Welcome to Finalytics Documentation

Symbols Module

This module provides functions related to symbols.

get_symbols(query, asset_class) → List[str]

Fetches ticker symbols that closely match the specified query and asset class.

• Arguments:

  • query (str): The query to search for.

  • asset_class (str): The asset class to search for.

• Returns:

  • List[str]: A list of ticker symbols that closely match the query and asset class.

• Example

  import finalytics
  
  symbols = finalytics.get_symbols("Apple", "Equity")
  print(symbols)
  

Ticker Module

This module contains the Ticker class.

class Ticker

The Ticker class enables you to fetch data for a given ticker symbol and perform security analysis.

__init__(symbol: str) → Ticker

Create a new Ticker object.

• Arguments:

  • symbol (str): The ticker symbol of the asset.

• Returns:

  • Ticker: A Ticker object.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  print(ticker.name, ticker.exchange, ticker.category, ticker.asset_class)
  

get_current_price() → float

Get the current price of the ticker.

• Returns:

  • float: The current price of the ticker.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  current_price = ticker.get_current_price()
  

get_summary_stats() → dict

Get summary technical and fundamental statistics for the ticker.

• Returns:

  • dict: A dictionary containing the summary statistics.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  summary_stats = ticker.get_summary_stats()
  

get_price_history(start: str, end: str, interval: str) → DataFrame

Get the ohlcv data for the ticker for a given time period.

• Arguments:

  • start (str): The start date of the time period in the format YYYY-MM-DD.

  • end (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).

• Returns:

  • DataFrame: A Polars DataFrame containing the ohlcv data.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  ohlcv = ticker.get_price_history("2020-01-01", "2020-12-31", "1d")
  

get_options_chain() → DataFrame

Get the options chain for the ticker.

• Returns:

  • DataFrame: A Polars DataFrame containing the options chain.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  options_chain = ticker.get_options_chain()
  

get_news(start: str, end: str, compute_sentiment: bool) → dict

Get the news for the ticker for a given time period.

• Arguments:

  • start (str): The start date of the time period in the format YYYY-MM-DD.

  • end (str): The end date of the time period in the format YYYY-MM-DD.

  • compute_sentiment (bool): Whether to compute the sentiment of the news articles.

• Returns:

  • dict: A dictionary containing the news articles (and sentiment results if requested).

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  news = ticker.get_news("2020-01-01", "2020-12-31", False)
  

get_income_statement() → DataFrame

Get the Income Statement for the ticker.

• Returns:

  • DataFrame: A Polars DataFrame containing the Income Statement.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  income_statement = ticker.get_income_statement()
  

get_balance_sheet() → DataFrame

Get the Balance Sheet for the ticker.

• Returns:

  • DataFrame: A Polars DataFrame containing the Balance Sheet.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  balance_sheet = ticker.get_balance_sheet()
  

get_cashflow_statement() → DataFrame

Get the Cashflow Statement for the ticker.

• Returns:

  • DataFrame: A Polars DataFrame containing the Cashflow Statement.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  cashflow_statement = ticker.get_cashflow_statement()
  

get_financial_ratios() → DataFrame

Get the Financial Ratios for the ticker.

• Returns:

  • DataFrame: A Polars DataFrame containing the Financial Ratios.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  financial_ratios = ticker.get_financial_ratios()
  

compute_performance_stats(start: str, end: str, interval: str, benchmark: str, confidence_level: float, risk_free_rate: float) → dict

Compute the performance statistics for the ticker.

• Arguments:

  • start (str): The start date of the time period in the format YYYY-MM-DD.

  • end (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 (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:

  • dict: A dictionary containing the performance statistics.

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  performance_stats = ticker.compute_performance_stats("2020-01-01", "2020-12-31", "1d", "^GSPC", 0.95, 0.02)
  

display_performance_chart(start: str, end: str, interval: str, benchmark: str, confidence_level: float, risk_free_rate: float, display_format: str) → None

Display the performance chart for the ticker.

• Arguments:

  • start (str): The start date of the time period in the format YYYY-MM-DD.

  • end (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 (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.

  • display_format (str): The format to display the chart in (png, html, notebook, colab).

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  ticker.display_performance_chart("2020-01-01", "2020-12-31", "1d", "^GSPC", 0.95, 0.02, "html")
  

display_candlestick_chart(start: str, end: str, interval: str, display_format: str) → None

Display the candlestick chart for the ticker.

• Arguments:

  • start (str): The start date of the time period in the format YYYY-MM-DD.

  • end (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).

  • display_format (str): The format to display the chart in (png, html, notebook, colab).

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  ticker.display_candlestick_chart("2020-01-01", "2020-12-31", "1d", "html")
  

display_options_chart(risk_free_rate: float, display_format: str) → None

Display the options volatility surface, smile, and term structure charts for the ticker.

• Arguments:

  • risk_free_rate (float): The risk free rate to use in the calculations.

  • display_format (str): The format to display the chart in (png, html, notebook, colab).

• Example:

  import finalytics
  
  ticker = finalytics.Ticker("AAPL")
  ticker.display_options_chart(0.02, "html")
  

Portfolio Module

This module contains the Portfolio class.

class Portfolio

The Portfolio class enables you perform portfolio optimization and compute portfolio performance statistics.

__init__(ticker_symbols: List[str], benchmark_symbol: str, start_date: str, end_date: str, interval: str, confidence_level: float, risk_free_rate: float, max_iterations: int, objective_function: str) → Portfolio

Create a new Portfolio object.

• Arguments:

  • ticker_symbols (List[str]): List of ticker symbols for the assets in the portfolio.

  • benchmark_symbol (str): The ticker symbol of the benchmark to compare against.

  • 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).

  • 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.

