scholarly journals PENGARUH PEMBAGIAN DIVIDEN MELALUI MODEL BLACK-SCHOLES

2021 ◽  
Vol 2 (3) ◽  
pp. 351-354
Author(s):  
Diana Purwandari
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
European Options ◽  
Financial Contracts ◽  
Stock Trading ◽  
Black Scholes Model ◽  
Black Scholes ◽  
Dividend Distribution ◽  
Option Pricing Model ◽  
The Right

Stock trading has a risk that can be said to be quite large due to fluctuations in stock prices. In stock trading, one alternative to reduce the amount of risk is options. The focus of this research is on European options which are financial contracts by giving the holder the right, not the obligation, to sell or buy the principal asset from the writer when it expires at a predetermined price. The Black-Scholes model is an option pricing model commonly used in the financial sector. This study aims to determine the effect of dividend distribution through the Black-Scholes model on stock prices. The effect of dividend distribution through the Black-Scholes model on stock prices results in the stock price immediately after the dividend distribution being lower than the stock price shortly before the dividend distribution

scholarly journals The Performance of Skewness and Kurtosis Adjusted Option Pricing Model in Emerging Markets

2016 ◽  
Vol 5 (3) ◽  
pp. 70-84
Author(s):  
Özge Sezgin Alp
Keyword(s):  
Emerging Markets ◽  
Option Pricing ◽  
Option Prices ◽  
Pricing Model ◽  
European Options ◽  
Black Scholes Model ◽  
Black Scholes ◽  
Option Pricing Model ◽  
Skewness And Kurtosis ◽  
Pricing Formula

In this study, the option pricing performance of the adjusted Black-Scholes model proposed by Corrado and Su (1996) and corrected by Brown and Robinson (2002), is investigated and compared with original Black Scholes pricing model for the Turkish derivatives market. The data consist of the European options written on BIST 30 index extends from January 02, 2015 to April 24, 2015 for given exercise prices with maturity April 30, 2015. In this period, the strike prices are ranging from 86 to 124. To compare the models, the implied parameters are derived by minimizing the sum of squared deviations between the observed and theoretical option prices. The implied distribution of BIST 30 index does not significantly deviate from normal distribution. In addition, pricing performance of Black Scholes model performs better in most of the time. Black Scholes pricing Formula, Carrado-Su pricing Formula, Implied Parameters

scholarly journals Fractional Black-Scholes Model and Technical Analysis of Stock Price

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Song Xu ◽  
Yujiao Yang
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Technical Analysis ◽  
Stochastic Volatility Model ◽  
Black Scholes Model ◽  
Dependent Process ◽  
Large Numbers ◽  
Volatility Model ◽  
Black Scholes

In the stock market, some popular technical analysis indicators (e.g., Bollinger bands, RSI, ROC, etc.) are widely used to forecast the direction of prices. The validity is shown by observed relative frequency of certain statistics, using the daily (hourly, weekly, etc.) stock prices as samples. However, those samples are not independent. In earlier research, the stationary property and the law of large numbers related to those observations under Black-Scholes stock price model and stochastic volatility model have been discussed. Since the fitness of both Black-Scholes model and short-range dependent process has been questioned, we extend the above results to fractional Black-Scholes model with Hurst parameterH>1/2, under which the stock returns follow a kind of long-range dependent process. We also obtain the rate of convergence.

scholarly journals Analysis of Right Issue Announcement Effect toward Stock Price Movement and Stock Trading Volume within Issuer in Indonesia Stock Exchange

2016 ◽  
Vol 7 (1) ◽  
pp. 33
Author(s):  
Wilson Yaputra Yakup ◽  
Yoyo Cahyadi
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Trading Volume ◽  
Stock Exchange ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Stock Trading ◽  
Before And After ◽  
The Right ◽  
Rights Issue

