Carl H. Korkpoe

Carl H. Korkpoe
University of Cape Coast | UCC · Department of Finance

Doctor of Philosophy

About

15
Publications
6,231
Reads
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20
Citations
Citations since 2017
12 Research Items
20 Citations
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Introduction
Carl H. Korkpoe currently works at the Department of Finance, University of Cape Coast. Carl does research in Risk Management and Insurance, Econometrics and Financial Economics. His current project is 'Markov Regime switching models in frontier markets'.

Publications

Publications (15)
Article
Full-text available
We investigated regime switching behaviour of the broad aggregate returns of the Ghana Stock Exchange within the context of frontier markets. The data covered the daily period from January 04, 2011 to March 31, 2017. We made the following findings: (a) there are clear market regimes corresponding to periods of tranquillity and turbulence as demonst...
Article
Full-text available
Complaints of heightened risks in the sub-Saharan African equities markets are rife in the practitioner literature. Investors need an understanding of the volatility dynamics in these frontier markets. This paper uses the Hidden Markov Models to detect the points of regime changes in the volatility in the markets of Ghana, Kenya, Nigeria and Botswa...
Article
Full-text available
We adopt a granular approach to estimating the risk of equity returns in sub-Saharan African frontier equity markets under the assumption that, returns are influenced by developments in the underlying economy. Four countries were studied – Botswana, Ghana, Kenya and Nigeria. We found heterogeneity in the evolution of volatility across these markets...
Article
Full-text available
The study used the Markov regime switching model to investigate the presence of regimes in the volatility dynamics of the returns of JSE All-Share Index (ALSI). Volatility regimes are as a result of sudden changes in the underlying economy generating the market returns. In all, twelve candidate models were fitted to the data. Estimates from the reg...
Article
Full-text available
The study used the Autoregressive Conditional Density (ACD) methodology to model time-varying higher moments in the distribution of returns of the JSE All Share Index (JSE-ALSI) over the15-year period, January 2003 to December 2017. We found that the fourth higher moment beyond the variance is needed to completely describe the distribution of retur...
Article
We studied regime-switching behaviour of the volatility of the returns from the ZAR/USD exchange rate for the period January 4, 2002 to December 31, 2017. The results showed that, contrary to mainstream approaches for estimating volatility using GARCH (1,1) there are clear regimes in the returns which necessitate regime switching models. The result...
Article
Full-text available
We investigated the model fit for volatility of returns from the Ghana Stock Exchange All Share Index for the Bayesian versions of GARCH(1,1) with student-t innovations and stochastic volatility. We found evidence in favour of the GARCH(1,1) with student-t innovations against the recommendation from the developed equity markets of preference for st...
Article
Full-text available
We investigated the presence of regimes in volatility of returns of the Ghana Stock Exchange index using single and two regime Markov-switching threshold GARCH with skewed- and student-t innovations separately for model fit. We found that the 2- regime threshold GARCH(1,1) with skewed student-t innovations provide a better fit to the data by using...
Article
Full-text available
We investigated the behaviour of returns of the Johannesburg Stock Exchange All Share Index using asymmetrical exponential-GARCH(1,1) and GJR-GARCH(1,1) incorporating the market reactions to news. We noted the returns distribution is skewed and have fat-tails with respect to the normal distribution. Thus we chose the skewed student t-distribution a...
Preprint
Full-text available
We investigated regime switching behaviour of the broad aggregate returns of the Ghana Stock Exchange within the context of frontier markets. The data covered the daily period from January 04, 2011 to March 31, 2017. We made the following findings: (a) there are clear market regimes corresponding to periods of tranquillity and turbulence as demonst...
Article
Full-text available
Modeling market returns involve selecting the appropriate statistical distribution that describes the entire behaviour of the data. Most models in finance make the simplifying assumption that returns are independent and identically normally distributed with a constant variance. This description is not entirely correct. The focus of this paper is to...
Article
The four-parameter generalised lambda distribution provides the flexibility required to describe the key moments of any distribution as compared with the normal distribution which characterises the distribution with only two moments. As markets have increasingly become nervous, the inadequacies of the normal distribution in capturing correctly the...
Article
Full-text available
In a frontier equity market like Ghana, trades can be quiet for long periods increasing the liquidity risk for investors. This notwithstanding, studies into the risk dynamics of the stock market are largely lacking for the Ghana Stock Exchange (GSE). In this paper, we have undertaken to use a dynamic volatility model, Generalized Autoregressive Con...
Article
Full-text available
Conceptually, new technologies have affected individuals and organisations resulting to the rethinking of all the fundamental operating assumptions of many organisations and the roles in them. Organisations exist in a rapidly changing environment, necessitating responsive and often radical strategic capabilities. This strategic move has allowed org...
Conference Paper
Full-text available
The problem of corruption has been universally acknowledged as a drain on a country's developmental efforts. Anticorruption reform hitherto has focused on political corruption. Administrative corruption which citizens have to contend with on a daily basis is only just beginning to attract attention. There have been various strategies, intensifying...

Questions

Questions (8)
Question
Academic papers are supposed to have theories underpinning them. Indeed, papers without theories are frowned on. Now, suppose I am writing a paper in the volatility of a given stock index, what is the theory here?
Question
I am looking at getting Python code that does regime-switching volatility models in Python. I want to be able to estimate the VaR and CVaR with the volatility model. Thank you.
Question
I am looking for R code snippet to do an out-of-sample analysis of a 2-regime EGARCH volatility model. I need to compare the in-sample and out-of-sample to check for overfitting of the model to the data. Thank you.
Question
I am wondering if anyone has R code on volatility jumps of equity returns . . . I will be grateful if you make it available to me. Thank you.
Question
I am running code in R to do a VaR test. The code is:
VaRTest(alpha = 0.01, actual = roll@forecast$VaR[,'Realized'], VaR = roll@forecast$VaR[, 'alpha(1%)'])
The error I am getting is:
Error in `[.default`(n, 1, 1) : subscript out of bounds
roll is an acdroll object which has ran successfully. I am using the racd package in R.
Question
This question come under regime switching volatility modeling of time series data. Using regime switching, by definition, invalidates any talk of stationarity in my opinion. What do financial economists think about this? Thank you.

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