  • max_iterations (int): The maximum number of iterations to use in the optimization.

  • objective_function (str): The objective function to use in the optimization (max_sharpe, min_vol, max_return, nin_var, min_cvar, min_drawdown).

• Returns:

  • Portfolio: A Portfolio object.

• Example:

  import finalytics
  
  portfolio = finalytics.Portfolio(["AAPL", "GOOG", "MSFT"], "^GSPC", "2020-01-01", "2021-01-01", "1d", 0.95, 0.02, 1000, "max_sharpe")
  

get_optimization_results() → dict

Get the portfolio optimization results.

• Returns:

  • dict: A dictionary containing optimization results.

• Example:

  import finalytics
  
  portfolio = finalytics.Portfolio(["AAPL", "GOOG", "MSFT"], "^GSPC", "2020-01-01", "2021-01-01", "1d", 0.95, 0.02, 1000, "max_sharpe")
  optimization_results = portfolio.get_optimization_results()
  

display_portfolio_charts(display_format: str) → None

Display the portfolio optimization charts.

• Arguments:

  • chart_type (str): The type of chart to display (optimization, performance, asset_returns).

  • display_format (str): The format to display the charts in (html, png, notebook, colab).

• Example:

  import finalytics
  
  portfolio = finalytics.Portfolio(["AAPL", "GOOG", "MSFT"], "^GSPC", "2020-01-01", "2021-01-01", "1d", 0.95, 0.02, 1000, "max_sharpe")
  portfolio.display_portfolio_charts("optimization","html")
  

DeFi Module

This module contains the DefiPools and DefiBalances classes.

class DefiPools

DefiPools is a class that provides information about DeFi liquidity pools.

__init__() → DefiPools

Create a new DefiPools object.

• Returns:

  • DefiPools: A DefiPools object.

• Example:

  import finalytics
  
  defi_pools = finalytics.DefiPools()
  print(f"Total Value Locked: ${defi_pools.total_value_locked:,.0f}")
  print(defi_pools.pools_data)
  

search_pools_by_symbol(symbol: str) → List[str]

Search the pools data for pools that match the search term.

• Arguments:

  • symbol (str): Cryptocurrency symbol.

• Returns:

  • List[str]: List of pools that match the search term.

• Example:

  import finalytics
  
  defi_pools = finalytics.DefiPools()
  print(defi_pools.search_pools_by_symbol("USDC"))
  

display_top_protocols_by_tvl(pool_symbol: str, num_protocols: int, display_format: str)

Display the top protocols for a given symbol by total value locked.

• Arguments:

  • pool_symbol (str): Liquidity pool symbol.

  • num_protocols (int): Number of protocols to display.

  • display_format (str): Display format for the chart (html, svg, notebook, colab).

• Example:

  import finalytics
  
  defi_pools = finalytics.DefiPools()
  defi_pools.display_top_protocols_by_tvl("USDC-USDT", 20, "html")
  

display_top_protocols_by_apy(pool_symbol: str, num_protocols: int, display_format: str)

Display the top protocols for a given symbol by APY.

• Arguments:

  • pool_symbol (str): Liquidity pool symbol.

  • num_protocols (int): Number of protocols to display.

  • display_format (str): Display format for the chart (html, svg, notebook, colab).

• Example:

  import finalytics
  
  defi_pools = finalytics.DefiPools()
  defi_pools.display_top_protocols_by_apy("USDC-USDT", 20, "html")
  

display_pool_tvl_history(pool_symbol: str, protocol: str, chain: str, display_format: str)

Display the total value locked history for a given pool.

• Arguments:

  • pool_symbol (str): Liquidity pool symbol.

  • protocol (str): Protocol.

  • chain (str): Blockchain.

  • display_format (str): Display format for the chart (html, svg, notebook, colab).

• Example:

  import finalytics
  
  defi_pools = finalytics.DefiPools()
  defi_pools.display_pool_tvl_history("USDC-USDT", "uniswap-v3", "ethereum", "html")
  

display_pool_apy_history(pool_symbol: str, protocol: str, chain: str, display_format: str)

Display the APY history for a given pool.

• Arguments:

  • pool_symbol (str): Liquidity pool symbol.

  • protocol (str): Protocol.

  • chain (str): Blockchain.

  • display_format (str): Display format for the chart (html, svg, notebook, colab).

• Example:

  import finalytics
  
  defi_pools = finalytics.DefiPools()
  defi_pools.display_pool_apy_history("USDC-USDT", "uniswap-v3", "ethereum", "html")
  

class DefiBalances

The DefiBalances class enables you to fetch DeFi Users’ wallet & protocol balances.

__init__(protocols: List[str], chains: List[str], address: str, display_format: str) → DefiBalances

Initializes a new DefiBalances object.

• Arguments:

  • protocols (List[str]): List of protocols to fetch balances for.

  • chains (List[str]): List of chains to fetch balances for.

  • address (str): Wallet address to fetch balances for.

  • display_format (str): Display format for the chart (html, svg, notebook, colab).

• Returns:

  • DefiBalances: A DefiBalances object.

• Example:

  import finalytics
  
  defi_balances = finalytics.DefiBalances(["wallet", "eigenlayer", "blast", "ether.fi"],
                                             ["ethereum", "arbitrum"],
                                             "0x7ac34681f6aaeb691e150c43ee494177c0e2c183",
                                             "html")
  print(defi_balances.balances)
  

get_supported_protocols() → Dict[str, List[str]]

Fetches the supported protocols and chains for the DefiBalances class.

• Returns:

  • Dict[str, List[str]]: Dictionary of protocols and chains.

• Example:

  import finalytics
  
  supported_protocols = finalytics.get_supported_protocols()
  print(supported_protocols)