diff --git a/asset_backtester/__init__.py b/asset_backtester/__init__.py
new file mode 100644
index 0000000..216e997
--- /dev/null
+++ b/asset_backtester/__init__.py
@@ -0,0 +1,2 @@
+from backtester import Backtest
+from signal import Signal, get_order
\ No newline at end of file
diff --git a/asset_backtester/backtester.py b/asset_backtester/backtester.py
new file mode 100644
index 0000000..e4c4fcd
--- /dev/null
+++ b/asset_backtester/backtester.py
@@ -0,0 +1,119 @@
+import pandas as pd
+import numpy as np
+import pyprind
+
+from strategy.strategy import Strategy
+
+
+class Backtest:
+ """Processes signals from the Strategy object"""
+ def __init__(self, schema):
+ self.schema = schema
+ self._strategy = None
+ self._data = None
+
+ @property
+ def strategy(self):
+ return self._strategy
+
+ @strategy.setter
+ def strategy(self, strat):
+ assert isinstance(strat, Strategy)
+ self._strategy = strat
+
+ @property
+ def data(self):
+ return self._data
+
+ @data.setter
+ def data(self, data):
+ self._data = data
+
+ def run(self, initial_capital=1_000_000):
+ assert self._data is not None
+ assert self._strategy is not None
+
+ self.current_capital = 0
+ self.current_cash = initial_capital
+
+ self.inventory = pd.DataFrame(columns=['symbol', 'cost', 'qty'])
+ self.balance = pd.DataFrame()
+
+ data_iterator = self._data.iter_dates()
+ monthly_iterator = self._data.iter_months()
+
+ rebalancing_days = []
+ for date, _ in monthly_iterator:
+ rebalancing_days.append(date)
+
+ bar = pyprind.ProgBar(data_iterator.ngroups, bar_char='█')
+
+ self.balance = pd.DataFrame(
+ {
+ 'capital': self.current_cash,
+ 'cash': self.current_cash
+ },
+ index=[self.data.start_date - pd.Timedelta(1, unit='day')])
+
+ for date, stocks in data_iterator:
+
+ if date in rebalancing_days:
+ self.rebalance_portfolio(stocks)
+
+ self._update_balance(date, stocks)
+
+ bar.update()
+
+ self.balance['% change'] = self.balance['capital'].pct_change()
+ self.balance['accumulated return'] = (
+ 1.0 + self.balance['% change']).cumprod()
+
+ return self.balance
+
+ def rebalance_portfolio(self, stocks):
+ money_total = self.current_cash + self.current_capital
+ for asset in self._strategy.assets:
+ stock = stocks[stocks['symbol'] == asset.symbol]
+ stock_price = stock[self.schema['Adj Close']].values[0]
+ qty = (money_total * asset.percentage) // stock_price
+ inventory_entry = self.inventory[self.inventory['symbol'] ==
+ asset.symbol]
+ self.inventory.drop(inventory_entry.index, inplace=True)
+ update = pd.Series([asset.symbol, stock_price, qty])
+ update.index = self.inventory.columns
+ self.inventory = self.inventory.append(update, ignore_index=True)
+
+ # Update current cash
+ invested_capital = sum(self.inventory['cost'] * self.inventory['qty'])
+ self.current_cash = money_total - invested_capital
+
+ def _update_balance(self, date, stocks):
+ """Updates positions and calculates statistics for the current date.
+
+ Args:
+ date (pd.Timestamp): Current date.
+ stocks (pd.DataFrame): DataFrame of (daily/monthly) stocks.
