NUMERICAL PROCEDURES FOR A WRONG WAY RISK MODEL WITH LOGNORMAL HAZARD RATES AND GAUSSIAN INTEREST RATES

2013 ◽  
Vol 16 (08) ◽  
pp. 1350049 ◽  
Author(s):  
LESLIE NG
Keyword(s):  
Interest Rates ◽  
Model Calibration ◽  
Risk Model ◽  
Data Availability ◽  
Hazard Rates ◽  
Single Factor ◽  
Default Intensity ◽  
Credit Default ◽  
Short Rate Models ◽  
Intensity Model

In this work, we present some numerical procedures for a wrong way risk model that can be used for credit value adjustment (CVA) calculations. We look at a model that uses a multi-factor Hull–White model for interest rates and a single-factor lognormal Black–Karasinski default intensity model for counterparty credit, where the default intensity driver is correlated with all interest rate drivers. We describe how a trinomial tree-based approach for implementing single factor short rate models by Hull and White (1994) can be modified and used to calibrate the intensity model to credit default swaps (CDSs) in the presence of correlation. We also provide approximate pricing methods for CDS options and single swap contingent CDS contracts. The latter methods could also be used for model calibration purposes subject to data availability.

CREDIT DEFAULT SWAPS IN TWO-DIMENSIONAL MODELS WITH VARIOUS INFORMATIONS FLOWS

2020 ◽  
Vol 23 (02) ◽  
pp. 2050010
Author(s):  
PAVEL V. GAPEEV ◽  
MONIQUE JEANBLANC
Keyword(s):  
Financial Market ◽  
Risk Model ◽  
Credit Default Swaps ◽  
Linear Combinations ◽  
Brownian Motions ◽  
No Arbitrage ◽  
Default Intensity ◽  
Credit Default ◽  
Geometric Brownian Motions ◽  
Credit Risk Model

We study a credit risk model of a financial market in which the dynamics of intensity rates of two default times are described by linear combinations of three independent geometric Brownian motions. The dynamics of two default-free risky asset prices are modeled by two geometric Brownian motions which are dependent of the ones describing the default intensity rates. We obtain closed form expressions for the no-arbitrage prices of both risk-free and risky credit default swaps given the reference filtration initially and progressively enlarged by the two default times. The accessible default-free reference filtration is generated by the standard Brownian motions driving the model.

Hedging of a credit default swaption in the CIR default intensity model

2010 ◽  
Vol 15 (3) ◽  
pp. 541-572 ◽  
Author(s):  
Tomasz R. Bielecki ◽  
Monique Jeanblanc ◽  
Marek Rutkowski
Keyword(s):  
Default Intensity ◽  
Credit Default ◽  
Intensity Model

scholarly journals The Relative Tax Gap Hypothesis: An Exploratory Analysis and Application to U.S. Financial Markets

2020 ◽  
Vol 23 (1) ◽  
pp. 35-52
Author(s):  
Richard J. Cebula
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Tax Evasion ◽  
Income Tax ◽  
Real Interest Rate ◽  
Strong Support ◽  
Current Data ◽  
Data Availability ◽  
Ex Ante ◽  
Tax Gap

This study empirically investigates the “relative tax gap hypothesis,” which posits that the greater the size of the relative tax gap, the greater the degree to which the U.S. Treasury must borrow from domestic and/or other credit markets and hence the higher the ex ante real interest rate yield on the Bellwether 30 year U.S. Treasury bond. The study uses the most current data available for computing what is referred to here as the “relative tax gap,” which is the ratio of the aggregate tax gap (the loss in federal income tax revenue resulting from personal income tax evasion) to the GDP level. For each year of the study period, the nominal value of the tax gap is scaled by the nominal GDP level and expressed as a percentage. The study period runs from 1982 through 2016, reflecting data availability for all of the variables. The estimation results provide strong support for the hypothesis. In addition, in separate estimations, evidence is provided that the relative tax gap also acts to elevate the ex ante real interest rate yield on Moody’s Baa-rated long-term corporate bonds. It logically follows, then, that to the extent that a greater relative tax gap leads to higher ex ante real interest rates, it may contribute to the crowding out of corporate investment in new plant equipment associated heretofore with government budget deficits per se.

