scholarly journals MENENTUKAN HARGA OPSI DENGAN METODE MONTE CARLO BERSYARAT MENGGUNAKAN BARISAN KUASI ACAK FAURE

2021 ◽  
Vol 10 (3) ◽  
pp. 141
Author(s):  
PUTU WIDYA ASTUTI ◽  
KOMANG DHARMAWAN ◽  
KARTIKA SARI
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Sequence ◽  
Random Number Generator ◽  
Option Price ◽  
Call Option ◽  
Standard Distribution ◽  
Real Value ◽  
Conditional Monte Carlo ◽  
The Right

An option contract is a contract that gives the owner the right to sell or even to buy an asset at the predetermined price and period time. The conditional Monte Carlo is one of the several methods that is used to determine the option price which in the process uses random numbers with normal standard distribution. At the same time, the random number generator can be substituted by using a quasi-random sequence, as in Faure's quasi-random sequence. The aim of this study is to determine the contract price of the call option with the European type by applying the conditional Monte Carlo method. This method used the Faure quasi-random sequence and compared it with the method of Monte Carlo standard, Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. The results of this study showed that the call option calculated using the conditional Monte Carlo method using the quasi-random Faure sequence began to stabilize at the 5000th simulation for K = 32575 and K = 34725 and in the 10000th simulation for K = 33000 and K = 33950. Research also show that with the conditional Monte Carlo in using the quasi-random sequence of Faure is more stable. Therefore, it is obtained its real value faster than the Monte Carlo standard, Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. The MAPE value of conditional Monte Carlo in using the quasi-random sequences of Faure and the Monte Carlo standard is smaller than the Monte Carlo standard in using the quasi-random sequence of Faure, and conditional Monte Carlo. Therefore, it can be said to be more accurate when calculating the European type call option price at BBCA.JK stocks.

scholarly journals PERBANDINGAN KEKONVERGENAN METODE CONDITIONAL MONTE CARLO DAN ANTITHETIC VARIATE DALAM MENENTUKAN HARGA OPSI CALL TIPE BARRIER

2018 ◽  
Vol 7 (3) ◽  
pp. 271
Author(s):  
NI LUH PUTU KARTIKA WATI ◽  
KOMANG DHARMAWAN ◽  
KARTIKA SARI
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Stock Price ◽  
Option Price ◽  
Life Time ◽  
Barrier Option ◽  
Strike Price ◽  
Stock Volatility ◽  
Volatility Risk ◽  
Conditional Monte Carlo

Barrier option is an option where the payoff price depends  on whether or not the stock price passes the barrier during its life time. The aim of the research is to compare the convergence between conditional Monte Carlo and antithetic variate methods in determining the call barrier option  price. The call barrier option price  is influenced by several factors: initial stock price, stock volatility, risk-free interest rate, maturity, strike price and barrier. The calculation of call barrier option price is obtained by simulating stock price movements with different simulation number. Based on the simulation result, it is obtained that the calculation of call barrier option price with conditional Monte Carlo method converge faster than the antithetic variate method.

MONTE CARLO METHODS IN FUZZY NON-LINEAR REGRESSION

2008 ◽  
Vol 04 (02) ◽  
pp. 123-141 ◽  
Author(s):  
AREEG ABDALLA ◽  
JAMES BUCKLEY
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Linear Regression ◽  
Fuzzy Numbers ◽  
Random Number ◽  
Random Number Generator ◽  
Search Space ◽  
Triangular Fuzzy Numbers ◽  
Non Linear ◽  
Regression Problems

We apply our new fuzzy Monte Carlo method to certain fuzzy non-linear regression problems to estimate the best solution. The best solution is a vector of triangular fuzzy numbers, for the fuzzy coefficients in the model, which minimizes an error measure. We use a quasi-random number generator to produce random sequences of these fuzzy vectors which uniformly fill the search space. We consider example problems to show that this Monte Carlo method obtains solutions comparable to those obtained by an evolutionary algorithm.

A Modification to the Monte Carlo Method—The Exodus Method

1968 ◽  
Vol 90 (3) ◽  
pp. 328-332 ◽  
Author(s):  
A. F. Emery ◽  
W. W. Carson
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Random Number ◽  
Random Number Generator ◽  
Number Generator ◽  
Calculation Time ◽  
The Monte Carlo Method

A modification to the Monte Carlo method is described which reduces calculation time and improves the accuracy. This method—termed “Exodus”—is not dependent upon a random number generator and may be applied to any problem which admits of a nodal network.

scholarly journals Variance and Dimension Reduction Monte Carlo Method for Pricing European Multi-Asset Options with Stochastic Volatilities

