1. 增加CTA模块的回测参数优化功能
2. 修复CTP接口中持仓价格的bug 3. 量衍更新vnokcoin的比特币期货合约交易功能
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36
vn.okcoin/README.md
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36
vn.okcoin/README.md
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# vn.okcoin
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贡献者：量衍投资
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### 简介
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OkCoin的比特币交易接口，基于Websocket API开发，实现了以下功能：
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1. 发送、撤销委托
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2. 查询委托、持仓、资金、成交历史
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3. 实时行情、成交、资金更新的推送
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### 特点
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相比较于[OkCoin官方](http://github.com/OKCoin/websocket/tree/master/python)给出的Python API实现，vn.okcoin的一些特点：
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1. 同时支持OkCoin的中国站和国际站交易，根据用户连接的站点会在内部自动切换结算货币（CNY、USD）
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2. 采用面向对象的接口设计模式，接近国内CTP接口的风格，并对主动函数的调用参数做了大幅简化
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3. 数据解包和签名生成两个热点函数使用了更加高效的实现方式
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### 参数命名
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函数的参数命名针对金融领域用户的习惯做了一些修改，具体对应如下：
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* expiry：原生命名的contract_type
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* order: 原生命名的match_price
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* leverage：原生命名的lever_rate
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* page：原生命名的current_page
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* length：原生命名的page_length
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### API版本
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日期：2016-06-29
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链接：[http://www.okcoin.com/about/ws_getStarted.do](http://www.okcoin.com/about/ws_getStarted.do)
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vn.okcoin/test.py
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vn.okcoin/test.py
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# encoding: UTF-8
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from vnokcoin import *
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# 在OkCoin网站申请这两个Key，分别对应用户名和密码
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apiKey = ''
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secretKey = ''
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# 创建API对象
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api = OkCoinApi()
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# 连接服务器，并等待1秒
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api.connect(OKCOIN_USD, apiKey, secretKey, True)
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sleep(1)
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# 测试现货行情API
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api.subscribeSpotTicker(SYMBOL_BTC)
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#api.subscribeSpotTradeData(SYMBOL_BTC)
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#api.subscribeSpotDepth(SYMBOL_BTC, DEPTH_20)
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#api.subscribeSpotKline(SYMBOL_BTC, INTERVAL_1M)
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# 测试现货交易API
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#api.subscribeSpotTrades()
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#api.subscribeSpotUserInfo()
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#api.spotUserInfo()
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#api.spotTrade(symbol, type_, price, amount)
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#api.spotCancelOrder(symbol, orderid)
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#api.spotOrderInfo(symbol, orderid)
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# 测试期货行情API
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#api.subscribeFutureTicker(SYMBOL_BTC, FUTURE_EXPIRY_THIS_WEEK)
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#api.subscribeFutureTradeData(SYMBOL_BTC, FUTURE_EXPIRY_THIS_WEEK)
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#api.subscribeFutureDepth(SYMBOL_BTC, FUTURE_EXPIRY_THIS_WEEK, DEPTH_20)
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#api.subscribeFutureKline(SYMBOL_BTC, FUTURE_EXPIRY_THIS_WEEK, INTERVAL_1M)
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#api.subscribeFutureIndex(SYMBOL_BTC)
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# 测试期货交易API
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#api.subscribeFutureTrades()
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#api.subscribeFutureUserInfo()
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#api.subscribeFuturePositions()
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#api.futureUserInfo()
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#api.futureTrade(symbol, expiry, type_, price, amount, order, leverage)
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#api.futureCancelOrder(symbol, expiry, orderid)
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#api.futureOrderInfo(symbol, expiry, orderid, status, page, length)
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raw_input()
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@ -49,6 +49,32 @@ TYPE_SELL = 'sell'
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TYPE_BUY_MARKET = 'buy_market'
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TYPE_SELL_MARKET = 'sell_market'
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# 期货合约到期类型
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FUTURE_EXPIRY_THIS_WEEK = 'this_week'
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FUTURE_EXPIRY_NEXT_WEEK = 'next_week'
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FUTURE_EXPIRY_QUARTER = 'quarter'
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# 期货委托类型
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FUTURE_TYPE_LONG = 1
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FUTURE_TYPE_SHORT = 2
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FUTURE_TYPE_SELL = 3
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FUTURE_TYPE_COVER = 4
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# 期货是否用现价
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FUTURE_ORDER_MARKET = 1
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FUTURE_ORDER_LIMIT = 0
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# 期货杠杆
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FUTURE_LEVERAGE_10 = 10
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FUTURE_LEVERAGE_20 = 20
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# 委托状态
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ORDER_STATUS_NOTTRADED = 0
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ORDER_STATUS_PARTTRADED = 1
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ORDER_STATUS_ALLTRADED = 2
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ORDER_STATUS_CANCELLED = -1
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ORDER_STATUS_CANCELLING = 4
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########################################################################
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class OkCoinApi(object):
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@ -65,6 +91,10 @@ class OkCoinApi(object):
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self.ws = None # websocket应用对象
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self.thread = None # 工作线程
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#######################
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## 通用函数
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#######################
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#----------------------------------------------------------------------
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def readData(self, evt):
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"""解压缩推送收到的数据"""
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@ -135,6 +165,10 @@ class OkCoinApi(object):
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self.thread = Thread(target=self.ws.run_forever)
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self.thread.start()
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#######################
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## 现货相关
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#######################
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#----------------------------------------------------------------------
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def sendMarketDataRequest(self, channel):
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"""发送行情请求"""
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@ -242,32 +276,106 @@ class OkCoinApi(object):
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self.sendTradingRequest(channel, {})
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#######################
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## 期货相关
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#######################
