A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors

Tu, Anthony H.; Chen, Cathy Yi‐Hsuan

doi:10.1016/j.jempfin.2017.11.010

Cited by 6 publications

(3 citation statements)

References 57 publications

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“…Although using these information variables was beneficial, the estimated confidence intervals for VaRs were wide, thus downgrading the applicability of the model. Tu and Chen (2018) evaluated U.S. bond indices with a factor-based approach. VaR estimations of the study present that market shocks (not macroeconomic developments) primarily cause the variations.…”

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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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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“…As has been used in several other related works, we have also controlled for international effects through the use of the return of gold (COMEX 100oz Gold, GCc1) as an alternative investment or potential hedging instrument against risk for both cryptocurrency and stock market indices (Baur et al., 2018; Corbet et al., 2018; Dyhrberg, 2016). Furthermore, we also include a macroeconomic indicator, Citigroup's Citi Macro Risk Index, a measure of risk aversion often used when comparing global financial markets (Tu & Chen, 2018).…”

Section: Methodsmentioning

confidence: 99%

Understanding the transmission of crash risk between cryptocurrency and equity markets

Dai

Goodell

Huynh

et al. 2023

The Financial Review

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We evidence that cryptocurrencies have a higher probability of crashes than equity indices, although such crashes are of shorter duration. Commonality of crash risk between cryptocurrency and equity markets occur in approximately 80% of the periods examined. Further, recently evolved cryptocurrency uncertainty indices are more relevant for predicting co-crash behavior than economic policy uncertainty. Results are consistent with cryptocurrencies being a growing source of financial instability.

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“…Roy and Shijin (2018) proposed a balanced six factor asset pricing model, which explained the change of asset returns by adding human capital to the five-factor model and tested the six-factor asset pricing model with four different portfolios. Tu and Chen (2018) developed a new factor-augmented model for calculating the value at risk (VaR) of bond portfolios based on the Nelson-Siegel structural framework and tested whether the information contained in macroeconomic variables and financial stress shocks could enhance the accuracy of VaR prediction.…”

Section: Multi-factor Modelsmentioning

confidence: 99%

Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review

Sun¹,

Liu

et al. 2019

JRFM

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The literature on portfolio selection and risk measurement has considerably advanced in recent years. The aim of the present paper is to trace the development of the literature and identify areas that require further research. This paper provides a literature review of the characteristics of financial data, commonly used models of portfolio selection, and portfolio risk measurement. In the summary of the characteristics of financial data, we summarize the literature on fat tail and dependence characteristic of financial data. In the portfolio selection model part, we cover three models: mean-variance model, global minimum variance (GMV) model and factor model. In the portfolio risk measurement part, we first classify risk measurement methods into two categories: moment-based risk measurement and moment-based and quantile-based risk measurement. Moment-based risk measurement includes time-varying covariance matrix and shrinkage estimation, while moment-based and quantile-based risk measurement includes semi-variance, VaR and CVaR.

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A factor-based approach of bond portfolio value-at-risk: The informational roles of macroeconomic and financial stress factors

Cited by 6 publications

References 57 publications

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

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

Understanding the transmission of crash risk between cryptocurrency and equity markets

Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review

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