2019 ◽  
Vol 11 (3) ◽  
pp. 815 ◽  
Author(s):  
Yijuan Liang ◽  
Xiuchuan Xu
Keyword(s):  
Monte Carlo ◽  
Variance Reduction ◽  
Convergence Rates ◽  
Option Price ◽  
Correlation Coefficients ◽  
Control Variate ◽  
Stochastic Volatilities ◽  
Conditional Monte Carlo ◽  
Mc Simulation ◽  
Martingale Representation Theorem

Pricing multi-asset options has always been one of the key problems in financial engineering because of their high dimensionality and the low convergence rates of pricing algorithms. This paper studies a method to accelerate Monte Carlo (MC) simulations for pricing multi-asset options with stochastic volatilities. First, a conditional Monte Carlo (CMC) pricing formula is constructed to reduce the dimension and variance of the MC simulation. Then, an efficient martingale control variate (CV), based on the martingale representation theorem, is designed by selecting volatility parameters in the approximated option price for further variance reduction. Numerical tests illustrated the sensitivity of the CMC method to correlation coefficients and the effectiveness and robustness of our martingale CV method. The idea in this paper is also applicable for the valuation of other derivatives with stochastic volatility.

PENENTUAN HARGA OPSI DENGAN MODEL BLACK-SCHOLES MENGGUNALKAN METODE BEDA HINGGA FORWARD TIME CENTRAL SPACE

2018 ◽  
Vol 1 (1) ◽  
pp. 45
Author(s):  
Werry Febrianti
Keyword(s):  
Finite Difference ◽  
Finite Difference Method ◽  
Difference Method ◽  
Option Price ◽  
Call Option ◽  
Put Option ◽  
Daily Data ◽  
Black Scholes ◽  
One Year ◽  
The Right

Option can be defined as a contract between two sides/parties said party one and party two. Party one has the right to buy or sell of stock to party two. Party two can invest by observe the put option price or call option price on a time period in the option contract. Black-Scholes option solution using finite difference method based on forward time central space (FTCS) can be used as the reference for party two in the investment determining. Option price determining by using Black-Scholes was applied on Samsung stock (SSNLF) by using finite difference method FTCS. Daily data of Samsung stock in one year was processed to obtain the volatility of the stock. Then, the call option and put option are calculated by using FTCS method after discretization on the Black-Scholes model. The value of call option was obtained as $1.457695030014260 and the put option value was obtained as $1.476925604670225.

American Basket Option Pricing Formulas in Uncertain Environment

2021 ◽  
pp. 2150011
Author(s):  
Rong Gao ◽  
Xiaofang Yin
Keyword(s):  
Option Pricing ◽  
Option Price ◽  
Weighted Average ◽  
Call Option ◽  
Strike Price ◽  
Basket Option ◽  
Put Option ◽  
The Right ◽  
The Relationship ◽  
Financial Environment

American basket option is a contract containing multiple underlying assets, and its payoff is correlated with average prices or weighted average prices of these assets on or before the expiration date. The type of option entitles a holder the right to trade at the strike price within a specified date, and this right can be waived. Therefore, there is a certain price to be paid for acquiring this right, which produces the problem of option pricing. A lot of literature shows blackthat basket option price is usually cheaper than option portfolios on individual underlying assets. Based on this advantage, basket option blackbecomes popular among investors. Consequently, this paper predominantly explores four types of American basket option pricing in uncertain financial environment. Specifically they are American arithmetic basket call option, American arithmetic basket put option, American geometric basket call option and American geometric basket put option. Assuming that these stocks prices follow corresponding uncertain differential equations, we derive corresponding option pricing formulas. Some numerical examples are taken to illustrate the feasibility of pricing formulas. Simultaneously, this paper discusses the relationship between option price and some parameters.

scholarly journals Penentuan Harga Opsi Asia dengan Metode Monte Carlo

2017 ◽  
Vol 3 (1) ◽  
pp. 44-48
Author(s):  
Surya Amami Pramuditya
Keyword(s):  
Monte Carlo ◽  
Confidence Interval ◽  
Stock Price ◽  
Variance Reduction ◽  
Option Price ◽  
Numerical Procedure ◽  
Reduction Technique ◽  
Asian Options ◽  
Call Option ◽  
Strike Price

An option is a contract between a holder and a writer in which the writer grants the rights (not obligations) to the holder to buy or sell the assets of the writer at a certain price (strike price) at maturity time. Asian options are included in the dependent path option. This means that Asia's payoff option depends not only on the stock price at maturity time, but it is the average stock price during its maturity and symbolized A (average). Monte Carlo is basically used as a numerical procedure to estimate the expected value of pricing product derivatives. The techniques used are the standard Monte Carlo and variance reduction. The result obtained the Asia call option price and put for both techniques with 95% confidence interval. The variance reduction technique looks faster reducing 95% confidence interval than standard method.

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