79 lines
1.9 KiB
Plaintext
79 lines
1.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "ad08f522",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import datetime\n",
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"import numpy as np\n",
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"import random"
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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": 2,
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"id": "b9b18667",
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"metadata": {},
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"outputs": [],
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"source": [
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"class riskManager:\n",
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" \n",
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" def __init__(self,commision=0.04):\n",
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" self.commision = commision\n",
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" pass\n",
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" def getDecision(self,signalDecision,probabilityDecision, price, deals=None) -> dict:\n",
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" ans = {}\n",
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" if probabilityDecision['trande'] == 'up':\n",
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" ans['decision'] = 'buy'\n",
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" ans['amount'] = 1\n",
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" elif probabilityDecision['trande'] == 'none':\n",
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" ans['decision'] = 'none'\n",
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" elif probabilityDecision['trande'] == 'down': \n",
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" for i in deals.shape[0]:\n",
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" ans['decision'] = 'None'\n",
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" ans['deals'] = []\n",
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" row = deals.iloc[i]\n",
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" if row.startPrice < price*pow(1+self.commission,2):\n",
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" ans['decision'] = 'sell'\n",
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" ans['deals'].append(row.name)\n",
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" return ans\n",
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" \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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"id": "8f5dd64e",
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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 (ipykernel)",
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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": "3.11.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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