def profile():
"""Access the user's profile and stats"""
if "user" in session:
user = session["user"]
geo_data = get_data()
event_data = generate_buzz()
return render_template('profile.html', title="My Profile | BestApp", username=user,
geo_data=geo_data, event_data=event_data)
else:
return redirect(url_for('login'))
def question4():
q = """
4.
The event is defined as when the actual close of the stock price drops below $9.00, more specifically, when:
price[t-1]>=9.0 and price[t]<9.0 an event has occurred on date t.
* Test this event using the Event Profiler over the period from 1st Jan, 2008 to 31st Dec 2009.
* Using the symbol list - SP5002012
* Starting Cash: $50,000
* At every event Buy 100 shares of the equity, and Sell them 5 trading days later. In case not enough days are available Sell them on the last trading day. (Similar to what the homework 4 description wanted).
* Run this in your simulator and analyze the results.
What is the sharpe ratio of the fund ?
* 1.0 to 1.1
* 0.9 to 1.0
* 0.8 to 0.9
* 0.7 to 0.8
"""
dt_start = dt.datetime(2008, 1, 1)
dt_end = dt.datetime(2009, 12, 31)
cash = 50000
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt.timedelta(hours=16))
dataobj = da.DataAccess('Yahoo')
ls_keys = ['open', 'high', 'low', 'close', 'volume', 'actual_close']
ls_2012_symbols = ev.get_symbols_in_year(dataobj, 2012)
d_2012_data = ev.get_data(dataobj, ldt_timestamps, ls_2012_symbols)
order_file = 'orders.csv'
analysis_file = 'values_9_dollar_event.csv'
benchmark_symbol = '$SPX'
df_events = ev.find_9_dollar_events(ls_2012_symbols, d_2012_data)
ev.generate_orders(ls_2012_symbols, df_events, order_file)
simulation_result = mksim.simulate(cash, order_file)
mksim.write_simulation_result(simulation_result, analysis_file)
fund, benchmark = an.analyze(analysis_file, benchmark_symbol)
return q, fund.sharpe