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