Tickers Module Documentation

Tickers

A class representing a Tickers object.

__new__

Create a new Tickers object.

Parameters:

  • symbols (List[str]): A list of ticker symbols.
  • start_date (str): The start date of the time period in the format YYYY-MM-DD.
  • end_date (str): The end date of the time period in the format YYYY-MM-DD.
  • interval (str): The interval of the data (2m, 5m, 15m, 30m, 1h, 1d, 1wk, 1mo, 3mo).
  • benchmark_symbol (str): The ticker symbol of the benchmark to compare against.
  • confidence_level (float): The confidence level for the VaR and ES calculations.
  • risk_free_rate (float): The risk free rate to use in the calculations.

Returns:

  • Tickers: A Tickers object.

Example:

from finalytics import Tickers

tickers = Tickers(symbols=["AAPL", "GOOG", "MSFT", "NVDA", "BTC-USD"],
                  start_date="2020-01-01",
                  end_date="2024-01-01",
                  interval="1d",
                  benchmark_symbol="^GSPC",
                  confidence_level=0.95,
                  risk_free_rate=0.02)
get_summary_stats

Fetch the Ticker Summary Stats Data for all tickers.

Returns:

  • DataFrame: Polars DataFrame containing summary statistics.

Example:

summary_stats = tickers.get_summary_stats()
print(summary_stats)
shape: (5, 53)
┌─────────┬──────────┬────────────┬────────────┬───┬───────────┬───────────┬───────────┬───────────┐
│ Symbol  ┆ Currency ┆ Current    ┆ Day Range  ┆ … ┆ High/Low  ┆ Analyst   ┆ Circulati ┆ CoinMarke │
│ ---     ┆ ---      ┆ Price      ┆ ---        ┆   ┆ Target    ┆ Count     ┆ ng Supply ┆ tCap Link │
│ str     ┆ str      ┆ ---        ┆ str        ┆   ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│         ┆          ┆ str        ┆            ┆   ┆ str       ┆ str       ┆ str       ┆ str       │
╞═════════╪══════════╪════════════╪════════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡
│ AAPL    ┆ USD      ┆ 228.58     ┆ 229.94 -   ┆ … ┆ 300.00 -  ┆ 37        ┆           ┆           │
│         ┆          ┆            ┆ 227.10     ┆   ┆ 175.00    ┆           ┆           ┆           │
│ GOOG    ┆ USD      ┆ 202.68     ┆ 205.13 -   ┆ … ┆ 237.00 -  ┆ 19        ┆           ┆           │
│         ┆          ┆            ┆ 201.41     ┆   ┆ 185.00    ┆           ┆           ┆           │
│ MSFT    ┆ USD      ┆ 525.32     ┆ 527.59 -   ┆ … ┆ 700.00 -  ┆ 51        ┆           ┆           │
│         ┆          ┆            ┆ 522.71     ┆   ┆ 470.00    ┆           ┆           ┆           │
│ NVDA    ┆ USD      ┆ 180.91     ┆ 182.99 -   ┆ … ┆ 250.00 -  ┆ 56        ┆           ┆           │
│         ┆          ┆            ┆ 179.46     ┆   ┆ 100.00    ┆           ┆           ┆           │
│ BTC-USD ┆ USD      ┆            ┆ 119,506.07 ┆ … ┆  -        ┆           ┆ 19,905,28 ┆ https://c │
│         ┆          ┆            ┆ -          ┆   ┆           ┆           ┆ 0.00      ┆ oinmarket │
│         ┆          ┆            ┆ 118,248.38 ┆   ┆           ┆           ┆           ┆ cap.com/c │
│         ┆          ┆            ┆            ┆   ┆           ┆           ┆           ┆ urr…      │
└─────────┴──────────┴────────────┴────────────┴───┴───────────┴───────────┴───────────┴───────────┘
get_price_history

Fetch the OHLCV Data for all tickers.

Returns:

  • DataFrame: Polars DataFrame containing OHLCV data.

Example:

