Distance-to-Default in Banking

In contrast to corporate defaults, regulators typically take a number of statutory actions to avoid the large fiscal costs associated with bank defaults. The distance-to-default, a widely used market-based measure of corporate default risk, overlooks such regulatory actions. To overcome this limitation, this paper introduces the concept of distance-to-capital that accounts for pre-default regulatory actions such as those prescribed in a prompt-corrective-actions framework. We show that both risk measures can be analysed using the same theoretical framework but differ depending on the level of capital adequacy thresholds and asset volatility. We also use the framework to illustrate pre-default regulatory actions in Japan in 2001–2003.

An axiomatic approach to default risk and model uncertainty in rating systems

In the post-marketing stage, cases of hypocalcemia associated with bisphosphonate preparations (BPs) have been reported in patients with decreased kidney function, despite warning against use of BPs in such patients in the package insert (PI) of Japan. The purpose of this study was to investigate the safety of BPs in patients with decreased kidney function. The cohort study was conducted in patients with osteoporosis and newly prescribed bisphosphonate utilizing real-world data from MID-NET® in Japan. The adjusted hazard ratios (aHRs) for hypocalcemia (a corrected serum Ca level < 8.00mg/dL) relative to the normal group were calculated in each decreased kidney function group (mild, moderate or severe group). A total of 14,551 patients were included in the analysis, comprising 2,601 (17.88%) with normal (eGFR ≥ 90mL/min/1.73m2), 7,613 (52.32%) with mild (60 ≤ eGFR < 90mL/min/1.73m2), 3,919 (26.93%) with moderate (30 ≤ eGFR < 60mL/min/1.73m2), and 418 (2.87%) with severe kidney function (eGFR < 30mL/min/1.73m2). The aHRs (95% confidence interval) for hypocalcemia were 1.85 (0.75-4.57), 2.30 (0.86-6.21), and 22.74 (8.37-61.78) in the mild, moderate, and severe groups, respectively. The increased risk of hypocalcemia depending on kidney function was also observed even when calculating the aHR for each specific BP such as alendronate sodium hydrate, minodronic acid hydrate, and sodium risedronate hydrate. Furthermore, similar results were obtained in the sensitivity analysis by altering the outcome definition to a 20% or more reduction in corrected serum Ca level from the baseline, as well as when focusing on patients with more than one laboratory test result per 30days during the follow-up period. These findings suggest that the risk of hypocalcemia during BP prescription is higher in patients with decreased kidney function, particularly those with severely decreased kidney function. The quantitative real-world evidence on the safety risk of BPs obtained in this study has led to the PI revision describing a relationship between hypocalcemia risk and decreased kidney function as a regulatory action in Japan and will contribute to promoting the proper use of BPs with appropriate risk management in clinical practice.

The article examines the relationship between the accounting determined and market determined measures of risk. Previous research would suggest that financial statement ratios can be used as measures of default risk, but little is known of their association with the concept of risk as defined in portfolio theory. The variance of a portfolio's return is the sum of two terms. Empirically, there may be positive association between a security's variance and its average covariance with other securities. In sum, portfolio theory provides a measure of security risk that has both a priori and empirical support. In particular, the accounting risk measures can be viewed as surrogates for the total variability of return of a firm's common equity securities. Computing an average of the payout ratios over several years does not adequately deal with this problem, because one extreme year will still dominate the average. Accounting data provided superior forecasts of the market determined risk measure for the time periods studied. In summary, this study will provide some additional insight into the interaction between accounting data and market price variables and will help to provide a foundation for structuring the accounting system in a way that will facilitate decisions by investors.

        Innovative Approach for Forecasting Corporate Default Risk       Submitted To: Journal of Global Economy                              By: Prashanta Kumar Behera, PhD                              Email: pkb_behera@yahoo.in . Ph : 91+8108932693Abstract: Present time corporate default risk parameters are dynamic in nature and understanding how these parameters change in time is a fundamental task for risk management. In this research paper I am trying to forecast for corporate default rates.  I work with historical credit migrations data to construct some time series of interest and to visualize default rates dynamics and also, I use some of the series constructed and some additional data to fit a forecasting model for corporate default rates and to shows some back testing and stress testing. A linear regression model for corporate default rates is presented but the tools and concepts described can be used in combination with other forecasting methodologies.Keywords: Default risk, back testing, stress testing and transition matrix.

