scholarly journals Multivariate Time Series in Macroeconomics

2020 ◽  
Vol 11 (2) ◽  
pp. 151
Author(s):  
Ahmadi Ahmadi ◽  
R Adisetiawan
Keyword(s):  
Inflation Rate ◽  
Stock Exchange ◽  
Multivariate Time Series ◽  
Arima Model ◽  
Gold Price ◽  
Price Inflation ◽  
Vector Error Correction ◽  
Jones Index ◽  
The Us ◽  
Us Dollar

Gold is one of the most popular commodities and investment alternatives. Gold prices are thought to be influenced by several other factors such as the US Dollar, oil price, inflation rate, and stock exchange so that gold price modeling is not only influenced by its own value. This research was conducted to determine the best forecasting model and to find out what factors influence the price of gold. This research modeled the price of gold in a multivariate and reviewed the univariate modeling that will be used as a comparison model of multivariate modeling. Univariate modeling is done using ARIMA model where the modeling results state that gold price fluctuations as white noise. Multivariate gold price modeling is done using Vector Error Correction Model with gold, oil, US Dollar and Dow Jones indices, and inflation rate as predictors. The results showed that the VECM model has been able to model the gold price well and all the factors studied influenced the gold price. The US dollar and oil prices are negatively correlated with gold prices, while the inflation rate is positively correlated with gold prices. The Dow Jones index was positively correlated with gold prices in just two periods.

scholarly journals Latent root regression dalam mengatasi multikolinearitas

2017 ◽  
Vol 12 (1) ◽  
pp. 23
Author(s):  
Desy Pramesti Untari ◽  
Mathilda Susanti
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Money Supply ◽  
Stock Exchange ◽  
Principal Component Regression ◽  
Principal Component ◽  
Latent Root ◽  
Gold Price ◽  
The Us ◽  
Us Dollar

Salah satu metode yang dapat digunakan untuk mengatasi masalah multikolinearitas pada model regresi adalah latent root regression. Latent root regression  merupakan perluasan dari principal component regression. Tujuan penelitian ini adalah untuk melakukan  analisis latent root regression dalam mengatasi multikolinearitas yang diterapkan pada faktor-faktor yang mempengaruhi IHSG di Bursa Efek Indonesia. Variabel-variabel yang digunakan pada penelitian ini adalah IHSG, jumlah uang beredar, kurs rupiah terhadap dolar AS, harga emas dunia dan Indeks Dow Jones. Hasil penelitian yang diperoleh adalah faktor jumlah uang beredar, kurs rupiah terhadap dolar AS, harga emas dunia dan Indeks Dow Jones berpengaruh terhadap IHSG, namun terjadi multikolinearitas diantara faktor-faktor tersebut sehingga diselesaikan dengan latent root regression. Kemudian analisis latent root regression tersebut dibandingkan dengan analisis principal component regression pada faktor-faktor yang mempengaruhi IHSG di Bursa Efek Indonesia yang hasilnya adalah latent root regression lebih baik daripada principal component regression karena  lebih tinggi dan asumsi regresi lebih banyak dipenuhi pada latent root regression.Kata Kunci: latent root regression, multikolinearitas, IHSG. Latent Root Regression to Solve Multicolinearity AbstractOne of methods can be used to overcome the problem of multicollinearuty in a regression model is latent root regression. Latent root regression is an extension of principal component regression. The purpose of this research is to perfom a latent root regression analysis in solving multicollinearity on the factors that affect JSX Composite in Indonesia Stock Exchange. The variables used in this research are JSX Composite, money supply, rupiah exchange rate against the US dollar, gold price and DJI. The research result obtained are the factors of money supply, rupiah exchange rate against the US dollar, gold price and DJI affect  JSX Composite, but multicollinearity occur among these factors thus solved by latent root regression. Then the latent root regression analysis is compared with principal component regression on the factors that affect JSX Composite in Indonesia Stock Exchange that the result is better than latent root regression of principal component regression because  is higher and regression assumptions more fulfilled in latent root regression.Keywords: latent root regression, multicollinearity, JSX composite

scholarly journals PENGARUH TINGKAT INFLASI, SUKU BUNGA DAN NILAI KURS DOLLAR AS TERHADAP INDEKS HARGA SAHAM GABUNGAN PADA BURSA EFEK INDONESIA

2019 ◽  
Author(s):  
Vira Yulia Viska ◽  
Irdha Yusra
Keyword(s):  
Interest Rate ◽  
Exchange Rates ◽  
Stock Price ◽  
Inflation Rate ◽  
Stock Exchange ◽  
Variable Effect ◽  
The Us ◽  
Negative Effect ◽  
Us Dollar ◽  
The Interest Rate

