Day33 Python and financial Quantitative Analysis (iii)

Source: Internet
Author: User
Tags stock prices

The third part realizes the simple quantization frame

Framework content:

    • Start time, end time, cash, position data
    • Get Historical data
    • Trading functions
    • Calculate and draw the yield curve
    • Backtesting Main Frame
    • Calculate the indicators
    • User-Pending code: initialization, daily processing function

Part IV online platform and quantitative investment

The content of this section:

    • First simple strategy (understanding the platform)
    • Double moving Average strategy
    • Factor stock selection Strategy
    • Multi-factor stock selection strategy
    • Small market capitalization strategy
    • Turtle Trading Rules
    • Mean reversion strategy
    • Momentum Strategy
    • Reversal Policy
    • Alpaca Trading Rules
    • Peg Strategy
    • Alligator Trading Rules

Joinquant Platform

    • Main framework
      • Initialize
      • Handle_data
      • ......
    • Get Historical data
    • Trading functions
    • Back Test frequency:
      • By day backtesting
      • Back to test by minute
    • Risk indicators

Double moving Average strategy

    • EMA: For each trading day, you can calculate the moving average of the first n days, and then connect the moving averages to become a line, called the N-day moving average.
    • Common lines for moving averages are 5-day, 10-day, 30-day, 60-day, 120-day, and 240-day indicators. 5-day and 10-day is the short-term operation of the reference indicators, known as the daily average line indicator, 30 days and 60 days is the medium-term moving average indicator, called the index of the seasonal average, 120 days, 240 days is the long-term average indicator, called the annual average line indicator.
    • Golden Fork: Long-term moving average on short moving average
    • Dead fork: Long-term EMA under short-term EMA

Factor stock selection Strategy

    • Factor:
      • Standard growth rate, market capitalization, ROE, ...
    • Stock Selection Strategy:
      • Select the maximum (or minimum) number of n stock positions for this factor
    • Multi-Factor stock selection: How to consider multiple factors at the same time?

The theory of Mean value regression

    • Mean reversion: "Sooner or later the fall will rise."
    • The theory of mean reversion is based on the following observations: Price fluctuations are generally centered on its moving average. That is, when the underlying price deviates from the moving average due to fluctuations, it adjusts and is re-attributed to the moving average.
    • Degree of deviation: (ma-p)/ma
    • Strategy: On each warehouse day (once a month)
      • Calculates the N-day moving average of a stock in a pool;
      • Calculates the deviation of all stock prices in the pool from the moving averages;
      • Select the Num_stocks stock with the highest deviation and make a position adjustment.

Bollinger bands Strategy

    • Bollinger Bands/Bollinger bands/Poly Plus channel (Bollinger Band): consists of three track lines, where the upper and lower lines can be regarded as the price of the pressure line and the support line, between the two lines is a price average line.
    • Calculation formula:
      • Median line =20 daily average line
      • Up line =20 daily average +N*SD (20th closing price)
      • Down Line =20 daily average-N*SD (20th closing price)

Peg Strategy

    • Peter Lynch: If the price of any company is reasonable, the P/E ratio will be equal to the rate of return.
    • Earnings per share (EPS)
    • Share price (P)
    • P/E (PE) = P/eps
    • Revenue Growth (G) = (epsi–epsi-1)/EPSi-1
    • PEG = pe/g/100
    • The lower the peg, the more likely it is to be undervalued, and the more likely it is to rise.
    • Peg is a comprehensive index, both to examine the value and to take into account the growth. Peg valuation method is suitable for growing companies.
    • Note: Filter out the price-earnings ratio or earnings growth is negative situation

Alpaca Trading Rules

    • At the beginning of the random buy n stocks, sell the lowest yield m per day, and then randomly buy the remaining stock pool of M.

Turtle Trading Rules

    • Donchian Channel:
      • Online =max (highest price for the first n trading days)
      • Downline =min (lowest price for the first n trading days)
      • midline = (on line + downline)/2

Minute backtesting

    • Market entry: If the current price is higher than the previous high of 20th, buy a unit
    • Added: If the stock price increases by 0.5N on the basis of the last buy (or increase), a unit
    • Take profit: Empty the position when the stock price falls below the lowest price within 10th (Donchian Channel, 10th)
    • Stop loss: Sell all position stop loss (no more than 2%) when the price falls 2N from the last buy price

Day33 Python and financial Quantitative Analysis (iii)

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