Aegis

Multi-dimensional asset valuation engine for capital market securities.

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What is Aegis?

Aegis is an open source asset valuation engine that uses many dimensions to create a price profile for an asset. A dimension is a general category of evaluation. This evaluation may or may not be a valuation as it could just relate to a general fact/figure such as employment statistics.

Dimensions are further broken down into components. For example "charts" is a dimension which is comprised of components: technical indicators, trading psychology, boundaries, and patterns.

In terms of package hierarchy: Aegis > Dimension > Component > Class > Function

E.g. Aegis > Equity > Risk > Risk > Sharpe()

Dimensions exist as sub-packages within the Aegis package and can/should be combined by the developer with various other dimensions/components to create hollistic asset valuation. The dimensions and their components are broken down as follows:

• Charts (incomplete)
  • Bounds (e.g. all_time_high, all_time_low))
  • Indicators (e.g. RSI, OBV, SMA)
  • Shapes (e.g. square_consolidating, head_and_shoulders)
  • Trend (e.g. strength, forecast)
• Debt
  • Utilities
• Equity
  • Accounting (e.g. asset_composition, liquidity)
  • Growth (e.g. plowback, roe, growth)
  • Risk (e.g. beta, cost_of_capital, wacc)
  • Statistics (e.g. var, covariance, correlation)
  • Valuation (e.g. div_yield, ddm, fixed_div, gordons, PVGO)
• Macroeconomic (incomplete)
  • GDP (e.g. GDP, gov_consum, investment)
  • Labour (e.g. employment, unemployment, labour_force)
  • Price (e.g. cpi, ppi)
  • Trade
• Rates (incomplete)
• Sentiment (incomplete)

These dimensions and their relevant components allow Aegis to evaluate most assets not only according to their accounting book value, but also in accordance with the market, similar-risk products, macro conditions, and more.

Getting Started

Aegis uses common data science libraries such as pandas for most of its needs.

Installation

1. To get started with aegis:

pip install git+ttps://github.com/itchysnake/aegis

If this is giving you errors you can alternatively try:

python -m pip install git+ttps://github.com/itchysnake/aegis

2. Check your installation directory

Usage

Once installed you can get started by calling the package:

import aegis

# Using 'charts' dimension
amzn_ath = aegis.charts.bounds.Bounds.ath("AMZN","6mo")
nflx_rsi = aegis.charts.indicators.Indicators.rsi(
    ticker = "NFLX", 
    period =" 6mo",
    window = 14
)

# Using 'equity' dimension
aapl_roe = aegis.equity.growth.Growth.roe("AAPL")
msft_risk = aegis.equity.risk.Risk.sharpe("MSFT")

# Using 'macro' dimension
spain_labour = aegis.macro.labour.Labour.unemployment("Spain")
jpn_gdp = aegis.macro.gdp.GDP.gdp("Japan", type = "real")

Feel free to experiment and combine indicators to create valuable insights into the markets.

Data Procurement

Data procurement is not included in Aegis natively. I am currently building a package to integrate Aegis with the existing Alpaca Markets API. At this time you must use whatever is comfortable for you.

License

Aegis is released under the MIT License.