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Research on Mortgage-Backed Securitization Structure
Issue:
Volume 4, Issue 2, April 2016
Pages:
21-28
Received:
6 March 2016
Published:
6 March 2016
Abstract: Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring model, this paper firstly introduced a method to estimate the repayment default rate based on distributional robust optimization. Then it improved a credit rating system by containing an option on the mortgage market value. Finally it proposed to use the dynamic programming model to structure the mortgage-backed securities. It is supposed to make a contribution to the financial innovation in China and put forward fresh ideals.
Abstract: Asset securitization is an important way to improve bank asset liability structure, and can offer investors financial tools with high yields. Owing to the rapid and stable development of the financial market, the large-scale asset securitization age is on the way. To establish a complete and reasonable mortgage-backed securitization structuring mod...
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Bayesian Structural Equation Modeling: A Business Culture Application in Kenya
Mutitu Ephantus Mwangi,
Antony Wanjoya
Issue:
Volume 4, Issue 2, April 2016
Pages:
37-42
Received:
12 October 2015
Accepted:
26 October 2015
Published:
16 March 2016
Abstract: Structural equation modeling (SEM) is a multivariate method that incorporates regression, path-analysis and factor analysis. Classical SEM requires the assumption of multivariate normality to be met and large sample size, also choice is made either to ignore uncertainties or treat the latent variables as observed. National culture Data gathered in a study or survey may be inform of ordered categories and may not follow the assumptions of multivariate normality. This restricts the use of frequentist method of estimation. A Bayesian approach to SEM allows inclusion of this uncertainty and directly models the uncertainties in predictive models. In addition Bayesian SEM does not require constant variance normal disturbances and the sample size can be a small number. The development and application of Bayesian SEM has been relatively slow but it has been made possible by Gibbs sampler. The main purpose of the study was model National Culture in Kenya based on Hofstede model and business performance. Maximum likelihood Estimation was used to estimate the parameters in Classical SEM. Gibbs sampler algorithm was employed in Bayesian approach to SEM. This study used non-informative priors. The convergence of parameter was evaluated using proportional scale reduction procedure and trace and density plots. Data was gathered from employees in Nairobi through structured questionnaires. Bayesian SEM with non-informative prior gave the best estimates indicating that personal distance, individualism and long term orientation were significantly related to business performance. However, Uncertainty Avoidance had no significant relationship with business performance.
Abstract: Structural equation modeling (SEM) is a multivariate method that incorporates regression, path-analysis and factor analysis. Classical SEM requires the assumption of multivariate normality to be met and large sample size, also choice is made either to ignore uncertainties or treat the latent variables as observed. National culture Data gathered in ...
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Factors Mediating Between Government Expenditure and Unemployment in Nigeria
Chike Henry Nwankwo,
Amechi Henry Igweze
Issue:
Volume 4, Issue 2, April 2016
Pages:
43-47
Received:
16 January 2016
Accepted:
8 February 2016
Published:
18 March 2016
Abstract: The study seeks to find economic variables mediating between unemployment and government expenditure in Nigeria. The indirect effect was tested using the method of difference of coefficient. the findings shoe that only labour force population and inflation showed evidence of partial mediation, although their mediational (indirect) effect are not statistically significant as the P-values of the test of indirect effect are all greater than the level of significance, 0.05. Further studies are recommended to ascertain factors mediating upon government expenditure and unemployment in Nigeria other than economic variables already studied.
Abstract: The study seeks to find economic variables mediating between unemployment and government expenditure in Nigeria. The indirect effect was tested using the method of difference of coefficient. the findings shoe that only labour force population and inflation showed evidence of partial mediation, although their mediational (indirect) effect are not st...
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The Inverse Problem of the Calculus of Variation
Issue:
Volume 4, Issue 2, April 2016
Pages:
48-51
Received:
8 February 2016
Accepted:
9 March 2016
Published:
28 March 2016
Abstract: In this paper, it is intended to determine the necessary and sufficient conditions for the existence and hence the construction of a Lagrangian
of a dynamical system from its equations of motion. The existence of a Lagrangian is vital importance for the Hamiltonian description of a dynamical system since via the Legendre transformation
we get the Hamiltonian of the system [1, 2]. It is also intended to show that the solution of the realization problem for the Hamiltonian system reduces to solving an inverse problem.
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Statistical Modeling of Quarterly Record of Rainfall Distribution in South West Nigeria
Iyabode Favour Oyenuga,
Benjamin Agboola Oyejola,
Johnson Taiwo Olajide
Issue:
Volume 4, Issue 2, April 2016
Pages:
52-58
Received:
26 February 2016
Accepted:
10 March 2016
Published:
29 March 2016
Abstract: Modelling distribution of rainfall in South West Nigeria is examined. Quarterly rainfall distribution data of Ibadan as a case study were collected for a period of 43 years (1971-2013) from Nigeria Meteorological Agency (NMA) quoted in Central Bank of Nigeria (CBN) bulletin. The time series analysis was used to model and forecast the quarterly rainfall. The time plot shows there is a seasonal cycles in the series, we used Akaike Information Criterion to detect auto-regressive (AR), moving average (MA) and auto-regressive moving average (ARMA) models of the best order. It was shown that AR(4), MA(4) and ARMA(4,4) have the least Akaike Information Criterion (AIC). These models were then used to forecast for the quarterly rainfall for five years.
