gistfile1.txt

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   "source": [
    "%matplotlib inline"
   ]
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    "\"\"\"\n",
    "FX Symbol Selection project\n",
    "Select FX Symbol for trading based on volatility, liquidity, momentum, etc.\n",
    "Use Dollar Index as benchmark.\n",
    "\"\"\"\n",
    "\n",
    "# Import Python standard libraries\n",
    "import csv\n",
    "import math\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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   "source": [
    "#################################################\n",
    "### Part I - read data from csv files as raw data\n",
    "\n",
    "# Read data from csv files\n",
    "EURUSDreader = csv.reader(open('EURUSD.csv'))\n",
    "GBPUSDreader = csv.reader(open('GBPUSD.csv'))\n",
    "USDJPYreader = csv.reader(open('USDJPY.csv'))\n",
    "USDCADreader = csv.reader(open('USDCAD.csv'))\n",
    "USDCHFreader = csv.reader(open('USDCHF.csv'))\n",
    "USDSEKreader = csv.reader(open('USDSEK.csv'))\n",
    "\n",
    "# 4 functions to process data\n",
    "def FX(FXreader):\n",
    "\tFX = []\n",
    "\tfor line in FXreader:\n",
    "\t\tFX.append(line)\n",
    "\treturn FX\n",
    "\n",
    "def FX_Time(FX):\n",
    "\tFX_Time = []\n",
    "\tfor row in FX:\n",
    "\t\tFX_Time.append(datetime.strptime((row[0] + \" \" + row[1]), \"%Y.%m.%d %H:%M\"))\n",
    "\treturn FX_Time\n",
    "\n",
    "def FX_Close(FX):\n",
    "\tFX_Close = []\n",
    "\tfor row in FX:\n",
    "\t\tFX_Close.append(float(row[5]))\n",
    "\treturn FX_Close\n",
    "\n",
    "def FX_Volume(FX):\n",
    "\tFX_Volume = []\n",
    "\tfor row in FX:\n",
    "\t\tFX_Volume.append(float(row[6]))\n",
    "\treturn FX_Volume\n",
    "\n",
    "# Call the functions to get Time, Close_price, Volume data series of each FX pair\n",
    "EURUSD = FX(EURUSDreader)\n",
    "GBPUSD = FX(GBPUSDreader)\n",
    "USDJPY = FX(USDJPYreader)\n",
    "USDCAD = FX(USDCADreader)\n",
    "USDCHF = FX(USDCHFreader)\n",
    "USDSEK = FX(USDSEKreader)\n",
    "\n",
    "EURUSD_Time = FX_Time(EURUSD)\n",
    "GBPUSD_Time = FX_Time(GBPUSD)\n",
    "USDJPY_Time = FX_Time(USDJPY)\n",
    "USDCAD_Time = FX_Time(USDCAD)\n",
    "USDCHF_Time = FX_Time(USDCHF)\n",
    "USDSEK_Time = FX_Time(USDSEK)\n",
    "\n",
    "EURUSD_Close = FX_Close(EURUSD)\n",
    "GBPUSD_Close = FX_Close(GBPUSD)\n",
    "USDJPY_Close = FX_Close(USDJPY)\n",
    "USDCAD_Close = FX_Close(USDCAD)\n",
    "USDCHF_Close = FX_Close(USDCHF)\n",
    "USDSEK_Close = FX_Close(USDSEK)\n",
    "\n",
    "EURUSD_Volume = FX_Volume(EURUSD)\n",
    "GBPUSD_Volume = FX_Volume(GBPUSD)\n",
    "USDJPY_Volume = FX_Volume(USDJPY)\n",
    "USDCAD_Volume = FX_Volume(USDCAD)\n",
    "USDCHF_Volume = FX_Volume(USDCHF)\n",
    "USDSEK_Volume = FX_Volume(USDSEK)"
   ]
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    "########################################\n",
    "# Part II - get Dollar Index as Benchmark\n",
    "\n",
    "# Get the Dollar_Index\n",
    "Index_Time = []\n",
    "for item in USDJPY_Time:\n",
    "\tif (item in EURUSD_Time) and (item in GBPUSD_Time) and (item in USDCAD_Time) and (item in USDCHF_Time) and (item in USDSEK_Time):\n",
    "\t\tIndex_Time.append(item)\n",
    "\n",
    "\n",
    "Dollar_Index_ClosePrice = []\n",
    "for item in Index_Time:\n",
    "\tEUR = EURUSD_Close[EURUSD_Time.index(item)]\n",
    "\tGBP = GBPUSD_Close[GBPUSD_Time.index(item)]\n",
    "\tJPY = USDJPY_Close[USDJPY_Time.index(item)]\n",
    "\tCAD = USDCAD_Close[USDCAD_Time.index(item)]\n",
    "\tCHF = USDCHF_Close[USDCHF_Time.index(item)]\n",
    "\tSEK = USDSEK_Close[USDSEK_Time.index(item)]\n",
    "\ttemp_element = 50.14348112 * EUR**(-0.576) * JPY**(0.136) * GBP**(-0.119) * CAD**(0.091) * SEK**(0.042) * CHF**(0.036)\n",
    "\tDollar_Index_ClosePrice.append(temp_element)\n",
    "\n",
