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Implement first version of manual strategy

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This commit is contained in:
Felix Martin
2020-10-27 19:57:46 -04:00
parent 1798e9569e
commit 4679910374
5 changed files with 56 additions and 112 deletions
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4
strategy_evaluation/BenchmarkStrategy.py
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@@ -25,10 +25,8 @@ class BenchmarkStrategy:
orders["Symbol"] = symbol
orders["Order"] = ""
orders["Shares"] = 0
orders.iloc[0] = [symbol, "BUY", 1000]
orders.iloc[-1] = [symbol, "SELL", 1000]
orders = orders[orders["Shares"] != 0]
orders.iloc[-1] = [symbol, "SELL", -1000]
if self.verbose:
print(type(orders)) # it better be a DataFrame!

56
strategy_evaluation/ManualStrategy.py
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@@ -1,6 +1,7 @@
import datetime as dt
import pandas as pd
import util as ut
import util
import indicators
class ManualStrategy:
@@ -20,7 +21,7 @@ class ManualStrategy:
# example usage of the old backward compatible util function
syms = [symbol]
dates = pd.date_range(sd, ed)
prices_all = ut.get_data(syms, dates) # automatically adds SPY
prices_all = util.get_data(syms, dates) # automatically adds SPY
prices = prices_all[syms] # only portfolio symbols
# prices_SPY = prices_all['SPY'] # only SPY, for comparison later
if self.verbose:
@@ -28,31 +29,60 @@ class ManualStrategy:
# example use with new colname
# automatically adds SPY
volume_all = ut.get_data(syms, dates, colname="Volume")
volume_all = util.get_data(syms, dates, colname="Volume")
volume = volume_all[syms] # only portfolio symbols
# volume_SPY = volume_all['SPY'] # only SPY, for comparison later
if self.verbose:
print(volume)
def macd_strat(self, macd, orders):
def strat(ser):
m = macd.loc[ser.index]
prev_macd, prev_signal = m.iloc[0]
cur_macd, cur_signal = m.iloc[1]
shares = 0
if cur_macd < -1 and prev_macd < prev_signal and cur_macd > cur_signal:
if self.holding == 0:
shares = 1000
elif self.holding == -1000:
shares = 2000
elif cur_macd > 1 and prev_macd > prev_signal and cur_macd < cur_signal:
if self.holding == 0:
shares = -1000
elif self.holding == 1000:
shares = -2000
self.holding += shares
return shares
orders['Shares'] = orders['Shares'].rolling(2).apply(strat)
# this method should use the existing policy and test it against new data
def testPolicy(self, symbol="IBM",
sd=dt.datetime(2009, 1, 1),
ed=dt.datetime(2010, 1, 1),
sv=10000):
dates = pd.date_range(sd, ed)
prices = ut.get_data([symbol], dates) # automatically adds SPY
orders = pd.DataFrame(index=prices.index)
self.holding = 0
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
macd = indicators.macd(df, symbol)
orders = pd.DataFrame(index=df.index)
orders["Symbol"] = symbol
orders["Order"] = ""
orders["Shares"] = 0
self.macd_strat(macd, orders)
# here we build a fake set of trades
orders.iloc[0] = [symbol, "BUY", 1000]
orders.iloc[40] = [symbol, "SELL", 1000]
orders.iloc[41] = [symbol, "BUY", 1000]
orders.iloc[60] = [symbol, "SELL", 2000]
orders.iloc[61] = [symbol, "BUY", 2000]
orders.iloc[-1] = [symbol, "SELL", 1000]
orders = orders[orders["Shares"] != 0]
# orders.iloc[0] = [symbol, "BUY", 1000]
# orders.iloc[40] = [symbol, "SELL", 1000]
# orders.iloc[41] = [symbol, "BUY", 1000]
# orders.iloc[60] = [symbol, "SELL", 2000]
# orders.iloc[61] = [symbol, "BUY", 2000]
# orders.iloc[-1] = [symbol, "SELL", 1000]
# orders = orders[orders["Shares"] != 0]
return orders

