equitysim

This code harnesses the AlphaVantage API to download and analyze equity data on any constituent of the following groups:

• the S&P 500 stock index
• the Dow 30 stock index
• the NASDAQ 100 stock index
• the top 100 most-traded ETFs
• the top 25 most-traded mutual funds These data are readily transformed using technical indicators and processed into features for machine learning.

This code also downloads and analyzes data from the United States SEC's Financial Statements datasets, which supplies additional feature data from a fundamental analysis standpoint.

AlphaVantage data download/update

• download.py
  • load_single downloads and processes a single symbol from AlphaVantage API into a file
  • load_single_drive downloads and processes a single symbol from local drive into a variable
  • load_separate downloads and processes many symbols from AlphaVantage API into many files
  • load_combined_drive downloads and processes many symbols from local drive into one variable
  • command prompt options:
    • -tickerUniverse: collection of tickers to download (can also be a CSV of ticker symbols)
    • -folderPath: location of folder to store file
    • -apiKey: AlphaVantage API key (user-specific)
    • -function: distinguishes between intraday, daily, weekly, etc. downloads
    • -interval specifies what kind of intraday (1min, 15min, etc.)
• auto_update.py
  • update_in_folder updates all equity files in a folder, using the latest data from AlphaVantage
  • command prompt options:
    • -folderPath: location of folder to look for files
    • -apiKey: AlphaVantage API key (user-specific)
• See the AlphaVantage documentation for more details on their API calls.

SEC EDGAR data download/update

• edgar_load.py
  • download_unzip downloads and unzips data directly from the SEC website
  • proc_in_directory walks through download directory and parses each file
  • post_proc performs post-processing on files, which makes them smaller
  • json_build builds one JSON file for each company chosen
  • command prompt options:
    • -folderPath: location of folder to download data
    • -stockFolderPath: location of folder to look for stock data
    • -financialFolderPath: location of folder to load financial data
    • -suppressDownload: order to suppress downloading data (i.e. already downloaded)
    • -suppressProcess: order to suppress processing data (i.e. already processed)
• edgar_parse.py
  • json_parse provides backup parsing code to clean up the JSON files in edgar_load.py
  • get_sic_names scrapes SEC.gov for data on industry codes (SICs)
  • submission_parse parses submission files
  • number_parse parses number files
  • presentation_parse parses presentation files
  • tag_parse parses tag files
  • command prompt options:
    • none (does not need any)

fundamental analysis

• edgar_pull.py
  • get_unique_tags returns list of unique tags in a single company's JSON file
  • get_data_this_tag writes data on one chosen tag to an output file
  • command prompt options:
    • pending
• return_calculator.py
  • get_rolling_returns calculates a list of rolling returns on an asset or portfolio
  • overall_returns calculates the overall return from start to finish
  • command prompt options:
    • none (does not need any)

technical analysis

• technicals.py
  • accum_swing computes the accumulation (running total) of the swing index, which depends on asset data
  • ad_line returns the accumulation-distribution line of asset data
  • adx returns the average directional (movement) index of asset data
  • adxr returns the average directional (movement) index rating of asset data
  • aroon returns the Aroon indicator of asset data
  • aroon_oscillator returns the Aroon oscillator of asset data
  • average_price returns the average price of asset data
  • average_true_range returns the average true range of asset data
  • bollinger returns the Bollinger bands and width thereof, for asset data
  • chaikin returns the Chaikin money flow of price data
  • chaikin_ad_osc returns the Chaikin accumulation-distribution oscillator of asset data
  • chaikin_volatility returns the Chaikin volatility of asset data
  • chande_momentum_oscillator returns the Chande momentum oscillator of a price input
  • dema returns the "double" exponential moving average of input
  • detrended_price_osc returns the de-trended price oscillator of a price input
  • directional_index returns the directional indices (+DI and -DI) of asset data
  • directional_movt_index returns the directional movement index (based directly on +DI and -DI) of asset data
  • dynamic_momentum_index returns the DSI of price data
  • ease_of_movt returns the ease of movement of asset data
  • exponential_moving_average returns the exponential moving average of input
  • general_stochastic returns the general Stochastic indicator of a price input
  • klinger_osc returns the Klinger oscillator of asset data
  • macd returns the MACD of a price input (same as price oscillator with 26-period slow EMA and 12-period fast EMA)
  • market_fac_index returns the market facilitation index of asset data
  • mass_index returns the mass index of asset data
  • median_price returns the median price of asset data
  • momentum returns the momentum of a price input
  • money_flow_index returns the money flow index of asset data
  • negative_volume_index returns the negative volume index of asset data
  • normalized_price returns the baseline-normalized price (a.k.a. performance indicator) of a price input
  • on_balance_volume returns the on balance volume of asset data
  • parabolic_sar returns the parabolic SAR of asset data
  • percent_volume_oscillator returns the percent volume oscillator of volume data
  • polarized_fractal_efficiency returns the polarized fractal efficiency of asset data
  • positive_volume_index returns the positive volume index of asset data
  • price_channel returns the high and low price channels of a price input
  • price_oscillator returns the price oscillator of a price input, which depends on a choice of moving average function
  • price_rate_of_change returns the price rate of change of a price input
  • price_volume_rank returns the price-volume rank of asset data (with user choice for which price)
  • price_volume_trend returns the price-volume trend of asset data
  • qstick returns the Q-stick indicator of asset data, which depends on a choice of moving average function
  • random_walk_index returns the random walk index of asset data
  • range_indicator returns the range indicator of asset data
  • rel_momentum_index returns the relative momentum index of a price input (typically closing price)
  • rel_strength_index returns the 14-day relative momentum index of a price input
  • rel_vol_index returns the relative volatility index of a price input
  • simple_moving_average returns the simple moving average of input
  • stochastic_momentum_index returns the stochastic momentum index of asset data
  • stochastic_oscillator returns the stochastic oscillator of asset data, which depends on a choice of moving average function
  • stochastic_rsi returns the general stochastic of the RSI (dependent on a price input)
  • swing_index returns the swing index of asset data
  • tee_three and tee_four return T3 and T4, generalizations of DEMA, of input, respectively
  • trend_score returns the trend score of a price input
  • triangular_moving_average returns the triangular moving average of input
  • triple_ema returns the triple exponential moving average of input
  • trix returns the TRIX indicator of a price input
  • true_range returns the true range of asset data
  • true_strength_index returns the true strength index of a price input
  • typical_price returns the typical price of asset data
  • ultimate_oscillator returns the ultimate oscillator of asset data
  • variable_moving_average returns the variable moving average of a price input
  • vertical_horizontal_filter returns the vertical-horizontal filter (VHF) of asset data
  • vol_adj_moving_average returns the volume-adjusted moving average of asset data
  • weighted_close returns the weighted close of asset data
  • weighted_moving_average returns the weighted moving average of a price input
  • williams_ad returns the Williams accumulation-distribution indicator of asset data
  • williams_percent returns the Williams %R indicator of asset data
  • zero_lag_ema returns the "zero-lag" exponential moving average of a price input

