Endogenous trading in credit default swaps

Understanding Decreasing CDS Curves

Abstract. The objective of this article is theoretical and methodological justifying of determining algorithm of the cost of debt capital for enterprises functioning in emerging markets (EM). The methods of research: analysis and synthesis, system analysis, comparative analysis, empirical and statistical methods, factor analysis. Results. In this article key determinants of interest rates on debt capital for enterprises and their impact on the procedure of discount rate calculation are determined. The issue of the cost of debt calculation of enterprises in condition of absence of complete information concerning systematic and non-systematic crediting risks is studied. Differences between interest rate on the loan fixed in credit agreement and expected by creditors the cost of debt are identified. It is determined that the key factor impacting the deviation level of market value of debt capital from the nominal, and respectively, deviation of the cost of debt from the cost of capital is probability of default (PD). At the minimum values of PD, the contract interest rate corresponds to the rate of cost of debt and it is advisable to use it for discount rate calculation. Critical analysis of alternative methodological approaches of the cost of debt calculation is made. Ways of integrating of market information concerning credit default swaps into the process of expected cost of debt calculation are justified. Factors of shadowing of rates of the cost of debt and ways of reducing of shadow transactions’ level in the credit market are identified. Conclusions. At high PD values, expected by market premium for default risk may exceed the contract interest rate, which necessitates constant monitoring of credit risks and appropriate adaptation of interest rates. In the paper the algorithm of such adaptation are proposed. It is shown that in the case of non-use of interest rates adjustment taking into account changes in PD, CDS and LGD, premium for creditors’ systematic risk can differ significantly from market values of similar enterprises (peer-group), and estimated value of the cost of debt can acquire negative values. Contract (promised) interest rate should be set in such way that the premium for systematic risk of providing debt capital will be at the level of similar companies and does not change significantly as a result of probability of default changes. If in practice the opposite situation occurs, it is the evidence of contract interest rate shadowing, absence of effective system of assessment and management of credit risks. For solving the problem of interest rate transparency and filling of information gaps concerning PD borrowers in EM countries, should intensify CDS market. Keywords: debt capital, default probability, non-performing loans, credit default swap, credit spread, debt capital premium, shadow economy. JEL Classification E47 Formulas: 16; fig.: 0; tabl.: 3; bibl.: 15.

ABSTRACTMost studies of the short sales ban of UK financial stocks from September 2008 to January 2009 fail to control for the UK’s worst ever banking crisis and the underlying increase in risk. This paper studies the ban’s impact on the 13 large financials with credit default swaps (CDS) and 20 smaller stocks without CDS. The results reveal that returns of banned stocks Granger cause CDS returns in the pre- and post-ban periods, but causality runs from CDS to stock returns during the ban period. Underlying risk proxied by the CDS probability of default increased during the ban and the immediate pre- and post-ban periods which highlights an endogeneity problem ignored in some studies. This increased risk provides a plausible rationale for why CDS and related equity bid-ask spreads - which increased during the ban period – failed to fall significantly in the post-ban period. Panel regression results indicate that probability of default was an important economic determinant of stock bid-ask spreads during the ban period. Finally, our results suggest that the ban offered direct price support for the smaller non-CDS stocks during the ban period and indirect support for CDS stocks from their pre-ban to their post-ban levels.

A Framework for Extracting the Probability of Default from Listed Stock Option Prices

Credit default swaps are the most popular of all the credit derivative contracts traded. Their purpose is to provide financial protection against losses incurred following a credit event for a reference obligation or reference issuer. Replication arguments attempting to link credit default swaps to the price of the underlying credits are generally used by the market as a first estimate for determining the price at which a credit default swap should trade. The replication argument, however, is flawed, but fortunately there exist superior models that can be used in pricing these instruments. Keywords: contractual spread; credit default swap (CDS); credit event; default probability; default swap; default swap basis; mark-to-market value; par asset swap spread; Poisson process; static replication; survival probability

This paper investigates the multifractal behavior of the probability of default (PD) of real sector firms and Turkey sovereign credit default swap (CDS). Moreover, we emphasize the co-movements of Hölder exponents during the financial crisis periods. For this reason, first, it is necessary to figure out the default probabilities of real sector firms. The default probability is evaluated weekly by the methodology of Moody’s Analytics, which is a commonly used approach, in which the market value of a firm is a call option written on its total assets. Multifractal detrended fluctuation analysis (MF-DFA), multifractal detrended cross-correlation analysis (MF-DCCA) and multifractal detrended moving average cross-correlation analysis (MF-X-DMA) techniques are applied to identify the multifractal behavior of the large-scale fluctuations of PDs and CDSs. In this way, we can evaluate the local Hurst exponents. Besides, the oscillation method is employed to estimate the pointwise and local Hölder exponents. In the period between January 2001 and March 2018, the structure of dynamic co-movements of Hölder exponents is determined by applying wavelet coherency methodology and the relations in crisis period are revealed. The selected period covers the crises with structural differences: Turkey banking crisis, the US sub-prime mortgage crisis and the European sovereign debt crisis that occurred in 2001, 2008 and 2009, respectively. Besides, during the periods of financial crises, among the local Hölder exponents, severely correlated large scales show multifractal features, and hence vector fractionally autoregressive integrated moving average (VFARIMA) forecasting provides better results than scalar models.

