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Stock Prediction using LSTM, Linear Regression, ARIMA and GARCH models. Hyperparameter Optimization using Optuna framework for LSTM variants.

Jupyter Notebook 100.00%
tensorflow lstm arima garch linearregression optuna hyperparameter-optimization exploratory-data-analysis jupyter-notebook googlecolab

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GARCH

Dear Sudip

Thanks for your great code
I think your code has a problem in calculating closing price in GARCH model

Thank you

issue in plotting data

MSc-Dissertation-2021
/MSc_Dissertation_GARCH(ver_2).ipynb

df = pd.read_csv('/content/drive/MyDrive/data/ADBL_data.csv')
df['Date'] = pd.to_datetime(df.Date)

df = df[df['Date'] >= '2015-01-01']

df.head()

`plt.plot(df["Date"], df["Close"])
plt.title("ADBL Stock Trend")
plt.xlabel("Year")
plt.ylabel("Price")
plt.show()

 `

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