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January 2, 2020 22:22
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| import pandas as pd | |
| import numpy as np | |
| import datetime as dt | |
| import math | |
| import warnings | |
| warnings.filterwarnings("ignore") | |
| prices = pd.read_csv("adjclose.csv", index_col="Date", parse_dates=True) | |
| volumechanges = pd.read_csv("volume.csv", index_col="Date", parse_dates=True).pct_change()*100 | |
| today = dt.date(2000, 1, 15) | |
| simend = dt.date(2019, 12, 31) | |
| tickers = [] | |
| transactionid = 0 | |
| money = 1000000 | |
| portfolio = {} | |
| activelog = [] | |
| transactionlog = [] | |
| def getprice(date, ticker): | |
| global prices | |
| return prices.loc[date][ticker] | |
| def transaction(id, ticker, amount, price, type, info): | |
| global transactionid | |
| if type == "buy": | |
| exp_date = today + dt.timedelta(days=14) | |
| transactionid += 1 | |
| else: | |
| exp_date = today | |
| if type == "sell": | |
| data = {"id": id, "ticker": ticker, "amount": amount, "price": price, "date": today, "type": type, | |
| "exp_date": exp_date, "info": info} | |
| elif type == "buy": | |
| data = {"id": transactionid, "ticker": ticker, "amount": amount, "price": price, "date": today, "type": type, | |
| "exp_date": exp_date, "info": info} | |
| activelog.append(data) | |
| transactionlog.append(data) | |
| def buy(interestlst, allocated_money): | |
| global money, portfolio | |
| for item in interestlst: | |
| price = getprice(today, item) | |
| if not np.isnan(price): | |
| quantity = math.floor(allocated_money/price) | |
| money -= quantity*price | |
| portfolio[item] += quantity | |
| transaction(0, item, quantity, price, "buy", "") | |
| def sell(): | |
| global money, portfolio, prices, today | |
| itemstoremove = [] | |
| for i in range(len(activelog)): | |
| log = activelog[i] | |
| if log["exp_date"] <= today and log["type"] == "buy": | |
| tickprice = getprice(today, log["ticker"]) | |
| if not np.isnan(tickprice): | |
| money += log["amount"]*tickprice | |
| portfolio[log["ticker"]] -= log["amount"] | |
| transaction(log["id"], log["ticker"], log["amount"], tickprice, "sell", log["info"]) | |
| itemstoremove.append(i) | |
| else: | |
| log["exp_date"] += dt.timedelta(days=1) | |
| itemstoremove.reverse() | |
| for elem in itemstoremove: | |
| activelog.remove(activelog[elem]) | |
| def simulation(): | |
| global today, volumechanges, money | |
| start_date = today - dt.timedelta(days=14) | |
| series = volumechanges.loc[start_date:today].mean() | |
| interestlst = series[series > 100].index.tolist() | |
| sell() | |
| if len(interestlst) > 0: | |
| #moneyToAllocate = 500000/len(interestlst) | |
| moneyToAllocate = currentvalue()/(2*len(interestlst)) | |
| buy(interestlst, moneyToAllocate) | |
| def getindices(): | |
| global tickers | |
| f = open("symbols.txt", "r") | |
| for line in f: | |
| tickers.append(line.strip()) | |
| f.close() | |
| def tradingday(): | |
| global prices, today | |
| return np.datetime64(today) in list(prices.index.values) | |
| def currentvalue(): | |
| global money, portfolio, today, prices | |
| value = money | |
| for ticker in tickers: | |
| tickprice = getprice(today, ticker) | |
| if not np.isnan(tickprice): | |
| value += portfolio[ticker]*tickprice | |
| return int(value*100)/100 | |
| def main(): | |
| global today | |
| getindices() | |
| for ticker in tickers: | |
| portfolio[ticker] = 0 | |
| while today < simend: | |
| while not tradingday(): | |
| today += dt.timedelta(days=1) | |
| simulation() | |
| currentpvalue = currentvalue() | |
| print(currentpvalue, today) | |
| today += dt.timedelta(days=7) | |
| main() |
Hi,
how to get adjclose.csv and volume.csv? is there any place to download or should we scrap?
BTW, Mark discusses how to get the files, but here is a short version...
- download the symbols.txt file from his git hub.
- Run this code to generate the files...
import pandas_datareader as web
stocks=[]
f = open("symbols.txt","r")
for line in f:
stocks.append(line.strip())
f.close()
web.DataReader(stocks,"yahoo",start="2000-1-1",end="2019-12-31")["Adj Close"].to_csv("prices.csv")
web.DataReader(stocks,"yahoo",start="2000-1-1",end="2019-12-31")["Volume"].to_csv("volume.csv")
Hi. I tried to run the main () function but instead got this syntax.
line 124, in main
portfolio[ticker] = 0
TypeError: list indices must be integers or slices, not str
The main() function is written exactly the same, and getindices() is almost the same except for the fact that I assigned a specific file path in f = open('xxx/symbols.txt', r).
Anyone knows how to solve this?
doesnt work sadly
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Hi,
how to get adjclose.csv and volume.csv? is there any place to download or should we scrap?