scholarly journals The Determinants of CDS Spreads in Multiple Industry Sectors: A Comparison between the US and Europe

Risks ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 89 ◽  
Author(s):  
Jatin Malhotra ◽  
Angelo Corelli
Keyword(s):  
Interest Rates ◽  
Global Financial Crisis ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Credit Default ◽  
The Us ◽  
Before And After ◽  
The Global Financial Crisis ◽  
Industry Sectors ◽  
The Relationship

The paper analyzes the relationship between the credit default swaps (CDS) spreads for 5-year CDS in Europe and US, and fundamental macroeconomic variables such as regional stock indices, oil prices, gold prices, and interest rates. The dataset includes consideration of multiple industry sectors in both economies, and it is split in two sections, before and after the global financial crisis. The analysis is carried out using multivariate regression of each index vs. the macroeconomic variables, and a Granger causality test. Both approaches are performed on the change of value of the variables involved. Results show that equity markets lead in price discovery, bidirectional causality between interest rate, and CDS spreads for most sectors involved. There is also bidirectional causality between stock and oil returns to CDS spreads.

Modeling the term structure of interest rates with general short-rate models

2003 ◽  
Vol 7 (3) ◽  
pp. 323-335 ◽  
Author(s):  
Hideyuki Takamizawa ◽  
Isao Shoji
Keyword(s):  
Interest Rates ◽  
Term Structure ◽  
Short Rate Models

scholarly journals A Raroc Valuation Scheme for Loans and Its Application in Loan Origination

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 63 ◽  
Author(s):  
Bernd Engelmann ◽  
Ha Pham
Keyword(s):  
Interest Rates ◽  
Finite Interval ◽  
Credit Default Swap ◽  
Credit Quality ◽  
Credit Default ◽  
Return On Capital ◽  
The Interest Rate ◽  
The Individual ◽  
Swap Spreads ◽  
Cost Components

In this article, a risk-adjusted return on capital (RAROC) valuation scheme for loans is derived. The critical assumption throughout the article is that no market information on a borrower’s credit quality like bond or CDS (Credit Default Swap) spreads is available. Therefore, market-based approaches are not applicable, and an alternative combining market and statistical information is needed. The valuation scheme aims to derive the individual cost components of a loan which facilitates the allocation to a bank’s operational units. After its introduction, a theoretical analysis of the scheme linking the level of interest rates and borrower default probabilities shows that a bank should only originate a loan, when the interest rate a borrower is willing to accept is inside the profitability range for this client. This range depends on a bank’s internal profitability target and is always a finite interval only or could even be empty if a borrower’s credit quality is too low. Aside from analyzing the theoretical properties of the scheme, we show how it can be directly applied in the daily loan origination process of a bank.

scholarly journals Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components

2019 ◽  
Vol 12 (3) ◽  
pp. 129
Author(s):  
Alfonso Novales ◽  
Alvaro Chamizo
Keyword(s):  
Risk Factor ◽  
Credit Risk ◽  
Interest Rates ◽  
Explanatory Power ◽  
Credit Default Swap ◽  
Global Risk ◽  
Additional Information ◽  
The North ◽  
Credit Default ◽  
Highly Correlated

We provide a methodology to estimate a global credit risk factor from credit default swap (CDS) spreads that can be very useful for risk management. The global risk factor (GRF) reproduces quite well the different episodes that have affected the credit market over the sample period. It is highly correlated with standard credit indices, but it contains much higher explanatory power for fluctuations in CDS spreads across sectors than the credit indices themselves. The additional information content over iTraxx seems to be related to some financial interest rates. We first use the estimated GRF to analyze the extent to which the eleven sectors we consider are systemic. After that, we use it to split the credit risk of individual firms into systemic, sectorial, and idiosyncratic components, and we perform some analyses to test that the estimated idiosyncratic components are actually firm-specific. The systemic and sectorial components explain around 65% of credit risk in the European industrial and financial sectors and 50% in the North American sectors, while 35% and 50% of risk, respectively, is of an idiosyncratic nature. Thus, there is a significant margin for portfolio diversification. We also show that our decomposition allows us to identify those firms whose credit would be harder to hedge. We end up analyzing the relationship between the estimated components of risk and some synthetic risk factors, in order to learn about the different nature of the credit risk components.

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