scholarly journals Stock Price Simulation Using Bootstrap and Monte Carlo

2017 ◽  
Vol 64 (2) ◽  
pp. 155-170 ◽  
Author(s):  
Martin Pažický
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Stock Price ◽  
Error Term ◽  
Monte Carlo Experiment ◽  
Asian Option ◽  
Heteroscedastic Error ◽  
Maturity Date ◽  
The Future ◽  
The Difference

Abstract In this paper, an attempt is made to assessment and comparison of bootstrap experiment and Monte Carlo experiment for stock price simulation. Since the stock price evolution in the future is extremely important for the investors, there is the attempt to find the best method how to determine the future stock price of BNP Paribas′ bank. The aim of the paper is define the value of the European and Asian option on BNP Paribas′ stock at the maturity date. There are employed four different methods for the simulation. First method is bootstrap experiment with homoscedastic error term, second method is blocked bootstrap experiment with heteroscedastic error term, third method is Monte Carlo simulation with heteroscedastic error term and the last method is Monte Carlo simulation with homoscedastic error term. In the last method there is necessary to model the volatility using econometric GARCH model. The main purpose of the paper is to compare the mentioned methods and select the most reliable. The difference between classical European option and exotic Asian option based on the experiment results is the next aim of tis paper.

scholarly journals On the Difference between Self-Assembling Process of Monomeric and Dimeric Surfactants with the Same Head to Tail Ratio: A Lattice Monte Carlo Simulation

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Reza Behjatmanesh-Ardakani ◽  
Maryam Farsad
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gemini Surfactants ◽  
Chain Structure ◽  
Single Chain ◽  
Lattice Monte Carlo ◽  
Self Assembling ◽  
Spacer Group ◽  
The Difference ◽  
Dimeric Surfactants

Experimental data show that gemini surfactants have critical micelle concentrations that are almost tenfold lower than the CMCs of single chain ones. It is believed that the spacer groups play an important role in this subject. Short hydrophilic or long hydrophobic spacers can reduce CMC dramatically. In this paper, self-assembling processes of double-chain and one-chain surfactants with the same head to tail ratio are compared. Dimeric chain structure is exactly double of single chain. In other words, hydrophilic-lyophilic balances of two chain models are the same. Two single chains are connected head-to-head to form a dimeric chain, without introducing extra head or tail beads as a spacer group. Premicellar, micellar, and shape/phase transition ranges of both models are investigated. To do this, lattice Monte Carlo simulation in canonical ensemble has been used. Results show that without introducing extra beads as spacer group, the CMC of (H3T3)2as a dimeric surfactant is much lower than the CMC of its similar single chain, H3T3. For dimeric case of study, it is shown that bolaform aggregates are formed.

scholarly journals PENENTUAN HARGA KONTRAK OPSI TIPE ASIA MENGGUNAKAN MODEL SIMULASI NORMAL INVERSE GAUSSIAN (NIG)

2014 ◽  
Vol 3 (3) ◽  
pp. 123
Author(s):  
I PUTU OKA PARAMARTHA ◽  
KOMANG DHARMAWAN ◽  
DESAK PUTU EKA NILAKUSMAWATI
Keyword(s):  
Monte Carlo ◽  
Stock Prices ◽  
Stock Price ◽  
Monte Carlo Model ◽  
Asian Option ◽  
Inverse Gaussian ◽  
Fair Price ◽  
Simulation Accuracy ◽  
Two Parameters ◽  
Normal Inverse Gaussian

The aim to determine of the simulation results and to calculate the stock price of Asian Option with Normal Inverse Gaussian (NIG) method and Monte Carlo method using MATLAB program. Results of both models are compared and selected a fair price. Besides to determine simulation accuracy of the stock price, speed of program execution MATLAB is calculated for both models for time efficiency. The first part, set variabels used to calculate the trajectory of stock prices at time t to simulate the stock price at the time. The second part, simulate the stock price with NIG model. The third part, simulate the stock price with Monte Carlo model. After simulating the stock price, calculated the value of the pay-off of the Asian Option, and then estimate the price of Asian Option by averaging the entire value of pay-off from each iteration. The last part, compare result of both models. The results of this research is price of Asian Option calculated using Monte Carlo simulation and NIG. The rates were calculated using the NIG produce a fair price, because of the pricing contract NIG using four parameters ?, ?, ?, and ?, while Monte Carlo is using only two parameters ? and ?. For execution time of the program, the Monte Carlo model is better in all iterations.

scholarly journals A note on the Gao et al. (2019) uniform mixture model in the case of regression

2019 ◽  
Vol 289 (2) ◽  
pp. 495-501
Author(s):  
Mike G. Tsionas ◽  
Athanasios Andrikopoulos
Keyword(s):  
Monte Carlo ◽  
Linear Regression ◽  
Mixture Model ◽  
Bayesian Methods ◽  
Error Term ◽  
Probability Distributions ◽  
Monte Carlo Experiment ◽  
Link Type ◽  
Irregular Data ◽  
Weighted Combination

AbstractWe extend the uniform mixture model of Gao et al. (Ann Oper Res, 2019. 10.1007/s10479-019-03236-9) to the case of linear regression. Gao et al. (Ann Oper Res, 2019. 10.1007/s10479-019-03236-9) proposed that to characterize the probability distributions of multimodal and irregular data observed in engineering, a uniform mixture model can be used. This model is a weighted combination of multiple uniform distribution components. This case is of empirical interest since, in many instances, the distribution of the error term in a linear regression model cannot be assumed unimodal. Bayesian methods of inference organized around Markov chain Monte Carlo are proposed. In a Monte Carlo experiment, significant efficiency gains are found in comparison to least squares justifying the use of the uniform mixture model.

