International Journal of Financial Studies

Research

33 pages, 423 KiB

Open AccessArticle

Reliability and Accuracy of Alternative Default Prediction Models: Evidence from Slovakia

by Daniela Rybárová, Helena Majdúchová, Peter Štetka and Darina Luščíková

Int. J. Financial Stud. 2021, 9(4), 65; https://doi.org/10.3390/ijfs9040065 - 30 Nov 2021

Cited by 3 | Viewed by 2586

The aim of this paper is to assess the reliability of alternative default prediction models in local conditions, with subsequent comparison with other generally known and globally disseminated default prediction models, such as Altman’s Z-score, Quick Test, Creditworthiness Index, and Taffler’s Model. The [...] Read more.

The aim of this paper is to assess the reliability of alternative default prediction models in local conditions, with subsequent comparison with other generally known and globally disseminated default prediction models, such as Altman’s Z-score, Quick Test, Creditworthiness Index, and Taffler’s Model. The comparison was carried out on a sample of 90 companies operating in the Slovak Republic over a period of 3 years (2016, 2017, and 2018) with a narrower focus on three sectors: construction, retail, and tourism, using alternative default prediction models, such as CH-index, G-index, Binkert’s Model, HGN2 Model, M-model, Gulka’s Model, Hurtošová’s Model, Model of Delina and Packová, and Binkert’s Model. To verify the reliability of these models, tests of the significance of statistical hypotheses were used, such as type I and type II error. According to research results, the highest reliability and accuracy was achieved by an alternative local Model of Delina and Packová. The least reliable results within the list of models were reported by the most globally disseminated model, Altman’s Z-score. Significant differences between sectors were identified. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

22 pages, 806 KiB

Open AccessArticle

Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula

by John Weirstrass Muteba Mwamba and Sutene Mwambetania Mwambi

Int. J. Financial Stud. 2021, 9(2), 30; https://doi.org/10.3390/ijfs9020030 - 31 May 2021

Cited by 12 | Viewed by 3862

Abstract

This paper investigates the dynamic tail dependence risk between BRICS economies and the world energy market, in the context of the COVID-19 financial crisis of 2020, in order to determine optimal investment decisions based on risk metrics. For this purpose, we employ a [...] Read more.

This paper investigates the dynamic tail dependence risk between BRICS economies and the world energy market, in the context of the COVID-19 financial crisis of 2020, in order to determine optimal investment decisions based on risk metrics. For this purpose, we employ a combination of novel statistical techniques, including Vector Autoregressive (VAR), Markov-switching GJR-GARCH, and vine copula methods. Using a data set consisting of daily stock and world crude oil prices, we find evidence of a structure break in the volatility process, consisting of high and low persistence volatility processes, with a high persistence in the probabilities of transition between lower and higher volatility regimes, as well as the presence of leverage effects. Furthermore, our results based on the C-vine copula confirm the existence of two types of tail dependence: symmetric tail dependence between South Africa and China, South Africa and Russia, and South Africa and India, and asymmetric lower tail dependence between South Africa and Brazil, and South Africa and crude oil. For the purpose of diversification in these markets, we formulate an asset allocation problem using raw returns, MS GARCH returns, and C-vine and R-vine copula-based returns, and optimize it using a Particle Swarm optimization algorithm with a rebalancing strategy. The results demonstrate an inverse relationship between the risk contribution and asset allocation of South Africa and the crude oil market, supporting the existence of a lower tail dependence between them. This suggests that, when South African stocks are in distress, investors tend to shift their holdings in the oil market. Similar results are found between Russia and crude oil, as well as Brazil and crude oil. In the symmetric tail, South African asset allocation is found to have a well-diversified relationship with that of China, Russia, and India, suggesting that these three markets might be good investment destinations when things are not good in South Africa, and vice versa. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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17 pages, 883 KiB

Open AccessArticle

Modeling System Risk in the South African Insurance Sector: A Dynamic Mixture Copula Approach

by John Weirstrass Muteba Mwamba and Ehounou Serge Eloge Florentin Angaman

Int. J. Financial Stud. 2021, 9(2), 29; https://doi.org/10.3390/ijfs9020029 - 31 May 2021

Cited by 5 | Viewed by 3063

Abstract

In this paper, a dynamic mixture copula model is used to estimate the marginal expected shortfall in the South African insurance sector. We also employ the generalized autoregressive score model (GAS) to capture the dynamic asymmetric dependence between the insurers’ returns and the [...] Read more.

