Forecasting and backtesting systemic risk in the cryptocurrency market

Fang, Sheng; Cao, Guangxi; Egan, Paul

doi:10.1016/j.frl.2023.103788

Cited by 9 publications

(6 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The comparison between the Basel IV model and the Simplified specification in terms of the capital levels brings about a handful of implications and, in this sense, a first glance at Columns [11] and [21] shows that the official formula nearly triples its alternative due to the stressed calibration, thus taking the LCR to levels in excess of 4.65 in contrast to the figure of the more limited approach, 1.82. Consequently, both models provide coverage against the significant market slumps recorded after the pandemic, albeit the alternative in (20) would appear somewhat tight, with only 82% to spare.…”

Section: Resultsmentioning

confidence: 99%

“…Table 5.7 deals with the concept of the capital floor, in terms of the comparison between SA, the official IMA and the Simplified Specification. As Columns [4] and [6] convey, the average coverage 20 of the capital floor established by the SA reaches 88% in the case of the official IMA, descending to 27% for the Simplified Specification. The table also shows another option, i.e., a very straightforward adaptation of (20), increasing the 1.5 multiple in (15) to 3 and embedding it.…”

Section: Resultsmentioning

confidence: 99%

“…The following graphs picture the performance of the MCR calculated via SA and IMA according to the BCBS mandate and the simplified formula (20). In all the portfolios the behavior is consistent: substantial capital increase for MCR's SA and IMA(BCBS) and high output floor set by the former, level that can only be attained by means of a highly leptokurtic model like EVT, and, for some portfolios like P3 and P5, IMA(BCBS) exceeds SA.…”

Section: Appendix a Portfolio Compositionmentioning

confidence: 86%

“…Appendix C 20. The author acknowledges the inconvenience of the averages; hence, it is only included for illustrative purposes given the apparent parity among the different portfolios.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Basel IV and the structural relationship between SA and IMA

Rossignolo

2024

REMEF

View full text Add to dashboard Cite

The current paper aims at ascertaining the massive overhaul of the Trading Book or Basel IV, comparing the capital requirements of the Standardized and Internal Models Approaches in market crisis context. Throughout an integral sequential analysis encompassing every step of both regimes –including several specifications for the latter-, the study finds that the radical revamp achieves its main objective: raising capital for market risks. Simultaneously, the Standardized Approach appears favored, establishing a high floor as a credible fall-back and penalizing the Internal Models with complex structures and stringent validation tests. With the general purpose apparently attained, it would be wise to review the whole process and grant some flexibility to local supervisors in its application. The investigation was focused on Mexican stock markets during Covid-19, and it is understood that extending it to more countries could bolster the results. The present article ranks among the first to study the effects of Basel IV and highlights some of its flaws, particularly the probably excessive capital levels and the crackdown on Internal Models, which could dent profits, restrict innovation and shrink credit.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Appendix a Portfolio Compositionmentioning

confidence: 86%

“…Appendix C 20. The author acknowledges the inconvenience of the averages; hence, it is only included for illustrative purposes given the apparent parity among the different portfolios.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Basel IV and the structural relationship between SA and IMA

Rossignolo

2024

REMEF

View full text Add to dashboard Cite

show abstract

“…For example, Likitratcharoen et al [15] assessed the efficiency of various VaR models in measuring risk under extreme market stress. Fang et al [16] focuses on predicting systemic risk in the cryptocurrency market, helping to understand the overall market risk associated with blockchain-based assets. Jana et al [17] examined the role of cryptocurrencies in hedging stock market risk, providing insights into their potential applications in the broader financial sector.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model

Huang,

Wang,

Chen

et al. 2024

IEEE Open J. Comput. Soc.

View full text Add to dashboard Cite

Cryptocurrency, a novel digital asset within the blockchain technology ecosystem, has recently garnered significant attention in the investment world. Despite its growing popularity, the inherent volatility and instability of cryptocurrency investments necessitate a thorough risk evaluation. This study utilizes the Autoregressive Moving Average (ARMA) model combined with the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model to analyze the volatility of three major cryptocurrencies-Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB)-over a period from January 1, 2017, to October 29, 2022. The dataset comprises daily closing prices, offering a comprehensive view of the market's fluctuations. Our analysis revealed that the value-at-risk (VaR) curves for these cryptocurrencies demonstrate significant volatility, encompassing a broad spectrum of returns. The overall risk profile is relatively high, with ETH exhibiting the highest risk, followed by BTC and BNB. The ARMA-GARCH-VaR model has proven effective in quantifying and assessing the market risks associated with cryptocurrencies, providing valuable insights for investors and policymakers in navigating the complex landscape of digital assets.

show abstract

Corporate ESG indices and stability during periods of deep concerns in financial markets

Janik,

Płuciennik

2024

Finance Research Letters

View full text Add to dashboard Cite

Forecasting and backtesting systemic risk in the cryptocurrency market

Cited by 9 publications

References 35 publications

Basel IV and the structural relationship between SA and IMA

Basel IV and the structural relationship between SA and IMA

Evaluating Cryptocurrency Market Risk on the Blockchain: An Empirical Study Using the ARMA-GARCH-VaR Model

Corporate ESG indices and stability during periods of deep concerns in financial markets

Contact Info

Product

Resources

About