Credit Default Swap Regulation in Experimental Bond Markets

Weber, Matthias; Duffy, John; Schram, Arthur

doi:10.2139/ssrn.3401706

Cited by 11 publications

(7 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the hash algorithm obtains the Merkle root value. It is highly sensitive to the transaction response and the block header's hash value change, thereby protecting the block information (Kaposty et al 2017 ; Weber et al 2019 ).…”

Section: Application Analysis Of Kmv Model and Bcmentioning

confidence: 99%

RETRACTED ARTICLE: Applying blockchain technology in the corporate bond model for default risk assessment under the marketization principle

Gao

2022

Oper Manag Res

View full text Add to dashboard Cite

This work expects to solve the problem that the traditional corporate bond model for default risk assessment has low accuracy and poor data collection and storage robustness. Firstly, this work uses the mature Kealhofer, McQuown, and Vasicek (KMV) model to evaluate the default risk of corporate bonds. Secondly, Blockchain (BC) technology's Information Security (SEC) performance in default risk assessment is studied. Finally, it analyzes the default disposal mechanism of Chinese bond corporates. The Wind database is selected to verify the proposed model. The results show that the proposed BC-based corporate bond model for default risk assessment has a good fitting effect and can meet practical needs. The BC-based data encryption only needs 14.1 ms to obtain a key from an 821-bytes public key. The encryption time and decryption time of the Number Theory Research Unit (NTRU) system are 7.9 ms and 2.9 ms, respectively. Therefore, BC technology shows good performance in data encryption and can improve ISEC. According to the KMV model, corporate bonds have certain default risks. The Distance to Default (DtD) of corporate bonds is 20.8% lower than that of companies. Thus, corporates have higher default risk. Therefore, methods are needed to reduce the default risk and improve the earnings. The finding provides important technical support for effectively reducing the default risk of bond corporates in China and ensuring the healthy development of bond markets.

show abstract

Section: Application Analysis Of Kmv Model and Bcmentioning

confidence: 99%

RETRACTED ARTICLE: Applying blockchain technology in the corporate bond model for default risk assessment under the marketization principle

Gao

2022

Oper Manag Res

View full text Add to dashboard Cite

show abstract

“…In Weber et al (2019), we analyze the role of credit default swap (CDS) regulation experimentally . We find that it is possible, in the laboratory, to introduce CDS regulation that increases the usage of CDS for hedging purposes while decreasing speculation.…”

Section: Financial Marketsmentioning

confidence: 99%

From Individual Human Decisions to Economic and Financial Policies

Weber

2022

SSRN Journal

Self Cite

View full text Add to dashboard Cite

“…Shestakova et al (2019) investigate bubble formation in markets with a mix of experienced and inexperienced traders and find some reoccurring bubbles (with a decreasing fundamental value; the bubbles that reoccur are of moderate magnitudes). Weber et al (2019) consider trade in bonds and credit default swaps and find that bubbles disappear with experience in the bond markets but not in the credit default swap markets. Weitzel that bubbles would never disappear; if we repeated the market many times, we could possibly observe that the bubbles disappear (we discuss this in more detail in Section 3.2).…”

Section: Experience and Bubblesmentioning

confidence: 99%

Experience Does not Eliminate Bubbles: Experimental Evidence

Kopányi-Peuker¹,

Weber²

2018

Preprint

Self Cite

View full text Add to dashboard Cite

We study the role of experience in the formation of asset price bubbles. Therefore, we conduct two related experiments. One is a call market experiment in which participants trade assets with each other. The other is a learning-to-forecast experiment in which participants only forecast future prices, while the trade, which is based on these forecasts, is computerized. Each experiment comprises three treatments that vary the amount of information about the fundamental value that participants receive. Each market is repeated three times. In both experiments and in all treatments, we observe sizable bubbles. These bubbles do not disappear with experience. Our findings in the call market experiment stand in contrast to the literature. Our findings in the learning- to-forecast experiment are novel. Interestingly, the shape of the bubbles is different between the two experiments. We observe flat bubbles in the call market experiment and boom-and-bust cycles in the learning-to-forecast experiment.

show abstract

Credit Default Swap Regulation in Experimental Bond Markets

Cited by 11 publications

References 38 publications

RETRACTED ARTICLE: Applying blockchain technology in the corporate bond model for default risk assessment under the marketization principle

RETRACTED ARTICLE: Applying blockchain technology in the corporate bond model for default risk assessment under the marketization principle

From Individual Human Decisions to Economic and Financial Policies

Experience Does not Eliminate Bubbles: Experimental Evidence

Contact Info

Product

Resources

About