+ """
+
+ costs = []
+
+ for asset in self._strategy.assets:
+ asset_entry = stocks[stocks['symbol'] == asset.symbol]
+ inventory_asset_entry = self.inventory[self.inventory['symbol'] ==
+ asset.symbol]
+ cost = asset_entry[self.schema['Adj Close']].values[0]
+ qty = inventory_asset_entry['qty'].values[0]
+ costs.append(cost * qty)
+
+ total_value = sum(costs)
+ self.current_capital = total_value
+ money_total = total_value + self.current_cash
+
+ row = pd.Series(
+ {
+ 'total_value': total_value,
+ 'cash': self.current_cash,
+ 'capital': money_total,
+ },
+ name=date)
+ self.balance = self.balance.append(row)
diff --git a/asset_backtester/datahandler/__init__.py b/asset_backtester/datahandler/__init__.py
new file mode 100644
index 0000000..3abd5ad
--- /dev/null
+++ b/asset_backtester/datahandler/__init__.py
@@ -0,0 +1,2 @@
+from .schema import *
+from .historical_stock_data import HistoricalStockData
\ No newline at end of file
diff --git a/asset_backtester/datahandler/historical_stock_data.py b/asset_backtester/datahandler/historical_stock_data.py
new file mode 100644
index 0000000..6e93179
--- /dev/null
+++ b/asset_backtester/datahandler/historical_stock_data.py
@@ -0,0 +1,80 @@
+import os
+from .schema import Schema
+import pandas as pd
+
+
+class HistoricalStockData:
+ """Historical Stock Data container class."""
+ def __init__(self, file, schema=None, **params):
+ if schema:
+ assert isinstance(schema, Schema)
+ else:
+ self.schema = HistoricalStockData.default_schema()
+
+ file_extension = os.path.splitext(file)[1]
+
+ if file_extension == '.h5':
+ self._data = pd.read_hdf(file, **params)
+ elif file_extension == '.csv':
+ params['parse_dates'] = [self.schema.date.mapping]
+ self._data = pd.read_csv(file, **params)
+
+ columns = self._data.columns
+ assert all((col in columns for _key, col in self.schema))
+
+ date_col = self.schema['date']
+
+ self.start_date = self._data[date_col].min()
+ self.end_date = self._data[date_col].max()
+
+ def apply_filter(self, f):
+ """Apply Filter `f` to the data. Returns a `pd.DataFrame` with the filtered rows."""
+ return self._data.query(f.query)
+
+ def iter_dates(self):
+ """Returns `pd.DataFrameGroupBy` that groups contracts by date"""
+ return self._data.groupby(self.schema['date'])
+
+ def iter_months(self):
+ """Returns `pd.DataFrameGroupBy` that groups contracts by month"""
+ date_col = self.schema['date']
+ iterator = self._data.groupby(pd.Grouper(
+ key=date_col, freq="MS")).apply(lambda g: g[g[date_col] == g[
+ date_col].min()]).reset_index(drop=True).groupby(date_col)
+ return iterator
+
+ def __getattr__(self, attr):
+ """Pass method invocation to `self._data`"""
+
+ method = getattr(self._data, attr)
+ if hasattr(method, '__call__'):
+
+ def df_method(*args, **kwargs):
+ return method(*args, **kwargs)
+
+ return df_method
+ else:
+ return method
+
+ def __getitem__(self, item):
+ if isinstance(item, pd.Series):
+ return self._data[item]
+ else:
+ key = self.schema[item]
+ return self._data[key]
+
+ def __setitem__(self, key, value):
+ self._data[key] = value
+ if key not in self.schema:
+ self.schema.update({key: key})
+
+ def __len__(self):
+ return len(self._data)
+
+ def __repr__(self):
+ return self._data.__repr__()
+
+ def default_schema():
+ """Returns default schema for Historical Options Data"""
+ schema = Schema.canonical()
+ return schema
diff --git a/asset_backtester/datahandler/schema.py b/asset_backtester/datahandler/schema.py
new file mode 100644
index 0000000..355401b
--- /dev/null
+++ b/asset_backtester/datahandler/schema.py
@@ -0,0 +1,163 @@
+class Schema:
+ """Data schema class.
+ Used to run validations and provide uniform access to fields in the data set.