This article provides a new approach to modeling dependent defaults in a portfolio. Our top-down approach involves modeling the defaults of a set of firms and then allocating the aggregate default risk in each set to the individual firms in the set. The major advantage of our approach is that we can easily incorporate economic factors that lead to high correlations in default intensities. Once we obtain a measure of default risk for a set of firms we apply a process called random thinning to characterize the default intensity of a single firm that is a member of the set. Each firm is assigned a portion of its set9s default risk based on firm characteristics such as leverage, asset volatility, and asset correlation. This allows both pricing of portfolios and single name credits with the ease of a reduced form model and the economic motivation of a structural model. Furthermore, we do comparative static exercises to show how the model behaves and we conduct simulations to compare it to the reduced form and structural models9 predictions of single and multi-name credit derivative prices. <b>TOPICS:</b>Accounting and ratio analysis, credit default swaps, simulations

Prior research uses the basic one-period European call-option pricing model to compute default measures for individual firms and concludes that both the size and book-to-market effects are related to default risk. For example, small firms earn higher return than big firms only if they have higher default risk and value stocks earn higher returns than growth stocks if their default risk is high. In this paper we use a more advanced compound option pricing model for the computation of default risk and provide a more exhaustive test of stock returns using univariate and double-sorted portfolios. The results show that long/short hedge portfolios based on Geske measures of default risk produce significantly larger return differentials than Merton’s measure of default risk. The paper provides new evidence that mediates between the rational and behavioral explanations of value premium.

Time-Varying Rating Standards and the Distorted Incentives of Credit Rating Agencies

The Financial Risk Meter (FRM) employs Quantile-LASSO regression to identify systemic financial risk and dependencies among tail events across financial assets. This paper establishes, both theoretically and empirically, a meaningful economic relationship between the FRM index, derived from the penalization parameter in quantile LASSO regression, and the volatility of assets' pricing kernels, the attainable maximal Sharpe ratio, and market volatility. Despite the rapid growth of the crypto market and its increasing integration with traditional financial markets, there remains a dearth of risk measures in this space. FRM @ Crypto exhibits robust predictive capabilities in anticipating future market risk, potentially filling a critical void in this market.

Is Systematic Default Risk Priced in Equity Returns?: A Cross-Sectional Analysis Using Credit Derivatives Prices

Modeling Financial Sector Joint Tail Risk in the Euro Area

SHARPE [12] AND LINTNER [7] have recently proposed models directed at the following questions: (a) What is the appropriate measure of the risk of a capital asset? (b) What is the equilibrium relationship between this measure of the asset's risk and its one-period expected return?' Lintner contends that the measure of risk derived from his model is different and more general than that proposed by Sharpe. In his reply to Lintner, Sharpe [13] agrees that their results are in some ways conflicting and that Lintner's paper supersedes his. This paper will show that in fact there is no conflict between the SharpeLintner models. Properly interpreted they lead to the same measure of the risk of an individual asset and to the same relationship between an asset's risk and its one-period expected return. The apparent conflicts discussed by Sharpe and Lintner are caused by Sharpe's concentration on a special stochastic process for describing returns that is not necessarily implied by his asset pricing model. When applied to the more general stochastic processes that Lintner treats, Sharpe's model leads directly to Lintner's conclusions.

Market makers are unique entities in a market ecosystem. Unlike other participants that have exposure (either speculative or endogenous) to potential future states of the world, market making agents either endeavor to secure a risk-free profit or to facilitate trade that would otherwise not occur. In this thesis we present a principled theoretical framework for market making along with applications of that framework to different contexts. We begin by presenting a synthesis of two concepts—automated market making from the artificial intelligence literature and risk measures from the finance literature—that were developed independently. This synthesis implies that the market making agents we develop in this thesis also correspond to better ways of measuring the riskiness of a portfolio—an important application in quantitative finance. We then present the results of the Gates Hillman Prediction Market (GHPM), a fielded large-scale test of automated market making that successfully predicted the opening date of the new computer science buildings at CMU. Ranging over 365 possible opening days, the market's large event partition required new advances like a novel span-based elicitation interface. The GHPM uncovered some practical flaws of automated market makers; we investigate how to rectify these failures by describing several classes of market makers that are better at facilitating trade in Internet prediction markets. We then shift our focus to notions of profit, and how a market maker can trade to maximize its own account. We explore applying our work to one of the largest and most heavily-traded markets in the world by recasting market making as an algorithmic options trading strategy. Finally, we investigate optimal market makers for fielding wagers when good priors are known, as in sports betting or insurance.

The Power of Information How Portfolio Weights Influence Investorss Asset Allocation

ABSTRACT:In this study, we examine the impact of state antipredatory lending laws (APLs) on neighborhood foreclosure and delinquency rates using a set of panel data regression models. We find strong evidence that neighborhoods have lower default rates in states with laws that extended federal coverage and/or restricted more mortgage contract terms, in states with broader coverage of subprime loans with high points and fees, and in states with more restrictive regulations on prepayment penalties. A typical APL lowers neighborhood default rates by between 3.8% and 18%, depending on the default risk measure considered. The findings remain consistent when we restrict the analysis to cross-border neighborhoods, suggesting that they are not due solely to unobservable market variation.