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Int. J. Financial Stud., Volume 4, Issue 4 (December 2016)

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Research

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Open AccessArticle The Valuation of Equities and the GDP Growth Effect: A Global Empirical Study
Int. J. Financial Stud. 2016, 4(4), 21; doi:10.3390/ijfs4040021
Received: 29 May 2016 / Revised: 28 September 2016 / Accepted: 9 October 2016 / Published: 20 October 2016
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Abstract
One of the main characteristics of the (recently proposed) non-arbitrage valuation of equities framework is the reduction in pricing subjectivity. This is evidenced in terms of the dividends discount rate and the outlook of future performance (dividends projection) of the company that is
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One of the main characteristics of the (recently proposed) non-arbitrage valuation of equities framework is the reduction in pricing subjectivity. This is evidenced in terms of the dividends discount rate and the outlook of future performance (dividends projection) of the company that is being valued. Under this framework, as in the case of derivatives pricing, the discount rate is the risk-free interest rate (not the cost of equity), and the subjectively-determined drift of the stochastic process that drives the operating profits of the company is eliminated. The challenge that emerges is that the structure of the new drift of the operating profits process is undetermined under the methodology (this is a similar feature that is observed in the case of derivatives related to non-tradable assets). This paper proposes that the structure of this new drift is represented by the (country-specific) GDP nominal growth effect. This proposition is tested through an empirical study that involves several companies of 10 equity indices worldwide, for two different periods (1995–2004 and 2005–2014). The results of the test are reasonably successful, meaning that further research related to the framework could provide useful information for the understanding of financial assets and their links to the macro-economy. Full article
Open AccessArticle Strategic Decision-Making and Social Skills: Integrating Behavioral Economics and Social Cognition Research
Int. J. Financial Stud. 2016, 4(4), 22; doi:10.3390/ijfs4040022
Received: 6 July 2016 / Revised: 11 October 2016 / Accepted: 25 October 2016 / Published: 4 November 2016
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Abstract
Strategic decisions are affected by beliefs about the expectations of others and their possible decisions. Thus, strategic decisions are influenced by the social context and by beliefs about other actors’ levels of sophistication. The present study investigated whether strategic decision-making, as measured by
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Strategic decisions are affected by beliefs about the expectations of others and their possible decisions. Thus, strategic decisions are influenced by the social context and by beliefs about other actors’ levels of sophistication. The present study investigated whether strategic decision-making, as measured by the beauty contest game, is associated with social skills, as measured by the Autism Quotient (AQ). In line with our hypothesis, we found that social skills were positively related to successful strategic decision-making. Furthermore, results showed a curvilinear relationship between steps of reasoning in the beauty contest game and social skills, indicating that very high as well as very low scoring individuals on the social skills subscale of the AQ engaged in high-levels of strategic thinking. Full article
(This article belongs to the Special Issue Behavioral Economics and Strategy)
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Open AccessArticle Oil Prices, Credit Risks in Banking Systems, and Macro-Financial Linkages across GCC Oil Exporters
Int. J. Financial Stud. 2016, 4(4), 23; doi:10.3390/ijfs4040023
Received: 21 August 2016 / Revised: 21 October 2016 / Accepted: 24 October 2016 / Published: 4 November 2016
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Abstract
This paper assesses the effect of the recent 2014–2015 oil price slump on the financial stability in the Gulf Cooperation Council (GCC) region. The first objective of this paper is to assess how oil price shock propagates within the macroeconomy and how the
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This paper assesses the effect of the recent 2014–2015 oil price slump on the financial stability in the Gulf Cooperation Council (GCC) region. The first objective of this paper is to assess how oil price shock propagates within the macroeconomy and how the macro shocks transmit to GCC banks’ balance sheets. This part of the paper implements a System Generalized Method of Moments (GMM) and a Panel Fixed Effect Model to estimate the response of nonperforming loans (NPLs) to its macroeconomic determinants. The second objective of this paper is to assess any negative feedback effects between the GCC banking systems and the economy. The paper, therefore, implements a Panel VAR model to explore the macro-financial linkages between GCC banking systems and the real economy. The results indicate that oil price, non-oil GDP, interest rate, stock prices, and housing prices are major determinants of NPLs across GCC banks and the overall financial stability in the region. Credit risk shock tends to propagate disturbances to non-oil GDP, credit growth, and stock prices across GCC economies. A higher level of NPLs restricts banks’ credit growth and can dampen economic growth in these economies. The results support the notion that disturbances in banking systems lead to unwanted economic consequences for the real sector. Full article
(This article belongs to the Special Issue Energy Finance)
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Open AccessArticle Model Selection Test for the Heavy-Tailed Distributions under Censored Samples with Application in Financial Data
Int. J. Financial Stud. 2016, 4(4), 24; doi:10.3390/ijfs4040024
Received: 19 June 2016 / Revised: 24 November 2016 / Accepted: 1 December 2016 / Published: 13 December 2016
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Abstract
Numerous heavy-tailed distributions are used for modeling financial data and in problems related to the modeling of economics processes. These distributions have higher peaks and heavier tails than normal distributions. Moreover, in some situations, we cannot observe complete information about the data. Employing
