Journal of Economics and Financial Analysis - JEFA

Journal of Economics and Financial Analysis - JEFA

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Journal of Economics and Financial Analysis (JEFA) is a peer-reviewed academic journal publishes hig

Journal of Economics and Financial Analysis (JEFA) is a peer-reviewed academic journal publishes high quality research studies, both empirical and theoretical, in the disciplines of economics and finance.

Vol 3, No 1 (2019) 28/03/2019

Vol 3, No 1 (2019)

The Journal of Economics and Financial Analysis (JEFA) is delighted to share the news that our latest issue is now live.

Please visit https://ojs.tripaledu.com/jefa/issue/view/5 to access the journal’s latest issue, which includes contributions inter alia by:

Antonio Amendola, Dennis M. Montagna, Mario Maggi - Analysis of Equity β Components: New Results and Prospectives in a Low β Framework

Dastun B. Ngonyani, Harun J. Mapesa - Implication of Credit Supervision Practices on Portfolio at risk of Microfinance Institutions in Tanzania

Muhammad Surajo Sanusi, Farooq Ahmad - Measuring Predictability of Oil and Gas Stock Returns and Performance of Moving Average Trading Rules

Akhilesh Maewal, Joel R. Bock - A Modified Risk Parity Method for Asset Allocation

Tekilu Tadesse, Jemal Abafia - The causality between Financial Development and Economic Growth in Ethiopia: Supply Leading vs Demand Following Hypothesis

Vol 3, No 1 (2019) Journal of Economics and Financial Analysis (JEFA) is a peer-reviewed academic journal publishing empirical studies in economics and finance. No Fee.

The causality between Financial Development and Economic Growth in Ethiopia: Supply Leading vs Demand Following Hypothesis | Tadesse | Journal of Economics and Financial Analysis 28/03/2019

The causality between Financial Development and Economic Growth in Ethiopia: Supply Leading vs Demand Following Hypothesis | Tadesse | Journal of Economics and Financial Analysis

Volume 3, Issue 1, 2019. Page: 87-115

The causality between Financial Development and Economic Growth in Ethiopia: Supply Leading vs Demand Following Hypothesis

TEKILU TADESSE
Jimma University, Ethiopia

JEMAL ABAFIA
Jimma University, Ethiopia

DOI: http://dx.doi.org/10.1991/jefa.v3i1.a25

Abstract:
This paper investig*tes linkage between financial development and economic growth in Ethiopia during the period from 1975 to 2016 using Autoregressive Distributed Lag (ARDL) approach. The paper also schedules Vector Error Correction Model (VECM) in order to observe how fast the cointegrated variables convergence in long-run. Accordingly, the results of bound test confirm existence of the long-run relationship between explanatory variables and economic growth. The empirical results show evidence of long- and short-run positive impacts of financial development on economic growth in Ethiopia which implies that progesses in financial sector contribute to economic growth in both short- and long-run. In consideration of few control variables, the study finds all indicators, except inflation and government expenditure, significantly influence economic growth in the long-run. However, it also reveals that government expenditure, trade openness, human capital, and gross investment are pioneering determinants of the economic growth in Ethiopia in short-run. Moreover, the study employs Granger causality tests in order to show direction of impact is running from financial development to economic growth both in short- and long-run. As a result, it finds that the ‘supply-leading’ hypothesis holds in Ethiopia.

Keywords: Financial Development; Economic Growth; ARDL Bound Test; VECM; Granger Causality Test.

JEL Classification: G12, D40, C51, C59.

Full Text: https://ojs.tripaledu.com/index.php/jefa/article/view/45/49

The causality between Financial Development and Economic Growth in Ethiopia: Supply Leading vs Demand Following Hypothesis | Tadesse | Journal of Economics and Financial Analysis The causality between Financial Development and Economic Growth in Ethiopia: Supply Leading vs Demand Following Hypothesis

A Modified Risk Parity Method for Asset Allocation | Maewal | Journal of Economics and Financial Analysis 28/03/2019

A Modified Risk Parity Method for Asset Allocation | Maewal | Journal of Economics and Financial Analysis

