scholarly journals Application of statistical methods in the analysis and forecasting of The Dow Jones index on the stock market

2021 ◽  
pp. 233-241
Author(s):  
Yana Fedorova
Keyword(s):  
Stock Market ◽  
Statistical Methods ◽  
Jones Index

scholarly journals THE ISLAMIC CAPITAL MARKET VOLATILITY: A COMPARATIVE STUDY BETWEEN IN INDONESIA AND MALAYSIA

2013 ◽  
Vol 15 (4) ◽  
pp. 391-415
Author(s):  
Muhammad Syafii Antonio ◽  
Hafidhoh Hafidhoh ◽  
Hilman Fauzi
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Capital Market ◽  
Oil Price ◽  
Crude Oil Price ◽  
Short Term ◽  
Macroeconomic Variables ◽  
Jones Index

This study attempts to examine the short-term and long-term relationship among selected global anddomestic macroeconomic variables fromeach country (Fed rate, crude oil price, Dow Jones Index, interest rate, exchange rate and inflation) for Indonesia and Malaysia Islamic capital market (Jakarta Islamic Index (JII) and FTSE Bursa Malaysia Hijrah Shariah Index (FHSI). The methodology used in this study is vector error correction model (VECM) for the monthly data starting from January 2006 to December 2010. The result shows that in the long-term, all selectedmacroeconomic variables except Dow Jones Index variable have significantly affect in both Islamic stock market FHSI and JII, while in the short-term there is no any selected macroeconomic variables that significantly affect FHSI and only inflation, exchange rate and crude oil price variables seem to significantly affect JII. Keywords : Islamic Stock Market, Jakarta Islamic Index, FTSE Hijrah Shariah Index, VAR/VECMJEL Classification: E52, E44

scholarly journals Impact of Lockdown in the FMCG sector of the Indian Stock Market – Analysis using Statistical Methods

2021 ◽  
Vol 12 (1S) ◽  
pp. 647-654
Author(s):  
M. Vivek Prabu, Et. al.
Keyword(s):  
Stock Market ◽  
Statistical Methods ◽  
Global Economy ◽  
Market Analysis ◽  
Negative Trend ◽  
High Demand ◽  
Statistical Tools ◽  
Indian Economy ◽  
Indian Stock Market ◽  
The Impact

The Covid19 outbreak has shattered the Global economy and Indian economy too had got no exemption from it. Despite the GDP of India moving in the negative trend, very few sectors like Pharmaceutical and FMCG have shown some positive signs because of this pandemic and the lockdown followed by it. Consumer staples will always remain essential irrespective of the economical movement. In particular, during the tougher times, whenever there arises an unprecedented scenario, the humankind will always try to safeguard itself and in turn that will certainly cause a high demand in the FMCG sector. In this paper, we will be analysing the impact of lockdown in the movement of the FMCG sector using some of the Statistical tools

COVID-19 Sentiments and Impact on Stock Market Prices

2021 ◽  
Vol 2 (2) ◽  
pp. 40-58
Author(s):  
Chandra Prayaga ◽  
Krishna Devulapalli ◽  
Lakshmi Prayaga ◽  
Aaron Wade
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Stock Prices ◽  
Multivariate Time Series ◽  
Market Prices ◽  
Vector Error Correction ◽  
Jones Index ◽  
Vector Error ◽  
The Impact ◽  
Stock Values

This paper studies the impact of sentiments expressed by tweets from Twitter on the stock market associated with COVID-19 during the critical period from December 1, 2019 to May 31, 2020. The stock prices of 30 companies on the Dow Jones Index were collected for this period. Twitter tweets were also collected, using the search phrases “COVID-19” and “Corona Virus” for the same period, and their sentiment scores were calculated. The three time series, open and close stock values, and the corresponding sentiment scores from tweets were sorted by date and combined. Multivariate time series models based on vector error correction (VEC) models were applied to this data. Forecasts for these 30 companies were made for the time series open, for the 30 days of June 2020, following the data collection period. Stock market data for the month of June was for all the companies was compared with the forecast from the model. These were found to be in excellent agreement, implying that sentiment had a significant impact or was significantly impacted by the stock market prices.

scholarly journals Study on the prediction of stock price based on the associated network model of LSTM

2019 ◽  
Vol 11 (6) ◽  
pp. 1307-1317 ◽  
Author(s):  
Guangyu Ding ◽  
Liangxi Qin
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Stock Market ◽  
Statistical Methods ◽  
Network Model ◽  
Recurrent Neural Network ◽  
Neural Network Model ◽  
Stock Price ◽  
Artificial Intelligence Methods ◽  
Deep Recurrent Neural Network

AbstractStock market has received widespread attention from investors. It has always been a hot spot for investors and investment companies to grasp the change regularity of the stock market and predict its trend. Currently, there are many methods for stock price prediction. The prediction methods can be roughly divided into two categories: statistical methods and artificial intelligence methods. Statistical methods include logistic regression model, ARCH model, etc. Artificial intelligence methods include multi-layer perceptron, convolutional neural network, naive Bayes network, back propagation network, single-layer LSTM, support vector machine, recurrent neural network, etc. But these studies predict only one single value. In order to predict multiple values in one model, it need to design a model which can handle multiple inputs and produces multiple associated output values at the same time. For this purpose, it is proposed an associated deep recurrent neural network model with multiple inputs and multiple outputs based on long short-term memory network. The associated network model can predict the opening price, the lowest price and the highest price of a stock simultaneously. The associated network model was compared with LSTM network model and deep recurrent neural network model. The experiments show that the accuracy of the associated model is superior to the other two models in predicting multiple values at the same time, and its prediction accuracy is over 95%.

