Competition - bitcoin
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    Should your fund invest in Bitcoin?

    📖 Background

    You work as an analyst at an investment fund in New York. Your CFO wants to explore if it is a good idea to invest some of the fund's assets in Bitcoin. You have to prepare a report on this asset and how it compares to the stock market in general.

    
!pip install ta-lib

    Should your fund invest in Bitcoin?

    📖 Background

    You work as an analyst at an investment fund in New York. Your CFO wants to explore if it is a good idea to invest some of the fund's assets in Bitcoin. You have to prepare a report on this asset and how it compares to the stock market in general.

    💾 The data

    You have access to three files:

    Bitcoin daily data in US dollars
    • "date" - date from September 17, 2014 to November 17, 2021
    • "open" - the price at the beginning of the trading day
    • "high" - the highest price reached that day
    • "low" - the lowest price reached that day
    • "close" - the price at the closing of the trading day
    • "volume" - how many Bitcoin were traded that day
    S&P 500 daily data
    • "date" - date from September 17, 2014 to November 17, 2021
    • "open" - the index level at the beginning of the trading day
    • "high" - the highest level reached that day
    • "low" - the lowest level reached that day
    • "close" - the level at the closing of the trading day
    • "volume" - how many shares in the companies that make up the index were traded that day
    inflation and gold as monthly data
    • "date" - date from September, 2014 to November, 2021
    • "gold_usd" - price in usd of gold for that month
    • "cpi_us" - the inflation index for the US for that month (cpi = consumer price index)

    CPI data from the U.S. Bureau of Labor Statistics. Publicly available information.

    import pandas as pd
bitcoin = pd.read_csv('./data/bitcoin-usd.csv', parse_dates=['date'])
bitcoin.head()
    sp500 = pd.read_csv('./data/sp500.csv', parse_dates=['date'])
sp500.head()
    monthly_data = pd.read_csv('./data/monthly_data.csv', parse_dates=['date'])
monthly_data.head()

    💪 Competition challenge

    Create a report that covers the following:

    1. How does the performance of Bitcoin compare to the S&P 500 and the price of gold?
    2. Analyze Bitcoin's returns and volatility profile. Do you believe it could help improve the performance of a portfolio? Do you believe Bitcoin could be used as a hedge versus inflation?
    3. The CFO is looking to lower volatility in the fund. Explore building a portfolio using some or all of these assets. Make a recommendation that minimizes overall risk.

    🧑‍⚖️ Judging criteria

    CATEGORYWEIGHTINGDETAILS
    Recommendations35%
    • Clarity of recommendations - how clear and well presented the recommendation is.
    • Quality of recommendations - are appropriate analytical techniques used & are the conclusions valid?
    • Number of relevant insights found for the target audience.
    Storytelling30%
    • How well the data and insights are connected to the recommendation.
    • How the narrative and whole report connects together.
    • Balancing making the report in depth enough but also concise.
    Visualizations25%
    • Appropriateness of visualization used.
    • Clarity of insight from visualization.
    Votes10%
    • Up voting - most upvoted entries get the most points.

    ✅ Checklist before publishing into the competition

    • Rename your workspace to make it descriptive of your work. N.B. you should leave the notebook name as notebook.ipynb.
    • Remove redundant cells like the judging criteria so the workbook is focused on your story.
    • Make sure the workbook reads well and explains how you found your insights.
    • Check that all the cells run without error.

    ⌛️ Time is ticking. Good luck!