+ """
+
+ columns = [
+ "symbol", "date", "open", "close", "high", "low", "volume", "Adj Close"
+ ]
+
+ def canonical():
+ """Builder method that returns a `Schema` with default mappings"""
+ mappings = {key: key for key in Schema.columns}
+ return Schema(mappings)
+
+ def __init__(self, mappings):
+ assert all((key in mappings for key in Schema.columns))
+
+ self._mappings = mappings
+
+ def update(self, mappings):
+ """Update schema according to given `mappings`"""
+ self._mappings.update(mappings)
+ return self
+
+ def __contains__(self, key):
+ """Returns True if key is in schema"""
+ return key in self._mappings.keys()
+
+ def __getattr__(self, key):
+ """Returns Field object used to build Filters"""
+ return Field(key, self._mappings[key])
+
+ def __setitem__(self, key, value):
+ self._mappings[key] = value
+
+ def __getitem__(self, key):
+ """Returns mapping of given `key`"""
+ return self._mappings[key]
+
+ def __iter__(self):
+ return iter(self._mappings.items())
+
+ def __repr__(self):
+ return "Schema({})".format(
+ [Field(k, m) for k, m in self._mappings.items()])
+
+ def __eq__(self, other):
+ return self._mappings == other._mappings
+
+
+class Field:
+ """Encapsulates data fields to build filters used by strategies"""
+
+ __slots__ = ("name", "mapping")
+
+ def __init__(self, name, mapping):
+ self.name = name
+ self.mapping = mapping
+
+ def _create_filter(self, op, other):
+ if isinstance(other, Field):
+ query = Field._format_query(self.mapping, op, other.mapping)
+ else:
+ query = Field._format_query(self.mapping, op, other)
+ return Filter(query)
+
+ def _combine_fields(self, op, other, invert=False):
+ if isinstance(other, Field):
+ name = Field._format_query(self.name, op, other.name, invert)
+ mapping = Field._format_query(self.mapping, op, other.mapping,
+ invert)
+ elif isinstance(other, (int, float)):
+ name = Field._format_query(self.name, op, other, invert)
+ mapping = Field._format_query(self.mapping, op, other, invert)
+ else:
+ raise TypeError
+
+ return Field(name, mapping)
+
+ def _format_query(left, op, right, invert=False):
+ if invert:
+ left, right = right, left
+ query = "{left} {op} {right}".format(left=left, op=op, right=right)
+ return query
+
+ def __add__(self, value):
+ return self._combine_fields("+", value)
+
+ def __radd__(self, value):
+ return self._combine_fields("+", value, invert=True)
+
+ def __sub__(self, value):
+ return self._combine_fields("-", value)
+
+ def __rsub__(self, value):
+ return self._combine_fields("-", value, invert=True)
+
+ def __mul__(self, value):
+ return self._combine_fields("*", value)
+
+ def __rmul__(self, value):
+ return self._combine_fields("*", value, invert=True)
+
+ def __truediv__(self, value):
+ return self._combine_fields("/", value)
+
+ def __rtruediv__(self, value):
+ return self._combine_fields("/", value, invert=True)
+
+ def __lt__(self, value):
+ return self._create_filter("<", value)
+
+ def __le__(self, value):
+ return self._create_filter("<=", value)
+
+ def __gt__(self, value):
+ return self._create_filter(">", value)
+
+ def __ge__(self, value):
+ return self._create_filter(">=", value)
+
+ def __eq__(self, value):
+ if isinstance(value, str):
+ value = "'{}'".format(value)
+ return self._create_filter("==", value)
+
+ def __ne__(self, value):
+ return self._create_filter("!=", value)
+
+ def __repr__(self):
+ return "Field(name='{}', mapping='{}')".format(self.name, self.mapping)
+
+
+class Filter:
+ """This class determines entry/exit conditions for strategies"""
+
+ __slots__ = ("query")
+
+ def __init__(self, query):
+ self.query = query
+
+ def __and__(self, other):
