Modeling non-normal corporate bond yield spreads by copula

Kim, Jong Min; Jung, Hojin

doi:10.1016/j.najef.2020.101210

Cited by 10 publications

(7 citation statements)

References 57 publications

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“…The results of the correlation analysis indicate that the higher the coupon rate, the less quantity of corporate bonds will be purchased and the smaller the amount of borrowed funds will be attracted to the enterprise. This contradicts the conclusion of Kim J., Kim D., and Jung H. [29], who argue that the coupon rate increases non-callable yield spreads, and hence the investment attractiveness of corporate bonds. However, the negative interdependence can be explained by investors' distrust of inflated coupon rates in the Ukrainian market, which is accompanied by high risk, especially given that the surveyed corporate bonds are unsecured.…”

Section: Discussionmentioning

confidence: 59%

“…Another indicator that is taken into account by investors in the decision-making process for the purchase of certain corporate bonds is the yield, which depends on the above factors. Many scientists pay attention to identifying factors shaping yield-to-maturity [26][27][28] and yield spreads [29,30]. Instead of focusing on the yield of corporate bonds, we offer to focus on demand.…”

Section: Disadvantages For the Investor Advantages For The Investormentioning

confidence: 99%

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Ensuring the issuance of investment-attractive corporate bonds

et al. 2021

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Despite the fact that the scientific literature pays considerable attention to ensuring the investment attractiveness of national corporate bond markets based on macro-environmental factors, as well as individual companies – based on micro-environmental factors, the issue of optimizing the characteristics of corporate bonds in the prospectus remains insufficiently disclosed. However, coupon rate, price and maturity are the basic indicators that investors take into account when deciding to purchase corporate bonds, so they need more detailed research. approach to ensuring the issuance of investment-attractive corporate bonds, based on the use of indicators of companies with the highest level of demand on the stock market to build a matrix of coupon rate, price and maturity of corporate bond, the use of which allows to establish the optimal ratio between these characteristics. Enterprises issue corporate bonds to attract additional financial resources in their activities, so they are interested in ensuring the investment attractiveness of these securities. The investment attractiveness of corporate bonds depends on their own characteristics, as well as on micro- and macro-environmental factors. The most affordable way to ensure the investment attractiveness of corporate bonds is to establish the optimal characteristics of bonds in the prospectus. The companies whose corporate bonds are in the highest demand on the stock market have the optimal ratio between coupon rate, price and maturity. Determining the trend of ensuring a balance between these indicators of leading companies allows us to establish a model of decision-making by investors in a particular market of corporate bonds.

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Section: Discussionmentioning

confidence: 59%

Section: Disadvantages For the Investor Advantages For The Investormentioning

confidence: 99%

Ensuring the issuance of investment-attractive corporate bonds

et al. 2021

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“…Furthermore, optimal parametric copula model selection (related goodness-of-fit tests), which affects tail dependence, is another discussion point (see also Weiß 2013). Recent applications in the fixed income market have usually been through developed markets or credit risks (see Kim et al 2020, Yang et al 2020, Chao and Zou 2018, Otani and Imai 2018, Bekiros et al 2018, Benlagha 2014, Chen et al 2014 The other technique, wavelet transformation, also drew attention, in recent years. Especially in stock markets and commodities, the wavelet method has been frequently applied to investigate interdependence and coherence.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Applying multivariate-fractionally integrated volatility analysis on emerging market bond portfolios

Demirel

Ünal

2020

Financ Innov

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This study examines emerging market (EM) local bonds from a portfolio risk perspective and suggests methodologies for risk evaluation, on which the literature is limited. Despite the growth of EM bond funds in recent years, comprehensive studies regarding this industry have been scarce. In light of this, 203 different local bonds of EM countries—Indonesia, Brazil, India, South Africa, Mexico, and Turkey—are elaborated in terms of return, volatility, and cross-correlation features. This study focuses on an untouched field—long memory properties—and the application of fractional models to EM bond portfolios. Based on the outcomes of a dynamic conditional correlation and fractionally integrated generalized autoregressive conditional heteroscedasticity approach and related value at risk analysis, the study finds that fractional models are useful tools for risk management, as they deliver satisfactory empirical results for several static and dynamic versions of EM bond portfolios.

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“…The GCMR method to find high dependence between the exchange rates and daily crude oil prices was considered in [18]. A multiple linear regression model made to measure the relationship between callable and non-callable corporate bond yields and explanatory variables such as liquidity and coupon rate experienced the problems of heteroscedasticity and the nonnormal distribution of the residuals [19]. To avoid the problems caused by using multiple linear regression with the movie data, we propose using a copula method (GCMR) to analyze the data.…”

Section: Introductionmentioning

confidence: 99%

Examining Factors That Affect Movie Gross Using Gaussian Copula Marginal Regression

Eklund

Kim

2022

Forecasting

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In this research, we investigate the relationship between a movie’s gross and its budget, year of release, season of release, genre, and rating. The movie data used in this research are severely skewed to the right, resulting in the problems of nonlinearity, non-normal distribution, and non-constant variance of the error terms. To overcome these difficulties, we employ a Gaussian copula marginal regression (GCMR) model after adjusting the gross and budget variables for inflation using a consumer price index. An analysis of the data found that year of release, budget, season of release, genre, and rating were all statistically significant predictors of movie gross. Specifically, one unit increases in budget and year were associated with an increase in movie gross. G movies were found to gross more than all other kinds of movies (PG, PG-13, R, and Other). Movies released in the fall were found to gross the least compared to the other three seasons. Finally, action movies were found to gross more than biography, comedy, crime, and other movie genres, but gross less than adventure, animation, drama, fantasy, horror, and mystery movies.

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Modeling non-normal corporate bond yield spreads by copula

Cited by 10 publications

References 57 publications

Ensuring the issuance of investment-attractive corporate bonds

Ensuring the issuance of investment-attractive corporate bonds

Applying multivariate-fractionally integrated volatility analysis on emerging market bond portfolios

Examining Factors That Affect Movie Gross Using Gaussian Copula Marginal Regression

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