STOCK_MARKET_ANALYSIS based on the data analysis

Stock market

1. STOCK MARKET ANALYSIS MAANG companies Stock Price Forecasting using Prophet Name: Prasanna Basavaraj Halalli College: Bldeacet Engineering College Guided By: Sumangla Biradar

2. Table of contents: 1.Loading the data. 2.Domain Knowledge. 3.Analyzing the data. 4.Visualizing historical performance of stocks. 5.Stock price forecasting. 6.Conclusion. 7.References.

3. Loading the data: Working with CSV files in Python using libraries like pandas simplifies data loading, manipulation, and analysis. It's a fundamental skill for data scientists, analysts, and anyone dealing with tabular data. CSV files are plain text files used to store tabular data. Each line represents a row, and columns are separated by commas (,). CSV files can be easily created and edited using text editors or spreadsheet software. Python Libraries: Python provides several libraries for working with CSV files. The most commonly used library is pandas.

4. 2.Domain Knowledge: Before we start analyzing our data it is always a good practice to get a clear understanding of the data by looking at what all the features mean. This greatly helps in structuring a solution to the problem and makes it easier to extract meaningful insights from the data. Let's take a look at all the features Open: Opening price of the stock on a given date High: Highest price of the stock on a given date Low: Lowest price of the stock on a given date Close: Closing price of the stock on a given date Adj Close: Adjusted closing price of the stock on a given date Volume: Total number of shares traded on a given date

5. Let's go into a bit more detail and study each of the terms with a more domain specific knowledge. Open means the price at which a stock started trading as soon as the market opens. This value can be the same as where the stock closed the night before, but not always. Sometimes events such as company earning reports after trading hours can alter a stock’s price overnight. Then comes “close”. Close refers to the price of an individual stock when the stock exchange closes for the day. It represents the last buy-sell order executed between two traders. This usually occurs in the final seconds of the trading day. There is not much to say about the High and Low. The high is the highest price at which a stock is traded during a period. The low is the lowest price of the period. These give us an idea of the stock’s trading range weekly, monthly, annually etc. The Adjusted Close requires a deep knowledge of how the stock market and the company dynamics function at large. To put it simply, it factors in the impact of dividends, stock splits, and other corporate events that can distort the raw closing price. Volume is the total number of shares traded in a specific period. Every time buyers and sellers exchange shares, the amount gets added to the period’s total volume.

6. Of all the features above the most important are Close and Volume: The Close price is considered the reference point for any time frame. When researching historical stock price data, financial institutions, regulators, and individual investors use the closing price as the standard measure of the stock’s value. Studying Volume patterns are an essential aspect of technical analysis because it can show the significance of a stock’s price movement. For example, a price change that occurs in high volume can carry more weight because it indicates that many traders were behind the move. Conversely, a lower volume price move can be perceived as less critical.

7. 4.Visualizing historical performance of stocks. Netflix: The highest ever price of a single Netflix stock was $690 and was recorded in October of 2021. I looked it up and found that Netflix began its streaming service in January 2007. According to the plot the price was `$3.25 back then and it is close to ‘429 in August2023.Thats an increase of 131 times.

8. This shows that most trades occurred in Sep 2011, Oct 2011 and Jan 2012 with as high as 1.8 billion trades in a single month.

9. Stocks Prices Comparison: It can be seen that at the start of 2020 stock prices started going high due to COVID. Netflix stocks went an all time high in 2020-21 due to obvious reasons. It can also be seen that stock prices started plummeting near the end of 2021 and start of 2022. Netflix's stock prices crashed and came down to the lowest in 4 years. Apple has the highest volume of stocks traded all time out of the five companies. Also the volume seems to go down with time.

10. 5.Stock Price Forecasting: Now we come to the main and most interesting task, forecasting the stock prices. I will use Facebook's Prophet library for the task of stock price forecasting. Some advantages of Prophet are listed below: Advantages of Prophet: Accurate and Fast: It is accurate and can generate results a lot faster compared to other time series libraries. Reliable: It can accommodate strong seasonal effects in the data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Domain Knowledge integration: Forecasting can be made better by adding domain knowledge expertise like holidays and patterns. Available in R or Python: It can be implemented both in Python and R and has extensive documentation available for both. Prophet takes a data frame as input with only 2 columns - ds and y. The ds (date stamp) column should be in a specific format, ideally YYYY-MM-DD for a date or YYYY-MM-DD HH:MM:SS for a timestamp to be parsed by Prophet. The y column must be numeric, and represents the variable we wish to forecast. The model is all set to go and make predictions for the future. To predict the stock prices for future dates Prophet provides the make_future_dataframe function. This make things easier and save a lot of time and effort. The model is all set to go and make predictions for the future. To predict the stock prices for future dates Prophet provides the  make_future_dataframe  function. This make things easier and save a lot of time and effort.

11. Forecasting Of Each Company: 1.Apple:

12. 2.Netflix:

13. 3.Meta:

14. 4.Amazon:

15. 5.Google:

16. Summary: In this notebook we looked at the historical stock prices of MAANG companies and how they varied over time. The analysis was done for monthly stock prices for each stock. The stock prices were then forecasted using Prophet for up to 1 year into the future. Stock market analysis involves assessing financial data, trends, and investor sentiment to make informed investment decisions. It encompasses fundamental and technical analysis, risk assessment, and portfolio diversification. Analysts use various strategies to time the market and manage risk, ultimately aiming for profitable trading and investment outcomes.

17. Thanks, for sticking till the end. I hope you found this notebook interesting and valuable.