+ """Returns logical *and* between `self` and `other`"""
+ assert isinstance(other, Filter)
+ new_query = "({}) & ({})".format(self.query, other.query)
+ return Filter(query=new_query)
+
+ def __or__(self, other):
+ """Returns logical *or* between `self` and `other`"""
+ assert isinstance(other, Filter)
+ new_query = "(({}) | ({}))".format(self.query, other.query)
+ return Filter(query=new_query)
+
+ def __invert__(self):
+ """Negates filter"""
+ return Filter("!({})".format(self.query))
+
+ def __call__(self, data):
+ """Returns dataframe of filtered data"""
+ return data.eval(self.query)
+
+ def __repr__(self):
+ return "Filter(query='{}')".format(self.query)
\ No newline at end of file
diff --git a/asset_backtester/statistics/__init__.py b/asset_backtester/statistics/__init__.py
new file mode 100644
index 0000000..bbf880d
--- /dev/null
+++ b/asset_backtester/statistics/__init__.py
@@ -0,0 +1 @@
+from .charts import returns_chart
diff --git a/asset_backtester/statistics/charts.py b/asset_backtester/statistics/charts.py
new file mode 100644
index 0000000..00e7f5a
--- /dev/null
+++ b/asset_backtester/statistics/charts.py
@@ -0,0 +1,48 @@
+"""Generates charts from a portfolio report"""
+
+import altair as alt
+
+
+def returns_chart(report):
+ # Time interval selector
+ time_interval = alt.selection(type='interval', encodings=['x'])
+
+ # Area plot
+ areas = alt.Chart().mark_area(opacity=0.7).encode(
+ x='index:T',
+ y=alt.Y('accumulated return:Q', axis=alt.Axis(format='%')))
+
+ # Nearest point selector
+ nearest = alt.selection(type='single',
+ nearest=True,
+ on='mouseover',
+ fields=['index'],
+ empty='none')
+
+ points = areas.mark_point().encode(
+ opacity=alt.condition(nearest, alt.value(1), alt.value(0)))
+
+ # Transparent date selector
+ selectors = alt.Chart().mark_point().encode(
+ x='index:T',
+ opacity=alt.value(0),
+ ).add_selection(nearest)
+
+ text = areas.mark_text(
+ align='left', dx=5, dy=-5).encode(text=alt.condition(
+ nearest, 'accumulated return:Q', alt.value(' '), format='.2%'))
+
+ layered = alt.layer(selectors,
+ points,
+ text,
+ areas.encode(
+ alt.X('index:T',
+ axis=alt.Axis(title='date'),
+ scale=alt.Scale(domain=time_interval))),
+ width=700,
+ height=350,
+ title='Wealth over time')
+
+ lower = areas.properties(width=700, height=70).add_selection(time_interval)
+
+ return alt.vconcat(layered, lower, data=report.reset_index())
\ No newline at end of file
diff --git a/asset_backtester/strategy/__init__.py b/asset_backtester/strategy/__init__.py
new file mode 100644
index 0000000..140f8c6
--- /dev/null
+++ b/asset_backtester/strategy/__init__.py
@@ -0,0 +1,2 @@
+from .strategy import Strategy
+from .asset import Asset
\ No newline at end of file
diff --git a/asset_backtester/strategy/asset.py b/asset_backtester/strategy/asset.py
new file mode 100644
index 0000000..d01e866
--- /dev/null
+++ b/asset_backtester/strategy/asset.py
@@ -0,0 +1,16 @@
+from .direction import Direction
+from datahandler.schema import Schema
+
+
+class Asset:
+ """Strategy Leg data class"""
+ def __init__(self, symbol, percentage, direction=Direction.BUY):
+ assert isinstance(direction, Direction)
+
+ self.symbol = symbol
+ self.percentage = percentage
+ self.direction = direction
+
+ def __repr__(self):
+ return "Asset(symbol={}, percentage={}, direction={})".format(
+ self.symbol, self.percentage, self.direction)
diff --git a/asset_backtester/strategy/direction.py b/asset_backtester/strategy/direction.py
new file mode 100644
index 0000000..85f85c2
--- /dev/null
+++ b/asset_backtester/strategy/direction.py
@@ -0,0 +1,10 @@
+from enum import Enum
+
+
+class Direction(Enum):
+ BUY = 'ask' # Schema field for BUY price