The purpose of this study were to identify and analyze the rights issue effect to the stock price, the effect of the rights issue on stock trading volume, the correlation between stock prices before and after the right issue, as well as the correlation between volume of trading activity before the right issue and after that event. The objects of the study are the companies listed on Indonesia Stock Exchange (JSX). The hypothesis stated that right issues have a significant effect on stock price on companies listed on the JSX, rights issues have a significant effect on the stock trading volume on companies listed on the JSX, there is a significant correlation between stock price before and after the rights issue on companies listed in JSX, there is a significant correlation between volume of the stock trading before the rights issue and after that event. Data analysis used were descriptive statistics, simple linear regression analysis and paired t-test. Hypothesis testing was performed by using the Pearson correlation test with significance level of 5%. The results show that the right issue has a positive effect but not significant toward stock prices of companies listed in JSX, right issue has a negative effect and not significant toward the trading volume activity (TVA) on companies listed in JSX.

scholarly journals Prediksi Harga Saham Dalam Berinvestasi Pada Perusahaan Manufaktur

2021 ◽  
Vol 9 (2) ◽  
pp. 101-114
Author(s):  
Fauziyah Fauziyah
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Manufacturing Industry ◽  
Stock Exchange ◽  
Manufacturing Sector ◽  
Prediction Method ◽  
Manufacturing Companies ◽  
Upward Trend ◽  
Stock Trading ◽  
The Past

Abstract Indonesia Stock Exchange (IDX) is a term that is well known in the world of stocks in Indonesia. One of the company sectors listed on the IDX is manufacturing. The contribution of the manufacturing sector to Gross Domestic Product (GDP) was recorded to be the largest compared to other sectors. In this research, the manufacturing companies that will be used as the object of research to predict their stock prices are manufacturing companies listed in LQ45. In stock trading, prices fluctuate up or down. Stock conditions that fluctuate every day make investors who are going to invest in the Manufacturing industry must observe and study the past company data before investing. This data is important for investors to find out what might happen to a company's stock price. Thus, predicting stock prices in the manufacturing industry for the future is needed as a stage in deciding which manufacturing companies are good to investing in. The prediction method in this research uses ARIMA. The results obtained are the stock prices of companies GGRM, HMSP, ICBP, INDF, INTP and UNVR following a downward trend, so that the actions taken by investor in these companies are selling stocks, while for the stock prices of companies ASII, CPIN, INKP, JPFA, SMGR, TKIM, following an upward trend, so that the actions taken by investors in these companies are buying stocks.Keywords: Prediction, ARIMA, Investment  BEI merupakan istilah yang terkenal pada dunia saham di Indonesia. Sektor perusahaan yang terdapat di BEI salah satunya adalah manufaktur. Kontribusi sektor manufaktur dalam Produk Domestik Bruto (PDB) tercatat yang paling besar dibandingkan sektor lainnya. Di dalam penelitian ini, perusahaan manufaktur yang akan dijadikan objek penelitian untuk diramalkan harga sahamnya yaitu perusahaan manufaktur yang terdaftar di LQ45.  Pada perdagangan saham, harga mengalami fluktuasi naik maupun turun.  Keadaan saham yang fluktuasi setiap hari menjadikan investor yang akan berinvestasi di industri Manufaktur harus mengamati dan mempelajari data perusahaan dimasa lalu sebelum melakukan investasi. Data tersebut penting bagi investor untuk mengetahui kemungkinan yang terjadi pada harga saham suatu perusahaan. sehingga, meramal harga saham pada industri manufaktur untuk masa yang akan datang sangat dibutuhkan sebagai tahapan dalam memutuskan perusahaan Manufaktur yang baik dalam melakukan investasi. Metode Prediksi dalam penelitian ini menggunakan ARIMA. Hasil yang didapat yaitu harga saham perusahaan GGRM, HMSP, ICBP, INDF, INTP dan UNVR mengikuti tren turun, sehingga langkah yang diambil untuk investor pada perusahaan tersebut adalah menjualnya sedangkan untuk harga saham perusahaan ASII, CPIN, INKP, JPFA, SMGR, TKIM, mengikuti tren naik, sehingga langkah yang diambil untuk investor pada perusahaan tersebut adalah membeli saham.Kata Kunci: Prediksi, ARIMA, Investasi

scholarly journals Multi-Order Rules Extraction by Genetic Network Programming with Rule Accumulation and its Application to Stock Trading Problems

