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J. Risk Financial Manag., Volume 10, Issue 4 (December 2017)

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Open AccessFeature PaperArticle Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models
J. Risk Financial Manag. 2017, 10(4), 23; https://doi.org/10.3390/jrfm10040023
Received: 30 October 2017 / Revised: 4 December 2017 / Accepted: 8 December 2017 / Published: 12 December 2017
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Abstract
This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the corresponding statistical properties of this model,
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This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the corresponding statistical properties of this model, discuss the spectral likelihood estimation and investigate the finite sample properties via Monte Carlo experiments. We provide empirical evidence by applying the GLMSV model to three exchange rate return series and conjecture that the results of out-of-sample forecasts adequately confirm the use of GLMSV model in certain financial applications. Full article
(This article belongs to the Special Issue Risk Analysis and Portfolio Modelling)
Open AccessArticle Intelligent Decision Support in Proportional–Stop-Loss Reinsurance Using Multiple Attribute Decision-Making (MADM)
J. Risk Financial Manag. 2017, 10(4), 22; https://doi.org/10.3390/jrfm10040022
Received: 8 July 2017 / Revised: 17 November 2017 / Accepted: 17 November 2017 / Published: 28 November 2017
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Abstract
This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process.
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This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM) into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust. Full article
(This article belongs to the Special Issue Risk Management Based on Intelligent Information Processing)
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Open AccessFeature PaperArticle Recovering Historical Inflation Data from Postage Stamps Prices
J. Risk Financial Manag. 2017, 10(4), 21; https://doi.org/10.3390/jrfm10040021
Received: 17 October 2017 / Revised: 7 November 2017 / Accepted: 9 November 2017 / Published: 14 November 2017
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Abstract
For many developing countries, historical inflation figures are rarely available. We propose a simple method that aims to recover such figures of inflation using prices of postage stamps issued in earlier years. We illustrate our method for Suriname, where annual inflation rates are
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For many developing countries, historical inflation figures are rarely available. We propose a simple method that aims to recover such figures of inflation using prices of postage stamps issued in earlier years. We illustrate our method for Suriname, where annual inflation rates are available for 1961 until 2015, and where fluctuations in inflation rates are prominent. We estimate the inflation rates for the sample 1873 to 1960. Our main finding is that high inflation periods usually last no longer than 2 or 3 years. An Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model for the recent sample and for the full sample with the recovered inflation rates shows the relevance of adding the recovered data. Full article
(This article belongs to the Special Issue Applied Econometrics)
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Open AccessFeature PaperArticle A Risk Management Approach for a Sustainable Cloud Migration
J. Risk Financial Manag. 2017, 10(4), 20; https://doi.org/10.3390/jrfm10040020
Received: 26 September 2017 / Revised: 27 October 2017 / Accepted: 30 October 2017 / Published: 9 November 2017
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Abstract
Cloud computing is not just about resource sharing, cost savings and optimisation of business performance; it also involves fundamental concerns on how businesses need to respond on the risks and challenges upon migration. Managing risks is critical for a sustainable cloud adoption. It
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Cloud computing is not just about resource sharing, cost savings and optimisation of business performance; it also involves fundamental concerns on how businesses need to respond on the risks and challenges upon migration. Managing risks is critical for a sustainable cloud adoption. It includes several dimensions such as cost, practising the concept of green IT, data quality, continuity of services to users and clients, guarantee tangible benefits. This paper presents a risk management approach for a sustainable cloud migration. We consider four dimensions of sustainability, i.e., economic, environmental, social and technology to determine the viability of cloud for the business context. The risks are systematically identified and analysed based on the existing in house controls and the cloud service provider offerings. We use Dempster Shafer (D-S) theory to measure the adequacy of controls and apply semi-quantitative approach to perform risk analysis based on the theory of belief. The risk exposure for each sustainability dimension allows us to determine the viability of cloud migration. A practical migration use case is considered to determine the applicability of our work. The results identify the risk exposure and recommended control for the risk mitigation. We conclude that risks depend on specific migration case and both Cloud Service Provider (CSP) and users are responsible for the risk mitigation. Inherent risks can evolve due to the cloud migration. Full article
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Open AccessArticle Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications
J. Risk Financial Manag. 2017, 10(4), 19; https://doi.org/10.3390/jrfm10040019
Received: 13 September 2017 / Revised: 15 October 2017 / Accepted: 26 October 2017 / Published: 1 November 2017
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Abstract
A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of FGM (Farlie–Gumbel–Morgenstern) bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It
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A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of FGM (Farlie–Gumbel–Morgenstern) bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It is established that construction of bivariate distributions by this method allows for greater flexibility in the values of Spearman’s correlation coefficient, ρ and Kendall’s τ . Full article
(This article belongs to the Special Issue Extreme Values and Financial Risk)
Open AccessArticle Financial Market Integration: Evidence from Cross-Listed French Firms
J. Risk Financial Manag. 2017, 10(4), 18; https://doi.org/10.3390/jrfm10040018
Received: 21 August 2017 / Revised: 27 September 2017 / Accepted: 8 October 2017 / Published: 12 October 2017
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Abstract
Using high frequency data we investigate the behavior of the intraday volatility and the volume of eight cross-listed French firms. There is a two hour “overlap” period during which French firms are traded in Paris and their related American Depositary Receipts (ADRs) are
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Using high frequency data we investigate the behavior of the intraday volatility and the volume of eight cross-listed French firms. There is a two hour “overlap” period during which French firms are traded in Paris and their related American Depositary Receipts (ADRs) are traded in New York. Using concurrent 15-min returns, this article examines the extent of market integration—defined as prices in both markets reflecting the same fundamental information—involving these firms. Our results suggest that these markets are not perfectly integrated. A significant rise in volatility and volume is observed during the two hour “overlap” period. This suggests the existence of informed trading. An error correction model (ECM) is then used to examine changes in prices of French firms in Paris and New York. These temporary changes appear to converge over time. Full article
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Open AccessArticle GARCH Modelling of Cryptocurrencies
J. Risk Financial Manag. 2017, 10(4), 17; https://doi.org/10.3390/jrfm10040017
Received: 31 August 2017 / Revised: 27 September 2017 / Accepted: 28 September 2017 / Published: 1 October 2017
Cited by 3 | PDF Full-text (262 KB) | HTML Full-text | XML Full-text
Abstract
With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are
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With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria. Conclusions are drawn on the best fitting models, forecasts and acceptability of value at risk estimates. Full article
(This article belongs to the Special Issue Extreme Values and Financial Risk)
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