自訂策略回測績效 -每天用前一天的收盤價下單 1 股 直到沒有資金可以購買 然後用前一天的收盤價賣出 直到可以賣出

import csv

import requests

import math

import pandas as pd # 引用套件並縮寫為 pd

import datetime

import time

import json

import numpy as np

from io import StringIO

import matplotlib.pyplot as plt

import pytz

from sklearn import preprocessing

def getStockPrice(stockName):

p = math.floor(time.time())

period1 = "0" # 2017/06/01

period2 = str(math.floor(time.time()))

url = (

"https://query1.finance.yahoo.com/v7/finance/download/"

+ stockName

+ "?period1="

+ period1

+ "&period2="

+ period2

+ "&interval=1d&events=history"

)

response = requests.get(url)

data = pd.read_csv(StringIO(response.text), index_col="Date")

return data

# print(data.index)

# print(type(data.index))

# 持股策略

# 初期資金 usd 2000

# step 1 每天用前一天的收盤價下單 1 股 直到沒有資金可以購買

# step 2 然後用前一天的收盤價賣出 直到可以賣出

# 然後重複 step 1 , 2

def stockStrategy(stockName, initialFund):

data = getStockPrice(stockName)

cash = initialFund

buyQty = 1

stockWarehouse = 0

theValue = {} # 總淨值

theStockValue = {} # 只計算股票帳面價值

tradeIndex = data.index

oneTimebidValue = {} # 只在期初下單買進 之後就不管了

oneTimebidstockWarehouse = initialFund // data.loc[tradeIndex[0]]["Adj Close"]

oneTimebidCash = (

initialFund - oneTimebidstockWarehouse * data.loc[tradeIndex[0]]["Adj Close"]

)

volum = {}

theDay = 1

Day = 0

for theDay in tradeIndex:

Day += 1

print(type(tradeIndex.size), tradeIndex.size, Day)

if Day >= tradeIndex.size:

break

lastDay = Day - 1

# print(tradeIndex[lastDay])

# print(data.loc[tradeIndex[lastDay]]["Adj Close"])

tradePrice = data.loc[tradeIndex[lastDay]]["Adj Close"]

if cash > tradePrice * buyQty:

if tradePrice < data.loc[tradeIndex[Day]]["Adj Close"]:

cash -= tradePrice * buyQty

stockWarehouse += buyQty

else:

if tradePrice > data.loc[tradeIndex[Day]]["Adj Close"]:

cash += tradePrice * stockWarehouse

stockWarehouse = 0

theValue[tradeIndex[Day]] = (

cash + stockWarehouse * data.loc[tradeIndex[Day]]["Adj Close"]

)

theStockValue[tradeIndex[Day]] = (

stockWarehouse * data.loc[tradeIndex[Day]]["Adj Close"]

)

oneTimebidValue[tradeIndex[Day]] = (

oneTimebidstockWarehouse * data.loc[tradeIndex[Day]]["Adj Close"]

) + oneTimebidCash

volum[tradeIndex[Day]] = data.loc[tradeIndex[Day]]["Volume"]

# print(theValue)

timeLine = list(theValue.keys())

values = list(theValue.values())

# print(timeLine, values)

plt.plot(timeLine, values)

# print(theValue)

timeLine = list(oneTimebidValue.keys())

values = list(oneTimebidValue.values())

# print(timeLine, values)

plt.plot(timeLine, values)

plt.show()

stockName = "V"

initialFund = 2000

stockStrategy(stockName, initialFund)

# us = pytz.timezone("US/Pacific")

# today = datetime.datetime.now(tz=us)

# yesterday = today - datetime.timedelta(days=1)

# yesterday = yesterday.strftime("%Y-%m-%d")

# print(yesterday, type(yesterday))