First working version with the backtest and live modes executing the same algorithm.

catalyst/examples/buy_low_sell_high_neo_with_interface.py

@@ -33,24 +33,25 @@ def initialize(context):
 
 
 def _handle_data(context, data):
-    prices = data.history(
-        context.asset,
-        fields='price',
-        bar_count=20,
-        frequency='30m'
-    )
-    rsi = talib.RSI(prices.values, timeperiod=14)[-1]
-    log.info('got rsi: {}'.format(rsi))
+    # prices = data.history(
+    #     context.asset,
+    #     fields='price',
+    #     bar_count=20,
+    #     frequency='30m'
+    # )
+    # rsi = talib.RSI(prices.values, timeperiod=14)[-1]
+    # log.info('got rsi: {}'.format(rsi))
 
     # Buying more when RSI is low, this should lower our cost basis
-    if rsi <= 30:
-        buy_increment = 1
-    elif rsi <= 40:
-        buy_increment = 0.5
-    elif rsi <= 70:
-        buy_increment = 0.1
-    else:
-        buy_increment = None
+    # if rsi <= 30:
+    #     buy_increment = 1
+    # elif rsi <= 40:
+    #     buy_increment = 0.5
+    # elif rsi <= 70:
+    #     buy_increment = 0.1
+    # else:
+    #     buy_increment = None
+    buy_increment = 0.1
 
     cash = context.portfolio.cash
     log.info('base currency available: {cash}'.format(cash=cash))
@@ -62,10 +63,10 @@ def _handle_data(context, data):
         log.warn('no pricing data')
         return
 
-    record(price=price, rsi=rsi)
+    record(price=price)
 
     orders = get_open_orders(context.asset)
-    if orders:
+    if len(orders) > 0:
         log.info('skipping bar until all open orders execute')
         return
 
@@ -104,7 +105,6 @@ def _handle_data(context, data):
 
     if is_buy:
         if buy_increment is None:
-            log.info('the rsi is too high to consider buying {}'.format(rsi))
             return
 
         if price * buy_increment > cash:
@@ -117,11 +117,13 @@ def _handle_data(context, data):
                 cost_basis
             )
         )
+        limit_price = price * (1 + context.SLIPPAGE_ALLOWED)
         order(
             asset=context.asset,
             amount=buy_increment,
-            limit_price=price * (1 + context.SLIPPAGE_ALLOWED)
+            limit_price=limit_price
         )
+        pass
 
 
 def handle_data(context, data):

catalyst/exchange/bitfinex/bitfinex.py

@@ -448,7 +448,7 @@ class Bitfinex(Exchange):
                     order_statuses['message'])
             )
 
-        orders = list()
+        orders = []
         for order_status in order_statuses:
             order, executed_price = self._create_order(order_status)
             if asset is None or asset == order.sid:

catalyst/exchange/data_portal_exchange.py

@@ -15,13 +15,12 @@ import abc
 import os
 from time import sleep
 
-import collections
 import pandas as pd
 from catalyst.assets._assets import TradingPair
 from logbook import Logger
 
-from catalyst.data.bundles.core import load, from_bundle_ingest_dirname, \
-    BundleData, minute_path, five_minute_path, daily_path
+from catalyst.data.bundles.core import from_bundle_ingest_dirname, \
+    minute_path, five_minute_path, daily_path
 from catalyst.data.data_portal import DataPortal
 from catalyst.data.five_minute_bars import BcolzFiveMinuteBarReader
 from catalyst.data.minute_bars import BcolzMinuteBarReader
@@ -200,6 +199,9 @@ class DataPortalExchangeBase(DataPortal):
                 )
 
     def get_spot_value(self, assets, field, dt, data_frequency):
+        if field == 'price':
+            field = 'close'
+
         return self._get_spot_value(assets, field, dt, data_frequency)
 
     @abc.abstractmethod
@@ -263,20 +265,29 @@ class DataPortalExchangeBacktest(DataPortalExchangeBase):
             if time_folder is None:
                 raise BundleNotFoundError(exchange=exchange_name)
 
-            self.daily_bar_readers[exchange_name] = \
-                BcolzDailyBarReader(
-                    daily_path(name, time_folder),
-                )
+            try:
+                self.daily_bar_readers[exchange_name] = \
+                    BcolzDailyBarReader(
+                        daily_path(name, time_folder),
+                    )
+            except IOError:
+                self.daily_bar_readers[exchange_name] = None
 
-            self.five_minute_bar_readers[exchange_name] = \
-                BcolzFiveMinuteBarReader(
-                    five_minute_path(name, time_folder),
-                )
+            try:
+                self.five_minute_bar_readers[exchange_name] = \
+                    BcolzFiveMinuteBarReader(
+                        five_minute_path(name, time_folder),
+                    )
+            except IOError:
+                self.five_minute_bar_readers[exchange_name] = None
 
