Using Python as a quantitative investment---handicap high frequency strategy

How to use: Put the previous configuration foundation, write to a python file, file name saved as Okcoinspotapi, and then put the following code, write to a new file, save it, you can directly run the

Principle: According to the handicap sale volume, the depth market pending orders quantity, carries on the sale decision-making. belong to high-frequency strategy.

Note: This strategy has been made firm and has been withdrawn. If used, it is recommended to further optimize.

One more step, qq:1733505732.

Please specify: python, bitcoin quantization

#-*-Coding:utf-8-*-"" "Created on Mon with 17:40:55 2017 @author: Yunjinqi e-mail:yunjinqi@qq.com
yourself in the world from anyone else. "" "####################################################### #盘口模型 from okcoinspotapi import * Import pandas as PD import n Umpy as NP import datetime import time ##################################################### #初始数据 #引入初始信息 apikey = ' 9b93e 53a-e803-4883-b8fc-64af2f3ccc57 ' Secretkey = ' 14284b3c0b9cf0f932e83888388855c9 ' okcoinresturl = ' www.okcoin.cn ' # Note: The domestic account needs to be modified to www.okcoin.cn Okcoinspot = Okcoinspot (okcoinresturl,apikey,secretkey) okcoinfuture = Okcoinfuture ( Okcoinresturl,apikey,secretkey) #info =eval (Okcoinspot.userinfo ()) #账户信息 #info #################################### #获取并整理数据 def cut (deep): deep[' bid_price ']= ' deep[' bid_volume ', ']= ', ' deep[' ask_price ', ']= ', ' deep[', ' Ask_price ' ' For I in Range (len (deep)): Deep.ix[i, ' Bid_price ']=deep.ix[i, ' bids '][0] deep.ix[i, ' Bid_volume ']=deep . Ix[i, ' BIDs '][1] deep.ix[i, ' Ask_price ']=deep.ix[i, ' asks '][0] deep.ix[i, ' Ask_volume ']=deep.ix[i, ' asks '][1] Del deep[' asks '] del deep[' bids '] deep[' bid_price ']=deep[' Bid_price ' to ('].astype ' float64 ') deep[' bid_volume ']=deep[' b Id_volume '].astype (' float64 ') deep[' ask_price ']=deep[' Ask_price '].astype (' float64 ') deep[' ask_price ']=deep[' Price '].astype (' float64 ') return deep def Bid_ask_vol_diff (deep): bidvol10=deep[' Bid_volume ' "][:10" askvol10=de ep[' Ask_volume '][-10:] Diff=bidvol10.sum ()-askvol10.sum () return diff #diff >0 is the admission condition 1 def bid_ask_price_diff (de EP): bidprice10=deep[' Bid_price '][:10] askprice10=deep[' Ask_price '][-10:] Bid_diff=bidprice10.max ()-bidprice10 . Min () Ask_diff=askprice10.max ()-askprice10.min () Diff=bid_diff-ask_diff #小于0是入场条件 return diff def Bid_ask_big Vol. (Deep): bidvol10=deep[' Bid_volume '][:10] askvol10=deep[' Ask_volume '][-10:] Diff=bidvol10.max () >askvol10. Max () #大于0是入场条件 returnDiff i=0 while True:deep=pd. Dataframe (okcoinspot.depth (' Btc_cny ')) deep=cut (deep) deep if Bid_ask_vol_diff (deep) >0 and Bid_ask_price_di FF (deep) <0 and Bid_ask_bigvol (deep) >0:price_buy=str (deep[' Bid_price '][1]+0.01) buy=okcoinspot.trade (' Btc_cny ', ' buy ', price_buy, ' 0.01 ') time.sleep (0.2) price_sell=str (deep[' Bid_price "][1]+0.50) sell=okcoin 
        Spot.trade (' Btc_cny ', ' sell ', Price_sell, ' 0.01 ') print (Sell) i=i+1 Try:buyid=str (eval (Buy) [' order_id ']) Sellid=str (eval (Sell) [' order_id ']) except Nameerror:pass except time. Sleep (5) try:cancel_buy=okcoinspot.cancelorder (' Btc_cny ', Buyid) cance1_sell=okcoinspot.cancelorder (' BTC _cny ', sellid) except Nameerror:pass except Keyerror:pass Info_btc_free=eval (eval (okcoinspot. UserInfo ()) [' Info '] [' funds '] [' free '] [' BTC ']] info_net=eval (eval (Okcoinspot.userinfo ()) [' Info '] [' funds '] [' Asset ' [' net ']] print (i,info_btc_free,info_net)