machine learning suite

• stats.py
  • adf computes the augmented Dickey-Fuller test for mean reversion properties
  • command prompt options:
    • none (for now!)
• feature_build.py
  • get_features returns a dataframe of features, with one column for each indicator listed above
  • command prompt options:
    • -tickerUniverse: collection of tickers to download (can also be a comma-delimited list of ticker symbols)
    • -baseline: selection of symbol to use as baseline asset/index
    • -startDate: start date of data to process into features
    • -endDate: end date of aforementioned
    • -function: distinguishes between intraday, daily, weekly, etc. downloads
    • -interval specifies what kind of intraday (1min, 15min, etc.)
    • -folderPath: location of folder to write the files
    • -plotOnly: if indicated, plot the heatmaps; otherwise, build from scratch without plots

general simulators

• strategy.py
  • hold_clear builds a simple strategy for buying/selling, holding one's position, and clearing
  • crossover builds a strategy for buying when trend crosses below baseline and selling when trend crosses above (or vice versa)
  • zscore_distance builds a strategy for for buying when trend crosses far below baseline and selling when trend crosses far above (or vice versa), as measured by z-scores
  • command prompt options:
    • none (does not need any)
• portfolio.py
  • asset_ranker ranks a group of assets based on a certain criterion, choosing which ones should be bought long or sold short
  • apply_trades applies any series of trades to any set of symbols, yielding a portfolio simulation
  • command prompt options:
    • none (does not need any)
• performance.py
  • beta calculates asset/portfolio beta
  • sharpe_ratio calculates the Sharpe ratio for a given portfolio
    • proxy for risk-free rate is the 3-month US T-bill
  • treynor_ratio calculates the Treynor ratio for given portfolio
    • proxy for risk-free rate is the 3-month US T-bill
  • returns_valuation values the portfolio (initial value, final value, and return) against a benchmark (such as an index)
  • command prompt options:
    • none (does not need any)

miscellaneous

• command_parser.py
  • get_generic_from_prompts gets any non-tickerverse prompt from a list of command prompts
  • get_tickerverse_from prompts returns a tickerverse and its name, from a list of command prompts
  • command prompt options:
    • none (does not need any)
• io_support.py
  • get_current_symbols looks for stock ticker symbols in the files within directory
  • memory_check verifies if file occupies too much space in RAM
  • merge_chunked inner-joins a small dataframe (left) with a large one (right), the latter being read in chunks
  • write_as_append writes dataframe to file path in append mode
  • command prompt options:
    • none (does not need any)
• bonds.py
  • periodic_compound calculates the bond discounting factor under periodic compounding
  • continuous_compound calculates the bond discounting factor under continuous compounding
  • fixed_rate_bond calculates the initial bond price for zero- and non-zero-coupon fixed-rate bonds
• ticker_universe.py
  • obtain_parse_nasdaq gets the Nasdaq 100 stocks from stockmonitor.com.
  • obtain_parse_wiki gets either the S&P 500 or the Dow 30 stocks from Wikipedia.
  • obtain_parse_mutual_funds gets the top 25 mutual funds from marketwatch.com.
  • obtain_parse_etfs gets the top 100 ETFs from etfdb.com.
  • command prompt options:
    • none (does not need any)
• plotter.py
  • feature_plot plots a file of features as a correlation heatmap
  • candle_plot plots a single asset in candlestick form
  • price_plot plots a single asset against any number of prices, trends, indicators, etc.
  • command prompt options:
    • -symbol: symbol of the asset to plot
    • -folderPath: location of folder to look for files
    • -function: distinguishes between intraday, daily, weekly, etc. downloads
    • -interval specifies what kind of intraday (1min, 15min, etc.)
    • -startDate: start date of data to plot
    • -endDate: end date of aforementioned
    • -column: choice of price or volume to plot
    • -candlestick: choice to use candlestick plot instead of typical plot