price_history = tickers.get_price_history()
print(price_history)
shape: (5_485, 8)
┌────────────┬─────────┬────────────┬────────────┬────────────┬────────────┬───────────┬───────────┐
│ timestamp  ┆ symbol  ┆ open       ┆ high       ┆ low        ┆ close      ┆ volume    ┆ adjclose  │
│ ---        ┆ ---     ┆ ---        ┆ ---        ┆ ---        ┆ ---        ┆ ---       ┆ ---       │
│ datetime[m ┆ str     ┆ f64        ┆ f64        ┆ f64        ┆ f64        ┆ f64       ┆ f64       │
│ s]         ┆         ┆            ┆            ┆            ┆            ┆           ┆           │
╞════════════╪═════════╪════════════╪════════════╪════════════╪════════════╪═══════════╪═══════════╡
│ 2020-01-02 ┆ AAPL    ┆ 74.059998  ┆ 75.150002  ┆ 73.797501  ┆ 75.087502  ┆ 1.354804e ┆ 72.538521 │
│ 00:00:00   ┆         ┆            ┆            ┆            ┆            ┆ 8         ┆           │
│ 2020-01-03 ┆ AAPL    ┆ 74.287498  ┆ 75.144997  ┆ 74.125     ┆ 74.357498  ┆ 1.463228e ┆ 71.83329  │
│ 00:00:00   ┆         ┆            ┆            ┆            ┆            ┆ 8         ┆           │
│ 2020-01-06 ┆ AAPL    ┆ 73.447502  ┆ 74.989998  ┆ 73.1875    ┆ 74.949997  ┆ 1.183872e ┆ 72.40567  │
│ 00:00:00   ┆         ┆            ┆            ┆            ┆            ┆ 8         ┆           │
│ 2020-01-07 ┆ AAPL    ┆ 74.959999  ┆ 75.224998  ┆ 74.370003  ┆ 74.597504  ┆ 1.08872e8 ┆ 72.06514  │
│ 00:00:00   ┆         ┆            ┆            ┆            ┆            ┆           ┆           │
│ 2020-01-08 ┆ AAPL    ┆ 74.290001  ┆ 76.110001  ┆ 74.290001  ┆ 75.797501  ┆ 1.320792e ┆ 73.224419 │
│ 00:00:00   ┆         ┆            ┆            ┆            ┆            ┆ 8         ┆           │
│ …          ┆ …       ┆ …          ┆ …          ┆ …          ┆ …          ┆ …         ┆ …         │
│ 2023-12-27 ┆ BTC-USD ┆ 42518.4687 ┆ 43683.1601 ┆ 42167.5820 ┆ 43442.8554 ┆ 2.5261e10 ┆ 43442.855 │
│ 00:00:00   ┆         ┆ 5          ┆ 56         ┆ 31         ┆ 69         ┆           ┆ 469       │
│ 2023-12-28 ┆ BTC-USD ┆ 43468.1992 ┆ 43804.7812 ┆ 42318.5507 ┆ 42627.8554 ┆ 2.2992e10 ┆ 42627.855 │
│ 00:00:00   ┆         ┆ 19         ┆ 5          ┆ 81         ┆ 69         ┆           ┆ 469       │
│ 2023-12-29 ┆ BTC-USD ┆ 42614.6445 ┆ 43124.3242 ┆ 41424.0625 ┆ 42099.4023 ┆ 2.6000e10 ┆ 42099.402 │
│ 00:00:00   ┆         ┆ 31         ┆ 19         ┆            ┆ 44         ┆           ┆ 344       │
│ 2023-12-30 ┆ BTC-USD ┆ 42091.7539 ┆ 42584.125  ┆ 41556.2265 ┆ 42156.9023 ┆ 1.6014e10 ┆ 42156.902 │
│ 00:00:00   ┆         ┆ 06         ┆            ┆ 62         ┆ 44         ┆           ┆ 344       │
│ 2023-12-31 ┆ BTC-USD ┆ 42152.0976 ┆ 42860.9375 ┆ 41998.2539 ┆ 42265.1875 ┆ 1.6397e10 ┆ 42265.187 │
│ 00:00:00   ┆         ┆ 56         ┆            ┆ 06         ┆            ┆           ┆ 5         │
└────────────┴─────────┴────────────┴────────────┴────────────┴────────────┴───────────┴───────────┘
get_options_chain

Fetch the Options Chain Data for all tickers.

