scholarly journals D-brane solutions under market panic

2018 ◽  
Vol 15 (06) ◽  
pp. 1850099 ◽  
Author(s):  
Richard Pincak
Keyword(s):  
Option Pricing ◽  
Financial Market ◽  
Stock Prices ◽  
Stock Price ◽  
Parallel Transport ◽  
Brane World ◽  
Relativistic Quantum Mechanic ◽  
Riemann Curvature ◽  
Arbitrage Opportunities ◽  
Equilibrium Market

The relativistic quantum mechanic approach is used to develop stock market dynamics. The relativistic is conceptional here as the meaning of big external volatility or volatility shock on a financial market. We used a differential geometry approach with the parallel transport of prices to obtain a direct shift of the stock price movement. The prices are represented here as electrons with different spin orientation. Up and down orientations of the spin particle are likened here to an increase or a decrease of stock prices. The parallel transport of stock prices is enriched by Riemann curvature, which describes some arbitrage opportunities in the market. To solve the stock-price dynamics, we used the Dirac equation for bispinors on the spherical brane-world. We found out that when a spherical brane is abbreviated to the disk on the equator, we converge to the ideal behavior of financial market where Black–Scholes as well as semi-classical equations are sufficient. Full spherical brane-world scenarios can describe non-equilibrium market behavior where all arbitrage opportunities as well as transaction costs are taken into account. Real application of the model to the option pricing was done. The model developed in this paper brings quantitative different results of option pricing dynamics in the case of nonzero Riemann curvature.

scholarly journals The Impacts Of Institutional Stock Ownership On Stock Returns And Performance: A Financial Market Perspective

2011 ◽  
Vol 3 (3) ◽  
Author(s):  
Johnston Osagie ◽  
Gbolahan Solomon Osho ◽  
Cynthia Sutton
Keyword(s):  
Stock Returns ◽  
Financial Market ◽  
Stock Prices ◽  
Stock Price ◽  
Institutional Ownership ◽  
Small Companies ◽  
Font Size ◽  
And Performance ◽  
The Relationship ◽  
Market Perspective

<p class="MsoBodyText" style="line-height: normal; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Recent studies indicate that corporations with high Institutional ownership have higher stock prices than those with less Institutional ownership. Even small companies with high Institutional ownership have higher stock prices in their range. Institutions have researchers and analysts to investigate the financials and the industry potential of the firms. As a result, the perception is that high institutional ownership indicates good value<span style="color: #ff6600;">. </span>This study investigates if the percentage of institutional ownership directly correlates with the price of stocks.<span style="mso-spacerun: yes;">&nbsp; </span>The relationship between the Institutional ownerships and price was prevalent. This was more indicative among the large cap stocks than the small caps stocks.<span style="mso-spacerun: yes;">&nbsp; </span>It was also found that the higher the percentage of Institutional ownership does reflect a higher stock price.<span style="mso-spacerun: yes;">&nbsp; </span>This was manifest among the large caps than the small caps. </span></span></p>

Stock price fluctuation as a diffusion in a random environment

1994 ◽  
Vol 347 (1684) ◽  
pp. 471-483 ◽  
Keyword(s):  
Cellular Automata ◽  
Financial Market ◽  
Random Environment ◽  
Stock Prices ◽  
Stock Price ◽  
Diffusion Limit ◽  
Large Set ◽  
Joint Work ◽  
Probabilistic Cellular Automata ◽  
Different Types

The fluctuation of stock prices is modelled as a sequence of temporary equilibria on a financial market with different types of agents. I summarize joint work with M. Schweizer on the class of Ornstein-Uhlenbeck processes in a random environment which appears in the diffusion limit. Moreover, it is shown how the random environment may be generated by the interaction of a large set of agents modelled by Markov chains as they appear in the theory of probabilistic cellular automata.

scholarly journals Determinan Harga Saham Perusahaan Yang Terdaftar Di Bursa Efek Indonesia

2018 ◽  
Vol 8 (1) ◽  
pp. 42-54
Author(s):  
Sukma Irdiana
Keyword(s):  
High Risk ◽  
Financial Market ◽  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Sample Selection ◽  
Selection Method ◽  
Coefficient Of Determination ◽  
Analysis Model ◽  
High Return