+ SELL = 'bid' # Schema field for SELL price
+
+ def __invert__(self):
+ flip = Direction.SELL if self == Direction.BUY else Direction.BUY
+ return flip
\ No newline at end of file
diff --git a/asset_backtester/strategy/strategy.py b/asset_backtester/strategy/strategy.py
new file mode 100644
index 0000000..332c375
--- /dev/null
+++ b/asset_backtester/strategy/strategy.py
@@ -0,0 +1,37 @@
+import math
+from functools import reduce
+
+import pandas as pd
+import numpy as np
+
+from .direction import Direction
+from .asset import Asset
+
+
+class Strategy:
+ def __init__(self, direction=Direction.BUY):
+ assert isinstance(direction, Direction)
+ self.direction = direction
+ self.assets = []
+
+ def add_asset(self, asset):
+ """Adds asset to the strategy"""
+ assert isinstance(asset, Asset)
+ self.assets.append(asset)
+ return self
+
+ def add_assets(self, assets):
+ """Adds assets to the strategy"""
+ for asset in assets:
+ self.add_asset(asset)
+ return self
+
+ def remove_asset(self, asset_number):
+ """Removes asset from the strategy"""
+ self.assets.pop(asset_number)
+ return self
+
+ def clear_assets(self):
+ """Removes *all* assets from the strategy"""
+ self.assets = []
+ return self
diff --git a/asset_backtester/test.ipynb b/asset_backtester/test.ipynb
new file mode 100644
index 0000000..e24fb30
--- /dev/null
+++ b/asset_backtester/test.ipynb
@@ -0,0 +1,2788 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import numpy as np\n",
+ "import os"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from backtester import Backtest\n",
+ "from strategy.strategy import Strategy\n",
+ "from strategy.asset import Asset\n",
+ "from strategy.direction import Direction\n",
+ "from datahandler import HistoricalStockData\n",
+ "from statistics.charts import returns_chart"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "%config InlineBackend.figure_format=\"retina\"\n",
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas_datareader.data as web\n",
+ "import datetime"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "start = datetime.datetime(2019, 1, 1)\n",
+ "end = datetime.datetime(2019, 12, 31)\n",
+ "\n",
+ "tickers = [\"VOO\", \"TUR\", \"RSX\", \"EWY\", \"EWS\", \"VTIP\", \"TLT\", \"BWX\", \"PDBC\", \"IAU\", \"VNQI\"]\n",
+ "portfolio = [0.1, 0.05, 0.05, 0.05, 0.05, 0.10, 0.20, 0.10, 0.05, 0.15, 0.10, 1]\n",
+ "\n",
+ "dfs = []\n",
+ "for ticker in tickers:\n",
+ " df = web.DataReader(ticker, 'yahoo', start, end).reset_index().rename(columns={'Date': 'date', 'High': 'high', 'Low': 'low', 'Open': 'open', 'Close': 'close', 'Volume': 'volume'})\n",
+ " df['symbol'] = ticker\n",
+ " dfs.append(df)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "portfolio = pd.concat(dfs)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "portfolio = portfolio.sort_values(by='date').reset_index(drop=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "portfolio.to_csv(\"data/portfolio.csv\", index=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data = HistoricalStockData(\"data/portfolio.csv\")\n",
+ "schema = data.schema"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " date | \n",
+ " high | \n",
+ " low | \n",
+ " open | \n",
+ " close | \n",
+ " volume | \n",
+ " Adj Close | \n",
+ " symbol | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " 2019-01-02 | \n",
+ " 230.850006 | \n",
+ " 226.020004 | \n",
+ " 226.179993 | \n",
+ " 229.990005 | \n",
+ " 4891300.0 | \n",
+ " 225.350449 | \n",
+ " VOO | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " 2019-01-02 | \n",
+ " 15.333000 | \n",
+ " 14.890000 | \n",
+ " 14.920000 | \n",
+ " 15.120000 | \n",
