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Parse orders and extract information (start/end date and symbols)

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Felix Martin 2020-10-08 21:28:12 -04:00
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commit 117d97b8e9
1 changed files with 126 additions and 91 deletions
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marketsim/marketsim.py
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"""MC2-P1: Market simulator. """MC2-P1: Market simulator.
Copyright 2018, Georgia Institute of Technology (Georgia Tech) Copyright 2018, Georgia Institute of Technology (Georgia Tech)
Atlanta, Georgia 30332 Atlanta, Georgia 30332
All Rights Reserved All Rights Reserved
Template code for CS 4646/7646 Template code for CS 4646/7646
Georgia Tech asserts copyright ownership of this template and all derivative Georgia Tech asserts copyright ownership of this template and all derivative
works, including solutions to the projects assigned in this course. Students works, including solutions to the projects assigned in this course. Students
and other users of this template code are advised not to share it with others and other users of this template code are advised not to share it with others
or to make it available on publicly viewable websites including repositories or to make it available on publicly viewable websites including repositories
such as github and gitlab. This copyright statement should not be removed such as github and gitlab. This copyright statement should not be removed
or edited. or edited.
We do grant permission to share solutions privately with non-students such We do grant permission to share solutions privately with non-students such
as potential employers. However, sharing with other current or future as potential employers. However, sharing with other current or future
students of CS 7646 is prohibited and subject to being investigated as a students of CS 7646 is prohibited and subject to being investigated as a
GT honor code violation. GT honor code violation.
-----do not edit anything above this line--- -----do not edit anything above this line---
Student Name: Tucker Balch (replace with your name) Student Name: Tucker Balch (replace with your name)
GT User ID: tb34 (replace with your User ID) GT User ID: felixm (replace with your User ID)
GT ID: 900897987 (replace with your GT ID) GT ID: 1337 (replace with your GT ID)
""" """
import pandas as pd import pandas as pd
import numpy as np import numpy as np
import datetime as dt import datetime as dt
import os import os
from util import get_data, plot_data from util import get_data, plot_data
from optimize_something.optimization import calculate_stats
def compute_portvals(orders_file = "./orders/orders.csv", start_val = 1000000, commission=9.95, impact=0.005):
# this is the function the autograder will call to test your code def read_orders(orders_file):
# NOTE: orders_file may be a string, or it may be a file object. Your """
# code should work correctly with either input Parser orders into the form:
# TODO: Your code here
Date datetime64[ns]
# In the template, instead of computing the value of the portfolio, we just Symbol object
# read in the value of IBM over 6 months Order object
start_date = dt.datetime(2008,1,1) Shares int32
end_date = dt.datetime(2008,6,1)
portvals = get_data(['IBM'], pd.date_range(start_date, end_date)) This is how the order book looks like:
portvals = portvals[['IBM']] # remove SPY
rv = pd.DataFrame(index=portvals.index, data=portvals.values) Date,Symbol,Order,Shares
2011-01-10,AAPL,BUY,1500
return rv 2011-01-10,AAPL,SELL,1500
return portvals """
orders = pd.read_csv(orders_file,
def test_code(): dtype='|str, str, str, i4',
# this is a helper function you can use to test your code parse_dates=["Date"])
# note that during autograding his function will not be called. orders.sort_values(by="Date", inplace=True)
# Define input parameters return orders
of = "./orders/orders2.csv"
sv = 1000000 def get_order_book_info(orders):
"""Return start_date, end_date, and symbols (as a list)."""
# Process orders start_date = orders.iloc[0].Date
portvals = compute_portvals(orders_file = of, start_val = sv) end_date = orders.iloc[0].Date
if isinstance(portvals, pd.DataFrame): symbols = sorted(list((set(orders.Symbol.tolist()))))
portvals = portvals[portvals.columns[0]] # just get the first column return start_date, end_date, symbols
else:
"warning, code did not return a DataFrame"
def compute_portvals(orders_file="./orders/orders-01.csv", start_val=1000000, commission=9.95, impact=0.005):
# Get portfolio stats orders = read_orders(orders_file)
# Here we just fake the data. you should use your code from previous assignments. start_date, end_date, symbols = get_order_book_info(orders)
start_date = dt.datetime(2008,1,1)
end_date = dt.datetime(2008,6,1) # In the template, instead of computing the value of the portfolio, we just
cum_ret, avg_daily_ret, std_daily_ret, sharpe_ratio = [0.2,0.01,0.02,1.5] # read in the value of IBM over 6 months
cum_ret_SPY, avg_daily_ret_SPY, std_daily_ret_SPY, sharpe_ratio_SPY = [0.2,0.01,0.02,1.5] start_date = dt.datetime(2008, 1, 1)
end_date = dt.datetime(2008, 6, 1)
# Compare portfolio against $SPX portvals = get_data(['IBM'], pd.date_range(start_date, end_date))
print(f"Date Range: {start_date} to {end_date}") portvals = portvals[['IBM']] # remove SPY
print()
print(f"Sharpe Ratio of Fund: {sharpe_ratio}") return portvals
print(f"Sharpe Ratio of SPY : {sharpe_ratio_SPY}") # Don't know why this was in template. Keep for now.
print() # rv = pd.DataFrame(index=portvals.index, data=portvals.values)
print(f"Cumulative Return of Fund: {cum_ret}") # return rv
print(f"Cumulative Return of SPY : {cum_ret_SPY}")
print()
print(f"Standard Deviation of Fund: {std_daily_ret}") def test_code():
print(f"Standard Deviation of SPY : {std_daily_ret_SPY}") of = "./orders/orders-02.csv"
print() sv = 1000000
print(f"Average Daily Return of Fund: {avg_daily_ret}")
print(f"Average Daily Return of SPY : {avg_daily_ret_SPY}") portvals = compute_portvals(orders_file=of, start_val=sv)
print() if isinstance(portvals, pd.DataFrame):
print(f"Final Portfolio Value: {portvals[-1]}") portvals = portvals[portvals.columns[0]] # just get the first column
else:
if __name__ == "__main__": raise Exception("warning, code did not return a DataFrame")
test_code()
# One way of getting the portfolio dates
# print(portvals.index[0])
# Get portfolio stats.
start_date = dt.datetime(2008, 1, 1)
end_date = dt.datetime(2008, 6, 1)
cum_ret, avg_daily_ret, \
std_daily_ret, sharpe_ratio = calculate_stats(portvals.to_frame(), [1])
spy = get_data(['SPY'], pd.date_range(start_date, end_date))
cum_ret_SPY, avg_daily_ret_SPY, \
std_daily_ret_SPY, sharpe_ratio_SPY = calculate_stats(spy, [1])
# Compare portfolio against $SPY
print(f"Date Range: {start_date} to {end_date}")
print()
print(f"Sharpe Ratio of Fund: {sharpe_ratio}")
print(f"Sharpe Ratio of SPY : {sharpe_ratio_SPY}")
print()
print(f"Cumulative Return of Fund: {cum_ret}")
print(f"Cumulative Return of SPY : {cum_ret_SPY}")
print()
print(f"Standard Deviation of Fund: {std_daily_ret}")
print(f"Standard Deviation of SPY : {std_daily_ret_SPY}")
print()
print(f"Average Daily Return of Fund: {avg_daily_ret}")
print(f"Average Daily Return of SPY : {avg_daily_ret_SPY}")
print()
print(f"Final Portfolio Value: {portvals[-1]}")
if __name__ == "__main__":
test_code()