105
strategy_evaluation/experiment1.py
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@@ -9,22 +9,6 @@ from BenchmarkStrategy import BenchmarkStrategy
from ManualStrategy import ManualStrategy
def macd_strat(macd):
def strat(x):
print(x)
macd['macd_trigger'] = macd.rolling(2).apply(strat)
# for i, row in macd.iterrows():
# if i == 0:
# continue
# print(row)
# prev_macd, prev_signal, _ = row
# cur_macd, cur_signal, _ = row
# if cur_macd < -.5 and (prev_macd < prev_signal) \
# and (cur_macd > cur_signal):
# macd.iloc[i]['macd_buy_sell'] = 1
def experiment1():
symbol = "JPM"
start_value = 10000
@@ -32,46 +16,33 @@ def experiment1():
ed = dt.datetime(2009, 12, 31)
df = util.get_data([symbol], pd.date_range(sd, ed))
df.drop(columns=["SPY"], inplace=True)
# df = pd.DataFrame(index=df.index)
bs = BenchmarkStrategy()
orders = bs.testPolicy(symbol, sd, ed, start_value)
df["Benchmark"] = marketsim.compute_portvals(orders, start_value)
df["Orders Benchmark"] = orders["Shares"]
ms = ManualStrategy()
orders = ms.testPolicy(symbol, sd, ed, start_value)
df["Manual"] = marketsim.compute_portvals(orders, start_value)
df["Orders Manual"] = orders["Shares"]
# indicators.price_sma(df, symbol, 21)
# sma = indicators.sma(df, symbol, [9, 21])
# rsi = indicators.rsi(df, symbol)
macd = indicators.macd(df, symbol).copy()
# macd_strat(macd)
fig, ax = plt.subplots(2, sharex=True)
fig, ax = plt.subplots(4, sharex=True)
df[symbol].plot(ax=ax[0])
# sma.plot(ax=ax[0])
macd.plot(ax=ax[1])
# macd.iloc[:,0].plot(ax=ax[1])
# rsi.plot(ax=ax[2])
# df[["Benchmark", "Manual"]].plot(ax=ax[3])
macd.plot(ax=ax[3])
df[["Benchmark", "Manual"]].plot(ax=ax[1])
df[["Orders Benchmark", "Orders Manual"]].plot(ax=ax[2])
# XXX: Plot where we buy and sell.
for a in ax: a.grid()
for a in ax:
a.grid()
multi = MultiCursor(fig.canvas, ax, color='r', lw=0.5)
plt.show()
# df.plot(title="results", subplots=True)
#sd = dt.datetime(2008, 1, 1)
#ed = dt.datetime(2009, 12, 31)
#df = get_data([symbol], pd.date_range(sd, ed))
#df.drop(columns=["SPY"], inplace=True)
# df_orig = df.copy()
#df = indicators.normalize(df)
#indicators.price_sma(df, symbol, 21)
#df.plot(title="21 SMA and EMA")
#plt.show()
# plt.savefig('figure_1.png')
# You may use data from other symbols (such as SPY) to inform both your
# Manual Learner and Strategy Learner. The in-sample/development period is
@@ -79,63 +50,5 @@ def experiment1():
# January 1, 2010 to December 31 2011.
class BlittedCursor:
"""
A cross hair cursor using blitting for faster redraw.
"""
def __init__(self, ax):
self.ax = ax
self.background = None
self.horizontal_line = ax.axhline(color='k', lw=0.8, ls='--')
self.vertical_line = ax.axvline(color='k', lw=0.8, ls='--')
# text location in axes coordinates
self.text = ax.text(0.72, 0.9, '', transform=ax.transAxes)
self._creating_background = False
ax.figure.canvas.mpl_connect('draw_event', self.on_draw)
def on_draw(self, event):
self.create_new_background()
def set_cross_hair_visible(self, visible):
need_redraw = self.horizontal_line.get_visible() != visible
self.horizontal_line.set_visible(visible)
self.vertical_line.set_visible(visible)
self.text.set_visible(visible)
return need_redraw
def create_new_background(self):
if self._creating_background:
# discard calls triggered from within this function
return
self._creating_background = True
self.set_cross_hair_visible(False)
self.ax.figure.canvas.draw()
self.background = self.ax.figure.canvas.copy_from_bbox(self.ax.bbox)
self.set_cross_hair_visible(True)
self._creating_background = False
def on_mouse_move(self, event):
if self.background is None:
self.create_new_background()
if not event.inaxes:
need_redraw = self.set_cross_hair_visible(False)
if need_redraw:
self.ax.figure.canvas.restore_region(self.background)
self.ax.figure.canvas.blit(self.ax.bbox)
else:
self.set_cross_hair_visible(True)
# update the line positions
x, y = event.xdata, event.ydata
self.horizontal_line.set_ydata(y)
self.vertical_line.set_xdata(x)
self.text.set_text('x=%1.2f, y=%1.2f' % (x, y))
self.ax.figure.canvas.restore_region(self.background)
self.ax.draw_artist(self.horizontal_line)
self.ax.draw_artist(self.vertical_line)
self.ax.draw_artist(self.text)
self.ax.figure.canvas.blit(self.ax.bbox)
if __name__ == "__main__":
experiment1()

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strategy_evaluation/figure_1.png Normal file
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3
strategy_evaluation/strategy_evaluation.md Normal file
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@@ -0,0 +1,3 @@
# Report
![First strategy based on MACD. Better than just holding](figure_1.png)