+ " 1382500.0 | \n",
+ " 14.909319 | \n",
+ " PDBC | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " 2019-01-02 | \n",
+ " 122.160004 | \n",
+ " 121.339996 | \n",
+ " 121.660004 | \n",
+ " 122.150002 | \n",
+ " 19841500.0 | \n",
+ " 119.344078 | \n",
+ " TLT | \n",
+ "
\n",
+ " \n",
+ " | 3 | \n",
+ " 2019-01-02 | \n",
+ " 47.910000 | \n",
+ " 47.860001 | \n",
+ " 47.860001 | \n",
+ " 47.910000 | \n",
+ " 771400.0 | \n",
+ " 46.986149 | \n",
+ " VTIP | \n",
+ "
\n",
+ " \n",
+ " | 4 | \n",
+ " 2019-01-02 | \n",
+ " 22.100000 | \n",
+ " 21.850000 | \n",
+ " 21.930000 | \n",
+ " 22.100000 | \n",
+ " 876200.0 | \n",
+ " 21.076557 | \n",
+ " EWS | \n",
+ "
\n",
+ " \n",
+ " | ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " | 2767 | \n",
+ " 2019-12-31 | \n",
+ " 27.180000 | \n",
+ " 27.000000 | \n",
+ " 27.110001 | \n",
+ " 27.090000 | \n",
+ " 132900.0 | \n",
+ " 27.090000 | \n",
+ " TUR | \n",
+ "
\n",
+ " \n",
+ " | 2768 | \n",
+ " 2019-12-31 | \n",
+ " 16.650000 | \n",
+ " 16.510000 | \n",
+ " 16.520000 | \n",
+ " 16.559999 | \n",
+ " 1780800.0 | \n",
+ " 16.559999 | \n",
+ " PDBC | \n",
+ "
\n",
+ " \n",
+ " | 2769 | \n",
+ " 2019-12-31 | \n",
+ " 295.989990 | \n",
+ " 294.170013 | \n",
+ " 294.529999 | \n",
+ " 295.799988 | \n",
+ " 2512700.0 | \n",
+ " 295.799988 | \n",
+ " VOO | \n",
+ "
\n",
+ " \n",
+ " | 2770 | \n",
+ " 2019-12-31 | \n",
+ " 136.460007 | \n",
+ " 135.380005 | \n",
+ " 136.210007 | \n",
+ " 135.479996 | \n",
+ " 10707400.0 | \n",
+ " 135.479996 | \n",
+ " TLT | \n",
+ "
\n",
+ " \n",
+ " | 2771 | \n",
+ " 2019-12-31 | \n",
+ " 59.090000 | \n",
+ " 58.849998 | \n",
+ " 58.950001 | \n",
+ " 59.090000 | \n",
+ " 219900.0 | \n",
+ " 59.090000 | \n",
+ " VNQI | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
2772 rows × 8 columns
\n",
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " capital | \n",
+ " cash | \n",
+ " total_value | \n",
+ " % change | \n",
+ " accumulated return | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 2019-01-01 | \n",
+ " 1.000000e+06 | \n",
+ " 1000000.000000 | \n",
+ " NaN | \n",
+ " NaN | \n",
+ " NaN | \n",
+ "
\n",
+ " \n",
+ " | 2019-01-02 | \n",
+ " 1.000000e+06 | \n",
+ " 403.112655 | \n",
+ " 9.995969e+05 | \n",
+ " 0.000000 | \n",
+ " 1.000000 | \n",
+ "
\n",
+ " \n",
+ " | 2019-01-03 | \n",
+ " 9.987008e+05 | \n",
+ " 403.112655 | \n",
+ " 9.982976e+05 | \n",
+ " -0.001299 | \n",
+ " 0.998701 | \n",
+ "
\n",
+ " \n",
+ " | 2019-01-04 | \n",
+ " 1.008706e+06 | \n",
+ " 403.112655 | \n",
+ " 1.008302e+06 | \n",
+ " 0.010018 | \n",
+ " 1.008706 | \n",
+ "
\n",
+ " \n",
+ " | 2019-01-07 | \n",
+ " 1.010929e+06 | \n",
+ " 403.112655 | \n",
+ " 1.010526e+06 | \n",
+ " 0.002205 | \n",
+ " 1.010929 | \n",
+ "
\n",
+ " \n",
+ " | ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ " ... | \n",
+ "
\n",
+ " \n",
+ " | 2019-12-24 | \n",
+ " 1.161007e+06 | \n",
+ " 447.309637 | \n",
+ " 1.160560e+06 | \n",
+ " 0.002650 | \n",
+ " 1.161007 | \n",
+ "
\n",
+ " \n",
+ " | 2019-12-26 | \n",
+ " 1.166209e+06 | \n",
+ " 447.309637 | \n",
+ " 1.165761e+06 | \n",
+ " 0.004480 | \n",
+ " 1.166209 | \n",
+ "
\n",
+ " \n",
+ " | 2019-12-27 | \n",
+ " 1.168988e+06 | \n",
+ " 447.309637 | \n",
+ " 1.168541e+06 | \n",
+ " 0.002383 | \n",
+ " 1.168988 | \n",
+ "
\n",
+ " \n",
+ " | 2019-12-30 | \n",
+ " 1.166540e+06 | \n",
+ " 447.309637 | \n",
+ " 1.166092e+06 | \n",
+ " -0.002094 | \n",
+ " 1.166540 | \n",
+ "
\n",
+ " \n",
+ " | 2019-12-31 | \n",
+ " 1.166803e+06 | \n",
+ " 447.309637 | \n",
+ " 1.166356e+06 | \n",
+ " 0.000226 | \n",
+ " 1.166803 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
253 rows × 5 columns
\n",
+ "