Volume 3, Issue 1, 2019. Page: 71-85

A Modified Risk Parity Method for Asset Allocation

AKHILESH MAEWAL
Yale University, United States

JOEL R. BOCK
University of California, San Diego, United States

DOI: http://dx.doi.org/10.1991/jefa.v3i1.a24

Abstract:
We propose a return based modification of the portfolio variance matrix for asset allocation using risk parity. The modification is based upon a single scalar parameter which can be tuned to tailor the allocation for desired expected risk and/or return. The present work contributes a new twist on risk parity. While classical risk parity methods are based exclusively on volatility, the new solution (Modified Risk Parity) considers both historical returns and their variance in the construction of an optimal, diversified investment portfolio. We present two examples for periods including the recent financial market crises. The results suggest that the modification may lead to significantly improved risk adjusted returns over those realized by the conventional risk parity method.

Keywords: Risk Parity; Asset Allocation; Decision Making; Portfolio Optimizaion.

JEL Classification: G11, G12, D81.

Full Text: https://ojs.tripaledu.com/index.php/jefa/article/view/44/48

A Modified Risk Parity Method for Asset Allocation | Maewal | Journal of Economics and Financial Analysis A Modified Risk Parity Method for Asset Allocation

Measuring Predictability of Oil and Gas Stock Returns and Performance of Moving Average Trading Rules | Sanusi | Journal of Economics and Financial Analysis 28/03/2019

Measuring Predictability of Oil and Gas Stock Returns and Performance of Moving Average Trading Rules | Sanusi | Journal of Economics and Financial Analysis

Volume 3, Issue 1, 2019. Page: 47-70

Measuring Predictability of Oil and Gas Stock Returns and Performance of Moving Average Trading Rules

MUHAMMAD SURAJO SANUSI
Birmingham City University, United Kingdom

FAROOQ AHMAD
Robert Gordon University, United Kingdom

DOI: http://dx.doi.org/10.1991/jefa.v3i1.a23

Abstract:
The paper re-examines whether investors can predict oil and gas stock prices for abnormal returns using autocorrelation-based trading and filter rules and moving average strategies. In this paper, short and long lengths moving averages are employed and their performances are measured against the returns from simple buy and hold investment strategy. As a result, the paper finds that employed trading rules do not indicate that investors can make abnormal returns in oil and gas stocks. Moreover, the performances of short and long moving averages in predicting abnormal returns also do not suggest a conclusive evidence that any of the moving averages can result in more returns compared to others.

Keywords: Trading and Filter Rules; Moving Average Trading Rule; Buy and Hold Investment Strategy; Oil and Gas Stock Returns.

JEL Classification: G100, G120.

Full Text: https://ojs.tripaledu.com/index.php/jefa/article/view/43/47

Measuring Predictability of Oil and Gas Stock Returns and Performance of Moving Average Trading Rules | Sanusi | Journal of Economics and Financial Analysis Measuring Predictability of Oil and Gas Stock Returns and Performance of Moving Average Trading Rules

Implication of Credit Supervision Practices on Portfolio at risk of Microfinance Institutions in Tanzania | Ngonyani | Journal of Economics and Financial Analysis 28/03/2019

Implication of Credit Supervision Practices on Portfolio at risk of Microfinance Institutions in Tanzania | Ngonyani | Journal of Economics and Financial Analysis

Volume 3, Issue 1, 2019. Page: 27-45

Implication of Credit Supervision Practices on Portfolio at risk of Microfinance Institutions in Tanzania

DASTUN B. NGONYANI
St. Johns University of Tanzania, Tanzania, United Republic of

HARUN J. MAPESA
Mzumbe University, Tanzania, United Republic of

DOI: http://dx.doi.org/10.1991/jefa.v3i1.a22

Abstract:
This study seeks to establish the implication of credit supervision practices on portfolio management of microfinance institutions in Tanzania. Utilizing multivariate regression technique over sampled 219 microfinance institutions from Dar es Salaam, Morogoro and Dodoma regions, it documents two plausible results. First, the study finds that timely loan release and number of borrowers per loan officer have positive and statistically significant impact on portfolio at risk of microfinance institutions. Second, it reveals that operation cost per borrower and provision of training sessions to borrowers have neg*tive and statistically significant impact on portfolio at risk of microfinance institutions.
These results suggest that microfinance institutions can diminish portfolio risks by (1) decreasing number of days for processing clients’ loan applications and releasing funds; (2) decreasing number of clients per each loan officer in order to increase efficiency of loan management of the officers; (3) increasing training sessions on various skills given to their borrowers which will increase knowledge and skills of clients on the best ways to keep their business records and proper utilization of funds, and so successful repayments; (4) allocating enough budgets for overall supervisory purposes including loan appraisal processes, disbursement procedures and collection of funds from their clients.