    "Dollar_Index_Volume = []\n",
    "for item in Index_Time:\n",
    "\tEUR = EURUSD_Volume[EURUSD_Time.index(item)]\n",
    "\tGBP = GBPUSD_Volume[GBPUSD_Time.index(item)]\n",
    "\tJPY = USDJPY_Volume[USDJPY_Time.index(item)]\n",
    "\tCAD = USDCAD_Volume[USDCAD_Time.index(item)]\n",
    "\tCHF = USDCHF_Volume[USDCHF_Time.index(item)]\n",
    "\tSEK = USDSEK_Volume[USDSEK_Time.index(item)]\n",
    "\ttemp_element = EUR**(-0.576) * JPY**(0.136) * GBP**(-0.119) * CAD**(0.091) * SEK**(0.042) * CHF**(0.036)\n",
    "\tDollar_Index_Volume.append(temp_element)\n"
   ]
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   "source": [
    "########################################\n",
    "# Part III - get FX_Return (closing price percentage change) data series\n",
    "\n",
    "# Function of FX_Return\n",
    "def get_FX_Return(FX_Close):\n",
    "\t\"\"\"\n",
    "\tInput data: closing price data series of the FX\n",
    "\tReturn: closing price change data series of the FX\n",
    "\t\"\"\"\n",
    "\tFX_Return = []\n",
    "\t\n",
    "\tfor index in (range(len(FX_Close) - 1)):\n",
    "\t\ttemp = abs(math.log(FX_Close[index + 1]) - math.log(FX_Close[index]))\n",
    "\t\tFX_Return.append(temp)\n",
    "\t\n",
    "\treturn FX_Return"
   ]
  },
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    "########################################\n",
    "# Part IV - Volatility\n",
    "\n",
    "\"\"\"\n",
    "How volatility guides retail traders:\n",
    "Risk aversion - prefer FX pairs with low volatility, stable performance with low risk\n",
    "Risk preference - prefer FX pairs with high volatility, may make sudden millionaire while high risk\n",
    "\"\"\"\n",
    "\n",
    "# Function of FX_Volatility, using Exponential Weighted Moving Average model\n",
    "def FX_Volatility(FX_Close_raw, FX_Time, starting_time, ending_time):\n",
    "\t\"\"\"\n",
    "\tFor production:\n",
    "\tusers should choose only starting_time and the name of FX symbol, \n",
    "\tthe ending_time should always be the latest time in our market database,\n",
    "\twe do the data processing(to generate FX_Close_raw and FX_Time) for users.\n",
    "\n",
    "\t4 input data:\n",
    "\t1-dimension array/list/vector of FX_Close_price series\n",
    "\t1-dimension array/list/vector of FX_Time series\n",
    "\ta time data of starting_time\n",
    "\ta time data of ending_time\n",
    "\t\"\"\"\n",
    "\t\n",
    "\t# Get the Close_price data within a period from starting_time to ending_time\n",
    "\tindex_1 = FX_Time.index(starting_time)\n",
    "\tindex_2 = FX_Time.index(ending_time) + 1\n",
    "\tFX_Close = FX_Close_raw[index_1 : index_2]\n",
    "\n",
    "\t# Get the Return_series of the FX symbol\n",
    "\tFX_Return = get_FX_Return(FX_Close)\n",
    "\n",
    "\t# Calculate EWMA model and get the volatility\n",
    "\tLAMBDA = 0.94\n",
    "\tVolatility = []\n",
    "\tVolatility.append(FX_Return[0])\n",
    "\n",
    "\tfor i in range(len(FX_Return)):\n",
    "\t\ttemp_Volatility = math.sqrt(LAMBDA * Volatility[i] ** 2 + (1 - LAMBDA) * FX_Return[i] ** 2)\n",
    "\t\tVolatility.append(temp_Volatility)\n",
    "\n",
    "\t# import matplotlib.pyplot as plt\n",
    "\t# time = FX_Time[index_1 : index_2]\n",
    "\t# plt.plot(time, Volatility)\n",
    "\n",
    "\t# The returned value is the last value of the volatility series\n",
    "\treturn Volatility[len(Volatility) - 1]"
   ]
  },
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    "########################################\n",
    "# Part V - Liquidity\n",
    "\n",
    "\"\"\"\n",
    "How liquidity guides retail traders:\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "def FX_Liquidity(FX_Close_raw, FX_Volume_raw, FX_Time, starting_time, ending_time):\n",
    "\t\"\"\"\n",
    "\tThe same as FX_Volatility :)\n",
    "\t\"\"\"\n",
    "\n",
    "\t# Get the Close_price data within a period from starting_time to ending_time\n",