In this paper, a dynamic mixture copula model is used to estimate the marginal expected shortfall in the South African insurance sector. We also employ the generalized autoregressive score model (GAS) to capture the dynamic asymmetric dependence between the insurers’ returns and the stock market returns. Furthermore, the paper implements a ranking framework that expresses to what extent individual insurers are systemically important in the South African economy. We use the daily stock return of five South African insurers listed on the Johannesburg Stock Exchange from November 2007 to June 2020. We find that Sanlam and Discovery contribute the most to systemic risk, and Santam turns out to be the least systemically risky insurance company in the South African insurance sector. Our findings defy common belief whereby only banks are systemically risky financial institutions in South Africa and should undergo stricter regulatory measures. However, our results indicate that stricter regulations such as higher capital and loss absorbency requirements should be required for systemically risky insurers in South Africa. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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18 pages, 1632 KiB

Open AccessArticle

Predicting Extreme Daily Regime Shifts in Financial Time Series Exchange/Johannesburg Stock Exchange—All Share Index

by Katleho Makatjane and Ntebogang Moroke

Int. J. Financial Stud. 2021, 9(2), 18; https://doi.org/10.3390/ijfs9020018 - 25 Mar 2021

Cited by 7 | Viewed by 4018

Abstract

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alternative to traditional linear models. Linear models are [...] Read more.

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear models can be an encouraging alternative to traditional linear models. Linear models are often compared to non-linear models with mixed conclusions in terms of superiority in forecasting performance. Therefore, the aim of this study is to build an early warning system (EWS) model for extreme daily losses for financial stock markets. A logistic model tree (LMT) is used in collaboration with a seasonal autoregressive integrated moving average-Markov-Switching exponential generalised autoregressive conditional heteroscedasticity-generalised extreme value distribution (SARIMA-MS-EGARCH-GEVD) estimates. A time series of the study is a five-day financial time series exchange/Johannesburg stock exchange-all share index (FTSE/JSE-ALSI) for the period of 4 January 2010 to 31 July 2020. The study is set into a two-stage framework. Firstly, SARIMA model is fitted to stock returns in order to obtain independently and identically distributed (i.i.d) residuals and fit the MS(k)-EGARCH(p,q)-GEVD to i.i.d residuals; while, in the second stage, we set-up an EWS model. The results of the estimated MS(2)-EGARCH(1,1) -GEVD revealed that the conditional distribution of returns is highly volatile giving the expected duration to approximately 36 months and 4 days in regime one and 58 months and 2 days in regime two. We further found that any degree losses above 25% implies that there will be no further losses. Using the seven statistical loss functions, the estimated

S A R I M A (2, 1, 0) \times {(2, 1, 0)}_{240} - M S (2) - E G A R C H (1, 1) - G E V D

proved to be the most appropriate model for predicting extreme regimes losses as it was ranked at 71%. Finally, the results of EWS model exhibit reasonably an overall performance of 98%, sensitivity of 79.89% and specificity of 98.40% respectively. The model further indicated a success classification rate of 89% and a prediction rate of 95%. This is a promising technique for EWS. The findings also confirmed 63% and 51% of extreme losses for both training sample and validation sample to be correctly classified. The findings of this study are useful for decision makers and financial sector for future use and planning. Furthermore, a base for future researchers for conducting studies on emerging markets, have been contributed. These results are also important to risk managers and and investors. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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13 pages, 535 KiB

Open AccessArticle

Does Time Varying Risk Premia Exist in the International Bond Market? An Empirical Evidence from Australian and French Bond Market

by Hira Aftab and A. B. M. Rabiul Alam Beg

Int. J. Financial Stud. 2021, 9(1), 3; https://doi.org/10.3390/ijfs9010003 - 4 Jan 2021

Cited by 1 | Viewed by 2771

Abstract

The presence of risk premium is an issue that weakens the rational expectation hypothesis. This paper investigates changing behavior of time varying risk premium for holding 10 year maturity bond using a bivariate VARMA-DBEKK-AGARCH-M model. The model allows for asymmetric risk premia, causality [...] Read more.