Returns:

  • DataFrame: Polars DataFrame containing the options chain.

Example:

options_chain = tickers.get_options_chain()
print(options_chain)
shape: (11_512, 17)
┌────────────┬───────────┬──────┬────────┬───┬─────────────┬─────────────┬────────────┬────────────┐
│ expiration ┆ ttm       ┆ type ┆ symbol ┆ … ┆ contractSiz ┆ lastTradeDa ┆ impliedVol ┆ inTheMoney │
│ ---        ┆ ---       ┆ ---  ┆ ---    ┆   ┆ e           ┆ te          ┆ atility    ┆ ---        │
│ str        ┆ f64       ┆ str  ┆ str    ┆   ┆ ---         ┆ ---         ┆ ---        ┆ bool       │
│            ┆           ┆      ┆        ┆   ┆ str         ┆ datetime[ms ┆ f64        ┆            │
│            ┆           ┆      ┆        ┆   ┆             ┆ ]           ┆            ┆            │
╞════════════╪═══════════╪══════╪════════╪═══╪═════════════╪═════════════╪════════════╪════════════╡
│ 2025-08-15 ┆ 0.098555  ┆ call ┆ AAPL   ┆ … ┆ REGULAR     ┆ 2025-08-11  ┆ 4.20313    ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 19:26:37    ┆            ┆            │
│ 2025-08-15 ┆ 0.098555  ┆ call ┆ AAPL   ┆ … ┆ REGULAR     ┆ 2025-08-11  ┆ 4.050786   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 14:02:05    ┆            ┆            │
│ 2025-08-15 ┆ 0.098555  ┆ call ┆ AAPL   ┆ … ┆ REGULAR     ┆ 2025-08-11  ┆ 3.644532   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 19:28:31    ┆            ┆            │
│ 2025-08-15 ┆ 0.098555  ┆ call ┆ AAPL   ┆ … ┆ REGULAR     ┆ 2025-08-08  ┆ 3.082034   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 17:57:07    ┆            ┆            │
│ 2025-08-15 ┆ 0.098555  ┆ call ┆ AAPL   ┆ … ┆ REGULAR     ┆ 2025-08-08  ┆ 3.427736   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 18:42:39    ┆            ┆            │
│ …          ┆ …         ┆ …    ┆ …      ┆ … ┆ …           ┆ …           ┆ …          ┆ …          │
│ 2027-12-17 ┆ 28.153745 ┆ put  ┆ NVDA   ┆ … ┆ REGULAR     ┆ 2025-08-11  ┆ 0.218086   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 18:17:27    ┆            ┆            │
│ 2027-12-17 ┆ 28.153745 ┆ put  ┆ NVDA   ┆ … ┆ REGULAR     ┆ 2025-07-30  ┆ 0.211922   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 16:43:40    ┆            ┆            │
│ 2027-12-17 ┆ 28.153745 ┆ put  ┆ NVDA   ┆ … ┆ REGULAR     ┆ 2025-08-05  ┆ 0.199593   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 14:00:00    ┆            ┆            │
│ 2027-12-17 ┆ 28.153745 ┆ put  ┆ NVDA   ┆ … ┆ REGULAR     ┆ 2025-08-05  ┆ 0.300727   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 19:11:43    ┆            ┆            │
│ 2027-12-17 ┆ 28.153745 ┆ put  ┆ NVDA   ┆ … ┆ REGULAR     ┆ 2025-08-11  ┆ 0.266365   ┆ true       │
│            ┆           ┆      ┆        ┆   ┆             ┆ 18:00:11    ┆            ┆            │
└────────────┴───────────┴──────┴────────┴───┴─────────────┴─────────────┴────────────┴────────────┘
No Options Data for BTC-USD
get_news

