The Interaction between Stock Prices and Commodity Prices: East Europe and Central Asia Countries

Ildırar, Mustafa; Işcan, Erhan

doi:10.36880/c06.01350

Cited by 10 publications

(9 citation statements)

References 6 publications

(7 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This result of the study is supported by a study by Anisa & Darmawan (2018), which stated that the tin commodity price impacts the stock price index of the mining sector in Indonesia. However, it is different from a study by Ildırar & Iscan (2015), which stated that commodity price does not impact the stock price. This is because Indonesia is the second-largest tin producer in the world after China.…”

Section: The Impact Of Tin Price On Stock Pricecontrasting

confidence: 83%

Stock Price Determinant of PT Timah Tbk During the Covid-19 Pandemic

Christiani

Annicha

Wiranata

et al. 2021

IJBTOB

View full text Add to dashboard Cite

Stock Price Determinant of PT Timah Tbk during the Covid-19 Pandemic, the Covid-19 Pandemic involves the world economy. Lockdown and Large-Scale Social Restrictions make the economy slow down due to the restricted activities. The prices of crude oil and metal commodities also corrected, including the price of tin commodity due to the decrease of demand. Therefore, the aim of this study is to analyze the impact of the tin price variable, Interest Rate (BI Rate), Net Profit Margin (NPM), and Debt to Equity Ratio (DER) on the Stock Price of PT Timah Tbk during the Covid-19 pandemic. This study used a quantitative method. The object of the study was PT Timah Tbk. The samples used were secondary data, which were tin commodity price, and interest rate of SBI in 2020, and the quarterly financial statements of PT Timah Tbk. The analysis method used was Multiple Linear Regression. The data collection techniques used in this study consisted of two stages: conducting library research (studying literature in the form of research journals, scientific papers, articles, and books) and the documentation stage. The results of the study show that (1) Partially, tin price has a positive and significant impact on the stock price of PT Timah Tbk. (2) Partially, variables of interest rate, NPM, and DER have a negative and not significant impact on the stock price of PT Timah Tbk. (2) Simultaneously, tin price, interest rate, NPM, and DER have a significant impact on the stock price of PT Timah Tbk. Keywords : Tin Price, Interest Rate (BI Rate), Net Profit Margin (NPM), Debt to Equity Ratio (DER), and Stock Price

show abstract

Section: The Impact Of Tin Price On Stock Pricecontrasting

confidence: 83%

Stock Price Determinant of PT Timah Tbk During the Covid-19 Pandemic

Christiani

Annicha

Wiranata

et al. 2021

IJBTOB

View full text Add to dashboard Cite

show abstract

“…Investigating interdependencies across asset classes allows to exploit the benefits of portfolio diversification: in the case of commodity prices and stock markets we have an additional interest also because several economies are dependent on commodity trading, and movements in commodity prices are an important cost component of manufactured goods through energy and raw materials (Silvennoinen and Thorp, 2013). Several contributions focus on the interconnections of advanced economies between commodities (for instance, Karanasos et al, 2018 andNazlioglu et al, 2013), stock markets (Hou and Li, 2020 and Berg and Vu, 2019), currencies (Greenwood-Nimmo et al, 2016) and all their possible interactions (Ildırar andIscan, 2016 andKang et al, 2015, among others). More recent is the interest about the volatility spillovers among the stock markets of emerging countries and/or among these latter and developed countries.…”

Section: Introductionmentioning

confidence: 99%

Energy and non–energy Commodities: Spillover Effects on African Stock Markets.

Amendola¹,

Boccia²,

Candila³

et al. 2020

Journal of Statistical and Econometric Methods

View full text Add to dashboard Cite

This paper examines the volatility transmission from energy and metal commodities to six major African exporters’ stock markets (Egypt for oil and gold, Nigeria for oil and gas, South Africa for coal and gold, Tunisia for oil, Uganda for gold and Zambia for copper). Modelling commodity volatility with the Double Asymmetric GARCH-MIDAS model with a Student’s t-distribution allows to detect the presence of impact and inertial stock market volatility spillovers at different lags and to take into account the leptokurtosis of the commodity series. We then derive the profile of Volatility Impulse Responses of the stock markets to commodity shocks.

show abstract

“…This gave the insight of using GRU in the proposed model of this paper. Mustafa et al [19] concluded in their research paper that the commodity prices (Soft, Hard, Energy) have no relation with the stock prices, especially in the south Asian countries. Maqsood et al [26] have experimented on a massive range of models like linear regression, support vector regression, neural networks, twitter sentiment analysis, the 2012 terrorist attack and Brexit.…”

Section: Related Workmentioning

confidence: 98%

Stock price prediction using BERT and GAN

Sonkiya¹,

Bajpai²,

Bansal³

2021

Preprint

View full text Add to dashboard Cite

The stock market has been a popular topic of interest in the recent past. The growth in the inflation rate has compelled people to invest in the stock and commodity markets and other areas rather than saving. Further, the ability of Deep Learning models to make predictions on the time series data has been proven time and again. Technical analysis on the stock market with the help of technical indicators has been the most common practice among traders and investors. One more aspect is the sentiment analysis -the emotion of the investors that shows the willingness to invest. A variety of techniques have been used by people around the globe involving basic Machine Learning and Neural Networks. Ranging from the basic linear regression to the advanced neural networks people have experimented with all possible techniques to predict the stock market. It's evident from recent events how news and headlines affect the stock markets and cryptocurrencies. This paper proposes an ensemble of state-of-the-art methods for predicting stock prices. Firstly sentiment analysis of the news and the headlines for the company Apple Inc, listed on the NASDAQ is performed using a version of BERT, which is a pre-trained transformer model by Google for Natural Language Processing (NLP). Afterward, a Generative Adversarial Network (GAN) predicts the stock price for Apple Inc using the technical indicators, stock indexes of various countries, some commodities, and historical prices along with the sentiment scores. Comparison is done with baseline models like -Long Short Term Memory (LSTM), Gated Recurrent Units (GRU), vanilla GAN, and Auto-Regressive Integrated Moving Average (ARIMA) model.

show abstract

The Interaction between Stock Prices and Commodity Prices: East Europe and Central Asia Countries

Cited by 10 publications

References 6 publications

Stock Price Determinant of PT Timah Tbk During the Covid-19 Pandemic

Stock Price Determinant of PT Timah Tbk During the Covid-19 Pandemic

Energy and non–energy Commodities: Spillover Effects on African Stock Markets.

Stock price prediction using BERT and GAN

Contact Info

Product

Resources

About