tranthetuan / algo-trade

algorithmic trading strategies

algo-trade

algorithmic trading strategies

This is a reimplementation of repository nickmccullum/algorithmic-trading-python in Go

Outline

• Strategy 1: Equal Weight S&P 500 Index Fund

  • The S&P 500 is the world's most popular stock market index. The largest fund that is benchmarked to this index is the SPDR® S&P 500® ETF Trust. It has more than US$250 billion of assets under management.
  • The goal of this section of the course is to create a Python script that will accept the value of your portfolio and tell you how many shares of each S&P 500 constituent you should purchase to get an equal-weight version of the index fund.

• Strategy 2: Quantitative Momentum Strategy

  • "Momentum investing" means investing in the stocks that have increased in price the most - taking into account the price return in 1 year, 6 months, 3 months, 1 months.
  • This strategy selects the 50 stocks with the highest price momentum. From there, we will calculate recommended trades for an equal-weight portfolio of these 50 stocks.

• Strategy 3: Quantitative Value Strategy

  • "Value investing" means investing in the stocks that are cheapest relative to common measures of business value (like earnings or assets)
  • This investing strategy selects the 50 stocks with the best value metrics. From there, we will calculate recommended trades for an equal-weight portfolio of these 50 stocks.