Capital market is one form of financial market, where the capital market players invest in the form of securities offered by the issuer. One of the most popular securities for sale on the stock market is stock. Stocks are securities that have high profits and risks or better known as high risk and high return. High risk and high return is the higher the risk of an investment, the higher the amount of profits derived from an investment. The purpose of this study is to obtain evidence empirically and find clarity about the influence of fundamental variables consisting of ROA, EPS, NPM, DER and BVS to stock prices of companies listed in IDX period 2010-2015, either partially or simultaneously. Sample selection method used is purposive sampling and analysis model used is multiple linier regression analysis. The results showed that partially ROA, EPS, NPM, DER, and BVS have a significant effect on stock prices. Simultaneously ROA, ROE, EPS, NPM, DER and BVS simultaneously affect the stock price. Coefficient of Determination (R Square) of 48% and the rest of 52% influenced by other variables that have not been studied in this study.

scholarly journals Option Pricing Incorporating Factor Dynamics in Complete Markets

2020 ◽  
Vol 13 (12) ◽  
pp. 321
Author(s):  
Yuan Hu ◽  
Abootaleb Shirvani ◽  
W. Brent Lindquist ◽  
Frank J. Fabozzi ◽  
Svetlozar T. Rachev
Keyword(s):  
Option Pricing ◽  
Financial Market ◽  
Stock Price ◽  
Influencing Factor ◽  
Pricing Model ◽  
Complete Markets ◽  
Forward Contracts ◽  
Short Sellers ◽  
Option Pricing Model ◽  
Arbitrage Strategy

Using the Donsker–Prokhorov invariance principle, we extend the Kim–Stoyanov–Rachev–Fabozzi option pricing model to allow for variably-spaced trading instances, an important consideration for short-sellers of options. Applying the Cherny–Shiryaev–Yor invariance principles, we formulate a new binomial path-dependent pricing model for discrete- and continuous-time complete markets where the stock price dynamics depends on the log-return dynamics of a market influencing factor. In the discrete case, we extend the results of this new approach to a financial market with informed traders employing a statistical arbitrage strategy involving trading of forward contracts. Our findings are illustrated with numerical examples employing US financial market data. Our work provides further support for the conclusion that any option pricing model must preserve valuable information on the instantaneous mean log-return, the probability of the stock’s upturn movement (per trading interval), and other market microstructure features.

scholarly journals Climate Finance: Mapping Air Pollution and Finance Market in Time Series

Econometrics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 43
Author(s):  
Zheng Fang ◽  
Jianying Xie ◽  
Ruiming Peng ◽  
Sheng Wang
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Financial Market ◽  
Stock Prices ◽  
Stock Price ◽  
Short Term Memory ◽  
Local Environment ◽  
Climate Finance ◽  
Time Series Regression ◽  
Stock Price Prediction

Climate finance is growing popular in addressing challenges of climate change because it controls the funding and resources to emission entities and promotes green manufacturing. In this study, we determined that PM2.5, PM10, SO2, NO2, CO, and O3 are the target pollutant in the atmosphere and we use a deep neural network to enhance the regression analysis in order to investigate the relationship between air pollution and stock prices of the targeted manufacturer. We also conduct time series analysis based on air pollution and heavy industry manufacturing in China, as the country is facing serious air pollution problems. Our study uses Convolutional-Long Short Term Memory in 2 Dimension (ConvLSTM2D) to extract the features from air pollution and enhance the time series regression in the financial market. The main contribution in our paper is discovering a feature term that impacts the stock price in the financial market, particularly for the companies that are highly impacted by the local environment. We offer a higher accurate model than the traditional time series in the stock price prediction by considering the environmental factor. The experimental results suggest that there is a negative linear relationship between air pollution and the stock market, which demonstrates that air pollution has a negative effect on the financial market. It promotes the manufacturer’s improving their emission recycling and encourages them to invest in green manufacture—otherwise, the drop in stock price will impact the company funding process.

An Empirical Study on Efficient Market Hypothesis with reference to FMCG Sector

GIS Business ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 109-126
Author(s):  
Nitin Tanted ◽  
Prashant Mistry
Keyword(s):  
Stock Prices ◽  
Stock Price ◽  
Abnormal Returns ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Controversial Issues ◽  
Efficient Market ◽  
Price Movements ◽  
Run Test ◽  
Stock Price Movements

One of the highly controversial issues in the area of finance is “Efficient Market Hypothesis”. Efficient Market Hypothesis states that, “In an efficient market, all available price information is reflected in the stock prices and it is not possible to generate abnormal returns compared to other investors.” A lot of studies conducted previouslyto test the Efficient Market Hypothesis, confirmed the theory until recent years, when some academicians found it to be non-applicable in financial markets. According to them, it is possible to forecast the stock price movements using Technical Analysis. The results of various studies have been inconclusive and indefinite about the issue. This study attempted to test the efficiency of FMCG Sector stocks in India in its weak form. For the study, closing prices of top 10 stocks from Nifty FMCG index has been taken for the 5-year period ranging from 1st October 2014 to 30th September 2019. Wald-Wolfowitz Run test has been used to test the haphazard movements in the stock price movements. The results indicated that FMCG sector stocks does support the Efficient Market Hypothesis and exhibit efficiency in its weak form. Hence, it is not possible to accurately predict the price movements of these stocks.

