A mutual fund is a company that pools money from many investors and invests the money in securities such as stocks, bonds, and short-term debt. The combined holdings of the mutual fund are known as its portfolio. Investors buy shares in mutual funds.
Datasource : https://finance.yahoo.com/mutualfunds/
The fund invests in financial instruments that the fund advisors believes, in combination, should produce daily returns consistent with the Daily Target. The index represents the biotechnology segment of the S&P Total Market Index, which comprises the following sub-industry: biotechnology.
The fund normally invests primarily in common stocks. It normally invests at least 80% of assets in securities of companies principally engaged in the design, manufacture, or sale of semiconductors and semiconductor equipment. The fund invests in domestic and foreign issuers. It uses fundamental analysis of factors such as each issuer's financial condition and industry position, as well as market and economic conditions, to select investments. The fund is non-diversified.
Under normal circumstances, the fund invests substantially all (at least 80%) of its net assets in equity securities of Electronics Companies that are traded in the United States and in derivatives, which primarily consist of futures contracts and options on securities, futures contracts, and stock indices. It may invest to a significant extent in the securities of Electronics Companies that have small to mid-sized capitalizations.
The fund normally invests at least 80% of its net assets in securities of gold and precious metals operation companies. It may buy securities of gold and precious metals operation companies located anywhere in the world and in general invests predominantly in non-U.S. companies. The fund may invest in companies without regard to market capitalization, and may heavily invest in small- and mid-capitalization companies. The fund is non-diversified.
To achieve its objective of providing investors the opportunity to participate in the investment characteristics of gold, the fund invests at least 80% of its net assets (plus any borrowings for investment purposes) in gold and/or securities directly related to gold or issuers principally engaged in the gold industry, including securities of gold mining finance companies as well as operating companies with long-, medium- or short-life mines. The fund is non-diversified.
The fund generally invests at least 80% of its net assets (including the amount of any borrowings for investment purposes) in equity securities of U.S. and non-U.S. companies with business operations in technology and technology-related industries. It generally invests at least 40% of its net assets in companies that maintain their principal place of business or conduct their principal business activities outside the U.S., have their securities traded on non-U.S. exchanges or have been formed under the laws of non-U.S. countrie
import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
C:\Users\jki\anaconda3\Lib\site-packages\yfinance\base.py:48: FutureWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning. _empty_series = pd.Series()
import yfinance as yf
# Define the stock symbols for Top Ten Mutual Funds
Profunds_symbol = "BIPIX"
Fidelity_symbol = "FELIX"
Rydex_symbol = "RYSIX"
First_Eagle_symbol = "FEGOX"
Columbia_symbol = "CSGZX"
Franklin_symbol = "FGPMX"
# Define start and end dates
start_date = '2019-01-01'
end_date = '2024-02-29'
# Fetch stock price data using yfinance
Profunds_data = yf.download(Profunds_symbol, start=start_date, end=end_date)
Fidelity_data = yf.download(Fidelity_symbol, start=start_date, end=end_date)
Rydex_data = yf.download(Rydex_symbol, start=start_date, end=end_date)
First_Eagle_data = yf.download(First_Eagle_symbol, start=start_date, end=end_date)
Columbia_data = yf.download(Columbia_symbol, start=start_date, end=end_date)
Franklin_data = yf.download(Franklin_symbol, start=start_date, end=end_date)
[*********************100%%**********************] 1 of 1 completed [*********************100%%**********************] 1 of 1 completed [*********************100%%**********************] 1 of 1 completed [*********************100%%**********************] 1 of 1 completed [*********************100%%**********************] 1 of 1 completed [*********************100%%**********************] 1 of 1 completed
# Extract the 'Close' prices
Profunds_close_prices = Profunds_data['Close']
Fidelity_close_prices = Fidelity_data['Close']
Rydex_close_prices = Rydex_data['Close']
First_Eagle_close_prices = First_Eagle_data['Close']
Columbia_close_prices = Columbia_data ['Close']
Franklin__close_prices = Franklin_data['Close']
# Create a DataFrame to store the Mutual Funds prices
Mutual_Fund_prices_df = pd.DataFrame({
'Profunds': Profunds_close_prices,
'Fidelity': Fidelity_close_prices,
'Rydex': Rydex_close_prices,
'First Eagle': First_Eagle_close_prices,
'Columbia Platforms': Columbia_close_prices,
'Franklin': Franklin__close_prices,
})
import matplotlib.pyplot as plt
# Set the figure size
plt.figure(figsize=(20, 80))
# Plot the Mutual prices
Mutual_Fund_prices_df.plot(title='Mutual Prices', ylabel='Mutual Prices (USD)', xlabel='Date')
plt.show()
<Figure size 2000x8000 with 0 Axes>