-            self.minute_bar_readers[exchange_name] = \
-                BcolzMinuteBarReader(
-                    minute_path(name, time_folder),
-                )
+            try:
+                self.minute_bar_readers[exchange_name] = \
+                    BcolzMinuteBarReader(
+                        minute_path(name, time_folder),
+                    )
+            except IOError:
+                self.minute_bar_readers[exchange_name] = None
 
     @staticmethod
     def find_most_recent_time(bundle_name):
@@ -309,6 +320,7 @@ class DataPortalExchangeBacktest(DataPortalExchangeBase):
                                     field,
                                     data_frequency,
                                     ffill=True):
+        # TODO: implement in the bundle
         df = exchange.get_history_window(
             assets,
             end_dt,

catalyst/exchange/exchange_algorithm.py

@@ -35,12 +35,15 @@ from catalyst.exchange.exchange_errors import (
     ExchangePortfolioDataError,
     ExchangeTransactionError,
     OrphanOrderError)
+from catalyst.exchange.exchange_execution import ExchangeStopLimitOrder, \
+    ExchangeLimitOrder, ExchangeStopOrder
 from catalyst.exchange.exchange_utils import get_exchange_minute_writer_root, \
     save_algo_object, get_algo_object, get_algo_folder, get_algo_df, \
     save_algo_df
 from catalyst.exchange.live_graph_clock import LiveGraphClock
 from catalyst.exchange.simple_clock import SimpleClock
 from catalyst.exchange.stats_utils import get_pretty_stats
+from catalyst.finance.execution import MarketOrder
 from catalyst.finance.performance.period import calc_period_stats
 from catalyst.gens.tradesimulation import AlgorithmSimulator
 from catalyst.utils.api_support import (
@@ -198,6 +201,43 @@ class ExchangeTradingAlgorithmBacktest(ExchangeTradingAlgorithmBase):
         )
         log.info('initialized trading algorithm in backtest mode')
 
+    def _calculate_order(self, asset, amount,
+                         limit_price=None, stop_price=None, style=None):
+        # Raises a ZiplineError if invalid parameters are detected.
+        self.validate_order_params(asset,
+                                   amount,
+                                   limit_price,
+                                   stop_price,
+                                   style)
+
+        # Convert deprecated limit_price and stop_price parameters to use
+        # ExecutionStyle objects.
+        style = self.__convert_order_params_for_blotter(limit_price,
+                                                        stop_price,
+                                                        style)
+        return amount, style
+
+    @staticmethod
+    def __convert_order_params_for_blotter(limit_price, stop_price, style):
+        """
+        Helper method for converting deprecated limit_price and stop_price
+        arguments into ExecutionStyle instances.
+
+        This function assumes that either style == None or (limit_price,
+        stop_price) == (None, None).
+        """
+        if style:
+            assert (limit_price, stop_price) == (None, None)
+            return style
+        if limit_price and stop_price:
+            return ExchangeStopLimitOrder(limit_price, stop_price)
+        if limit_price:
+            return ExchangeLimitOrder(limit_price)
+        if stop_price:
+            return ExchangeStopOrder(stop_price)
+        else:
+            return MarketOrder()
+
 
 class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
     def __init__(self, *args, **kwargs):

catalyst/exchange/exchange_blotter.py

@@ -1,8 +1,141 @@
+from logbook import Logger
+
 from catalyst.finance.blotter import Blotter
-from catalyst.finance.commission import PerShare
-from catalyst.finance.slippage import VolumeShareSlippage
+from catalyst.finance.commission import PerShare, CommissionModel
+from catalyst.finance.slippage import VolumeShareSlippage, SlippageModel, \
+    LiquidityExceeded
 from catalyst.assets._assets import TradingPair
 
