Decision and Value Theory.

Credit default swaps (CDS) have been growing in importance in the global financial markets. However, their role has been hotly debated, in industry and academia, particularly since the credit crisis of 2007-2009. We review the extant literature on CDS that has accumulated over the past two decades. We divide our survey into seven topics after providing a broad overview in the introduction. The second section traces the historical development of CDS markets and provides an introduction to CDS contract definitions and conventions. The third section discusses the pricing of CDS, from the perspective of no-arbitrage principles, structural, and reduced-form credit risk models. It also summarizes the literature on the determinants of CDS spreads, with a focus on the role of fundamental credit risk factors, liquidity and counterparty risk. The fourth section discusses how the development of the CDS market has affected the characteristics of the bond and equity markets, with an emphasis on market efficiency, price discovery, information flow, and liquidity. Attention is also paid to the CDS-bond basis, the wedge between the pricing of the CDS and its reference bond, and the mispricing between the CDS and the equity market. The fifth section examines the effect of CDS trading on firms' credit and bankruptcy risk, and how it affects corporate financial policy, including bond issuance, capital structure, liquidity management, and corporate governance. The sixth section analyzes how CDS impact the economic incentives of financial intermediaries. The seventh section reviews the growing literature on sovereign CDS and highlights the major differences between the sovereign and corporate CDS markets. In the eight section, we discuss CDS indices, especially the role of synthetic CDS index products backed by residential mortgage-backed securities during the financial crisis.We close with our suggestions for promising future research directions on CDS contracts and markets.

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Credit Default Swaps: A Survey

We investigate the impact of COVID-19 on the Indian financial market and compare it with the outcomes of two recent structural changes of the Indian economy: demonetization and implementation of th...

https://www.tandfonline.com/doi/pdf/10.1080/1540496X.2020.1785425

Does the Indian Financial Market Nosedive because of the COVID-19 Outbreak, in Comparison to after Demonetisation and the GST?

We provide a synthesis of the empirical evidence on market liquidity. The liquidity measurement literature has established standard measures of liquidity that apply to broad categories of market microstructure data. Specialized measures of liquidity have been developed to deal with data limitations in specific markets, to provide proxies from daily data, and to assess institutional trading programs. The general liquidity literature has established local cross-sectional patterns, global cross-sectional patterns, and time-series patterns. Commonality in liquidity is prevalent. Certain exchange designs enhance market liquidity: a limit order book for high volume markets, a hybrid exchange for low volume markets, and multiple competing exchanges. Automatic execution increases speed, but increases spreads. A tick size reduction yields a large improvement in liquidity. Providing ex-post transparency to an otherwise opaque market dramatically improves liquidity. Opening up the limit order book improves liquidity. Regulatory reforms that increase the number of competitive alternatives, move towards linking them up, and level the playing field between exchanges improves liquidity. High-frequency traders trade in both a passive, liquidity-supplying manner and an aggressive, liquidity-demanding manner. Their overall impact improves both liquidity and price efficiency, but concerns remain regarding occasional trading glitches, order anticipation strategies, and latency arbitrage at the expense of slow traders. The liquidity and corporate finance literature provides abundant evidence that liquidity is beneficial in many corporate settings: liquidity increases the power of governance via exit, reduces the cost of governance via intervention, facilitates the entrance of informed traders who produce valuable information about the firm, enhances the effectiveness of equity-based compensation to managers, reduces the cost of equity financing, mitigates trading frictions investors encounter when trading in the market to recreate a preferred payout policy, and lowers the immediate transaction costs and subsequent liquidity costs for firms conducting large share repurchases. Further, the influence goes both ways. There is evidence that firms influence their own liquidity through a broad range of corporate decisions including internal governance standards, equity issuance form and pricing, share repurchases, acquisition targets, and disclosure timeliness and quality. The literature on liquidity and asset pricing demonstrates that both average liquidity cost and liquidity risk are priced, liquidity enhances market efficiency, and liquidity strengthens the arbitrage linkage between related markets. We conclude with directions for future research.

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The Empirical Analysis of Liquidity

In the present paper we study the optimal cutting strategy { τ 1 , τ 2 , …} for an ongoing forest. By using stochastic impulse control we show how Faustmann's formula can be generalized to stochastic growing forests. The paper extends and clarifies previous studies by Miller and Voltaire (1983), Clarke and Reed (1989), and Reed and Clarke (1990).

