scholarly journals Application of Vector Autoregressive with Exogenous Variable: Case Study of Closing Stock Price of PT INDF.Tbk and PT ICBP.Tbk

2021 ◽  
Vol 1751 ◽  
pp. 012012
Author(s):  
A R Putri ◽  
M Usman ◽  
Warsono ◽  
Widiarti ◽  
E Virginia
Keyword(s):  
Stock Price ◽  
Exogenous Variable ◽  
Vector Autoregressive

FORECASTING STOCK PRICES ON THE LQ45 INDEX USING THE VARIMAX METHOD

2021 ◽  
Vol 14 (1) ◽  
pp. 98-107
Author(s):  
Dinul Darma Atmaja ◽  
Widowati Widowati ◽  
Budi Warsito
Keyword(s):  
Formation Process ◽  
Stock Prices ◽  
Predictive Value ◽  
Stock Price ◽  
Moving Average ◽  
Exogenous Variable ◽  
Initial Model ◽  
Vector Autoregressive ◽  
Autoregressive Integrated Moving Average ◽  
Model Formation

Forecasting using the Autoregressive Integrated Moving Average (ARIMA) method is not appropriate to predict more than one stock price because this method is only able to model one dependent variable. Therefore, to expect more than one stock prices, the ARIMA method expansion can be used, namely the Vector Autoregressive Integrated Moving Average (VARIMA) method. Furthermore, this research will discuss forecasting stock prices on the LQ45 index using the Vector Autoregressive Integrated Moving Average with Exogenous Variable (VARIMAX) method. Then, after the initial model formation process, the best model is the VARIMAX (0,1,2) model. Finally, the results of this study using the VARIMAX (0,1,2) model obtained the predictive value of the prices and the error values of stocks on the LQ45 index.

The Value of Assurance on Voluntary Nonfinancial Disclosure: An Experimental Evaluation

2009 ◽  
Vol 28 (1) ◽  
pp. 137-151 ◽  
Author(s):  
Paul J. Coram ◽  
Gary S. Monroe ◽  
David R. Woodliff
Keyword(s):  
Attribution Theory ◽  
Performance Indicators ◽  
Stock Price ◽  
Annual Report ◽  
Corporate Disclosure ◽  
Financial Report ◽  
Nonfinancial Performance ◽  
Assurance Services ◽  
Context Specific

SUMMARY: This study examines whether assurance on the voluntary provision of nonfinancial performance indicators affects the stock price estimates of a group of sophisticated financial report users. We conducted an experiment where participants were provided with a case study containing excerpts from a hypothetical company's annual report. Nonfinancial performance and assurance were manipulated in a 2 (positive and negative nonfinancial performance indicators) ×2 (assurance and no assurance) +1 (control condition) between-subjects design. After reading the case materials, the participants indicated whether they believed the company's stock price would increase or decrease based on the information provided. As expected, we found that the nonfinancial performance indicators had a significant effect on stock price estimates. In addition, consistent with attribution theory, an assurance report on the voluntarily disclosed nonfinancial performance indicators only had a significant effect on stock price estimates when the nonfinancial performance indicators were positive, suggesting that the value of assurance is context-specific. Our research contributes to the discussion on the value of expanded assurance services and also on the value of enhanced corporate disclosure.

Perbandingan harga saham, volume transaksi dan return saham sebelum dan sesudah terjadi pandemi covid-19 pada PT Agung Podomoro Land, Tbk

2021 ◽  
Vol 5 (4) ◽  
pp. 720
Author(s):  
Anggun Putri Romadhina ◽  
Eka Kusuma Dewi
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Research Data ◽  
Paired Sample ◽  
First Case ◽  
Significant Difference ◽  
Before And After ◽  
Stock Transaction

The first Covid-19 case in Indonesia was announced on March 2, 2020. This study aims to determine whether there is a significant difference in stock prices, stock transaction volume and stock returns due to the COVID-19 pandemic (case study at PT. Agung Podomoro Land, Tbk). This research data was taken 90 days before and 90 days after the announcement of the first case of COVID-19 in Indonesia. The data was processed by paired sample t-test, using SPSS version 20. From the results of data processing, it was shown that there was a significant difference in stock prices before and after the announcement of the first case of covid-19 in Indonesia. This is indicated by a significance value of 0.000 < 0.05 where the stock price has decreased compared to before the Covid-19 case. Meanwhile, the volume of stock transactions also showed a significant difference with a significance value of 0.007 <0.05, where the volume of stock transactions after the announcement showed a decrease. Likewise, stock returns show a significant difference with a significance value of 0.025 < 0.05 where stock returns have decreased after the announcement of the first case of covid-10 in Indonesia.  