Fetch the Historical News Headlines for all tickers.

Returns:

  • DataFrame: Polars DataFrame containing news headlines.

Example:

news = tickers.get_news()
print(news)
get_income_statement

Fetch the income statement for all tickers.

Parameters:

  • frequency (str): The frequency of the data (annual or quarterly).
  • formatted (optional[bool]): Whether to return the data in a formatted manner, defaults to True.

Returns:

  • DataFrame: Polars DataFrame containing the income statement.

Example:

income_statement = tickers.get_income_statement(frequency="quarterly")
print(income_statement)
Error Fetching Data for BTC-USD: not found: "asOfDate" not found
Unable to stack shape: (13, 7)
┌─────────────────────────────┬────────┬───────────┬───────────┬───────────┬───────────┬───────────┐
│ Items                       ┆ symbol ┆ 2024Q1    ┆ 2024Q2    ┆ 2024Q3    ┆ 2024Q4    ┆ 2025Q1    │
│ ---                         ┆ ---    ┆ ---       ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│ str                         ┆ str    ┆ f64       ┆ f64       ┆ f64       ┆ f64       ┆ f64       │
╞═════════════════════════════╪════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡
│ Revenue                     ┆ NVDA   ┆ 2.6044e10 ┆ 3.0040e10 ┆ 3.5082e10 ┆ 3.9331e10 ┆ 4.4062e10 │
│ Cost of Goods Sold          ┆ NVDA   ┆ 5.6380e9  ┆ 7.4660e9  ┆ 8.9260e9  ┆ 1.0608e10 ┆ 1.7394e10 │
│ Gross Profit                ┆ NVDA   ┆ 2.0406e10 ┆ 2.2574e10 ┆ 2.6156e10 ┆ 2.8723e10 ┆ 2.6668e10 │
│ Operating Expenses          ┆ NVDA   ┆ 3.4970e9  ┆ 3.9320e9  ┆ 4.2870e9  ┆ 4.6890e9  ┆ 5.0300e9  │
│ EBITDA                      ┆ NVDA   ┆ 1.7753e10 ┆ 1.9708e10 ┆ 2.2855e10 ┆ 2.5821e10 ┆ 2.2584e10 │
│ …                           ┆ …      ┆ …         ┆ …         ┆ …         ┆ …         ┆ …         │
│ Interest Expense            ┆ NVDA   ┆ 6.4e7     ┆ 6.1e7     ┆ 6.1e7     ┆ 6.1e7     ┆ 6.3e7     │
│ Income Tax Expense          ┆ NVDA   ┆ 2.3980e9  ┆ 2.6150e9  ┆ 3.0070e9  ┆ 3.1260e9  ┆ 3.1350e9  │
│ Net Income                  �� NVDA   ┆ 1.4881e10 ┆ 1.6599e10 ┆ 1.9309e10 ┆ 2.2091e10 ┆ 1.8775e10 │
│ Earnings per Share - Basic  ┆ NVDA   ┆ 0.6       ┆ 0.68      ┆ 0.79      ┆ 0.9       ┆ 0.77      │
│ Earnings per Share -        ┆ NVDA   ┆ 0.6       ┆ 0.67      ┆ 0.78      ┆ 0.89      ┆ 0.76      │
│ Diluted                     ┆        ┆           ┆           ┆           ┆           ┆           │
└─────────────────────────────┴────────┴───────────┴───────────┴───────────┴───────────┴───────────┘: lengths don't match: unable to vstack, column names don't match: "2024Q2" and "2024Q1"
shape: (37, 7)
┌─────────────────────────────┬────────┬───────────┬───────────┬───────────┬───────────┬───────────┐
│ Items                       ┆ symbol ┆ 2024Q2    ┆ 2024Q3    ┆ 2024Q4    ┆ 2025Q1    ┆ 2025Q2    │
│ ---                         ┆ ---    ┆ ---       ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│ str                         ┆ str    ┆ f64       ┆ f64       ┆ f64       ┆ f64       ┆ f64       │
╞═════════════════════════════╪════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡
│ Revenue                     ┆ AAPL   ┆ 8.5777e10 ┆ 9.4930e10 ┆ 1.2430e11 ┆ 9.5359e10 ┆ 9.4036e10 │
│ Cost of Goods Sold          ┆ AAPL   ┆ 4.6099e10 ┆ 5.1051e10 ┆ 6.6025e10 ┆ 5.0492e10 ┆ 5.0318e10 │
│ Gross Profit                ┆ AAPL   ┆ 3.9678e10 ┆ 4.3879e10 ┆ 5.8275e10 ┆ 4.4867e10 ┆ 4.3718e10 │
│ Operating Expenses          ┆ AAPL   ┆ 1.4326e10 ┆ 1.4288e10 ┆ 1.5443e10 ┆ 1.5278e10 ┆ 1.5516e10 │
│ EBITDA                      ┆ AAPL   ┆ 2.8202e10 ┆ 3.2502e10 ┆ 4.5912e10 ┆ 3.2250e10 ┆ 3.1032e10 │
│ …                           ┆ …      ┆ …         ┆ …         ┆ …         ┆ …         ┆ …         │
│ Interest Expense            ┆ MSFT   ┆ 7.01e8    ┆ 5.82e8    ┆ 5.94e8    ┆ 5.94e8    ┆ 6.15e8    │
│ Income Tax Expense          ┆ MSFT   ┆ 5.2140e9  ┆ 5.6020e9  ┆ 5.2570e9  ┆ 5.5530e9  ┆ 5.3830e9  │
│ Net Income                  ┆ MSFT   ┆ 2.2036e10 ┆ 2.4667e10 ┆ 2.4108e10 ┆ 2.5824e10 ┆ 2.7233e10 │
│ Earnings per Share - Basic  ┆ MSFT   ┆ 2.96      ┆ 3.32      ┆ 3.24      ┆ 3.47      ┆ 3.66      │
│ Earnings per Share -        ┆ MSFT   ┆ 2.95      ┆ 3.3       ┆ 3.23      ┆ 3.46      ┆ 3.65      │
│ Diluted                     ┆        ┆           ┆           ┆           ┆           ┆           │
└─────────────────────────────┴────────┴───────────┴───────────┴───────────┴───────────┴───────────┘
get_balance_sheet