The Stochastic Rotation Problem - A Generalization of faustmann's Formula to Stochastic Forest Growth

Mean–Variance portfolio selection in presence of infrequently traded stocks

This paper introduces a new temperature index, which can suitably represent the underlying of a weather derivative. Such an index is defined as the weighted mean of daily average temperatures measured in different locations. It may be used to hedge volumetric risk, that is the effect of unexpected fluctuations in the demand/supply for some specific commodities—of agricultural or energy type, for example—due to unfavorable temperature conditions. We aim at exploring the long term memory property of the volatility of such an index, in order to assess whether there exist some long-run paths and regularities in its riskiness. The theoretical part of the paper proceeds in a stepwise form: first, the daily average temperatures are modeled through autoregressive dynamics with seasonality in mean and volatility; second, the assessment of the distributional hypotheses on the parameters of the model is carried out for analyzing the long term memory property of the volatility of the index. The theoretical results suggest that the single terms of the index drive the long memory of the overall aggregation; moreover, interestingly, the proper selection of the parameters of the model might lead both to cases of persistence and antipersistence. The applied part of the paper provides some insights on the behaviour of the volatility of the proposed index, which is built starting from single daily average temperature time series.

/pdf/exploring-the-financial-risk-of-a-temperature-index-a-16lkoh8ykl.pdf

Exploring the financial risk of a temperature index: a fractional integrated approach

Single-name Credit Default Swaps (CDS) are considered the main providers of direct information related with a reference entity’s creditworthiness and, for this reason, they have often been the core of news on the current financial crisis. The academic research has focused mainly on the capacity of CDS in anticipating agencies’ official rating changes and—in this respect—on their superior signalling power, compared to bond and stock markets. The aim of this work is, instead, to investigate the ability of fluctuations in CDS indexes in anticipating the occurrence of stock market crises. Our goal is to show that CDS indexes may provide investors and institutions with early warning signals of financial distresses in the stock market. We make use of a Markov switching model with states characterized by increasing levels of volatility and compare the times in which the first switch in a high volatility state occurs, respectively, in CDS and stock market index quotes. The data set consists of daily closing quotes for 5 years CDS and stock market index prices, covering the time period from 2004 to 2010. In order to capture possible geographic differences in CDS index capacity of foreseeing stock market distresses, data referring to two different regions, Europe and United States, are analyzed.

Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective

In this paper, we search whether the Benford’s law is applicable to monitor daily changes in sovereign credit default swaps (CDS) quotes, which are acknowledged to be complex systems of economic content. This test is of paramount importance since the CDS of a country proxy its health and probability to default, being associated to an insurance against the event of its default. We fit the Benford’s law to the daily changes in sovereign CDS spreads for 13 European countries – both inside and outside the European Union and European Monetary Union. Two different tenors for the sovereign CDS contracts are considered: 5 years and 10 years – the former being the reference and most liquid one. The time period under investigation is 2008–2015 which includes the period of distress caused by the European sovereign debt crisis. Moreover, (i) an analysis over relevant sub-periods is carried out; (ii) several insights are also provided by implementing the tracking of the Benford’s law over moving windows. The main test for checking the conformance to Benford’s law is – as usual – the χ2 test, whose values are presented and discussed for all cases. The analysis is further completed by elaborations based on Chebyshev’s distance and Kullback and Leibler’s divergence. The results highlight differences by countries and tenors. In particular, these results suggest that liquidity seems to be associated to higher levels of distortion. Greece – representing a peculiar case – shows a very different path with respect to the other European countries.

Regularities and discrepancies of credit default swaps: a data science approach through Benford's law

This paper investigates the role of CDS volatility in providing information concerning the credit quality of a company. In Castellano and D’Ecclesia (J. Financ. Decis. Mak. 2:27, 2011) a first analysis of how CDS quotes respond to rating announcements is provided and it showed that market participants do not rely much on Rating Agencies, especially during periods characterized by very high volatility, i.e. during a financial crisis. Here, a more accurate analysis of the CDS’s ability to provide timely information on the creditworthiness of reference entities is performed, estimating the volatility of CDS quotes by using Exponential GARCH(1,1) models. The event study methodology is applied to a sample of CDS quotes for US and European markets, over the period 2004–2009. Results provide an accurate understanding of market behavior in the presence of news released by Rating Agencies. Overall, market participants seem to provide timely reactions around the event date and we show that the key element of signaling is represented by the changing volatility in CDS quotes, before and after the rating event.

Rosella Castellano

Papers

Mean–Variance portfolio selection in presence of infrequently traded stocks

Exploring the financial risk of a temperature index: a fractional integrated approach

Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective

Regularities and discrepancies of credit default swaps: a data science approach through Benford's law

CDS volatility: the key signal of credit quality