Welcome to the Intelligent Stock Market Forecasting System designed to aid your portfolio investment company's value investing efforts in emerging markets. The system leverages stock market data from 2020 to predict stock price valuations for the first quarter of 2021 (Q1 2021). The primary goal is to recommend BUY, HOLD, or SELL decisions for portfolio companies' stocks, aiming to maximize capital returns and minimize losses. The system uses Bollinger Bands to measure its effectiveness.

The provided data includes trading data for portfolio companies from various emerging markets. The data spans four quarters of 2020 (Q1, Q2, Q3, Q4) and the first quarter of 2021 (Q1 2021). Each company's stock data is organized in separate sheets, and the operating days may vary based on the country and market of the companies.

The key goals of the Intelligent Stock Market Forecasting System are as follows:

1. Predict Stock Price Valuations: Utilize historical stock market data from 2020 to predict stock price valuations for portfolio companies during Q1 2021.

The Intelligent Stock Market Forecasting System will be evaluated based on its effectiveness in generating capital returns. The primary metric for evaluation will be the performance of the system's recommendations in generating profits during the Q1 2021 period. The Bollinger Bands will be used as a tool to measure the system's effectiveness in predicting stock price movements.

The Intelligent Stock Market Forecasting System will be built using advanced forecasting techniques and machine learning algorithms. Some of the key components of the system's methodology include:

1. Data Preprocessing: The historical stock market data from 2020 will be cleaned, normalized, and preprocessed to remove noise and prepare it for training.

2. Feature Engineering: Relevant features will be extracted from the data to represent the stock price patterns effectively. Technical indicators like Bollinger Bands, Moving Averages, Relative Strength Index (RSI), etc., will be computed to aid in forecasting.

3. Time Series Forecasting Models: Advanced forecasting models like LSTM (Long Short-Term Memory), ARIMA (AutoRegressive Integrated Moving Average), and Prophet will be explored and evaluated for their predictive capabilities.

4. Value Investing Principles: Value investing principles will be integrated into the decision-making process to align with your company's investment strategy.

5. Evaluation and Fine-tuning: The system's performance will be evaluated using historical data and refined iteratively to optimize its effectiveness.

To use the Intelligent Stock Market Forecasting System:

1. Download the provided stock market data for 2020 and Q1 2021 from the link provided.

2. Preprocess the data and organize it in a suitable format for training and evaluation.

3. Train the forecasting models and integrate them into the decision-making process.

4. Evaluate the system's performance using the Q1 2021 data and measure its effectiveness based on capital returns and Bollinger Bands.

5. Fine-tune the system as needed to improve its predictive capabilities.

Please note that stock market forecasting, despite using advanced techniques, involves inherent uncertainty. The predictions made by the Intelligent Stock Market Forecasting System are based on historical data and patterns, and future stock market behavior may vary due to various unpredictable factors. It is essential to exercise caution and perform due diligence before making any investment decisions.