Group of python scripts for analyzing Bitcoin.
Prerequisites:
- Python 2.7, NumPy, SciPy, Matplotlib, Pandas.
- We assume that you have downloaded some bitcoin historical prices, e.g.,
from Mt.Gox Bitcoin Exchange, into a csv file
data/mtgoxUSD.csv. You can download these data from: http://api.bitcoincharts.com/v1/csv/
Script for loading and analyzing bitcoin historical time-series.
Example:
# Read raw bitcoin price history from a csv file
mtgox_raw = read_bitcoin_csv('data/mtgoxUSD.csv')
# Get bitcoin OHLC data frame with 5min frequency
mtgox_ohlc = get_bitcoin_ohlc(mtgox_raw, '5min')
# Sample output
mtgox_ohlc['2013-01-01':].head()
Output:
open high low close amount
date
2013-01-01 00:00:00 13.51001 13.51001 13.51001 13.51001 36.874308
2013-01-01 00:05:00 13.55999 13.55999 13.51001 13.51001 0.010000
2013-01-01 00:10:00 13.51001 13.56000 13.51001 13.51001 0.010000
2013-01-01 00:15:00 13.51001 13.51001 13.51001 13.51001 1.610000
2013-01-01 00:20:00 13.51001 13.51002 13.51000 13.51000 0.041716
Script for backtesting simple trading strategies.
We make the following simplifying assumptions:
- At any time during trading all our resources are allocated either in BTC or in USD. Therefore, we consider only long positions, during which all our resources are allocated in BTC.
- We use BTC/USD as our benchmark. In other words, a trading strategy beats the benchmark if and only if it is better than mere holding of BTC.
Class LongPositions is used for bookkeeping our trades. It can compute
the resulting profit and profit time-series.
Class TradingStrategyMA is a simple trading strategy based on two
moving averages - one with a short period and one with a long period.
Example:
# Read raw bitcoin price history from a csv file
mtgox_raw = read_bitcoin_csv('data/mtgoxUSD.csv')
# Get bitcoin OHLC data frame with 1h frequency
mtgox = get_bitcoin_ohlc(mtgox_raw, '1h')
# Select test time interval
test_from_date = '2013-01-01'
test_to_date = '2013-10-01'
mtgox_test = mtgox[
(mtgox.index >= test_from_date) &
(mtgox.index < test_to_date)]
# Initial balance
balance = 1000
# Initialize a trading strategy
trading = TradingStrategyMA(30, 50)
# Compute long positions
long_positions = trading.compute(mtgox_test.close)
# Compute resulting profit
profit = long_positions.profit(balance)
# Compare resulting profit with BTC/USD benchmark
print 'Test benchmark: %.2f' % \
(balance * mtgox_test.close[-1] / mtgox_test.close[0])
print 'Test profit %.2f' % profit
Output:
Test benchmark: 10464.34
Test profit 17674.91
The Bitcoin Tools project is licensed to you under MIT.X11:
Copyright (c) 2013 Peter Cerno.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.