MODELING THE INTERACTIONS OF STOCK PRICE AND EXCHANGE RATE IN MALAYSIA

2009 ◽  
Vol 54 (04) ◽  
pp. 605-619 ◽  
Author(s):  
MOHD TAHIR ISMAIL ◽  
ZAIDI BIN ISA
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Price Index ◽  
Composite Index ◽  
Regime Shifts ◽  
Var Model ◽  
Vector Autoregressive ◽  
Stock Price Index

After the East Asian crisis in 1997, the issue of whether stock prices and exchange rates are related or not have received much attention. This is due to realization that during the crisis the countries affected saw turmoil in both their currencies and stock markets. This paper studies the non-linear interactions between stock price and exchange rate in Malaysia using a two regimes multivariate Markov switching vector autoregression (MS-VAR) model with regime shifts in both the mean and the variance. In the study, the Kuala Lumpur Composite Index (KLCI) and the exchange rates of Malaysia ringgit against four other countries namely the Singapore dollar, the Japanese yen, the British pound sterling and the Australian dollar between 1990 and 2005 are used. The empirical results show that all the series are not cointegrated but the MS-VAR model with two regimes manage to detect common regime shifts behavior in all the series. The estimated MS-VAR model reveals that as the stock price index falls the exchange rates depreciate and when the stock price index gains the exchange rates appreciate. In addition, the MS-VAR model fitted the data better than the linear vector autoregressive model (VAR).

scholarly journals Comparison the Error Rate of Autoregressive Distributed Lag (ARDL) and Vector Autoregressive (VAR) (Case study: Forecast of Export Quantities in DIY)

2018 ◽  
Vol 18 (2) ◽  
pp. 167-177
Author(s):  
Dewi Kusuma Ningrum ◽  
Sugiyarto Surono
Keyword(s):  
Dynamic Model ◽  
Causality Test ◽  
Vector Autoregressive ◽  
Model Stability ◽  
Distributed Lag ◽  
Distributed Lag Model ◽  
Autoregressive Distributed Lag ◽  
Integration Test ◽  
Lag Model

Forecasting is estimating the size or number of something in the future. Regression model that enters current independent variable value, and lagged value is called distributed-lag model, if it enters one or more lagged value, it is called autoregressive. Koyck method is used for dynamic model which the lagged length is unknown, for the known lagged length it is used the Almon method. Vector Autoregressive (VAR) is a method that explains every variable in the model depend on the lag movement from the variable itself and all the others variable. This research aimed to explain the application of Autoregressive distributed-lag model and Vector Autoregressive (VAR) method for the forecasting for export amount in DIY. It takes export amount in DIY and inflation data, kurs, and Indonesias foreign exchange reserve. Forecasting formation: defining Koyck and Almon distributed-lag dynamic model, then the best model is chosen and distribution-lag dynamic forecasting is performed. After that it is performed stationary test, co-integration test, optimal lag examination, granger causality test, parameter estimation, VAR model stability, and performs forecasting with VAR method. The forecasting result shows MAPE value from ARDL method obtained is 0.475812%, while MAPE value from VAR method is 0.464473%. Thus it can be concluded that Vector Autoregressive (VAR) method is more effective to be used in case study of export amount in DIY forecasting. Keywords: Koyck; Almon; Lag; Autoregressive Distributed-Lag; Vector Autoregressive;

scholarly journals External macroeconomic shocks and stock price behavior in Nigeria

2021 ◽  
Vol 10 (6) ◽  
pp. 174-180
Author(s):  
Mojeed Olanrewaju Saliu
Keyword(s):  
Interest Rate ◽  
Stock Price ◽  
Real Interest Rate ◽  
Research Work ◽  
Estimation Method ◽  
Oil Price ◽  
Share Price ◽  
Price Behavior ◽  
Macroeconomic Shocks ◽  
Vector Autoregressive

This research work investigates the relationship between external macroeconomic shocks and stock price behavior in Nigeria. Variables such as exchange rate (EXR), US real interest rate (USRINTR), and world oil price (WOP) are adopted to capture external macroeconomic shocks while all share price index is used to proxy stock price. The research work uses Johansen cointegration and structural vector autoregressive model as the estimation method. Findings from the study confirm that no long-term co-movement exists between the stock price and the selected external shocks. Findings from the study equally show that both US real interest rate (USRINTR) and world oil price (WOP) are the major external shock predictors of the stock price in Nigeria.

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