Fetch the balance sheet for all tickers.

Parameters:

  • frequency (str): The frequency of the data (annual or quarterly).
  • formatted (optional[bool]): Whether to return the data in a formatted manner, defaults to True.

Returns:

  • DataFrame: Polars DataFrame containing the balance sheet.

Example:

balance_sheet = tickers.get_balance_sheet(frequency="quarterly")
print(balance_sheet)
shape: (64, 7)
┌─────────────────────────────┬────────┬───────────┬───────────┬───────────┬───────────┬───────────┐
│ Items                       ┆ symbol ┆ 2024Q2    ┆ 2024Q3    ┆ 2024Q4    ┆ 2025Q1    ┆ 2025Q2    │
│ ---                         ┆ ---    ┆ ---       ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│ str                         ┆ str    ┆ f64       ┆ f64       ┆ f64       ┆ f64       ┆ f64       │
╞═════════════════════════════╪════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡
│ Cash and Cash Equivalents   ┆ AAPL   ┆ 2.5565e10 ┆ 2.9943e10 ┆ 3.0299e10 ┆ 2.8162e10 ┆ 3.6269e10 │
│ Accounts Receivable         ┆ AAPL   ┆ 2.2795e10 ┆ 3.3410e10 ┆ 2.9639e10 ┆ 2.6136e10 ┆ 2.7557e10 │
│ Inventories                 ┆ AAPL   ┆ 6.1650e9  ┆ 7.2860e9  ┆ 6.9110e9  ┆ 6.2690e9  ┆ 5.9250e9  │
│ Other Current Assets        ┆ AAPL   ┆ 1.4297e10 ┆ 1.4287e10 ┆ 1.3248e10 ┆ 1.4109e10 ┆ 1.4359e10 │
│ Total Current Assets        ┆ AAPL   ┆ 1.2544e11 ┆ 1.5299e11 ┆ 1.3324e11 ┆ 1.1867e11 ┆ 1.2249e11 │
│ …                           ┆ …      ┆ …         ┆ …         ┆ …         ┆ …         ┆ …         │
│ Total Liabilities           ┆ MSFT   ┆ 2.4369e11 ┆ 2.3529e11 ┆ 2.3120e11 ┆ 2.4073e11 ┆ 2.7552e11 │
│ Common Stock                ┆ MSFT   ┆ 1.0092e11 ┆ 1.0298e11 ┆ 1.0483e11 ┆ 1.0696e11 ┆ 1.0910e11 │
│ Retained Earnings           ┆ MSFT   ┆ 1.7314e11 ┆ 1.8893e11 ┆ 2.0348e11 ┆ 2.1976e11 ┆ 2.3773e11 │
│ Total Equity                ┆ MSFT   ┆ 2.6848e11 ┆ 2.8772e11 ┆ 3.0270e11 ┆ 3.2189e11 ┆ 3.4348e11 │
│ Total Liabilities and       ┆ MSFT   ┆ 2.6848e11 ┆ 2.8772e11 ┆ 3.0270e11 ┆ 3.2189e11 ┆ 3.4348e11 │
│ Equity                      ┆        ┆           ┆           ┆           ┆           ┆           │
└─────────────────────────────┴────────┴───────────┴───────────┴───────────┴───────────┴───────────┘
Error Fetching Data for BTC-USD: not found: "asOfDate" not found
Unable to stack shape: (22, 7)
┌─────────────────────────────┬────────┬───────────┬───────────┬───────────┬───────────┬───────────┐
│ Items                       ┆ symbol ┆ 2024Q1    ┆ 2024Q2    ┆ 2024Q3    ┆ 2024Q4    ┆ 2025Q1    │
│ ---                         ┆ ---    ┆ ---       ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│ str                         ┆ str    ┆ f64       ┆ f64       ┆ f64       ┆ f64       ┆ f64       │
╞═════════════════════════════╪════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡
│ Cash and Cash Equivalents   ┆ NVDA   ┆ 7.5870e9  ┆ 8.5630e9  ┆ 9.1070e9  ┆ 8.5890e9  ┆ 1.5234e10 │
│ Accounts Receivable         ┆ NVDA   ┆ 1.2365e10 ┆ 1.4132e10 ┆ 1.7693e10 ┆ 2.3065e10 ┆ 2.2132e10 │
│ Inventories                 ┆ NVDA   ┆ 5.8640e9  ┆ 6.6750e9  ┆ 7.6540e9  ┆ 1.0080e10 ┆ 1.1333e10 │
│ Other Current Assets        ┆ NVDA   ┆ 4.0620e9  ┆ 4.0260e9  ┆ 3.8060e9  ┆ 3.7710e9  ┆ 2.7790e9  │
│ Total Current Assets        ┆ NVDA   ┆ 5.3729e10 ┆ 5.9633e10 ┆ 6.7640e10 ┆ 8.0126e10 ┆ 8.9935e10 │
│ …                           ┆ …      ┆ …         ┆ …         ┆ …         ┆ …         ┆ …         │
│ Total Liabilities           ┆ NVDA   ┆ 2.7930e10 ┆ 2.7070e10 ┆ 3.0114e10 ┆ 3.2274e10 ┆ 4.1411e10 │
│ Common Stock                ┆ NVDA   ┆ 2e6       ┆ 2.5e7     ┆ 2.5e7     ┆ 2.4e7     ┆ 2.4e7     │
│ Retained Earnings           �� NVDA   ┆ 3.6598e10 ┆ 4.5961e10 ┆ 5.3950e10 ┆ 6.8038e10 ┆ 7.2158e10 │
│ Total Equity                ┆ NVDA   ┆ 4.9142e10 ┆ 5.8157e10 ┆ 6.5899e10 ┆ 7.9327e10 ┆ 8.3843e10 │
│ Total Liabilities and       ┆ NVDA   ┆ 4.9142e10 ┆ 5.8157e10 ┆ 6.5899e10 ┆ 7.9327e10 ┆ 8.3843e10 │
│ Equity                      ┆        ┆           ┆           ┆           ┆           ┆           │
└─────────────────────────────┴────────┴───────────┴───────────┴───────────┴───────────┴───────────┘: lengths don't match: unable to vstack, column names don't match: "2024Q2" and "2024Q1"
get_cashflow_statement

