takes into account the vulnerability of the information to a security breach and the potential loss should such a breach occur.
Abstract: This article presents an economic model that determines the optimal amount to invest to protect a given set of information. The model takes into account the vulnerability of the information to a security breach and the potential loss should such a breach occur. It is shown that for a given potential loss, a firm should not necessarily focus its investments on information sets with the highest vulnerability. Since extremely vulnerable information sets may be inordinately expensive to protect, a firm may be better off concentrating its efforts on information sets with midrange vulnerabilities. The analysis further suggests that to maximize the expected benefit from investment to protect information, a firm should spend only a small fraction of the expected loss due to a security breach.
TL;DR: The basics of credit risk management Expected Loss Unexpected loss Regulatory Capital and the Basel Initiative Modeling Correlated Defaults The Bernoulli Model The Poisson Model Bernouley versus Poisson Mixture An Overview of Common Model Concepts One-Factor/Sector Models Loss Dependence by Means of Copula Functions Working Example on Asset Correlations Generating the Portfolio Loss Distribution Asset Value Models Introduction and a Brief Guide to the Literature A Few Words about Calls and Puts Merton's Asset Value Model Transforming Equity into Asset Values: A Working Approach The CreditR
Abstract: The Basics of Credit Risk Management Expected Loss Unexpected Loss Regulatory Capital and the Basel Initiative Modeling Correlated Defaults The Bernoulli Model The Poisson Model Bernoulli versus Poisson Mixture An Overview of Common Model Concepts One-Factor/Sector Models Loss Dependence by Means of Copula Functions Working Example on Asset Correlations Generating the Portfolio Loss Distribution Asset Value Models Introduction and a Brief Guide to the Literature A Few Words about Calls and Puts Merton's Asset Value Model Transforming Equity into Asset Values: A Working Approach The CreditRisk+ Model The Modeling Framework of CreditRisk+ Construction Step 1: Independent Obligors Construction Step 2: Sector Model Risk Measures and Capital Allocation Coherent Risk Measures and Expected Shortfall Contributory Capital Term Structure of Default Probability Survival Function and Hazard Rate Risk-Neutral vs. Actual Default Probabilities Term Structure Based on Historical Default Information Term Structure Based on Market Spreads Credit Derivatives Total Return Swaps Credit Default Products Basket Credit Derivatives Credit Spread Products Credit-Linked Notes Collateralized Debt Obligations Introduction to Collateralized Debt Obligations (CDOs) Different Roles of Banks in the CDO Market CDOs from the Modeling Point of View Multi-Period Credit Models Former Rating Agency Model: Moody's BET Developments, Model Issues, and Further Reading References Index
TL;DR: In this paper, the authors exploit variation in the delay in expected loss recognition under the current incurred loss model, and find that reductions in lending during recessionary relative to expansionary periods are lower for banks that delay less.