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if __name__ == "__main__":
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# 在OkCoin网站申请这两个Key，分别对应用户名和密码
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apiKey = ''
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secretKey = ''
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#----------------------------------------------------------------------
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def subscribeFutureTicker(self, symbol, expiry):
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"""订阅期货普通报价"""
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self.sendMarketDataRequest('ok_sub_future%s_%s_ticker_%s' %(self.currency, symbol, expiry))
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# 创建API对象
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api = OkCoinApi()
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#----------------------------------------------------------------------
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def subscribeFutureDepth(self, symbol, expiry, depth):
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"""订阅期货深度报价"""
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self.sendMarketDataRequest('ok_sub_future%s_%s_depth_%s_%s' %(self.currency, symbol,
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expiry, depth))
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# 连接服务器，并等待1秒
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api.connect(OKCOIN_CNY, apiKey, secretKey, True)
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#----------------------------------------------------------------------
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def subscribeFutureTradeData(self, symbol, expiry):
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"""订阅期货成交记录"""
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self.sendMarketDataRequest('ok_sub_future%s_%s_trade_%s' %(self.currency, symbol, expiry))
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sleep(1)
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#----------------------------------------------------------------------
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def subscribeFutureKline(self, symbol, expiry, interval):
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"""订阅期货K线"""
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self.sendMarketDataRequest('ok_sub_future%s_%s_kline_%s_%s' %(self.currency, symbol,
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expiry, interval))
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# 测试现货行情API
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#api.subscribeSpotTicker(SYMBOL_BTC)
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#api.subscribeSpotTradeData(SYMBOL_BTC)
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#api.subscribeSpotDepth(SYMBOL_BTC, DEPTH_20)
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#api.subscribeSpotKline(SYMBOL_BTC, INTERVAL_1M)
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#----------------------------------------------------------------------
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def subscribeFutureIndex(self, symbol):
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"""订阅期货指数"""
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self.sendMarketDataRequest('ok_sub_future%s_%s_index' %(self.currency, symbol))
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#----------------------------------------------------------------------
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def futureTrade(self, symbol, expiry, type_, price, amount, order, leverage):
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"""期货委托"""
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params = {}
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params['symbol'] = str(symbol+self.currency)
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params['type'] = str(type_)
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params['price'] = str(price)
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params['amount'] = str(amount)
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params['contract_type'] = str(expiry)
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params['match_price'] = str(order)
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params['lever_rate'] = str(leverage)
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channel = 'ok_future%s_trade' %(self.currency)
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self.sendTradingRequest(channel, params)
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#----------------------------------------------------------------------
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def futureCancelOrder(self, symbol, expiry, orderid):
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"""期货撤单"""
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params = {}
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params['symbol'] = str(symbol+self.currency)
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params['order_id'] = str(orderid)
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params['contract_type'] = str(expiry)
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channel = 'ok_future%s_cancel_order' %(self.currency)
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self.sendTradingRequest(channel, params)
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#----------------------------------------------------------------------
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def futureUserInfo(self):
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"""查询期货账户"""
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channel = 'ok_future%s_userinfo' %(self.currency)
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self.sendTradingRequest(channel, {})
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#----------------------------------------------------------------------
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def futureOrderInfo(self, symbol, expiry, orderid, status, page, length):
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"""查询期货委托信息"""
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params = {}
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params['symbol'] = str(symbol+self.currency)
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params['order_id'] = str(orderid)
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params['contract_type'] = expiry
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params['status'] = status
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params['current_page'] = page
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params['page_length'] = length
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channel = 'ok_future%s_orderinfo'
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self.sendTradingRequest(channel, params)
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#----------------------------------------------------------------------
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def subscribeFutureTrades(self):
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"""订阅期货成交信息"""
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channel = 'ok_sub_future%s_trades' %(self.currency)
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self.sendTradingRequest(channel, {})
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#----------------------------------------------------------------------
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def subscribeFutureUserInfo(self):
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"""订阅期货账户信息"""
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channel = 'ok_sub_future%s_userinfo' %(self.currency)
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self.sendTradingRequest(channel, {})
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#----------------------------------------------------------------------
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def subscribeFuturePositions(self):
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"""订阅期货持仓信息"""
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channel = 'ok_sub_future%s_positions' %(self.currency)
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self.sendTradingRequest(channel, {})
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# 测试现货交易API
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#api.subscribeSpotTrades()
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#api.subscribeSpotUserInfo()
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api.spotUserInfo()
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#api.spotTrade(symbol, type_, price, amount)
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#api.spotCancelOrder(symbol, orderid)
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#api.spotOrderInfo(symbol, orderid)
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raw_input()
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@ -7,6 +7,7 @@
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from datetime import datetime, timedelta
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from collections import OrderedDict