Fetch the cash flow statement for all tickers.

Parameters:

  • frequency (str): The frequency of the data (annual or quarterly).
  • formatted (optional[bool]): Whether to return the data in a formatted manner, defaults to True.

Returns:

  • DataFrame: Polars DataFrame containing the cash flow statement.

Example:

cashflow_statement = tickers.get_cashflow_statement(frequency="quarterly")
print(cashflow_statement)
shape: (86, 7)
┌────────────────────────┬────────┬────────────┬────────────┬────────────┬────────────┬────────────┐
│ Items                  ┆ symbol ┆ 2024Q2     ┆ 2024Q3     ┆ 2024Q4     ┆ 2025Q1     ┆ 2025Q2     │
│ ---                    ┆ ---    ┆ ---        ┆ ---        ┆ ---        ┆ ---        ┆ ---        │
│ str                    ┆ str    ┆ f64        ┆ f64        ┆ f64        ┆ f64        ┆ f64        │
╞════════════════════════╪════════╪════════════╪════════════╪════════════╪════════════╪════════════╡
│ Net Income from        ┆ AAPL   ┆ 2.1448e10  ┆ 1.4736e10  ┆ 3.6330e10  ┆ 2.4780e10  ┆ 2.3434e10  │
│ Continuing Ope…        ┆        ┆            ┆            ┆            ┆            ┆            │
│ Depreciation,          ┆ AAPL   ┆ 2.8500e9   ┆ 2.9110e9   ┆ 3.0800e9   ┆ 2.6610e9   ┆ 2.8300e9   │
│ Amortization, an…      ┆        ┆            ┆            ┆            ┆            ┆            │
│ Stock-Based            ┆ AAPL   ┆ 2.8690e9   ┆ 2.8580e9   ┆ 3.2860e9   ┆ 3.2260e9   ┆ 3.1680e9   │
│ Compensation           ┆        ┆            ┆            ┆            ┆            ┆            │
│ Changes in Working     ┆ AAPL   ┆ 1.6840e9   ┆ 6.6080e9   ┆ -1.0752e10 ┆ -6.5070e9  ┆ -2.0340e9  │
│ Capital                ┆        ┆            ┆            ┆            ┆            ┆            │
│ Cash Flow from         ┆ AAPL   ┆ 2.8858e10  ┆ 2.6811e10  ┆ 2.9935e10  ┆ 2.3952e10  ┆ 2.7867e10  │
│ Continuing Oper…       ┆        ┆            ┆            ┆            ┆            ┆            │
│ …                      ┆ …      ┆ …          ┆ …          ┆ …          ┆ …          ┆ …          │
│ Operating Cash Flow    ┆ MSFT   ┆ 3.7195e10  ┆ 3.4180e10  ┆ 2.2291e10  ┆ 3.7044e10  ┆ 4.2647e10  │
│ Investing Cash Flow    ┆ MSFT   ┆ -1.4848e10 ┆ -1.5201e10 ┆ -1.4112e10 ┆ -1.2714e10 ┆ -3.0572e10 │
│ Financing Cash Flow    ┆ MSFT   ┆ -2.3563e10 ┆ -1.6576e10 ┆ -1.1243e10 ┆ -1.3036e10 ┆ -1.0844e10 │
│ Ending Cash Position   ┆ MSFT   ┆ 1.8315e10  ┆ 2.0840e10  ┆ 1.7482e10  ┆ 2.8828e10  ┆ 3.0242e10  │
│ Free Cash Flow         ┆ MSFT   ┆ 2.3322e10  ┆ 1.9257e10  ┆ 6.4870e9   ┆ 2.0299e10  ┆ 2.5568e10  │
└────────────────────────┴────────┴────────────┴────────────┴────────────┴────────────┴────────────┘
Error Fetching Data for BTC-USD: not found: "asOfDate" not found
Unable to stack shape: (27, 7)
┌──────────────────────────┬────────┬───────────┬────────────┬────────────┬───────────┬────────────┐
│ Items                    ┆ symbol ┆ 2024Q1    ┆ 2024Q2     ┆ 2024Q3     ┆ 2024Q4    ┆ 2025Q1     │
│ ---                      ┆ ---    ┆ ---       ┆ ---        ┆ ---        ┆ ---       ┆ ---        │
│ str                      ┆ str    ┆ f64       ┆ f64        ┆ f64        ┆ f64       ┆ f64        │
╞══════════════════════════╪════════╪═══════════╪════════════╪════════════╪═══════════╪════════════╡
│ Net Income from          ┆ NVDA   ┆ 1.4881e10 ┆ 1.6599e10  ┆ 1.9309e10  ┆ 2.2091e10 ┆ 1.8775e10  │
│ Continuing Ope…          ┆        ┆           ┆            ┆            ┆           ┆            │
│ Depreciation,            ┆ NVDA   ┆ 4.1e8     ┆ 4.33e8     ┆ 4.78e8     ┆ 5.43e8    ┆ 6.11e8     │
│ Amortization, an…        ┆        ┆           ┆            ┆            ┆           ┆            │
│ Stock-Based Compensation ┆ NVDA   ┆ 1.0110e9  ┆ 1.1530e9   ┆ 1.2520e9   ┆ 1.3210e9  ┆ 1.4740e9   │
│ Deferred Income Tax      ┆ NVDA   ┆ -1.5770e9 ┆ -1.6990e9  ┆ -6.0300e8  ┆ -5.9800e8 ┆ -2.1770e9  │
│ Changes in Working       ┆ NVDA   ┆ 8.34e8    ┆ -1.6600e9  ┆ -2.6940e9  ┆ -5.8630e9 ┆ 8.6540e9   │
│ Capital                  ┆        ┆           ┆            ┆            ┆           ┆            │
│ …                        ┆ …      ┆ …         ┆ …          ┆ …          ┆ …         ┆ …          │
│ Operating Cash Flow      ┆ NVDA   ┆ 1.5345e10 ┆ 1.4488e10  ┆ 1.7627e10  ┆ 1.6629e10 ┆ 2.7414e10  │
│ Investing Cash Flow      ┆ NVDA   ┆ -5.6930e9 ┆ -3.1840e9  ┆ -4.3460e9  ┆ -7.1980e9 ┆ -5.2160e9  │
│ Financing Cash Flow      ┆ NVDA   ┆ -9.3450e9 ┆ -1.0320e10 ┆ -1.2745e10 ┆ -9.9490e9 ┆ -1.5553e10 │
│ Ending Cash Position     ┆ NVDA   ┆ 7.5870e9  ┆ 8.5710e9   ┆ 9.1070e9   ┆ 8.5890e9  ┆ 1.5234e10  │
│ Free Cash Flow           ┆ NVDA   ┆ 1.4976e10 ┆ 1.3511e10  ┆ 1.6814e10  ┆ 1.5552e10 ┆ 2.6187e10  │
└──────────────────────────┴────────┴───────────┴────────────┴────────────┴───────────┴────────────┘: lengths don't match: unable to vstack, column names don't match: "2024Q2" and "2024Q1"
get_financial_ratios

Fetch the financial ratios for all tickers.

Parameters:

  • frequency (str): The frequency of the data (annual or quarterly).

Returns:

  • DataFrame: Polars DataFrame containing the financial ratios.

Example:

