Lots of changes. Modified the Position object to handle more of the actual position calculations instead of the Portfolio. Added more unit tests for both Position and Portfolio. Allowed Positions to trade in currencies other than GBPUSD and in base/quotes which aren't the home currency. Modified the backtester to be single-threaded and added a basic Moving Average Crossover strategy. Also added a basic equity curve output script.
This commit is contained in:
Michael Halls-Moore
+104
-11
@@ -3,6 +3,8 @@ import datetime
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from decimal import Decimal, getcontext, ROUND_HALF_DOWN
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import os
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import os.path
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import time
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import numpy as np
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import pandas as pd
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@@ -59,28 +61,119 @@ class HistoricCSVPriceHandler(PriceHandler):
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self.pairs = pairs
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self.events_queue = events_queue
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self.csv_dir = csv_dir
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self.cur_bid = None
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self.cur_ask = None
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self.prices = self._set_up_prices_dict()
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self.pair_frames = {}
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self._open_convert_csv_files()
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def _set_up_prices_dict(self):
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"""
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Due to the way that the Position object handles P&L
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calculation, it is necessary to include values for not
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only base/quote currencies but also their reciprocals.
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This means that this class will contain keys for, e.g.
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"GBPUSD" and "USDGBP".
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At this stage they are calculated in an ad-hoc manner,
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but a future TODO is to modify the following code to
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be more robust and straightforward to follow.
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"""
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prices_dict = dict(
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(k, v) for k,v in [
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(p, {"bid": None, "ask": None, "time": None}) for p in self.pairs
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]
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)
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inv_prices_dict = dict(
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(k, v) for k,v in [
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(
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"%s%s" % (p[3:], p[:3]),
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{"bid": None, "ask": None, "time": None}
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) for p in self.pairs
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]
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)
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prices_dict.update(inv_prices_dict)
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return prices_dict
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def _open_convert_csv_files(self):
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"""
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Opens the CSV files from the data directory, converting
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them into pandas DataFrames within a pairs dictionary.
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The function then concatenates all of the separate pairs
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for a single day into a single data frame that is time
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ordered, allowing tick data events to be added to the queue
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in a chronological fashion.
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"""
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pair_path = os.path.join(self.csv_dir, '%s.csv' % self.pairs[0])
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self.pair = pd.io.parsers.read_csv(
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pair_path, header=True, index_col=0, parse_dates=True,
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names=("Time", "Ask", "Bid", "AskVolume", "BidVolume")
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).iterrows()
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for p in self.pairs:
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pair_path = os.path.join(self.csv_dir, '%s.csv' % p)
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self.pair_frames[p] = pd.io.parsers.read_csv(
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pair_path, header=True, index_col=0, parse_dates=True,
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names=("Time", "Ask", "Bid", "AskVolume", "BidVolume")
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)
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self.pair_frames[p]["Pair"] = p
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self.all_pairs = pd.concat(self.pair_frames.values()).sort().iterrows()
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def invert_prices(self, row):
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"""
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Simply inverts the prices for a particular currency pair.
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This will turn the bid/ask of "GBPUSD" into bid/ask for
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"USDGBP" and place them in the prices dictionary.
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"""
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pair = row["Pair"]
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bid = row["Bid"]
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ask = row["Ask"]
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inv_pair = "%s%s" % (pair[3:], pair[:3])
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inv_bid = Decimal(str(1.0/bid)).quantize(
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Decimal("0.00001", ROUND_HALF_DOWN)
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)
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inv_ask = Decimal(str(1.0/ask)).quantize(
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Decimal("0.00001", ROUND_HALF_DOWN)
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)
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return inv_pair, inv_bid, inv_ask
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def stream_next_tick(self):
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"""
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The Backtester has now moved over to a single-threaded
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model in order to fully reproduce results on each run.
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This means that the stream_to_queue method is unable to
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be used and a replacement, called stream_next_tick, is
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used instead.
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This method is called by the backtesting function outside
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of this class and places a single tick onto the queue, as
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well as updating the current bid/ask and inverse bid/ask.
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"""
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try:
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index, row = self.all_pairs.next()
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except StopIteration:
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return
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else:
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self.prices[row["Pair"]]["bid"] = Decimal(str(row["Bid"])).quantize(
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Decimal("0.00001", ROUND_HALF_DOWN)
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)
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self.prices[row["Pair"]]["ask"] = Decimal(str(row["Ask"])).quantize(
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Decimal("0.00001", ROUND_HALF_DOWN)
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)
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self.prices[row["Pair"]]["time"] = index
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inv_pair, inv_bid, inv_ask = self.invert_prices(row)
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self.prices[inv_pair]["bid"] = inv_bid
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self.prices[inv_pair]["ask"] = inv_ask
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self.prices[inv_pair]["time"] = index
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tev = TickEvent(row["Pair"], index, row["Bid"], row["Ask"])
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self.events_queue.put(tev)
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def stream_to_queue(self):
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self._open_convert_csv_files()
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for index, row in self.pair:
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self.cur_bid = Decimal(str(row["Bid"])).quantize(
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for index, row in self.all_pairs:
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self.prices[row["Pair"]]["bid"] = Decimal(str(row["Bid"])).quantize(
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Decimal("0.00001", ROUND_HALF_DOWN)
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)
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self.cur_ask = Decimal(str(row["Ask"])).quantize(
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self.prices[row["Pair"]]["ask"] = Decimal(str(row["Ask"])).quantize(
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Decimal("0.00001", ROUND_HALF_DOWN)
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)
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tev = TickEvent(self.pairs[0], index, row["Bid"], row["Ask"])
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self.prices[row["Pair"]]["time"] = index
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inv_pair, inv_bid, inv_ask = self.invert_prices(row)
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self.prices[inv_pair]["bid"] = inv_bid
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self.prices[inv_pair]["ask"] = inv_ask
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self.prices[inv_pair]["time"] = index
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tev = TickEvent(row["Pair"], index, row["Bid"], row["Ask"])
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self.events_queue.put(tev)
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