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Numerous heavy-tailed distributions are used for modeling financial data and in problems related to the modeling of economics processes. These distributions have higher peaks and heavier tails than normal distributions. Moreover, in some situations, we cannot observe complete information about the data. Employing the efficient estimation method and then choosing the best model in this situation are very important. Thus, the purpose of this article is to propose a new interval for comparing the two heavy-tailed candidate models and examine its suitability in the financial data under complete and censored samples. This interval is equivalent to encapsulating the results of many hypotheses tests. A maximum likelihood estimator (MLE) is used for evaluating the parameters of the proposed heavy-tailed distribution. A real dataset representing the top 30 companies of the Tehran Stock Exchange indices is used to illustrate the derived results. Full article
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Open AccessArticle Sectoral Differences in the Choice of the Time Horizon during Estimation of the Unconditional Stock Beta
Int. J. Financial Stud. 2016, 4(4), 25; doi:10.3390/ijfs4040025
Received: 8 July 2016 / Revised: 28 November 2016 / Accepted: 2 December 2016 / Published: 17 December 2016
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Abstract
The stock beta coefficient literature extensively discusses the proper methods for the estimation of beta as well as its use in asset valuation. However, there are fewer references with respect to the appropriate time horizon that investors should utilize when evaluating the risk-return
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The stock beta coefficient literature extensively discusses the proper methods for the estimation of beta as well as its use in asset valuation. However, there are fewer references with respect to the appropriate time horizon that investors should utilize when evaluating the risk-return relationship of a stock. We examine the appropriate time horizon for beta estimation, differentiating our results by sector according to the Industry Classification Benchmark. We employ data from the NYSE and estimate varying lengths of beta employing data from 30 to 250 trading days. The constructed beta series is then examined for the presence of breaks using the endogenous structural break literature. Results show evidence against the use of betas that employ more than 90 trading days of data provisional to the sector under study. Full article
Open AccessArticle Stock Selection as a Problem in Phylogenetics—Evidence from the ASX
Int. J. Financial Stud. 2016, 4(4), 18; doi:10.3390/ijfs4040018
Received: 17 March 2016 / Revised: 16 September 2016 / Accepted: 20 September 2016 / Published: 29 September 2016
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Abstract
We report the results of fifteen sets of portfolio selection simulations using stocks in the ASX200 index for the period May 2000 to December 2013. We investigated five portfolio selection methods, random selection, selection within industrial groups, and three based on neighbor-Net phylogenetic
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We report the results of fifteen sets of portfolio selection simulations using stocks in the ASX200 index for the period May 2000 to December 2013. We investigated five portfolio selection methods, random selection, selection within industrial groups, and three based on neighbor-Net phylogenetic networks. We report that using random, industrial groups, or neighbor-Net phylogenetic networks alone rarely produced statistically significant reduction in risk, though in four out of the five cases in which it did so, the portfolios selected using the phylogenetic networks had the lowest risk. However, we report that when using the neighbor-Net phylogenetic networks in combination with industry group selection that substantial reductions in portfolio return spread were achieved. Full article
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Open AccessArticle The Effect of Straight-Line and Accelerated Depreciation Rules on Risky Investment Decisions—An Experimental Study
Int. J. Financial Stud. 2016, 4(4), 19; doi:10.3390/ijfs4040019
Received: 27 April 2016 / Revised: 13 September 2016 / Accepted: 21 September 2016 / Published: 13 October 2016
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Abstract
The aim of this study is to analyze how depreciation rules influence the decision behavior of investors. For this purpose, we conduct a laboratory experiment in which participants decide on the composition of an asset portfolio in different choice situations. Using an experimental
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The aim of this study is to analyze how depreciation rules influence the decision behavior of investors. For this purpose, we conduct a laboratory experiment in which participants decide on the composition of an asset portfolio in different choice situations. Using an experimental setting with different payment periods, we show that accelerated compared to straight-line depreciation can increase the willingness to invest as hypothesized by theory. However, this expected behavior is only observed in a more complex environment (with a subsidy) and not in a less complex environment (without a subsidy). Full article
(This article belongs to the Special Issue Behavioral Economics and Strategy)
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Review

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Open AccessReview Operational Risk Management in Financial Institutions: A Literature Review
Int. J. Financial Stud. 2016, 4(4), 20; doi:10.3390/ijfs4040020
Received: 27 July 2016 / Revised: 30 September 2016 / Accepted: 3 October 2016 / Published: 19 October 2016
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Abstract
Following the three-pillar structure of the Basel II/III framework, the article categorises and surveys 279 academic papers on operational risk in financial institutions, covering the period from 1998 to 2014. In doing so, different lines of both theoretical and empirical directions for research
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Following the three-pillar structure of the Basel II/III framework, the article categorises and surveys 279 academic papers on operational risk in financial institutions, covering the period from 1998 to 2014. In doing so, different lines of both theoretical and empirical directions for research are identified. In addition, this study provides an overview of existing consortia databases and other publicly available sources on operational loss that may be incorporated into empirical research, as well as in risk measurement processes by financial institutions. Finally, this paper highlights the research gaps in operational risk and outlines recommendations for further research. Full article
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