The presence of risk premium is an issue that weakens the rational expectation hypothesis. This paper investigates changing behavior of time varying risk premium for holding 10 year maturity bond using a bivariate VARMA-DBEKK-AGARCH-M model. The model allows for asymmetric risk premia, causality and co-volatility spillovers jointly in the global bond markets. Empirical results show significant asymmetric partial co-volatility spillovers and risk premium exist in the bond markets. The estimates of the bivariate risk premia show bi-directional causality exist between the Australia and France Bond markets. Overall results suggest nonexistence of pure rational expectation theory in the risk premium model. This information is useful for the agents’ strategic policy decision making in global bond markets. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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13 pages, 2451 KiB

Open AccessArticle

The Fractional Step Method versus the Radial Basis Functions for Option Pricing with Correlated Stochastic Processes

by Yusho Kagraoka

Int. J. Financial Stud. 2020, 8(4), 77; https://doi.org/10.3390/ijfs8040077 - 1 Dec 2020

Viewed by 2045

Abstract

In option pricing models with correlated stochastic processes, an option premium is commonly a solution to a partial differential equation (PDE) with mixed derivatives in more than two space dimensions. Alternating direction implicit (ADI) finite difference methods are popular for solving a PDE [...] Read more.

In option pricing models with correlated stochastic processes, an option premium is commonly a solution to a partial differential equation (PDE) with mixed derivatives in more than two space dimensions. Alternating direction implicit (ADI) finite difference methods are popular for solving a PDE with more than two space dimensions; however, it is not straightforward to employ the ADI method for solving a PDE with mixed derivatives. The aim of this study is to find out which numerical method would be appropriate to solve PDEs with mixed derivatives based on the accuracy of the solutions and the computation time. This study applies the fractional step method and the radial basis functions to solve a PDE with a mixed derivative, and investigates the efficiency of these numerical methods. Numerical experiments are conducted by applying these methods to exchange option pricing; exchange options are selected because the exchange option premium has an analytical form. The numerical results show that the both methods calculate premiums with high accuracy in the presence of mixed derivatives. The fractional step method calculates the option premium more accurately and much faster than the radial basis functions. Therefore, from the numerical experiments, this study concludes that the fractional step method is more appropriate than the radial basis functions for solving a PDE with a mixed derivative. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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16 pages, 1517 KiB

Open AccessArticle

Monetary Policy Rule and Taylor Principle in Mongolia: GMM and DSGE Approaches

by Hiroyuki Taguchi and Ganbayar Gunbileg

Int. J. Financial Stud. 2020, 8(4), 71; https://doi.org/10.3390/ijfs8040071 - 16 Nov 2020

Cited by 7 | Viewed by 3822

Abstract

This article aims to examine the monetary policy rule under an inflation targeting in Mongolia with a focus on its conformity to the Taylor principle, through two kinds of approaches: a monetary policy reaction function by the generalized-method-of-moments (GMM) estimation and a New [...] Read more.

