Objective：Lay the groundwork by introducing the stock market basics and getting familiar with handling financial data programmatically.

1.1 What is a Stock Market?

• Definition: A marketplace where buyers and sellers trade shares of public companies.

• Key Terms to Know:
• Stock: A representation of ownership in a company.
• Exchange: A platform where stocks are traded (e.g., NYSE, NASDAQ).
• Ticker Symbol: A unique identifier for a company's stock (e.g., AAPL for Apple).
• Price: Current value of a stock determined by supply and demand.
• Volume: Number of shares traded during a given period.

1.2 Types of Stock Data

• OHLC Data:
• Open: Price at market opening.
• High: Highest price of the stock during the day.
• Low: Lowest price of the stock during the day.
• Close: Price at market close.
• Volume: Total shares traded.

• Time Frames: Intraday, Daily, Weekly, Monthly.

1.3 Setting Up Python Environment

• Install Python and essential libraries:

1.4 Fetching and Handling Stock Data

• Using Yahoo Finance API (via yfinance):

• Understanding the Output:
• The data DataFrame includes columns like Open, High, Low, Close, Volume.

1.5 Visualizing Stock Data

• Plotting Stock Prices:

Insights and Explanation

1. Why Stock Data Matters:
Understanding stock data is the foundation of quantitative investment. It forms the input for all analysis and strategy development.

2. Key Takeaway from Visualization:
A simple price plot provides a visual understanding of trends and fluctuations, which is the first step towards identifying patterns.

Extra Reading and Resources

1. The Intelligent Investor by Benjamin Graham (Chapter 1-3).

2. Introduction to Stock Markets (Investopedia).

3. Official Yahoo Finance API Documentation.

4. Python for Finance by Yves Hilpisch (Chapter 2).

课后作业

Homework for Unit 1: Introduction to Stock Markets and Data Handling

Task 1: Explore Stock Market Basics

1. Research and define the following terms:
• Market capitalization
• Dividend yield
• Price-to-Earnings (P/E) ratio

2. Write a short paragraph explaining how stock prices are determined by supply and demand.

Task 2: Fetch and Analyze Stock Data

1. Use the yfinance library to fetch daily stock data for any three companies of your choice over the past two years. Example companies:
• Technology: Microsoft (MSFT)
• Healthcare: Johnson & Johnson (JNJ)
• Retail: Amazon (AMZN)

2. Save the data for each company to a CSV file using the code

Task 3: Visualize Stock Trends

1. Plot the closing prices of your chosen stocks on a single graph for comparison. Include:
• A legend indicating which line corresponds to each stock.
• Labels for the X-axis (Date) and Y-axis (Price in USD).
• Customize the plot by:
• Adding a title.
• Displaying a grid for better readability.
• Using different colors or line styles for each stock.

Task 4: Interpret Insights

1. Which stock showed the most consistent upward trend over the selected period?

2. Did any stock experience significant price volatility? What might have caused this (hint: research news or events)?

Task 5: Bonus Challenge (Optional)

1. Calculate the daily percentage change for one of the stocks and add it as a new column to the DataFrame. Use the formula: Code example:

2. Plot the daily percentage changes over time.

Submission Format

• Submit a Jupyter Notebook or Python script (.py file) with:
1. Code implementations for each task.
2. Plots and any additional visualizations.
3. Written answers to the interpretive questions (Task 4).

我自己做的答案：

Task 1: Explore Stock Market Basics

1. Research and define the following terms:

• Market capitalization:公司的市值，等于当前股价 乘以 所有股数

• Dividend yield: 股息率，是衡量一家公司派发股息相对于其股价的比例，是投资者评估股票收益的重要指标之一。它用来表示每年从股息中获得的收益与股票价格的比值，公式如下：
例如，如果某公司股票的当前股价为50元，而每年每股派发股息为2元，那么其股息率为：4%。
意义：
• 高股息率通常意味着投资者可以从股息中获得较高的现金回报，但可能也反映公司增长潜力有限（因为它更倾向于派发利润而非再投资）。
• 低股息率可能意味着公司选择将更多利润用于再投资以推动增长，但现金回报较低。

• Price-to-Earnings (P/E) ratio: 市盈率，是衡量股票估值的一个重要指标，它表示投资者为每单位的公司盈利支付的价格。公式为：
• 我们在平时看一个股票中，常常还会有动态PE和静态PE两个指标，而且两个指标往往不相同。静态PE和动态PE的分母都是当前股价。静态PE的分子是过去12个月的每股收益。动态PE是分析师对未来12个月或者下一个财年的盈利预测数据下的预期每股收益。动态PE更适用于成长型公司，投资者希望通过它了解未来的增长空间。静态PE适合评价成熟公司，尤其是稳定盈利的企业，能直观反映当前估值水平。
• EPS的实际意义: 投资者通常会结合EPS和市盈率（P/E）等指标，评估股票是否值得购买。 在比较同行业公司时，EPS是判断盈利能力的一个核心维度，但需要结合公司规模、行业特性等综合分析，避免单纯依赖该指标。

1. Write a short paragraph explaining how stock prices are determined by supply and demand.
在股市当中要明白一个道理，当前股价是由边际交易决定的。假设十万个人持有某股票C，该股票今天被100个人交易，这100个人认为这个股值多少钱，这个股今天就会在涨跌幅区间内按照这个价格去波动。然而一百人仅占十万人的千分之一。这就是边际交易决定当前股价。但是，长期来看，股价的走势和金额和筹码的供需程度决定的。当一个公司有很好的预期，业绩也很好时，更多人愿意买入，这个时候市场上卖出的少，买入的多，价格就容易被抬升。反之亦然。所以我们要坚持长期持有，买股票并不是买筹码，而是真正的参与到公司的成长中，获得成长的收益。虽说如此，我们仍然要给我们的买入价格留取足够的安全边际，价格不能太高。但是我们无法保证在买入的节点一定是一个底价，所以要分批建仓，按时间、按幅度动态调整。
记住，股价的波动不是亏损。要有耐心和公司成长

Task 2: Fetch and Analyze Stock Data

1. Use the yfinance library to fetch daily stock data for any three companies of your choice over the past two years. Example companies:
• Technology: Microsoft (MSFT)
• Healthcare: Johnson & Johnson (JNJ)
• Retail: Amazon (AMZN)

2. Save the data for each company to a CSV file using the code:

Task 3: Visualize Stock Trends

1. Plot the closing prices of your chosen stocks on a single graph for comparison. Include:
• A legend indicating which line corresponds to each stock.
• Labels for the X-axis (Date) and Y-axis (Price in USD).
Customize the plot by:
• Adding a title.
• Displaying a grid for better readability.
• Using different colors or line styles for each stock.

Task 4: Interpret Insights

1. Which stock showed the most consistent upward trend over the selected period?

1. Did any stock experience significant price volatility? What might have caused this (hint: research news or events)?

Task 5: Bonus Challenge (Optional)

1. Calculate the daily percentage change for one of the stocks and add it as a new column to the DataFrame. Use the formula:

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