2011 ◽  
Vol 15 (5) ◽  
pp. 515-524
Author(s):  
Yafei Xing ◽  
◽  
Singo Mabu ◽  
Lian Yuzhu ◽  
Kotaro Hirasawa
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Genetic Network ◽  
Rule Extraction ◽  
Network Programming ◽  
Evolutionary Computations ◽  
Stock Trading ◽  
Trading Rules ◽  
Rules Extraction ◽  
Genetic Network Programming

As the effectiveness of the trading rules for stock trading problems has been verified, a method of extracting multi-order rules by Genetic Network Programming (GNP) is proposed using the rule accumulation for improving the efficiency of the trading rules in this paper. GNP is one of the evolutionary computations having a directed graph structure. Because of this special structure, the rule accumulation from GNP individuals is more effective for trading the stock than other methods. In this paper, there are two main points: rule extraction and trading action determination. Rule extraction is carried out in the training period, where the rules including the 1st order rules and multi-order rules, are extracted from the best individual and accumulated into the rule pools generation by generation. In the testing period, the trading action is determined by the matching degree of the stock price information with the rules, and the profits of the trading are evaluated. In the simulations, the stock prices of 16 brands in 2004, 2005 and 2006 are used for the training and those in 2007 for the testing. The simulation results show that the multi-order rules perform better than the 1st order rules. So, it is proved that themulti-order rules extracted by GNP is more effective than the 1st order rules for stock trading.

scholarly journals IntelliFin: Advanced Stock Prediction using Hybrid ML and LSTM Model with Financial Indicators powered by Sentiment Determination using NLP

2020 ◽  
Vol 9 (5) ◽  
pp. 428-433
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
Nearest Neighbor ◽  
Learning Algorithm ◽  
Majority Voting ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Financial History ◽  
The Right

Stock Trading has been one of the most important parts of the financial world for decades. People investing in the share market analyze the financial history of a corporation, the news related to it and study huge amounts of data so as to predict its stock price trend. The right investment i.e. buying and selling a company stock at the right time leads to monetary benefits and can make one a millionaire overnight. The stock market is an extremely fluctuating platform wherein data is produced in humongous quantities and is influenced by numerous disparate factors such as socio-political issues, financial activities like splits and dividends, news as well as rumors. This work proposes a novel system “IntelliFin” to predict the share market trend. The system uses the various stock market technical indicators along with the company's historical market data trends to predict the share prices. The system employs the sentiment determination of a company's financial and socio-political news for a more accurate prediction. This system is implemented using two models. The first is a hybrid LSTM model optimized by an ADAM optimizer. The other is a hybrid ML model which integrates a Support Vector Regressor, K-Nearest Neighbor classifier, an RF classifier and a Linear Regressor using a Majority Voting algorithm. Both models employ a sentiment analyzer to account for the news impacting the stock prices which is powered by NLP. The models are trained continuously using Reinforcement Learning implemented by the Q-Learning Algorithm to increase the consistency and accuracy. The project aims to support the inexperienced investors, who don't have enough experience in investing in the stock market and help them maximize their profit and minimize or eliminate the losses. The developed system will also serve as a tool for professional investors to help and aid their decision making.