financial_ratios = tickers.get_financial_ratios(frequency="quarterly")
print(financial_ratios)
shape: (63, 7)
┌─────────────────────────┬────────┬───────────┬───────────┬───────────┬───────────┬───────────┐
│ Items                   ┆ symbol ┆ 2024Q2    ┆ 2024Q3    ┆ 2024Q4    ┆ 2025Q1    ┆ 2025Q2    │
│ ---                     ┆ ---    ┆ ---       ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│ str                     ┆ str    ┆ f64       ┆ f64       ┆ f64       ┆ f64       ┆ f64       │
╞═════════════════════════╪════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡
│ Gross Profit Margin     ┆ AAPL   ┆ 0.462572  ┆ 0.462225  ┆ 0.468825  ┆ 0.470506  ┆ 0.464907  │
│ Operating Profit Margin ┆ AAPL   ┆ 0.295557  ┆ 0.311714  ┆ 0.344586  ┆ 0.310291  ┆ 0.299906  │
│ Net Profit Margin       ┆ AAPL   ┆ 0.250044  ┆ 0.15523   ┆ 0.292277  ┆ 0.25986   ┆ 0.249202  │
│ Return on Assets        ┆ AAPL   ┆ 0.064678  ┆ 0.040375  ┆ 0.105584  ┆ 0.074811  ┆ 0.070692  │
│ Return on Equity        ┆ AAPL   ┆ 0.321521  ┆ 0.258753  ┆ 0.544204  ┆ 0.37098   ┆ 0.355978  │
│ …                       ┆ …      ┆ …         ┆ …         ┆ …         ┆ …         ┆ …         │
│ Price to Earnings       ┆ MSFT   ┆ 14.120757 ┆ 13.402157 ┆ 14.203459 ┆ 14.009178 ┆ 14.08699  │
│ Price to Book           ┆ MSFT   ┆ 1.159001  ┆ 1.148991  ┆ 1.131228  ┆ 1.123899  ┆ 1.116898  │
│ Price to Sales          ┆ MSFT   ┆ 4.807345  ┆ 5.04065   ┆ 4.917524  ┆ 5.163317  ┆ 5.018655  │
│ Price to Cashflow       ┆ MSFT   ┆ 8.365775  ┆ 9.67206   ┆ 15.361222 ┆ 9.766035  ┆ 8.995498  │
│ Price to Free Cashflow  ┆ MSFT   ┆ 13.342123 ┆ 17.167316 ┆ 52.785109 ┆ 17.822208 ┆ 15.004341 │
└─────────────────────────┴────────┴───────────┴───────────┴───────────┴───────────┴───────────┘
Error Fetching Data for BTC-USD: not found: "asOfDate" not found
Unable to stack shape: (21, 7)
┌─────────────────────────┬────────┬──────────┬──────────┬──────────┬──────────┬──────────┐
│ Items                   ┆ symbol ┆ 2024Q1   ┆ 2024Q2   ┆ 2024Q3   ┆ 2024Q4   ┆ 2025Q1   │
│ ---                     ┆ ---    ┆ ---      ┆ ---      ┆ ---      ┆ ---      ┆ ---      │
│ str                     ┆ str    ┆ f64      ┆ f64      ┆ f64      ┆ f64      ┆ f64      │
╞═════════════════════════╪════════╪══════════╪══════════╪══════════╪══════════╪══════════╡
│ Gross Profit Margin     ┆ NVDA   ┆ 0.78352  ┆ 0.751465 ┆ 0.745568 ┆ 0.730289 ┆ 0.605238 │
│ Operating Profit Margin ┆ NVDA   ┆ 0.665912 ┆ 0.641644 ┆ 0.637848 ┆ 0.642699 ┆ 0.498684 │
│ Net Profit Margin       ┆ NVDA   ┆ 0.571379 ┆ 0.552563 ┆ 0.550396 ┆ 0.561669 ┆ 0.426104 │
│ Return on Assets        ┆ NVDA   ┆ 0.193079 ┆ 0.194762 ┆ 0.201108 ┆ 0.197946 ┆ 0.149895 │
│ Return on Equity        ┆ NVDA   ┆ 0.302816 ┆ 0.285417 ┆ 0.293009 ┆ 0.27848  ┆ 0.22393  │
│ …                       ┆ …      ┆ …        ┆ …        ┆ …        ┆ …        ┆ …        │
│ Price to Earnings       ┆ NVDA   ┆ 3.870842 ┆ 4.013374 ┆ 3.851106 ┆ 3.974017 ┆ 4.916485 │
│ Price to Book           ┆ NVDA   ┆ 1.172154 ┆ 1.145485 ┆ 1.128409 ┆ 1.106685 ┆ 1.100951 │
│ Price to Sales          ┆ NVDA   ┆ 2.211719 ┆ 2.217643 ┆ 2.119634 ┆ 2.232082 ┆ 2.094934 │
│ Price to Cashflow       ┆ NVDA   ┆ 3.753796 ┆ 4.59815  ┆ 4.218585 ┆ 5.279331 ┆ 3.367148 │
│ Price to Free Cashflow  ┆ NVDA   ┆ 3.846287 ┆ 4.930649 ┆ 4.422565 ┆ 5.644933 ┆ 3.524917 │
└─────────────────────────┴────────┴──────────┴──────────┴──────────┴──────────┴──────────┘: lengths don't match: unable to vstack, column names don't match: "2024Q2" and "2024Q1"
returns

Compute the returns for all tickers.

Returns:

  • DataFrame: Polars DataFrame containing the returns.

Example:

returns = tickers.returns()
print(returns)
shape: (1_461, 6)
┌─────────────────────┬───────────┬───────────┬───────────┬───────────┬───────────┐
│ timestamp           ┆ AAPL      ┆ GOOG      ┆ MSFT      ┆ NVDA      ┆ BTC-USD   │
│ ---                 ┆ ---       ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│ str                 ┆ f64       ┆ f64       ┆ f64       ┆ f64       ┆ f64       │
╞═════════════════════╪═══════════╪═══════════╪═══════════╪═══════════╪═══════════╡
│ 2020-01-01 00:00:00 ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       │
│ 2020-01-02 00:00:00 ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ -2.981929 │
│ 2020-01-03 00:00:00 ┆ -0.972215 ┆ -0.490725 ┆ -1.245172 ┆ -1.600602 ┆ 5.145166  │
│ 2020-01-04 00:00:00 ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.895487  │
│ 2020-01-05 00:00:00 ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.008915  │
│ …                   ┆ …         ┆ …         ┆ …         ┆ …         ┆ …         │
│ 2023-12-27 00:00:00 ┆ 0.051803  ┆ -0.966238 ┆ -0.157459 ┆ 0.28004   ┆ 2.169436  │
│ 2023-12-28 00:00:00 ┆ 0.222626  ┆ -0.113124 ┆ 0.32345   ┆ 0.212486  ┆ -1.876028 │
│ 2023-12-29 00:00:00 ┆ -0.542419 ┆ -0.247745 ┆ 0.202522  ┆ 0.0       ┆ -1.23969  │
│ 2023-12-30 00:00:00 ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.136582  │
│ 2023-12-31 00:00:00 ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ 0.256862  │
└─────────────────────┴───────────┴───────────┴───────────┴───────────┴───────────┘
performance_stats

Compute the performance stats for all tickers.