scholarly journals PENENTUAN HARGA OPSI BELI TIPE ASIA DENGAN METODE MONTE CARLO-CONTROL VARIATE

2017 ◽  
Vol 6 (1) ◽  
pp. 29
Author(s):  
NI NYOMAN AYU ARTANADI ◽  
KOMANG DHARMAWAN ◽  
KETUT JAYANEGARA
Keyword(s):  
Monte Carlo ◽  
Standard Error ◽  
Asset Price ◽  
Option Price ◽  
Asian Option ◽  
Underlying Asset ◽  
Average Value ◽  
Control Variate ◽  
Exercise Price ◽  
Maturity Date

Option is a contract between the writer and the holder which entitles the holder to buy or sell an underlying asset at the maturity date for a specified price known as an exercise price. Asian option is a type of financial derivatives which the payoff taking the average value over the time series of the asset price. The aim of the study is to present the Monte Carlo-Control Variate as an extension of Standard Monte Carlo applied on the calculation of the Asian option price. Standard Monte Carlo simulations 10.000.000 generate standard error 0.06 and the option price convergent at Rp.160.00 while Monte Carlo-Control Variate simulations 100.000 generate standard error 0.01 and the option price convergent at Rp.152.00. This shows the Monte Carlo-Control Variate achieve faster option price toward convergent of the Monte Carlo Standar.

Rekursive oder nicht-rekursive Modelle? / Testing for non-recursiveness in causal modelling

1975 ◽  
Vol 4 (3) ◽  
Author(s):  
Christof Ammermann ◽  
Peter Gluchowski ◽  
Peter Schmidt
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Error Term ◽  
Causal Model ◽  
Identification Problem ◽  
Testing Procedure ◽  
Small Samples ◽  
Theory Construction ◽  
Causal Modelling ◽  
Oder Nicht

AbstractThe paper discusses a stubborn problem of theory construction: deciding between recursive and non- recursive variants of a causal model by testing them against empirical data. After pointing out the consequences of a correlation between an exogeneous variable and the error term of an endogeneous variable as well as certain aspects of the identification problem we show for the asymptotic case (n → ∞) that a test is possible if the correlation between the exogeneous and the error term is in fact zero. Following this we present the results of a Monte-Carlo simulation investigating the robustness of the proposed test when applied to small samples. Finally we suggest conclusions of this testing procedure for empirical research.

Reliability Estimation of Buried Pipeline Using FORM, SORM and Monte Carlo Simulation

2006 ◽  
Vol 326-328 ◽  
pp. 597-600 ◽  
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Exposure Time ◽  
Failure Probability ◽  
Reliability Estimation ◽  
Buried Pipeline ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method ◽  
The Difference

In this paper, the failure probability is estimated by using the FORM (first order reliability method), the SORM (second order reliability method) and the Monte Carlo simulation to evaluate the reliability of the corroded pipeline. It is found that the FORM technique is more effective in estimating the failure probability than the SORM technique for B31G and MB31G models with three different corrosion models. Furthermore, it is noted that the difference between the results of the FORM, the SORM and the Monte Carlo simulation decreases with the increase of the exposure time.

scholarly journals M/M/C Queue under Monte Carlo Simulation for a Restaurant Model

2019 ◽  
Vol 8 (10) ◽  
pp. 1818-1823
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Waiting Time ◽  
Analytical Methods ◽  
Queuing Model ◽  
Stationary Density ◽  
Density Flow ◽  
The Future

In this paper we present a stochastic queuing model for a restaurant which captures the stationary density flow relations. The performance of controlling the heterogeneous crowd in a restaurant under Monte Carlo simulation with various service distributions has been discussed. Using this analysis in future the waiting time of the customers can be reduced and the profit of the management can also be increased. The future behaviour of a restaurant networks both in simulation and analytical methods have been analysed.

scholarly journals MANOVA: POWER ANALYSIS OF MODELS OF SUDOKU SQUARE DESIGNS

2020 ◽  
Vol 4 (2) ◽  
pp. 350-364
Author(s):  
A. Shehu ◽  
N. S. Dauran
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Sample Size ◽  
Power Analysis ◽  
Design Models ◽  
Power Test ◽  
Power Difference ◽  
The Difference ◽  
Interval Value

This paper assesses the performance of multivariate treatment tests (Wilk’s Lambda, Hoteling-lawley, Roy’s largest root and Pillai) on multivariate Sudoku square design models in terms of power analysis. Monte carlo simulation was conducted to compare the power of these four tests for the four multivariate Sudoku square design models. This study used  0.062 as interval value for Power difference between two tests of the same sample size. The test is considered powerful or having advantage, if the difference between the powers of the tests is   . The results of Power test show that Hoteling-lawley has advantage over three other tests at P=2 while at P=3 Wilk’s lambda test has power advantage over other tests in all the multivariate Sudoku models.

scholarly journals Prediction of Stock Price Movements using Monte Carlo Simulation

2019 ◽  
Vol 8 (12) ◽  
pp. 2012-2016
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Stock Price ◽  
Narrow Band ◽  
Share Price ◽  
Share Prices ◽  
The Past ◽  
Price Movements ◽  
A Minor ◽  
Random Behaviour

Monte Carlo Simulation depends on random behaviour of events. When a variable takes values at random and becomes highly unpredictable due to its nature of randomness, the property of random numbers is made use of for predicting the future values that the variable may take. This property can be made use of for predicting share price movements, when the past share prices exhibit random behaviour, without exhibiting high fluctuations. This article explains the methodology of using Monte Carlo Simulation for predicting share price movements and explains the process with the help of an illustration taking the monthly share price data of ITC Limited for a period of 36 months, where the share prices have moved within a narrow band. Findings of the analysis show that it works well and that the method of prediction is reasonably accurate, showing only a minor deviation from the actual prices.

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