+# It seems like we need to accept greate slippage risk in cryptos
+# Orders won't often close at Equity levels.
+# TODO: consider adjusting dynamically based on trading pair
+from catalyst.finance.transaction import Transaction
+
+log = Logger('exchange_blotter')
+
+DEFAULT_SLIPPAGE_SPREAD = 0.02
+DEFAULT_MAKER_FEE = 0.001
+DEFAULT_TAKER_FEE = 0.002
+
+
+class TradingPairFeeSchedule(CommissionModel):
+    """
+    Calculates a commission for a transaction based on a per percentage fee.
+
+    Parameters
+    ----------
+    fee : float, optional
+        The percentage fee.
+    """
+
+    def __init__(self,
+                 maker_fee=DEFAULT_MAKER_FEE,
+                 taker_fee=DEFAULT_TAKER_FEE):
+        self.maker_fee = maker_fee
+        self.taker_fee = taker_fee
+
+    def __repr__(self):
+        return (
+            '{class_name}(maker_fee={maker_fee}, '
+            'taker_fee={taker_fee})'
+                .format(
+                class_name=self.__class__.__name__,
+                maker_fee=self.maker_fee,
+                taker_fee=self.taker_fee,
+            )
+        )
+
+    def calculate(self, order, transaction):
+        """
+        Calculate the final fee based on the order parameters.
+
+        :param order:
+        :param transaction:
+
+        :return float:
+            The total commission.
+        """
+        cost = abs(transaction.amount) * transaction.price
+
+        # Assuming just the taker fee for now
+        fee = cost * self.taker_fee
+        return fee
+
+
+class TradingPairFixedSlippage(SlippageModel):
+    """
+    Model slippage as a fixed spread.
+
+    Parameters
+    ----------
+    spread : float, optional
+        spread / 2 will be added to buys and subtracted from sells.
+    """
+
+    def __init__(self, spread=DEFAULT_SLIPPAGE_SPREAD):
+        super(TradingPairFixedSlippage, self).__init__()
+        self.spread = spread
+
+    def __repr__(self):
+        return '{class_name}(spread={spread})'.format(
+            class_name=self.__class__.__name__, spread=self.spread,
+        )
+
+    def simulate(self, data, asset, orders_for_asset):
+        self._volume_for_bar = 0
+        volume = data.current(asset, "volume")
+
+        if volume == 0:
+            return
+
+        # can use the close price, since we verified there's volume in this
+        # bar.
+        price = data.current(asset, "close")
+        dt = data.current_dt
+
+        for order in orders_for_asset:
+            if order.open_amount == 0:
+                continue
+
+            order.check_triggers(price, dt)
+            if not order.triggered:
+                continue
+
+            transaction = None
+            try:
+                execution_price, execution_volume = \
+                    self.process_order(data, order)
+
+                if execution_price is not None:
+                    transaction = Transaction(
+                        asset=order.asset,
+                        amount=abs(execution_volume),
+                        dt=data.current_dt,
+                        price=execution_price,
+                        order_id=order.id
+                    )
+
+            except LiquidityExceeded:
+                break
+
+            if transaction:
+                self._volume_for_bar += abs(transaction.amount)
+                yield order, transaction
+
+    def process_order(self, data, order):
+        price = data.current(order.asset, 'close')
+
+        if order.amount > 0:
+            # Buy order
+            adj_price = price * (1 + self.spread)
+        else:
+            # Sell order
+            adj_price = price & (1 - self.spread)
+
+        log.debug('added slippage to price: {} => {}'.format(price, adj_price))
+
+        return (adj_price, order.amount)
+
 
 class ExchangeBlotter(Blotter):
     def __init__(self, *args, **kwargs):
@@ -12,8 +145,8 @@ class ExchangeBlotter(Blotter):
         # We may be able to define more sophisticated models based on the fee
         # structure of each exchange.
         self.slippage_models = {
-            TradingPair: VolumeShareSlippage()
+            TradingPair: TradingPairFixedSlippage()
         }
         self.commission_models = {
-            TradingPair: PerShare()
+            TradingPair: TradingPairFeeSchedule()
         }

catalyst/exchange/exchange_bundle.py

@@ -64,6 +64,7 @@ def process_bar_data(exchange, assets, writer, data_frequency,
                      show_progress, start, end):
     open_calendar = get_calendar('OPEN')
 
+    writer.default_ohlc_ratio = 1000000
     writer.calendar = open_calendar
     writer.minutes_per_day = 1440
     writer.write_metadata = True

tests/exchange/test_bundle.py

@@ -16,12 +16,12 @@ class ExchangeBundleTestCase:
     def test_ingest(self):
         exchange_name = 'bitfinex'
 
-        start = pd.Timestamp.utcnow() - timedelta(days=365)
+        start = pd.to_datetime('2017-09-01', utc=True)
         end = pd.Timestamp.utcnow()
         open_calendar = get_calendar('OPEN')
 
         root = data_root(os.environ)
-        output_dir = '{root}/exchange_{exchange}/test'.format(
+        output_dir = '{root}/exchange_{exchange}/2017-09-21T05;34;37.274482'.format(
             root=root,
             exchange=exchange_name
         )
@@ -40,7 +40,8 @@ class ExchangeBundleTestCase:
                 minutes_per_day=1440,
                 start_session=start_session,
                 end_session=end,
-                write_metadata=True
+                write_metadata=True,
+                default_ohlc_ratio=1000000
             )
 
         ingest = exchange_bundle(