Macroeconomic Factors and Pakistani Equity Market”

2004 ◽  
Vol 43 (4II) ◽  
pp. 619-637 ◽  
Author(s):  
Muhammad Nishat ◽  
Rozina Shaheen
Keyword(s):  
Stock Market ◽  
Industrial Production ◽  
Stock Prices ◽  
Stock Price ◽  
Consumer Price Index ◽  
Reverse Causality ◽  
Macroeconomic Factors ◽  
Macroeconomic Variables ◽  
Equilibrium Relationships

This paper analyzes long-term equilibrium relationships between a group of macroeconomic variables and the Karachi Stock Exchange Index. The macroeconomic variables are represented by the industrial production index, the consumer price index, M1, and the value of an investment earning the money market rate. We employ a vector error correction model to explore such relationships during 1973:1 to 2004:4. We found that these five variables are cointegrated and two long-term equilibrium relationships exist among these variables. Our results indicated a "causal" relationship between the stock market and the economy. Analysis of our results indicates that industrial production is the largest positive determinant of Pakistani stock prices, while inflation is the largest negative determinant of stock prices in Pakistan. We found that while macroeconomic variables Granger-caused stock price movements, the reverse causality was observed in case of industrial production and stock prices. Furthermore, we found that statistically significant lag lengths between fluctuations in the stock market and changes in the real economy are relatively short.

Effect Of Leverage, Inflation And GDP To Share Price Pt. Astra Otoparts Tbk.

ProBank ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 17-21
Author(s):  
Heriyanta Budi Utama ◽  
Florianus Dimas Gunurdya Putra Wardana
Keyword(s):  
Gross Domestic Product ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Sampling Technique ◽  
Share Price ◽  
Domestic Product ◽  
Coefficient Of Determination ◽  
Test Results ◽  
Purposive Sampling

The purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015. The sampling technique in this study using a purposive sampling. With the technique of purposive  sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression. The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share priceThe purpose of this study was to obtain empirical evidence about the effect of leverage, inflation and Gross Domestic Product (GDP) of the share price at PT. Astra Autopart, Tbk. companies in Indonesia Stock Exchange in 2011-2015.The sampling technique in this study using a purposive sampling. With the technique of purposive  sampling, all the members of the research samples by criteria. Samples that meet the criteria are used research data. Then followed the classic assumption test and test hypotheses by linear regression.The results of this study demonstrate the regression results in regression equation that Y = 2605,424 + 1561,550 X1 + 2,338 X2 + 38,994X3. T test results showed that the leverage anda GDP (Gross Domestic Product) is positive and significant effect on stock prices, while inflation is not positive and significant effect on stock prices. F test results showed that jointly leverage variables, inflation and GDP variables affecting the stock price significantly. The test results R2 (coefficient of determination) found that the variable leverage, inflation and GDP able to explain 35,4% of the stock price variable, while the remaining 64,6% is explained by other variables.Keywords: leverage, inflation, GDP, and the share price

Znaczenie czynników behawioralnych w podejmowaniu decyzji inwestycyjnych na rynku kapitałowym

2016 ◽  
pp. 173-183
Author(s):  
Mirosław Wasilewski ◽  
Marta Juszczyk
Keyword(s):  
Capital Market ◽  
Stock Prices ◽  
Stock Price ◽  
Investment Decisions ◽  
Price Volatility ◽  
Decision Making Process ◽  
Emotional States ◽  
Psychological Conditions ◽  
History Of ◽  
Research Show

The aim of the study was to investigate the investors’ opinions concerning the usefulness of behavioral factors for investment decisions. The research was carried out in the group of 100 investors, using the services of five brokerages with a long history of operation. The results of the research show that people’s psychological conditions and sentiment in the stock market play an important role in the decision-making process of investors in the capital market. The importance of this factor increased with the length of the investment period. The emotional states of people and their psychological conditions affect the stock price volatility. However, the complexity of the determinants of stock prices makes the market value of stocks can be affected by many factors at the same time and investors seem aware of this.

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