Returns:

  • DataFrame: Polars DataFrame containing the performance stats.

Example:

performance_stats = tickers.performance_stats()
print(performance_stats)
shape: (5, 17)
┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐
│ Symbol  ┆ Daily      ┆ Daily Vol ┆ Cumulativ ┆ … ┆ Calmar    ┆ Maximum   ┆ Value at  ┆ Expected  │
│ ---     ┆ Return     ┆ atility   ┆ e Return  ┆   ┆ Ratio     ┆ Drawdown  ┆ Risk      ┆ Shortfall │
│ str     ┆ ---        ┆ ---       ┆ ---       ┆   ┆ ---       ┆ ---       ┆ ---       ┆ ---       │
│         ┆ str        ┆ str       ┆ str       ┆   ┆ str       ┆ str       ┆ str       ┆ str       │
╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡
│ AAPL    ┆ 0.11853875 ┆ 2.1124921 ┆ 163.18933 ┆ … ┆ 1.0362996 ┆ 33.534604 ┆ -3.243676 ┆ -4.714313 │
│         ┆ 316439175  ┆ 374554164 ┆ 495334144 ┆   ┆ 087960261 ┆ 95897686  ┆ 692274868 ┆ 174575061 │
│         ┆            ┆           ┆           ┆   ┆           ┆           ┆ 8         ┆           │
│ GOOG    ┆ 0.09414068 ┆ 2.1059432 ┆ 106.13297 ┆ … ┆ 0.5105194 ┆ 52.362250 ┆ -3.194601 ┆ -4.806254 │
│         ┆ 814520443  ┆ 547258057 ┆ 145127274 ┆   ┆ 147187577 ┆ 18080071  ┆ 700883718 ┆ 311329883 │
│ MSFT    ┆ 0.10935394 ┆ 2.0525392 ┆ 142.95209 ┆ … ┆ 0.7723260 ┆ 41.012558 ┆ -2.951155 ┆ -4.550189 │
│         ┆ 148249847  ┆ 507092386 ┆ 724482433 ┆   ┆ 029173278 ┆ 05238269  ┆ 744262347 ┆ 39634677  │
│ NVDA    ┆ 0.26818823 ┆ 3.4126849 ┆ 728.90273 ┆ … ┆ 1.0561096 ┆ 91.152605 ┆ -5.126370 ┆ -6.999368 │
│         ┆ 686706145  ┆ 41160901  ┆ 0599302   ┆   ┆ 996451254 ┆ 93004216  ┆ 07303044  ┆ 083651968 │
│ BTC-USD ┆ 0.18312342 ┆ 3.4774959 ┆ 487.00228 ┆ … ┆ 0.7734174 ┆ 122.82135 ┆ -5.098586 ┆ -7.981326 │
│         ┆ 434915735  ┆ 999729025 ┆ 137108877 ┆   ┆ 145027587 ┆ 584673281 ┆ 481791351 ┆ 501258104 │
│         ┆            ┆           ┆           ┆   ┆           ┆           ┆           ┆ 5         │
└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘
returns_chart

Display the cumulative returns chart for all tickers.

Returns:

  • Plot: Plot object containing the returns chart.

Example:

returns_chart = tickers.returns_chart()
returns_chart.show()
returns_matrix

Display the returns correlation matrix for all tickers.

Returns:

  • Plot: Plot object containing the returns chart.

Example:

returns_matrix = tickers.returns_matrix(height=600, width=800)
returns_matrix.show()
report

Generate a report for all tickers.

Parameters:

  • report_type (Optional[str]): The type of report to generate (“performance”).
  • display (Optional[str]): The display mode for the report. set to “notebook” for Jupyter Notebook display, defaults to “browser”.

Example:

tickers.report("performance")
get_ticker

Fetch the Ticker object for a specific ticker symbol.

Parameters:

  • symbol (str): The ticker symbol.

Returns:

  • Ticker: A Ticker object.

Example:

ticker = tickers.get_ticker(symbol="AAPL")
ticker.performance_chart().show()
optimize

Optimizes the tickers given the objective function and constraints.

Parameters:

  • objective_function (Optional[str]): The objective function for optimization:
    • max_sharpe: Maximize return per unit of risk.
    • min_vol: Minimize overall volatility.
    • max_return: Maximize expected return.
    • min_var: Minimize Value-at-Risk (VaR).
    • min_cvar: Minimize Conditional Value-at-Risk (CVaR).
    • min_drawdown: Minimize maximum portfolio drawdown.
  • constraints (Optional[List[Tuple[float, float]]]): List of constraints for optimization.
  • weights (Optional[List[float]]): Weights for asset allocation. If provided, overrides the optimization process.

Returns:

  • Portfolio: A Portfolio object.

Example:

portfolio = tickers.optimize(objective_function="max_sharpe", constraints=[(0, 1), (0, 1), (0, 1), (0, 1), (0,1)])
portfolio.performance_chart().show()