Keywords: Credit Supervision; Portfolio at Risk; Microfinance Institutions; Credit Risk

JEL Classification: D23, G21, G23.

Full Text: https://ojs.tripaledu.com/index.php/jefa/article/view/42/46

Implication of Credit Supervision Practices on Portfolio at risk of Microfinance Institutions in Tanzania | Ngonyani | Journal of Economics and Financial Analysis Implication of Credit Supervision Practices on Portfolio at risk of Microfinance Institutions in Tanzania

Analysis of Equity β Components: New Results and Prospectives in a Low β Framework | Amendola | Journal of Economics and Financial Analysis 28/03/2019

Analysis of Equity β Components: New Results and Prospectives in a Low β Framework | Amendola | Journal of Economics and Financial Analysis

Volume 3, Issue 1, 2019. Page: 1-26

Analysis of Equity β Components: New Results and Prospectives in a Low β Framework

ANTONIO AMENDOLA
University of Pavia, Italy

DENNIS M. MONTAGNA
University of Pavia, Italy

MARIO MAGGI
University of Pavia, Italy

DOI: http://dx.doi.org/10.1991/jefa.v3i1.a21

Abstract:
This work aims to exploit the so-called "Beta anomaly" regarding the risk-reward relationship, and set up rules and methodologies in order to build new efficient portfolios. It is well known in literature, and among practitioners, that “Low Beta strategies” generate good performances exploiting alpha opportunities. In this paper, we focus on β parameters: we analyze this one and its components (Correlation and Standard Deviation) in order to better understand the drivers and contributions behind the “Low Beta strategies”, and eventually exploit them. We perform an extensive empirical analysis on the S&P500 and the relative sectors, covering more than 10 years. In addition, we follow Long/Short strategies in building portfolios based on β and their components where we compare results against the benchmark.
We also introduce "Walking Beta" approach in order to give a deep and innovative view on the market risk/reward relationship, illustrating different time frames and the evolution of risk parameters.

Keywords: Asset Allocation; Quantitative Portfolio Management; CAPM; Hedge Funds; Correlation; Beta Anomaly.

JEL Classification: G11, G12, G14.

Full Text: https://ojs.tripaledu.com/index.php/jefa/article/view/41/45

Analysis of Equity β Components: New Results and Prospectives in a Low β Framework | Amendola | Journal of Economics and Financial Analysis Analysis of Equity β Components: New Results and Prospectives in a Low β Framework

Journal of Economics and Financial Analysis 17/02/2018

Journal of Economics and Financial Analysis

The Journal of Economics and Financial Analysis (JEFA) is delighted to share the news that our latest issue is now live.

Please visit https://ojs.tripaledu.com/jefa/issue/view/4 to access the journal’s latest issue, which includes contributions inter alia by:

Yhlas Sovbetov - Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero

Sebahattin Demirkan, Harlan Platt - Differential Investors' Response to Restatement Announcements: An Empirical Investig*tion

Ahmad Sahyouni, Man Wang - The determinants of Bank Profitability: Does Liquidity Creation matter?

Nicholas Burgess - Interest Rate Swaptions: A Review and Derivation of Swaption Pricing Formulae

Mohamed Chikhi, Ali Bendob - Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology

Journal of Economics and Financial Analysis Journal of Economics and Financial Analysis (JEFA) is a peer-reviewed academic journal publishing empirical studies in economics and finance. No Fee.

Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology | Chikhi | Journal of Economics and Financial Analysis 17/02/2018

Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology | Chikhi | Journal of Economics and Financial Analysis

Volume 2, Issue 2, 2018. Page: 105-120

Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology

MOHAMED CHIKHI
University of Ouargla, Algeria

ALI BENDOB
University of Ain-Temouchent, Algeria

DOI: http://dx.doi.org/10.1991/jefa.v2i2.a20

Abstract:
This paper analyses cyclical behaviour of Orange stock price listed in French stock exchange over 01/03/2000 to 02/02/2017 by testing the nonlinearities through a class of conditional heteroscedastic nonparametric models. The linearity and Gaussianity assumptions are rejected for Orange Stock returns and informational shocks have transitory effects on returns and volatility. The forecasting results show that Orange stock prices are short-term predictable and nonparametric NAR-ARCH model has better performance over parametric MA-APARCH model for short horizons. Plus, the estimates of this model are also better comparing to the predictions of the random walk model. This finding provides evidence for weak form of inefficiency in Paris stock market with limited rationality, thus it emerges arbitrage opportunities.

Keywords: Final Prediction Error; Kernel; Bandwidth; Conditional Heteroscedastic Functional Autoregressive Process; Orange Stock Price; Forecasts.

JEL Classification: C14, C22, C58, G17.

Full Text: https://ojs.tripaledu.com/jefa/article/view/19/41

Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology | Chikhi | Journal of Economics and Financial Analysis Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology

Interest Rate Swaptions: A Review and Derivation of Swaption Pricing Formulae | Burgess | Journal of Economics and Financial Analysis 17/02/2018

Interest Rate Swaptions: A Review and Derivation of Swaption Pricing Formulae | Burgess | Journal of Economics and Financial Analysis

Volume 2, Issue 2, 2018. Page: 87-103

Interest Rate Swaptions: A Review and Derivation of Swaption Pricing Formulae

NICHOLAS BURGESS
University of Reading, United Kingdom

DOI: http://dx.doi.org/10.1991/jefa.v2i2.a19

Abstract:
In this paper we outline the European interest rate swaption pricing formula from first principles using the Martingale Representation Theorem and the annuity measure. This leads to an expression that allows us to apply the generalized Black-Scholes result. We show that a swaption pricing formula is nothing more than the Black-76 formula scaled by the underlying swap annuity factor. Firstly, we review the Martingale Representation Theorem for pricing options, which allows us to price options under a numeraire of our choice. We also highlight and consider European call and put option pricing payoffs. Next, we discuss how to evaluate and price an interest swap, which is the swaption underlying instrument. We proceed to examine how to price interest rate swaptions using the martingale representation theorem with the annuity measure to simplify the calculation. Finally, applying the Radon-Nikodym derivative to change measure from the annuity measure to the savings account measure we arrive at the swaption pricing formula expressed in terms of the Black-76 formula. We also provide a full derivation of the generalized Black-Scholes formula for completeness.

Keywords: Interest Rate Swaps; European Swaption Pricing; Martingale Representation Theorem; Radon-Nikodym Derivative; Generalized Black-Scholes Model.

JEL Classification: C02, C20, E43, E47, E49, G15.

Full Text: https://ojs.tripaledu.com/jefa/article/view/38/40

Interest Rate Swaptions: A Review and Derivation of Swaption Pricing Formulae | Burgess | Journal of Economics and Financial Analysis Interest Rate Swaptions: A Review and Derivation of Swaption Pricing Formulae

The determinants of Bank Profitability: Does Liquidity Creation matter? | Sahyouni | Journal of Economics and Financial Analysis 17/02/2018

The determinants of Bank Profitability: Does Liquidity Creation matter? | Sahyouni | Journal of Economics and Financial Analysis

Volume 2, Issue 2, 2018. Page: 61-85

The determinants of Bank Profitability: Does Liquidity Creation matter?

AHMAD SAHYOUNI
Dongbei University of Finance and Economics, China

MAN WANG
Dongbei University of Finance and Economics, China

DOI: http://dx.doi.org/10.1991/jefa.v2i2.a18

Abstract:
Using a panel data set of 4995 banks across 11 developed and emerging countries during the period (2011-2015), this report analyses the amount of liquidity created by banks, how liquidity creation, bank-specific and the macroeconomic factors affecting bank profitability. The results show evidence of increased creation of liquidity over the period. By applying the panel data fixed effect technique, banks that create more liquidity, are set up to have lower profitability. As well as, Asset management, bank size and capital ratio are positively correlated with bank profitability. While, credit quality and operating efficiency affect bank’s profits neg*tively. Additionally, macroeconomic factors have different impact on profitability indicators in each market. Our findings may help decision makers inside and outside bank to determine important factors affecting bank profitability.

