2019-01-29 07:35:37 +00:00
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{
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2019-01-29 20:39:04 +00:00
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#%%\n",
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"from vnpy.app.cta_strategy.backtesting import BacktestingEngine\n",
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"from vnpy.app.cta_strategy.strategies.turtle_signal_strategy import (\n",
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" TurtleSignalStrategy,\n",
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")\n",
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"from datetime import datetime"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#%%\n",
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"engine = BacktestingEngine()\n",
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"engine.set_parameters(\n",
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" vt_symbol=\"IF88.CFFEX\",\n",
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" interval=\"1m\",\n",
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" start=datetime(2013, 1, 1),\n",
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" end=datetime(2015, 3, 30),\n",
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" rate=0,\n",
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" slippage=0,\n",
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" size=300,\n",
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" pricetick=0.2,\n",
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" capital=1_000_000,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"scrolled": false
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},
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"outputs": [],
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"source": [
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"#%%\n",
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"engine.add_strategy(TurtleSignalStrategy, {})\n",
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"engine.load_data()\n",
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"engine.run_backtesting()\n",
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"df = engine.calculate_result()\n",
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"engine.calculate_statistics()\n",
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"engine.show_chart()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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}
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2019-01-29 07:35:37 +00:00
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"nbformat": 4,
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}
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