kpsstest: A command that implements the Kwiatkowski, Phillips, Schmidt, and Shin test with sample-specific critical values and reports p-values

Kagalwala, Ali

doi:10.1177/1536867x221106371

Cited by 8 publications

(2 citation statements)

References 13 publications

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“…A unit root analysis is a fundamental tool in time series analysis to determine the stationarity of a time series. The Dickey-Fuller and Phillips-Perron tests are commonly used unit root tests (Kagalwala, 2022;Ozigbo & Ewubare, 2019). These tests are determined to see if a series contains a unit root and provide information about the stationarity of a series.…”

Section: Econometric Methodsmentioning

confidence: 99%

Time Series Analysis of Long-Term Stock Performance of Airlines: The Case of Turkish Airlines

Akusta

2024

Politik Ekonomik Kuram

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This study presents a time series analysis of the long-term stock performance of airlines, with a focus on Turkish Airlines (THY). Stock-related variables were obtained from the Istanbul Stock Exchange, and other variables were obtained from the Turkish Statistical Institute. The research investigates various economic factors that may influence THY's stock prices over an extended period. Specifically, the study examines the relationship between global energy prices, inflation, the BIST100 index, gold prices, exchange rates, and THY stock prices. The analysis employs the Autoregressive Distributed Lag (ARDL) approach, a versatile technique capable of estimating both short-term and long-term relationships between variables. The findings of this research reveal significant and statistically meaningful connections between these economic variables and THY's stock prices. Notably, the study highlights the impact of global energy prices and other economic factors on the long-term stock performance of Turkish Airlines. These results provide valuable insights for investors and analysts seeking to understand and forecast THY's stock price movements.

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Section: Econometric Methodsmentioning

confidence: 99%

Time Series Analysis of Long-Term Stock Performance of Airlines: The Case of Turkish Airlines

Akusta

2024

Politik Ekonomik Kuram

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“…The Augmented Dickey-Fuller (ADF) [34], [35] and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) [36], [37] tests were carried out. The ADF test was conducted to find out the unit root of the data, while the KPSS test was to find out the stationarity of the data.…”

Section: ) Data Transformationmentioning

confidence: 99%

Stock Price Time Series Data Forecasting Using the Light Gradient Boosting Machine (LightGBM) Model

Hartanto,

Nur Kholik,

Pristyanto

2023

JOIV : Int. J. Inform. Visualization

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In the world of stock investment, one of the things that commonly happens is stock price fluctuations or the ups and downs of stock prices. As a result of these fluctuations, many novice investors are afraid to play stocks. However, on the other hand, stocks are a type of investment that can be relied upon during disasters or economic turmoil, such as in 2019, namely the Covid-19 pandemic. For stock price fluctuations to be estimated by investors, it is necessary to carry out a forecasting activity. This study builds stock price forecasting using the Light Gradient Boosting Machine (LightGBM) algorithm, which has high accuracy and efficiency. To forecast stock price time series, the model used is the LightGBM ensemble. At the same time, they were optimizing the determination of hyperparameters using Grid Search Cross Validation (GSCV). This study will also compare the LGBM algorithm with other algorithms to see which model is optimal in forecasting price stock data. In this study, the test used the RMSE metric by comparing the original data (testing data) with the predicted results. The experimental results show that the LightGBM model can compete with and outperform boosting-based forecasting models like XGBoost, AdaBoost, and CatBoost. In comparing forecasting models, the same dataset is used so that the results are accurate, and the comparisons are equivalent. In future research, paying attention to the data during pre-processing is necessary because it has many outliers. In addition, it is necessary to include exogenous variables and external variables, which are determined to involve many parties.

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Economic policy uncertainty and cryptocurrencies

Oldani,

Bruno,

Signorelli

2024

Eurasian Econ Rev

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kpsstest: A command that implements the Kwiatkowski, Phillips, Schmidt, and Shin test with sample-specific critical values and reports p-values

Cited by 8 publications

References 13 publications

Time Series Analysis of Long-Term Stock Performance of Airlines: The Case of Turkish Airlines

Time Series Analysis of Long-Term Stock Performance of Airlines: The Case of Turkish Airlines

Stock Price Time Series Data Forecasting Using the Light Gradient Boosting Machine (LightGBM) Model

Economic policy uncertainty and cryptocurrencies

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