scholarly journals ASURANSI JIWA ENDOWMENT DENGAN PENGEMBALIAN PREMI MENGGUNAKAN SIMULASI MONTE CARLO

2019 ◽  
Vol 8 (2) ◽  
pp. 95
Author(s):  
MADE EDI HENDRAWAN ◽  
I NYOMAN WIDANA ◽  
KETUT JAYANEGARA
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Interest Rates ◽  
Life Insurance ◽  
Mortality Rates ◽  
Numerical Calculations ◽  
Gompertz Distribution ◽  
Constant Interest

Premium refunds are a sum of the money returned to the insured. The purpose of this study was to compare the premium of endowment life insurance with premium refund on constant interest rates numerical calculations and using Monte Carlo simulations. Gompertz distribution was used to obtain the mortality rates. The results showed that the premiums generated by Monte Carlo simulations for insurance participants issued under 45 years will be more expensive than the ones which were generated by numerical calculations. However, the premiums generated by Monte Carlo simulations for insurance participants issued above 45 years will be cheaper than the ones which were generated by numerical calculations.

MATHEMATICAL BASIS OF COMPUTATIONAL PHYSICS

1996 ◽  
Vol 07 (03) ◽  
pp. 355-359 ◽  
Author(s):  
M. SUZUKI
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Quantum Monte Carlo ◽  
Computational Physics ◽  
Numerical Calculations ◽  
Symplectic Integration ◽  
Mathematical Basis ◽  
Small Parameters ◽  
Quantum Monte Carlo Simulations

The present paper explains some general basic formulas concerning quantum Monte Carlo simulations, symplectic integration and other numerical calculations. A generalization of the BCH formula is given with an application to the decomposition of exponential operators in the presence of small parameters.

Mortality Estimation: Biased Results from Unbiased Ages

1984 ◽  
Vol 41 (12) ◽  
pp. 1843-1847 ◽  
Author(s):  
Jay Barlow
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Age Estimation ◽  
Age Determination ◽  
Mortality Rates ◽  
Age Classes ◽  
Estimation Errors ◽  
Mortality Estimation ◽  
Age Estimates

Estimates of mortality rates from age distributions are biased by imprecision in age estimation, even if age estimates are unbiased. I have derived a method for predicting the magnitude of this bias from information on the precision of age determination. Monte Carlo simulations show that bias can be accurately predicted. The commonly used Chapman–Robson mortality estimator is shown to be robust to imprecision in age determination if all age-classes are included. Errors are likely, however, if one or more age-classes are excluded or if other mortality estimators are used. Biases can be corrected if the distribution of age-estimation errors is known.

scholarly journals Monte Carlo Simulations of a Scanning System Based on a Panoramic X-Ray Tube with a Conical Anode

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Andrii Sofiienko ◽  
Chad Jarvis ◽  
Ådne Voll
Keyword(s):  
Monte Carlo ◽  
Electron Beam ◽  
Angular Distribution ◽  
Monte Carlo Simulations ◽  
Electron Beams ◽  
Numerical Calculations ◽  
Scanning System ◽  
Pencil Beam ◽  
X Ray ◽  
Photon Intensity

Monte Carlo simulations were used to study photon production in a panoramic X-ray tube with a conical tungsten target to determine the optimal characteristics of the target shape and electron beam configuration. Several simulations were performed for accelerating potentials equal to 250 kV, 300 kV, and 500 kV with electron beams of various radii and anode sizes. The angular distribution of the photon intensity was analysed by numerical calculations for an assembly composed of an X-ray tube and an external collimator with a cylindrical hole to simulate a panoramic scanning system with an X-ray pencil beam.

scholarly journals PENENTUAN CADANGAN PREMI UNTUK ASURANSI JOINT LIFE

2016 ◽  
Vol 5 (1) ◽  
pp. 32
Author(s):  
NI LUH PUTU RATNA DEWI ◽  
I NYOMAN WIDANA ◽  
DESAK PUTU EKA NILAKUSMAWATI
Keyword(s):  
Interest Rates ◽  
Life Insurance ◽  
Calculation Method ◽  
First Year ◽  
Insurance Company ◽  
Premium Payment ◽  
Mortality Table ◽  
Constant Interest ◽  
Annual Premium