Predicting the stock price of frontier markets using machine learning and modified Black–Scholes Option pricing model

2020 ◽  
Vol 555 ◽  
pp. 124444 ◽  
Author(s):  
Reaz Chowdhury ◽  
M.R.C. Mahdy ◽  
Tanisha Nourin Alam ◽  
Golam Dastegir Al Quaderi ◽  
M. Arifur Rahman
Keyword(s):  
Machine Learning ◽  
Option Pricing ◽  
Stock Price ◽  
Pricing Model ◽  
Black Scholes ◽  
Option Pricing Model

AN APPROPRIATE APPROACH TO PRICING EUROPEAN-STYLE OPTIONS WITH THE ADOMIAN DECOMPOSITION METHOD

2018 ◽  
Vol 59 (3) ◽  
pp. 349-369
Author(s):  
ZIWIE KE ◽  
JOANNA GOARD ◽  
SONG-PING ZHU
Keyword(s):  
Decomposition Method ◽  
Adomian Decomposition Method ◽  
European Options ◽  
Black Scholes Model ◽  
Adomian Decomposition ◽  
Black Scholes ◽  
Interest Rate Model ◽  
Vasicek Interest Rate Model ◽  
Digital Options ◽  
Continuous Estimation

We study the numerical Adomian decomposition method for the pricing of European options under the well-known Black–Scholes model. However, because of the nondifferentiability of the pay-off function for such options, applying the Adomian decomposition method to the Black–Scholes model is not straightforward. Previous works on this assume that the pay-off function is differentiable or is approximated by a continuous estimation. Upon showing that these approximations lead to incorrect results, we provide a proper approach, in which the singular point is relocated to infinity through a coordinate transformation. Further, we show that our technique can be extended to pricing digital options and European options under the Vasicek interest rate model, in both of which the pay-off functions are singular. Numerical results show that our approach overcomes the difficulty of directly dealing with the singularity within the Adomian decomposition method and gives very accurate results.

Valuation Method of Equity Incentives of Listed Companies Based on the Black-Scholes Model

2020 ◽  
Vol 12 (2) ◽  
pp. 36-49
Author(s):  
Zhongwen Liu ◽  
Yifei Chen
Keyword(s):  
Stock Price ◽  
Turnover Rate ◽  
Garch Model ◽  
Listed Companies ◽  
Valuation Method ◽  
Black Scholes Model ◽  
Black Scholes ◽  
S Model ◽  
The Garch Model ◽  
Equity Incentive

This article applies the classic Black-Scholes model (i.e. B-S model) and turnover rate adapted B-S model (revised B-S model) to equity incentive valuation of listed companies. Unlike other studies on equity incentive valuation which generally adopt historical volatility, this article applies the GARCH model to equity incentive valuation. The volatility of stock price is estimated by the GARCH model to improve the accuracy of equity incentive valuation. The turnover rate has an important impact on the equity incentive valuation of listed companies. Considering the turnover rate can improve the accuracy of the equity incentive valuation and reduce the error of equity incentive valuation. Through the case study of the equity incentive valuation of Infinova, the practicality of the equity incentive valuation method is further verified.

The Recurring Option Contract

1982 ◽  
Vol 6 (4) ◽  
pp. 211-215
Author(s):  
Robert M. Shaffer
Keyword(s):  
Timber Management ◽  
Private Landowner ◽  
Management Objectives ◽  
Option Contract ◽  
Black Scholes ◽  
Attractive Option ◽  
Option Pricing Model ◽  
The Right ◽  
Management Contracts

Abstract Long-term timber management contracts can be an attractive option to both the nonindustrial private landowner and the forest industry firm. However, many such contracts incorporate inequities or operational problems which may lead to eventual dissatisfaction by one or both parties. The recurring option contract presented is both equitable and operationally sound. Using a modified version of the Black-Scholes Option Pricing Model, an option premium is calculated for each year of the contract in which timber is sold. Through this premium, the firm retains control over the stumpage and the landowner is compensated for relinquishing the right to market his timber independently. The considerable flexibility of the contract permits adaptation to a variety of management objectives.

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