Non-Linear Impact of Chinese Treasury Bond Futures on the Information Content of IRS

Yang, Wei; Ruan, Qingsong; Luo, Yin

doi:10.1142/s0219477521500516

Cited by 5 publications

(3 citation statements)

References 58 publications

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“…When the borrower has credit problems, the bank can consider increasing interest rate discounts for such customers to reduce credit risk and improve bank income. ird, the financial market is developing toward diversification; correspondingly, S Bank can hedge through financial derivatives such as exchange options and interest rate futures to realize the effective control of housing credit risk [30][31][32].…”

Section: Improving the Construction Of Bank Risk Assessmentmentioning

confidence: 99%

Investigating the Impact of Bank Housing Credit Risk Control Strategy by Blockchain Technology on the Household Consumption Plan

Liu

2022

Computational Intelligence and Neuroscience

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It is essential to solve the problem of information asymmetry in bank housing credit management, thus reducing bank operating costs and credit risk. Therefore, the present work constructs a bank housing credit blockchain alliance system based on the technical characteristics of blockchain to strengthen bank housing credit risk control. First, according to blockchain’s elements and system architecture, the application of blockchain to bank housing credit business is analyzed. On this basis, the bank housing credit risk control strategy is proposed. Finally, the mathematical model is used to investigate residents’ household consumption to explore the impact of housing credit on the household consumption plan of residents. The results show that when the educational level of the head of household is illiterate or semi-illiterate, the coefficients of participation credit (PC), nonparticipation credit (NPC), and total samples (TSs) of total household consumption are −0.064, 0.067, and 0.174, respectively; when the educational level of the head of household is primary school or junior middle school, the coefficients of PC, NPC, and TS of total household consumption are -0.026, 0.017, and 0.105, respectively; when the educational level of the head of household is high school or above, the coefficients of PC, NPC, and TS of total household consumption are 0.084, 0.073, and 0.064, respectively. The results indicate that the education level of the head of household plays a crucial role in the family consumption plan. Those with a high educational level will compromise on the best consumption decision after constantly weighing the consumption motivation and consumption thinking after obtaining the credit funds. The content reported here is vitally significant in guiding households to clarify the proportion of credit fund distribution and understand their consumption tendency.

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Section: Improving the Construction Of Bank Risk Assessmentmentioning

confidence: 99%

Investigating the Impact of Bank Housing Credit Risk Control Strategy by Blockchain Technology on the Household Consumption Plan

Liu

2022

Computational Intelligence and Neuroscience

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“…The econophysics literature has investigated multifractal cross-correlations in various financial markets. Examples of these research areas include the stock market [30,31], crude oil [32,33], cryptocurrencies [34][35][36], energy market [37,38], bond market [39], precious metals [40], and green bonds [41].…”

Section: Introductionmentioning

confidence: 99%

“…They demonstrated that China's new energy market is not efficient and has multifractal cross-correlations with other markets. Furthermore, Yang et al [39] provided additional evidence of the multifractality of financial markets by studying the treasury bond market in China. On the commodity market side, Wang et al [40] demonstrated multifractality in the Chinese Rebar market using asymmetric MFDCCA, revealing complex structures.…”

Section: Introductionmentioning

confidence: 99%

Multifractal Detrended Cross-Correlations between Green Bonds and Commodity Markets: An Exploration of the Complex Connections between Green Finance and Commodities from the Econophysics Perspective

Acikgoz,

Gokten,

Soylu

2024

Fractal Fract

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Green bonds represent a compelling financial innovation that presents a financial perspective solution to address climate change and promote sustainable development. On the other hand, the recent process of financialisation of commodities disrupts the dynamics of the commodity market, increasing its correlation with financial markets and raising the risks associated with commodities. In this context, understanding the dynamics of the interconnectivity between green bonds and commodity markets is crucial for risk management and portfolio diversification. This study aims to reveal the multifractal cross-correlations between green bonds and commodities by employing methods from statistical physics. We apply multifractal detrended cross-correlation analysis (MFDCCA) to both return and volatility series, demonstrating that green bonds and commodities exhibit multifractal characteristics. The analysis reveals long-range power-law cross-correlations between these two markets. Specifically, volatility cross-correlations persist across various fluctuations, while return series display persistence in small fluctuations and antipersistence in large fluctuations. These findings carry significant practical implications for hedging and risk diversification purposes.

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Effect of Futures Trading Restrictions on Market Efficiency: A Multifractal Analysis

Jin

et al. 2023

Fluct. Noise Lett.

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Based on the China Securities Index 300 (CSI 300 index) futures trading restrictions in 2015, this paper uses the multifractal detrending moving-average cross-correlation analysis method (MF-X-DMA) to investigate the effect of introducing futures trading restrictions on the market efficiency of CSI 300 index spot and futures markets. We begin by using multifractal detrending moving-average analysis (MF-DMA) and find that the futures trading restrictions improve spot market efficiency but decrease futures market efficiency. Moreover, we examine the cross-correlation between spot and futures markets and the information transmission process. MF-X-DMA analysis shows an increase in the level of persistent cross-correlation between spot and futures markets, and a decrease in the multifractality degree of cross-correlation, suggesting that the relationship between spot and futures markets becomes stronger and less complicated after the futures trading restrictions. Moreover, the nonlinear Granger causality test shows that futures returns do not Granger cause spot returns after the restrictions. Therefore, the futures trading restrictions may mitigate the harmful effect of speculative trading in the futures market and thus improve spot market efficiency.

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Non-Linear Impact of Chinese Treasury Bond Futures on the Information Content of IRS

Cited by 5 publications

References 58 publications

Investigating the Impact of Bank Housing Credit Risk Control Strategy by Blockchain Technology on the Household Consumption Plan

Investigating the Impact of Bank Housing Credit Risk Control Strategy by Blockchain Technology on the Household Consumption Plan

Multifractal Detrended Cross-Correlations between Green Bonds and Commodity Markets: An Exploration of the Complex Connections between Green Finance and Commodities from the Econophysics Perspective

Effect of Futures Trading Restrictions on Market Efficiency: A Multifractal Analysis

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