This research conducted to find out either simultaneously or partially the influence of the inflation rate, the interest rate and the exchange rates of the US Dollar on composite stock price indeks in Indonesia Stock Exchange. This type or research is quantitative research. Data analysis technique used is multiple linear regression using the program eviews. The results of this study indicite that : 1) inflation rate variable has negative effect that is not significant to composite stock price indeks, 2) the interest rate variable has negative effect significantly to composite stock price indeks, 3) the exchange rates of the US Dollar variable effect significantly positive to the exchange rates of the US Dollar. Determination of coefficient test result shows that the three variable used may explain the variable composite stock price indeks 40,86% while the remaining 59,14% influenced by other variables outside this research model.

scholarly journals PENGARUH TINGKAT INFLASI, SUKU BUNGA DAN NILAI KURS DOLLAR AS TERHADAP INDEKS HARGA SAHAM GABUNGAN PADA BURSA EFEK INDONESIA (BEI) PERIODE 2011-2015

2019 ◽  
Author(s):  
Vira Yulia Viska ◽  
Aminar Sutra Dewi
Keyword(s):  
Interest Rate ◽  
Exchange Rates ◽  
Stock Price ◽  
Inflation Rate ◽  
Stock Exchange ◽  
Variable Effect ◽  
The Us ◽  
Negative Effect ◽  
Us Dollar ◽  
The Interest Rate

This research conducted to find out either simultaneously or partially the influence of the inflation rate, the interest rate and the exchange rates of the US Dollar on composite stock price indeks in Indonesia Stock Exchange. This type or research is quantitative research. Data analysis technique used is multiple linear regression using the program eviews. The results of this study indicite that : 1) inflation rate variable has negative effect that is not significant to composite stock price indeks, 2) the interest rate variable has negative effect significantly to composite stock price indeks, 3) the exchange rates of the US Dollar variable effect significantly positive to the exchange rates of the US Dollar. Determination of coefficient test result shows that the three variable used may explain the variable composite stock price indeks 40,86% while the remaining 59,14% influenced by other variables outside this research model.

scholarly journals How Does the Budget Deficit Affect Inflation Rate – Evidence from Western Balkans Countries

2020 ◽  
Vol 9 (1) ◽  
pp. 01-10
Author(s):  
Esat Ali Durguti
Keyword(s):  
Time Series ◽  
Budget Deficit ◽  
Inflation Rate ◽  
Multivariate Time Series ◽  
Secondary Data ◽  
Western Balkans ◽  
Vector Error Correction ◽  
Explanatory Variables ◽  
Vector Error ◽  
Point Increase

The main purpose of this study is to investigate if determinants that we selected in our analysis have any effects on inflation rate in Western Balkans Countries[1] by using panel data for the period of 2001-2017, in yearly basis in total of 102 observation. The study used quantitative analysis approach and secondary data by applying the multivariate time series, respectively vector error correction model [VECM]. Multivariate time series was applied to investigate whether the budget deficit and other explanatory variable have any significant impact on inflation rate. The results from our analysis shows that three of four determinates that we used are significant on inflation rate. The model summaries statistics for inflation rate which shows that inflation rate has a moderate correlation with explanatory variables that we used in our model, that explanatory variables explain 45.5 percent of dependent variable and we can conclude that a model is a proper and fit. The results suggest that one percent point increase in budget deficit to GDP ratio is associated with about a 9.34 percent point increase in inflation rate.  The overall inference is that the ratios that we selected has a significant influence on the inflation rate in Western Balkans Countries.      [1] Western Balkans Countries: Albania, Bosnia & Hercegovina, Kosovo, Montenegro, North Macedonia and Serbia.

scholarly journals ANALYSIS OF THE INFLUENCE OF INTEREST RATE, EXCHANGE VALUE, WORLD GOLD PRICES, DOW JONES INDEX, AEX INDEX, DAX INDEX, AND SHANGHAI INDEX ON LQ45 INDEX IN INDONESIA STOCK EXCHANGE 2012 – 2018

2021 ◽  
Vol 7 (2) ◽  
pp. 135
Author(s):  
Andini Nurwulandari ◽  
Hasanudin Hasanudin ◽  
Ari Jatmiko Setiyo Budi
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Exchange ◽  
Negative Influence ◽  
Positive Influence ◽  
Gold Price ◽  
Jones Index ◽  
Exchange Value ◽  
The Interest Rate ◽  
Significant Positive Influence

<p><em>This research aims to find out the influence of interest rate, exchange rate, world gold price, Dow Jones Index, AEX Index, DAX Index, and Shanghai Index on the LQ45 Index at the Indonesia Stock Exchange from 2012 through 2018 using the ARCH/GARCH model as the method of analysis.  The result of the test shows that the exchange rate had a significant negative influence, Dow Jones Index, AEX Index, and DAX Index had a significant positive influence on the LQ45 index, while the interest rate and world gold price had a non-significant negative influence and the Shanghai Index had a non-significant positive influence on the LQ45 index.</em></p>

The Effect of Macroeconomic Conditions on the Performance of Vietnamese Stock Market