Keywords: Liquidity Creation; Bank Profitability; Emerging Countries; Developed Countries.

JEL Classification: G21, G32.

Full Text: https://ojs.tripaledu.com/index.php/jefa/article/view/30/38

The determinants of Bank Profitability: Does Liquidity Creation matter? | Sahyouni | Journal of Economics and Financial Analysis The determinants of Bank Profitability: Does Liquidity Creation matter?

Differential Investors’ Response to Restatement Announcements: An Empirical Investig*tion | Demirkan | Journal of Economics and Financial Analysis 17/02/2018

Differential Investors’ Response to Restatement Announcements: An Empirical Investig*tion | Demirkan | Journal of Economics and Financial Analysis

Volume 2, Issue 2, 2018. Page: 29-59

Differential Investors' Response to Restatement Announcements: An Empirical Investig*tion

SEBAHATTIN DEMIRKAN
Morgan State University, United States

HARLAN PLATT
Northeastern University, United States

DOI: http://dx.doi.org/10.1991/jefa.v2i2.a17

Abstract:
When firms announce a restatement of their financial reports, they inform investors that their prior announcements were faulty. Not only do companies lose credibility at times such as this but also their securities are revalued as investors respond to the substance of the announcement. We investig*te investor size to understand how large and small investors differ in their responses to restatement announcements. Our results indicate that large investors seemingly anticipate the announcement; their holdings decrease before restatement announcements; consequently large investors trading after announcements is less pronounced than for smaller investors. The response of small investors depends on who has prompted the restatement: the company itself, FASB or the SEC and not on the reason for the restatement such as problems with revenue recognition, restructuring or cost/expense. Large investor trading volume is affected by both the source of the restatement and the reason for it. Large investors seem to anticipate potential problems, and sell securities before restatement announcements.

Keywords: Restatement; Investor Size; Information; Trading Response; Prompters of restatement; Reasons of Restatements.

JEL Classification: D40, D49, E44, F30, G15.

Full Text: https://ojs.tripaledu.com/jefa/article/view/37/37

Differential Investors’ Response to Restatement Announcements: An Empirical Investig*tion | Demirkan | Journal of Economics and Financial Analysis Differential Investors’ Response to Restatement Announcements: An Empirical Investig*tion

Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero | Sovbetov | Journal of Economics and Financial Analysis 17/02/2018

Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero | Sovbetov | Journal of Economics and Financial Analysis

Volume 2, Issue 2, 2018. Page: 1-27

Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero

YHLAS SOVBETOV
London School of Commerce, United Kingdom

DOI: http://dx.doi.org/10.1991/jefa.v2i2.a16

Abstract:
This paper examines factors that influence prices of most common five cryptocurrencies such Bitcoin, Ethereum, Dash, Litecoin, and Monero over 2010-2018 using weekly data. The study employs ARDL technique and documents several findings. First, cryptomarket-related factors such as market beta, trading volume, and volatility appear to be significant determinant for all five cryptocurrencies both in short- and long-run. Second, attractiveness of cryptocurrencies also matters in terms of their price determination, but only in long-run. This indicates that formation (recognition) of the attractiveness of cryptocurrencies are subjected to time factor. In other words, it travels slowly within the market. Third, SP500 index seems to have weak positive long-run impact on Bitcoin, Ethereum, and Litcoin, while its sign turns to neg*tive losing significance in short-run, except Bitcoin that generates an estimate of -0.20 at 10% significance level.
Lastly, error-correction models for Bitcoin, Etherem, Dash, Litcoin, and Monero show that cointegrated series cannot drift too far apart, and converge to a long-run equilibrium at a speed of 23.68%, 12.76%, 10.20%, 22.91%, and 14.27% respectively.

Keywords: Cryptocurrency; Bitcoin; Ethereum; Cointegration; ARDL Bound Test; Error Correction Model.

JEL Classification: G12, D40, C51, C59.

Full Text: https://ojs.tripaledu.com/jefa/article/view/36/35

Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero | Sovbetov | Journal of Economics and Financial Analysis Factors Influencing Cryptocurrency Prices: Evidence from Bitcoin, Ethereum, Dash, Litcoin, and Monero

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