This article aims to examine the monetary policy rule under an inflation targeting in Mongolia with a focus on its conformity to the Taylor principle, through two kinds of approaches: a monetary policy reaction function by the generalized-method-of-moments (GMM) estimation and a New Keynesian dynamic stochastic general equilibrium (DSGE) model with a small open economy version by the Bayesian estimation. The main findings are summarized as follows. First, the GMM estimation identified an inflation-responsive rule fulfilling the Taylor principle in the recent phase of the Mongolian inflation targeting. Second, the DSGE-model estimation endorsed the GMM estimation by producing a consistent outcome on the Mongolian monetary policy rule. Third, the Mongolian rule was estimated to have a weaker response to inflation than the rules of the other emerging Asian adopters of an inflation targeting. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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22 pages, 572 KiB

Open AccessArticle

Non-Performing Loans for Italian Companies: When Time Matters. An Empirical Research on Estimating Probability to Default and Loss Given Default

by Giuseppe Orlando and Roberta Pelosi

Int. J. Financial Stud. 2020, 8(4), 68; https://doi.org/10.3390/ijfs8040068 - 9 Nov 2020

Cited by 15 | Viewed by 4819

Abstract

Within bank activities, which is normally defined as the joint exercise of savings collection and credit supply, risk-taking is natural, as in many human activities. Among risks related to credit intermediation, credit risk assumes particular importance. It is most simply defined as the [...] Read more.

Within bank activities, which is normally defined as the joint exercise of savings collection and credit supply, risk-taking is natural, as in many human activities. Among risks related to credit intermediation, credit risk assumes particular importance. It is most simply defined as the potential that a bank borrower or counterparty fails to fulfil correctly at maturity the pecuniary obligations assumed as principal and interest. Whenever this happens, a loan is non-performing. Among the main risk components, the Probability of Default (PD) and the Loss Given Default (LGD) have been the subject of greater interest for research. In this paper, logit model is used to predict both components. Financial ratios are used to estimate the PD. Time of recovery and presence of collateral are used as covariates of the LGD. Here, we confirm that the main driver of economic losses is the bureaucratically encumbered recovery system and the related legal environment. The long time required by Italian bureaucratic procedures, simply put, seems to lower dramatically the chance of recovery from defaulting counterparties. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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16 pages, 1458 KiB

Open AccessArticle

A Quasi-Closed-Form Solution for the Valuation of American Put Options

by Cristina Viegas and José Azevedo-Pereira

Int. J. Financial Stud. 2020, 8(4), 62; https://doi.org/10.3390/ijfs8040062 - 16 Oct 2020

Cited by 1 | Viewed by 2719

Abstract

This study develops a quasi-closed-form solution for the valuation of an American put option and the critical price of the underlying asset. This is an important area of research both because of a large number of transactions for American put options on different [...] Read more.

This study develops a quasi-closed-form solution for the valuation of an American put option and the critical price of the underlying asset. This is an important area of research both because of a large number of transactions for American put options on different underlying assets (stocks, currencies, commodities, etc.) and because this type of evaluation plays a role in determining the value of other financial assets such as mortgages, convertible bonds or life insurance policies. The procedure used is commonly known as the method of lines, which is considered to be a formulation in which time is discrete rather than continuous. To improve the quality of the results obtained, the Richardson extrapolation is applied, which allows the convergence of the outputs to be accelerated to values close to reality. The model developed in this paper derives an explicit formula of the finite-maturity American put option. The results obtained, besides allowing us to quickly determine the option value and the critical price, enable the graphical representation—in two and three dimensions—of the option value as a function of the other components of the model. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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15 pages, 1728 KiB

Open AccessArticle

Candlestick—The Main Mistake of Economy Research in High Frequency Markets

by Michał Dominik Stasiak

Int. J. Financial Stud. 2020, 8(4), 59; https://doi.org/10.3390/ijfs8040059 - 10 Oct 2020

Cited by 3 | Viewed by 3286

Abstract

One of the key problems of researching the high-frequency financial markets is the proper data format. Application of the candlestick representation (or its derivatives such as daily prices, etc.), which is vastly used in economic research, can lead to faulty research results. Yet, [...] Read more.