Abstract: Modelling distribution of rainfall in South West Nigeria is examined. Quarterly rainfall distribution data of Ibadan as a case study were collected for a period of 43 years (1971-2013) from Nigeria Meteorological Agency (NMA) quoted in Central Bank of Nigeria (CBN) bulletin. The time series analysis was used to model and forecast the quarterly rain...
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An Approach of Power Estimation for Linear Mixed Models for Clinical Studies
Issue:
Volume 4, Issue 2, April 2016
Pages:
59-63
Received:
10 April 2016
Published:
11 April 2016
Abstract: This study aims to demonstrate a practical way of power estimation for linear mixed models in clinical studies. Approximation methods using z and t statistics are discussed and compared to the simulated results. It was found that the approximation methods generally provide a slight overestimation of power, relative to simulated results using the Kenward and Roger estimation of degree of freedom. However, results of approximation methods can be informative in certain scenarios. In conclusion, the z approximation and t approximation with a residual degree of freedom can be useful in certain situations. Simulation method can serve as a general solution.
Abstract: This study aims to demonstrate a practical way of power estimation for linear mixed models in clinical studies. Approximation methods using z and t statistics are discussed and compared to the simulated results. It was found that the approximation methods generally provide a slight overestimation of power, relative to simulated results using the Ke...
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Modeling and Forecasting Kenyan GDP Using Autoregressive Integrated Moving Average (ARIMA) Models
Musundi Sammy Wabomba,
M’mukiira Peter Mutwiri,
Mungai Fredrick
Issue:
Volume 4, Issue 2, April 2016
Pages:
64-73
Received:
14 March 2016
Accepted:
25 March 2016
Published:
13 April 2016
Abstract: The Gross Domestic Product (GDP) is the market value of all goods and services produced within the borders of a nation in a year. In this paper, Kenya’s annual GDP data obtained from the Kenya National Bureau of statistics for the years 1960 to 2012 was studied. Gretl and SPSS 21 statistical softwares were used to build a class of ARIMA (autoregressive integrated moving average) models following the Box-Jenkins method to model the GDP. ARIMA (2, 2, 2) time series model was established as the best for modeling the Kenyan GDP according to the recognition rules and stationary test of time series under the AIC criterion. The results of an in-sample forecast showed that the relative and predicted values were within the range of 5%, and the forecasting effect of this model was relatively adequate and efficient in modeling the annual returns of the Kenyan GDP. Finally, we used the fitted ARIMA model to forecast the GDP of Kenya for the next five years.
Abstract: The Gross Domestic Product (GDP) is the market value of all goods and services produced within the borders of a nation in a year. In this paper, Kenya’s annual GDP data obtained from the Kenya National Bureau of statistics for the years 1960 to 2012 was studied. Gretl and SPSS 21 statistical softwares were used to build a class of ARIMA (autoregres...
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Implicit Exponentially Fitted RKNd Methods for Solving Oscillatory ODEs
Wenjuan Zhai,
Bingzhen Chen
Issue:
Volume 4, Issue 2, April 2016
Pages:
74-80
Received:
12 April 2016
Published:
13 April 2016
Abstract: In this paper, we derive the implicit exponentially fitted RKNd methods for solving oscillatory ODEs. The new methods integrate exactly differential systems whose solutions can be expressed as linear combinations of functions from the set {exp(λt), exp(−λt)}, λ ∈ C, or equivalently 
when λ = iω, ω ∈ R. Numerical experiments are accompanied to show the efficiency and competence of the implicit exponentially fitted RKNd methods compared with implicit RKNd methods.
Abstract: In this paper, we derive the implicit exponentially fitted RKNd methods for solving oscillatory ODEs. The new methods integrate exactly differential systems whose solutions can be expressed as linear combinations of functions from the set {exp(λt), exp(−λt)}, λ ∈ C, or equivalently when λ = iω, ω ∈ R. Numerical experiments are accompanied to show ...
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Key Performance Indicators for Electricity Conservation in Open Pit Mining
Qinglin Yu,
Long Wen,
Craig Haight,
Alex Russell-Jones
Issue:
Volume 4, Issue 2, April 2016
Pages:
81-87
Received:
12 April 2016
Published:
13 April 2016
Abstract: In mining operation, blasts are used to fracture the in-situ rock mass and prepare it for excavation, crushing and grinding. The High-energy blasting, which uses increased amount of explosive material per tonne of rock, is considered to be one of most effective ways to reduce the consumption of energy in the milling process, resulting production saving as well as reduction in dust (PM5) and tailing. In this article, the main focus is to investigate the electrical intensity of the five grinding lines in the mill, as they accounted for the majority of site electricity consumption, in relations to other operational procedures, in particular the high-energy blasting. Several regression models were established, the data points were fitted within 10% of the actual values, and the majority within 5%. The models provide management better ways to predict and target electrical consumption and environmental impact.
Abstract: In mining operation, blasts are used to fracture the in-situ rock mass and prepare it for excavation, crushing and grinding. The High-energy blasting, which uses increased amount of explosive material per tonne of rock, is considered to be one of most effective ways to reduce the consumption of energy in the milling process, resulting production sa...
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