    "\tindex_1 = FX_Time.index(starting_time)\n",
    "\tindex_2 = FX_Time.index(ending_time) + 1\n",
    "\tFX_Close = FX_Close_raw[index_1 : index_2]\n",
    "\tFX_Volume = FX_Volume_raw[index_1 : index_2]\n",
    "\n",
    "\t# Get the absolute value of Return_series of the FX symbol\n",
    "\tFX_Return = get_FX_Return(FX_Close)\n",
    "\n",
    "\t# Calculate liquidity\n",
    "\tLiquidity = 0.0\n",
    "\tfor i in range(len(FX_Return)):\n",
    "\t\tLiquidity += FX_Return[i] / FX_Volume[i+1]\n",
    "\n",
    "\treturn Liquidity"
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
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     "text": [
      "0.000953732576007\n",
      "91.8201186094\n",
      "\n",
      "['FX pair ', 'Volatility', 'Liquidity']\n",
      "['EURUSD: ', 1.195790928621961, 0.0035493317347093296]\n",
      "['GBPUSD: ', 1.2575349936397355, 0.00219394492243788]\n",
      "['USDJPY: ', 0.8344798291117231, 0.0033466999799656554]\n",
      "['USDCAD: ', 1.2940480442538815, 0.0041707638560959884]\n",
      "['USDCHF: ', 2.418970052091221, 0.0034447129042055515]\n",
      "['USDSEK: ', 2.4387256180025756, 0.0049629575755860455]\n"
     ]
    }
   ],
   "source": [
    "# Test module\n",
    "EURUSD_volatility = FX_Volatility(EURUSD_Close, EURUSD_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "GBPUSD_volatility = FX_Volatility(GBPUSD_Close, GBPUSD_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 23, 23, 0))\n",
    "USDJPY_volatility = FX_Volatility(USDJPY_Close, USDJPY_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 23, 23, 0))\n",
    "USDCAD_volatility = FX_Volatility(USDCAD_Close, USDCAD_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 23, 23, 0))\n",
    "USDCHF_volatility = FX_Volatility(USDCHF_Close, USDCHF_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 23, 23, 0))\n",
    "USDSEK_volatility = FX_Volatility(USDSEK_Close, USDSEK_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 23, 23, 0))\n",
    "\n",
    "EURUSD_liquidity = FX_Liquidity(EURUSD_Close, EURUSD_Volume, EURUSD_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "GBPUSD_liquidity = FX_Liquidity(GBPUSD_Close, GBPUSD_Volume, GBPUSD_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "USDJPY_liquidity = FX_Liquidity(USDJPY_Close, USDJPY_Volume, USDJPY_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "USDCAD_liquidity = FX_Liquidity(USDCAD_Close, USDCAD_Volume, USDCAD_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "USDCHF_liquidity = FX_Liquidity(USDCHF_Close, USDCHF_Volume, USDCHF_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "USDSEK_liquidity = FX_Liquidity(USDSEK_Close, USDSEK_Volume, USDSEK_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "\n",
    "Benchmark_volatility = FX_Volatility(Dollar_Index_ClosePrice, Index_Time, datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "Benchmark_liquidity = FX_Liquidity(Dollar_Index_ClosePrice, Dollar_Index_Volume, Index_Time,  datetime(2014, 01, 01, 23, 0), datetime(2015, 04, 01, 07, 0))\n",
    "print Benchmark_volatility\n",
    "print Benchmark_liquidity\n",
    "print \n",
    "\n",
    "board = [[\"FX pair \", \"Volatility\", \"Liquidity\"],\n",
    "\t\t [\"EURUSD: \", EURUSD_volatility / Benchmark_volatility, EURUSD_liquidity],\n",
    "         [\"GBPUSD: \", GBPUSD_volatility / Benchmark_volatility, GBPUSD_liquidity],\n",
    "         [\"USDJPY: \", USDJPY_volatility / Benchmark_volatility, USDJPY_liquidity],\n",
    "         [\"USDCAD: \", USDCAD_volatility / Benchmark_volatility, USDCAD_liquidity],\n",
    "         [\"USDCHF: \", USDCHF_volatility / Benchmark_volatility, USDCHF_liquidity],\n",
    "         [\"USDSEK: \", USDSEK_volatility / Benchmark_volatility, USDSEK_liquidity]]\n",
    "\n",
    "for row in board:\n",
    "\tprint row"
   ]
  },
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