One of the key problems of researching the high-frequency financial markets is the proper data format. Application of the candlestick representation (or its derivatives such as daily prices, etc.), which is vastly used in economic research, can lead to faulty research results. Yet, this fact is consistently ignored in most economic studies. The following article gives examples of possible consequences of using candlestick representation in modelling and statistical analysis of the financial markets. Emphasis should be placed on the problem of research results being detached from the investing practice, which makes most of the results inapplicable from the investor’s point of view. The article also presents the concept of a binary-temporal representation, which is an alternative to the candlestick representation. Using binary-temporal representation allows for more precise and credible research and for the results to be applied in investment practice. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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36 pages, 5212 KiB

Open AccessArticle

A Holistic Model Validation Framework for Current Expected Credit Loss (CECL) Model Development and Implementation

by Michael Jacobs, Jr.

Int. J. Financial Stud. 2020, 8(2), 27; https://doi.org/10.3390/ijfs8020027 - 2 May 2020

Cited by 5 | Viewed by 6721

Abstract

The Current Expected Credit Loss (CECL) revised accounting standard for credit loss provisioning is the most important change to United States (US) accounting standards in recent history. In this study, we survey and assess practices in the validation of models that support CECL, [...] Read more.

The Current Expected Credit Loss (CECL) revised accounting standard for credit loss provisioning is the most important change to United States (US) accounting standards in recent history. In this study, we survey and assess practices in the validation of models that support CECL, across dimensions of both model development and model implementation. On the development side, this entails the usual SR 11-7 aspects of model validation; however, highlighted in the CECL context is the impact of several key modeling assumptions upon loan loss provisions. We also consider the validation of CECL model implementation or execution elements, which assumes heightened focus in CECL given the financial reporting implications. As an example of CECL model development validation, we investigate a modeling framework that we believe to be very close to that being contemplated by institutions, which projects loan losses using time-series econometric models, for an aggregated “average” bank using Federal Deposit Insurance Corporation (FDIC) Call Report data. In this example, we assess the accuracy of 14 alternative CECL modeling approaches, and we further quantify the level of model risk using the principle of relative entropy. Apart from the illustration of several model validation issues and practices that are of particular relevance to CECL, the empirical analysis has some potentially profound policy and model risk management implications. Specifically, implementation of the CECL standard may lead to under-prediction of credit losses; furthermore, coupled with the assumption that we are at an end to the favorable phase of the credit cycle, this may be interpreted as evidence that the goal of mitigating the procyclicality in the provisioning process that motivated CECL may fail to materialize. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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26 pages, 318 KiB

Open AccessArticle

Corporate Governance Mechanisms, Ownership and Firm Value: Evidence from Listed Chinese Firms

by Yusheng Kong, Takuriramunashe Famba, Grace Chituku-Dzimiro, Huaping Sun and Ophias Kurauone

Int. J. Financial Stud. 2020, 8(2), 20; https://doi.org/10.3390/ijfs8020020 - 2 Apr 2020

Cited by 22 | Viewed by 9782

Abstract

This study analyzes corporate ownership as a corporate governance mechanism and its role in creating firm value. Previous research shows that there is no convergence on the firm-value corporate ownership relationship. Most research in this area takes a cross national approach ignoring the [...] Read more.

This study analyzes corporate ownership as a corporate governance mechanism and its role in creating firm value. Previous research shows that there is no convergence on the firm-value corporate ownership relationship. Most research in this area takes a cross national approach ignoring the uniqueness of each institutional setting particularly those of emerging nations. Using a unique firm level dataset, we investigate how corporate control nature and ownership concentration affect the value of Chinese listed firms. First, non-state owned control is associated with a higher Tobin’s Q while a negative premium is found for state owned. Using the hybrid and the correlated random effects model we confirm a U-shaped non-linear relationship between ownership concentration and Tobin’s Q, implying that firm value first decreases and then increases as block holders own more shares. Further investigation reveals that the negative effect of ownership concentration is weaker when a firm equity nature is non-state owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). While ownership concentration appears to be an efficient mechanism for corporate governance its effect is weaker for SOEs compared to non-SOEs. The results support privatization of SOEs, sound reforms such as the split share structure reform as crucial for the development of China’s stock market. Full article

(This article belongs to the Special Issue Alternative Models and Methods in Financial Economics)

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