• [ML] Daily Portfolio Statistics


    Let's you have $10000, and you inverst 4 stocks. ['SPY', 'IBM', 'XOM', 'GOOG']. The allocation is [0.4, 0.4, 0.1, 0.1] separately.  

    The way to calculate the daily porfolio is

    1. Normalize the price by devide price of first day.
    2. Nored * allocation
    3. * starting value
    4. Sum up each row

    After we can port value, the first thing we can calculate is the daily return.

    The important thing to remember that the first value of daily return is alwasy zero, so we need to remove the first value.

    daily_rets = daily_rets[1:]

    Four statics:

    1. Cumulative return:

      Is a just a measure of how much the value of the portfolio has go up from the beginning to the end.

    cum_ret = (port_val[-1] / port_val[0]) -1

    2. Average daily return:

      The mean value of daily return

    avg_daily_ret = daily_rets.mean()

    3. Standard deviation of odaily return:

    std_daily_ret = daily_rets.std()

    4. Sharp ratio:

      The idea for sharp ratio is to consider our return, or rewards in the context of risk. 

      All else being equal:

        Lower risk is better

        Higher return is better

      Also considers risk free rate of return, nowadays, risk free return is almost 0. (Put menoy into the bank has very low interests)

    Both stocks have similar volatility, so ABC is better due greater returns.

    Here both stocks have similar returns, but XYZ has lower volatility (risk).

     In this case, we actually do not have a clear picture of which stock is better!

    Calculate Shape ratio:

    Risk free value can be replace by:

    1. LIBOR

    2. 3mo T-Bill

    3. 0%

    Because risk free is so small, noramlly we can just drop it when calculate the sharp raito.

    IF we calcualte daily shape ratio: use K = srq(252), monly then srq(12)

  • 相关阅读:
    Unity--截取屏幕任意区域
    IOS 提交审核,遇到Missing Push Notification Entitlement 问题。
    VSync Count 垂直同步
    unity3d 自动保存
    首次发布App,In-App Purchase 无法submit for review 问题的解决方案
    国内银行CNAPS CODE 查询
    苹果开发——App内购以及验证store的收据(二)
    C#
    AJAX
    SQLite连接C#笔记
  • 原文地址:https://www.cnblogs.com/Answer1215/p/8304181.html
Copyright © 2020-2023  润新知