Premium reserve is a number of fund that need to be raised by insurance company in preparation for the payment of claims. This study aims to get the formula of premium reserve as well as the value of the premium reserve for joint life insurance by using retrospective calculation method. Joint life insurance participants in this study are limited to 2 people. Calculations in this study is using Indonesian Mortality Table (TMI) 2011, joint life mortality tables, commutation tables, value of annuities, value of single premiums and constant annual premium and using constant interest rates of 5%. The results showed that by using age of the participant insurance joint life of x = 50 and y = 45 years and the premium payment period of t = 10 years, we obtained that the value of premium reserve from the end of the first year until the  end of the 11th year has increased every year, while the value of premium reserves from the end of the 12th year and so on until a lifetime has decreased every year.

scholarly journals A neural network model for solvency calculations in life insurance

2020 ◽  
pp. 1-17
Author(s):  
Lucio Fernandez-Arjona
Keyword(s):  
Neural Network ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Life Insurance ◽  
Insurance Companies ◽  
Feature Engineering ◽  
Proposed Model ◽  
Risk Framework ◽  
Proxy Models ◽  
Function Selection

Abstract Insurance companies make extensive use of Monte Carlo simulations in their capital and solvency models. To overcome the computational problems associated with Monte Carlo simulations, most large life insurance companies use proxy models such as replicating portfolios (RPs). In this paper, we present an example based on a variable annuity guarantee, showing the main challenges faced by practitioners in the construction of RPs: the feature engineering step and subsequent basis function selection problem. We describe how neural networks can be used as a proxy model and how to apply risk-neutral pricing on a neural network to integrate such a model into a market risk framework. The proposed model naturally solves the feature engineering and feature selection problems of RPs.

Low-voltage EDS of magnesium ferrite Dendrites in a FEG-SEM

1996 ◽  
Vol 54 ◽  
pp. 478-479
Author(s):  
Matthew T. Johnson ◽  
Ian M. Anderson ◽  
Jim Bentley ◽  
C. Barry Carter
Keyword(s):  
Monte Carlo ◽  
Quantitative Analysis ◽  
Monte Carlo Simulations ◽  
Cross Section ◽  
Spatial Resolution ◽  
Low Voltage ◽  
Magnesium Ferrite ◽  
X Ray ◽  
Interaction Volume ◽  
Ferrite Spinel

Energy-dispersive X-ray spectrometry (EDS) performed at low (≤ 5 kV) accelerating voltages in the SEM has the potential for providing quantitative microanalytical information with a spatial resolution of ∼100 nm. In the present work, EDS analyses were performed on magnesium ferrite spinel [(MgxFe1−x)Fe2O4] dendrites embedded in a MgO matrix, as shown in Fig. 1. spatial resolution of X-ray microanalysis at conventional accelerating voltages is insufficient for the quantitative analysis of these dendrites, which have widths of the order of a few hundred nanometers, without deconvolution of contributions from the MgO matrix. However, Monte Carlo simulations indicate that the interaction volume for MgFe2O4 is ∼150 nm at 3 kV accelerating voltage and therefore sufficient to analyze the dendrites without matrix contributions.Single-crystal {001}-oriented MgO was reacted with hematite (Fe2O3) powder for 6 h at 1450°C in air and furnace cooled. The specimen was then cleaved to expose a clean cross-section suitable for microanalysis.

MONTE CARLO SIMULATIONS OF ELECTRON DRIFT VELOCITIES IN THE NOBLE GASES AND THEIR MIXTURES

1979 ◽  
Vol 40 (C7) ◽  
pp. C7-63-C7-64
Author(s):  
A. J. Davies ◽  
J. Dutton ◽  
C. J. Evans ◽  
A. Goodings ◽  
P.K. Stewart
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Noble Gases ◽  
Electron Drift
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