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Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context (2024)
Journal Article
Cheng, J. (in press). Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context. Computational Economics, https://doi.org/10.1007/s10614-024-10571-y

Scoring rules are commonly applied to assess the accuracy of density forecasts in both univariate and multivariate settings. In a financial risk management context, we are mostly interested in a particular region of the density: the (left) tail of a... Read More about Evaluating Density Forecasts Using Weighted Multivariate Scores in a Risk Management Context.

Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies. (2023)
Journal Article
Cheng, J. (2023). Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies. Empirical Economics, 65(2), 899-924. https://doi.org/10.1007/s00181-023-02360-7

In this paper, we investigate the co-dependence and portfolio value-at-risk of cryptocurrencies, with the Bitcoin, Ethereum, Litecoin and Ripple price series from January 2016 to December 2021, covering the crypto crash and pandemic period, using the... Read More about Modelling and forecasting risk dependence and portfolio VaR for cryptocurrencies..

A latent-factor-driven endogenous regime-switching non-Gaussian model: Evidence from simulation and application (2020)
Journal Article
Bu, R., Cheng, J., & Jawadi, F. (2022). A latent-factor-driven endogenous regime-switching non-Gaussian model: Evidence from simulation and application. International Journal of Finance and Economics, 27(4), 3881-3896. https://doi.org/10.1002/ijfe.2192

Abstract Regime-switching models are widely used in empirical economics and finance research for their ability to identify and account for the impact of latent regimes or states on the behaviour of the interested variables. Meanwhile, empirical evide... Read More about A latent-factor-driven endogenous regime-switching non-Gaussian model: Evidence from simulation and application.

Datafication of epistemic equality: advancing understandings of teaching excellence beyond benchmarked performativity. (2020)
Journal Article
Hayes, & Cheng. (2020). Datafication of epistemic equality: advancing understandings of teaching excellence beyond benchmarked performativity. Teaching in Higher Education, 25(4), 493-509. https://doi.org/10.1080/13562517.2019.1689387

The paper critiques key international teaching excellence and higher education outcomes frameworks for their lack of attention to epistemic equality. It subsequently argues that adequate ‘datafication’ of these frameworks, to demonstrate the extent t... Read More about Datafication of epistemic equality: advancing understandings of teaching excellence beyond benchmarked performativity..

“Liberating the ‘oppressed’ and the ‘oppressor’: A model for a new TEF metric, internationalisation and democracy” (2018)
Journal Article
Hayes, A., & Cheng, J. (2018). “Liberating the ‘oppressed’ and the ‘oppressor’: A model for a new TEF metric, internationalisation and democracy”. Educational Review, 72(3), 346-364. https://doi.org/10.1080/00131911.2018.1505713

The paper proposes a statistical model for a TEF metric that could liberate the “oppressed” (international students) and the “oppressors” (home students) from the influence of public policies which, through constructions of international students as... Read More about “Liberating the ‘oppressed’ and the ‘oppressor’: A model for a new TEF metric, internationalisation and democracy”.

Spectral density of Markov switching models: Derivation, simulation studies and application (2016)
Journal Article
Cheng, J. (2016). Spectral density of Markov switching models: Derivation, simulation studies and application. Model Assisted Statistics and Applications, 44(4), 277-291. https://doi.org/10.3233/MAS-160373

This paper is concerned with frequency domain analysis of Markov mean-switching autoregressive (MMSAR) models, linear Markov switching autoregressive (LMSAR) model and transitional Markov switching autoregressive (TMSAR) model. We derive the general... Read More about Spectral density of Markov switching models: Derivation, simulation studies and application.

Nonlinearity and Endogeneity in Continuous-Time Regime-Switching Diffusion Models for Market Volatility (2016)
Journal Article
Bu, R., Cheng, J., & Hadri, K. (2016). Nonlinearity and Endogeneity in Continuous-Time Regime-Switching Diffusion Models for Market Volatility. Studies in Nonlinear Dynamics and Econometrics, 21(1), https://doi.org/10.1515/snde-2016-0047

We examine model specification in regime-switching continuous-time diffusions for modeling S&P 500 Volatility Index (VIX). Our investigation is carried out under two nonlinear diffusion frameworks, the NLDCEV and the CIRCEV frameworks, and our focus... Read More about Nonlinearity and Endogeneity in Continuous-Time Regime-Switching Diffusion Models for Market Volatility.

A transitional Markov switching autoregressive model (2016)
Journal Article
Cheng. (2016). A transitional Markov switching autoregressive model. Communications in Statistics - Theory and Methods, 45(10), 2785-2800. https://doi.org/10.1080/03610926.2014.894065

This paper is concerned with properties of a transitional Markov switching autoregressive (TMSAR) model, together with its maximum-likelihood estimation and inference. We extend existing MSAR models by allowing dependence of AR parameters on hidden s... Read More about A transitional Markov switching autoregressive model.

Applications of Poisson-Hidden Markov Model (2015)
Journal Article
Huang, X., & Cheng, J. (2015). Applications of Poisson-Hidden Markov Model. International Journal of Applied Mathematics and Statistics (IJAMAS), 53(4),

Some real discrete time-series counts can be considered as the random variables which follow Poisson distribution governed by Hidden Markov Chain. In this paper, a Poisson-Hidden Markov Model is employed to capture the switching between two states in... Read More about Applications of Poisson-Hidden Markov Model.

Using Hidden Markov Model to Detect Macro-economic Risk Level (2013)
Journal Article
Zhu, Y., & Cheng, J. (2013). Using Hidden Markov Model to Detect Macro-economic Risk Level. Review of Integrative Business and Economics Research (RIBER), 2(1), 238-249

In this paper, inspired by Moody’s BET model, a stochastic hidden Markov model is constructed to detect the macro-economic risk states hidden in the corporate default data. The observed default statistics are from four geographic regions, namely Asia... Read More about Using Hidden Markov Model to Detect Macro-economic Risk Level.