Probability of default (PD) estimation is essential to the calculation of expected credit loss under the Basel III framework and the International Financial Reporting Standard 9. Gross domestic product (GDP) growth has been adopted as a key determinant in PD estimation models. However, PD models with a GDP covariate may not perform well under aberrant (i.e., outlier) conditions such as the COVID-19 pandemic. This study explored the robustness of a PD model with a GDP determinant (the test model) in comparison with that of a PD model with a credit default swap index (CDX) determinant (the alternative model). The test model had a significantly greater ratio of increase in Akaike information criterion than the alternative model in comparisons of the fit performance of models including 2020 data with that of models excluding 2020 data (i.e., that do not cover the COVID-19 pandemic). Furthermore, the Cook’s distance of the 2020 data of the test model was significantly greater than that of the alternative model. Therefore, the test model exhibited a serious robustness issue in outlier scenarios, such as the COVID-19 pandemic, whereas the alternative model was more robust. This finding opens the prospect for the CDX to potentially serve as an alternative to GDP in PD estimation models.

Dynamic Credit Default Swaps Curves in a Network Topology

The major sources of credit risk are default probability and recovery. Together with interest rate risk, they determine the price of credit derivatives. In this article, we study the relative importance of these sources by testing pair-nested structural models with data from credit default swaps. By comparing pairs of models that are nested in terms of their assumptions about these sources (one model is a special case, or restriction, of the other), we are able to understand what causes a pricing model to succeed or fail. Using credit default swap data from 2/15/2000 through 4/8/2003, we find that random interest rates and random (asset value) recovery are important assumptions for achieving accurate pricing, while continuous default times (as opposed to a single default time) is not. <b>TOPICS:</b>Risk management, credit risk management

We consider the valuation of credit default swaps (CDSs) under an extended version of Merton’s structural model for a firm’s corporate liabilities. In particular, the interest rate process of a money market account, the appreciation rate, and the volatility of the firm’s value have switching dynamics governed by a finite-state Markov chain in continuous time. The states of the Markov chain are deemed to represent the states of an economy. The shift from one economic state to another may be attributed to certain factors that affect the profits or earnings of a firm; examples of such factors include changes in business conditions, corporate decisions, company operations, management strategies, macroeconomic conditions, and business cycles. In this article, the Esscher transform, which is a well-known tool in actuarial science, is employed to determine an equivalent martingale measure for the valuation problem in the incomplete market setting. Systems of coupled partial differential equations (PDEs) satisfied by the real-world and risk-neutral default probabilities are derived. The consequences for the swap rate of a CDS brought about by the regimeswitching effect of the firm’s value are investigated via a numerical example for the case of a two-state Markov chain. We perform sensitivity analyses for the real-world default probability and the swap rate when different model parameters vary. We also investigate the accuracy and efficiency of the PDE approach by comparing the numerical results from the PDE approach to those from the Monte Carlo simulation.

It has already been indicated in Chapter 1.2 that credit rationing may occur if p, the expected gross return per loan of a bank, is not a monotonically increasing function of the loan rate of interest r. This could happen if the probability of default is an increasing function of r, and if this negative effect of raising r outweighs its positive effect on p. In this section it is shown more precisely how the non-monotonicity of p with respect to r creates the possibility of equilibrium credit rationing. The following sections present various mechanisms, based on asymmetric information implying adverse selection and moral hazard, which may induce the existence of a “bank-optimal” loan rate where p reaches a maximum.

We extend the theoretical model of external corporate financing to the case when the buyers of the borrowing firm may default during the financing period. In our setup there is an asymmetric information and hence moral hazard between the lender and the borrower concerning the efforts of the borrower. We define the optimal debt contract in two cases. In the symmetric case the lender and the borrower has the same information about the buyer, its probability of default. In the asymmetric case the borrower learns whether the buyer will pay or not before choosing her level of efforts. We prove that in the asymmetric case the borrowing capacity and the welfare of the society is weakly smaller than in the symmetric case. We also show that the nonnegative default risk of a buyer weakly decreases borrowing capacity compared to the case when the buyer pays for sure. However, it turns out that having a risky buyer might increase borrowing capacity and welfare.

We use Google internet search volumes to measure households’ pessimism about overall market-wide credit health in the economy and show that this “household default sentiment” is positively correlated with the credit default swap (CDS) spread level in the market. However, while household default sentiment might drive the cost of credit to some degree, either directly or indirectly through its effect on the stock market, we find the stock market’s opinion about the credit risk in the economy (default probabilities backed out from structural models) to be much more important in explaining credit spreads. The rather weak link between household sentiment and CDS spreads, meanwhile, is consistent with the almost complete absence of retail investors (households) in the institutional investor-dominated credit derivatives market. The results are essentially the same, whether we look at market-wide CDS indexes or single-name CDS contracts, and whether we exclude the financial crisis or not.

In this paper we examine the moral hazard of credit derivatives that made them the roll boosters of the financial crisis, and develop a model of optimal contract design on credit default swap transaction to review the function of the financial instruments and the optimal contract aiming to control the moral hazard. The research presents that credit default swap transaction can optimize allocation of the credit risk, improve the bank’s return, and expanse channels of the investors. However, it reduces the bank’s efforts of monitoring credit assets, which accumulates and increases credit risks. By introducing the partial protection mechanism, we obtain an optimal contract which could effectively control the moral hazard.

Bank credit default swaps and deposit insurance around the world