2021 ◽  
Vol 8 (12) ◽  
pp. 73-82
Author(s):  
Hien-Ly Pham ◽  
Ching-Chung Lin ◽  
Shih-Ju Chan
Keyword(s):  
Exchange Rate ◽  
Interest Rate ◽  
Stock Market ◽  
Inflation Rate ◽  
Stock Exchange ◽  
Global Supply Chain ◽  
Gold Price ◽  
Monthly Data ◽  
Macroeconomic Conditions ◽  
The Impact

Vietnam plays an important role in the global supply chain. As one of important emerging markets, many studies have focused on Vietnam-related issues. Vietnam established two stock markets in 2000s. The market performance becomes one of interesting issues to explore. This study is to investigate the impact of macroeconomic variables, including inflation rate, exchange rate, interest rate, imports, exports, and gold price, on Ho Chi Minh stock market. The study period is from July 2000 to October 2014. Using the monthly data collected from Vietnam General Statistic Office, IMF International Financial Statistics, and Ho Chi Minh stock exchange, the empirical findings of our regression model show that there exists a positive relationship for imports and gold price, while the relationships for exchange rate and interest rate are negative. No significant relationship has been found for the variables of inflation rate and exports.

How to Hedge Against Inflation Risk in Vietnam

2021 ◽  
Author(s):  
T. Thanh-Binh Nguyen
Keyword(s):  
Predictive Power ◽  
Gold Price ◽  
Price Stability ◽  
Leading Indicators ◽  
Inflation Risk ◽  
Monthly Data ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
Us Dollar

Abstract Vietnam has experienced galloping inflation and faced serious dollarization since its reform. To effectively control its inflation for promoting price stability, it is necessary to find efficacious leading indicators and the hedging mechanism. Using monthly data over the period from January 1997 to June 2020, this study finds the predictive power and hedge effectiveness of both gold and the US dollar on inflation in the long-run and short-run within the asymmetric framework. Especially, the response of inflation to the shocks of gold price and the US dollar are quick and decisive, disclosing the sensitiveness of inflation to these two variables.

scholarly journals Effect of Exchange Rate Returns on Equity Prices: Evidence from South Africa and Nigeria

2017 ◽  
Vol 9 (11) ◽  
pp. 35
Author(s):  
Jibrin Daggash ◽  
Terfa W. Abraham
Keyword(s):  
South Africa ◽  
Exchange Rate ◽  
Stock Market ◽  
Stock Exchange ◽  
Equity Prices ◽  
The Us ◽  
Short Run ◽  
Us Dollar ◽  
The Exchange Rate ◽  
The Uk

This paper examines the exchange rate returns of the Rand (relative to the US dollar) and the Naira (relative to the US dollar) for the presence of volatility. It also examines the effect of the exchange rate returns on the performance of their respective stock market. While it was found that the returns of the South African Rand was volatile, the Nigerian naira was not. Estimating the effect of exchange rate returns and crude oil price on the stock market indices of both countries showed that exchange rate return have a positive effect on the performance of the Nigerian stock exchange thus, confirming the stock flow hypothesis for Nigeria and refuting same for South Africa. Although the VAR granger causality identifies short run fluctuation of the naira as a significant factor affecting the performance of the Nigerian stock exchange in the short run, the Johannesburg stock exchange was found to be mostly affected by short run changes in the Rand and the UK FTSE 100. The paper concludes that policies aimed at stabilizing exchange rate and encouraing more non-oil stocks to be quoted in the Nigerian stock exchange will important. For the Johanesburg stock exchange, raising the listing requirement for firms quoted in the UK FTSE 100 and also seeking listing or already listed in the JSE will be a plausible idea. For both countries, however, curtailing swings in their exchange rate returns would help attract new investments and sustain existing ones hence, helping to spur growth.

scholarly journals Is Gold a Hedge Against Turkish Lira?

2008 ◽  
Vol 3 (1) ◽  
pp. 35-40 ◽  
Author(s):  
Feride Ozturk ◽  
Sezgin Acikalin
Keyword(s):  
Exchange Rate ◽  
Price Index ◽  
Consumer Price Index ◽  
Gold Price ◽  
Dollar Exchange Rate ◽  
Vector Error Correction ◽  
Vector Error ◽  
Us Dollar ◽  
Turkish Lira

Is Gold a Hedge Against Turkish Lira?This paper investigates whether gold is an internal hedge and/or an external hedge against Turkish lira (TL) by using monthly data from January 1995 to November 2006. Cointegration test results confirm the long-term relationships between the gold price and consumer price index and between the gold price and TL/US dollar exchange rate. The Granger Tests, based on vector error correction model (VECM), indicate that gold price Granger causes the consumer price index and TL/US dollar exchange rate in a unidirectional way. It is concluded that gold acts as an effective hedge against potential future TL depreciation and rising domestic inflation. Furthermore, gold price may be considered as a good indicator of inflation and hence it can be used as a guide to monetary policy.

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.

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