scholarly journals THE ISLAMIC CAPITAL MARKET VOLATILITY: A COMPARATIVE STUDY BETWEEN IN INDONESIA AND MALAYSIA

2013 ◽  
Vol 15 (4) ◽  
pp. 377-400
Author(s):  
Muhammad Syafii Antonio ◽  
Hafidhoh Hafidhoh ◽  
Hilman Fauzi
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Capital Market ◽  
Oil Price ◽  
Crude Oil Price ◽  
Short Term ◽  
Macroeconomic Variables ◽  
Jones Index

This study attempts to examine the short-term and long-term relationship among selected global and domestic macroeconomic variables from each country (Fed rate, crude oil price, Dow Jones Index, interest rate, exchange rate and inflation) for Indonesia and Malaysia Islamic capital market (Jakarta Islamic Index (JII) and FTSE Bursa Malaysia Hijrah Shariah Index (FHSI). The methodology used in this study is vector error correction model (VECM) for the monthly data starting from January 2006 to December 2010. The result shows that in the long-term, all selected macroeconomic variables except Dow Jones Index variable have significantly affect in both Islamic stock market FHSI and JII, while in the short-term there is no any selected macroeconomic variables that significantly affect FHSI and only inflation, exchange rate and crude oil price variables seem to significantly affect JII. Keywords : Islamic Stock Market, Jakarta Islamic Index, FTSE Hijrah Shariah Index, VAR/VECMJEL Classification: E52, E44

The Empirical Evidence of GARCH Effects on Return Series: Vietnam Stock Market 2000-2003

2019 ◽  
Author(s):  
Quan-Hoang Vuong
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Empirical Evidence ◽  
Statistical Methods ◽  
Serial Correlation ◽  
Empirical Models ◽  
English Abstract ◽  
Regional Markets ◽  
National Economic

The Vietnamese Stock Market was officially born on July 20, 2000, and considered an experiment, in the sense that it would likely accept adjustment and constraints to reflect the contemporaneous national economic settings. This paper is one of the first applied econometric studies investigating an evidence of GARCH effects on return series of 10 individual assets and the VNI, an index devised as the market general price indicator. The results are encouraging: Firstly, we found evidence that the time series exhibit many similar properties as those for other regional markets, such as autoregressive and serial correlation; Secondly, using rather sophisticated empirical models for a newborn market, we succeed in achieving some nontrivial remarks with respect to the use of policy matters. This paper demonstrates the importance of the application of statistical methods, a topic still not received much attention from the economic researchers in Vietnam. (Downloadable paper in Vietnamese, with English abstract.)

Irving Fisher and Financial Economics: The Equity Premium Puzzle, the Predictability of Stock Prices, and Intertemporal Allocation Under Risk

2007 ◽  
Vol 29 (2) ◽  
pp. 153-166 ◽  
Author(s):  
Robert W. Dimand
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Stock Prices ◽  
Equity Premium ◽  
Stock Market Crash ◽  
Net Worth ◽  
Jones Index ◽  
Market Crashes ◽  
Intertemporal Allocation ◽  
Premium Puzzle

Irving Fisher is renowned as the pundit who declared in October 1929 that stock prices appeared to have reached a permanently high plateau and who, having amassed a net worth of ten million dollars in the boom of the 1920s, proceeded to lose eleven million dollars of that fortune in the crash, which, as John Kenneth Galbraith (1977, p. 192) remarked, “was a substantial sum, even for an economics professor.” Along with the Dow-Jones index, Fisher's reputation for understanding financial markets declined relative to that of Roger Babson, the stock forecaster, amateur economist, and founder of Babson College, who presciently predicted the stock market crash of autumn 1929 (and, with less prescience, the stock market crashes of 1926, 1927, and 1928, and the stock market recovery of 1930). An editorial in The Commercial and Financial Chronicle (November 9, 1929) declared of Fisher: “The learned professor is wrong as he usually is when he talks about the stock market” (quoted by Galbraith 1972, p. 151).

scholarly journals Russian stock market: The practice of using credit derivatives

2021 ◽  
Vol 27 (6) ◽  
pp. 1416-1440
Author(s):  
Natal'ya I. KRAVTSOVA ◽  
Anna D. NIKONOROVA
Keyword(s):  
Stock Market ◽  
Statistical Methods ◽  
Credit Derivatives ◽  
Market Segment ◽  
University Staff ◽  
Over The Counter ◽  
Legislative Framework ◽  
Russian Stock Market ◽  
Market Infrastructure

Subject. This article explores the practice of using credit derivatives in the Russian stock market. Objectives. The article aims to identify the problems and advantages of the Russian credit derivatives market, and propose certain improvements concerning this derivatives market segment. Methods. For the study, we used analysis, comparison, and statistical methods. Results. The article describes the problems and advantages of using credit derivatives in the Russian stock market and proposes certain activities to improve this segment of the market. Conclusions. The results obtained can be used by students and university staff to study over-the-counter derivatives. The proposed measures to improve the credit derivatives market can also be applied for practical purposes to improve the legislative framework and develop the market infrastructure.

Sign in / Sign up

Export Citation Format

Share Document