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from itertools import product
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import pymongo
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from ctaBase import *
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@ -55,6 +56,9 @@ class BacktestingEngine(object):
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self.initData = [] # 初始化用的数据
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#self.backtestingData = [] # 回测用的数据
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self.dbName = '' # 回测数据库名
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self.symbol = '' # 回测集合名
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self.dataStartDate = None # 回测数据开始日期，datetime对象
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self.dataEndDate = None # 回测数据结束日期，datetime对象
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self.strategyStartDate = None # 策略启动日期（即前面的数据用于初始化），datetime对象
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@ -93,12 +97,18 @@ class BacktestingEngine(object):
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self.mode = mode
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#----------------------------------------------------------------------
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def loadHistoryData(self, dbName, symbol):
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def setDatabase(self, dbName, symbol):
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"""设置历史数据所用的数据库"""
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self.dbName = dbName
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self.symbol = symbol
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#----------------------------------------------------------------------
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def loadHistoryData(self):
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"""载入历史数据"""
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host, port = loadMongoSetting()
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self.dbClient = pymongo.MongoClient(host, port)
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collection = self.dbClient[dbName][symbol]
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collection = self.dbClient[self.dbName][self.symbol]
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self.output(u'开始载入数据')
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@ -134,6 +144,9 @@ class BacktestingEngine(object):
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#----------------------------------------------------------------------
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def runBacktesting(self):
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"""运行回测"""
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# 载入历史数据
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self.loadHistoryData()
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# 首先根据回测模式，确认要使用的数据类
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if self.mode == self.BAR_MODE:
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dataClass = CtaBarData
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@ -431,23 +444,20 @@ class BacktestingEngine(object):
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#----------------------------------------------------------------------
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def output(self, content):
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"""输出内容"""
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print content
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print str(datetime.now()) + "\t" + content
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#----------------------------------------------------------------------
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def showBacktestingResult(self):
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def calculateBacktestingResult(self):
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"""
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显示回测结果
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计算回测结果
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"""
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self.output(u'显示回测结果')
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self.output(u'计算回测结果')
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# 首先基于回测后的成交记录，计算每笔交易的盈亏
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pnlDict = OrderedDict() # 每笔盈亏的记录
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resultDict = OrderedDict() # 交易结果记录
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longTrade = [] # 未平仓的多头交易
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shortTrade = [] # 未平仓的空头交易
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# 计算滑点，一个来回包括两次
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totalSlippage = self.slippage * 2
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for trade in self.tradeDict.values():
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# 多头交易
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if trade.direction == DIRECTION_LONG:
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@ -457,12 +467,10 @@ class BacktestingEngine(object):
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# 当前多头交易为平空
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else:
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entryTrade = shortTrade.pop(0)
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# 计算比例佣金
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commission = (trade.price+entryTrade.price) * self.rate
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# 计算盈亏
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pnl = ((trade.price - entryTrade.price)*(-1) - totalSlippage - commission) \
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* trade.volume * self.size
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pnlDict[trade.dt] = pnl
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result = TradingResult(entryTrade.price, trade.price, -trade.volume,
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self.rate, self.slippage, self.size)
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resultDict[trade.dt] = result
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# 空头交易
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else:
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# 如果尚无多头交易
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@ -471,56 +479,93 @@ class BacktestingEngine(object):
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# 当前空头交易为平多
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else:
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entryTrade = longTrade.pop(0)
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# 计算比例佣金
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commission = (trade.price+entryTrade.price) * self.rate
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# 计算盈亏
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pnl = ((trade.price - entryTrade.price) - totalSlippage - commission) \
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* trade.volume * self.size
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pnlDict[trade.dt] = pnl
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result = TradingResult(entryTrade.price, trade.price, trade.volume,
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self.rate, self.slippage, self.size)
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resultDict[trade.dt] = result
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# 检查是否有交易
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if not resultDict:
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self.output(u'无交易结果')
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return {}
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# 然后基于每笔交易的结果，我们可以计算具体的盈亏曲线和最大回撤等
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timeList = pnlDict.keys()
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pnlList = pnlDict.values()
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capital = 0 # 资金
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maxCapital = 0 # 资金最高净值
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drawdown = 0 # 回撤
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capital = 0
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maxCapital = 0
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drawdown = 0
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totalResult = 0 # 总成交数量
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totalTurnover = 0 # 总成交金额（合约面值）
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totalCommission = 0 # 总手续费
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totalSlippage = 0 # 总滑点
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timeList = [] # 时间序列
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pnlList = [] # 每笔盈亏序列
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capitalList = [] # 盈亏汇总的时间序列
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maxCapitalList = [] # 最高盈利的时间序列
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drawdownList = [] # 回撤的时间序列
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for pnl in pnlList:
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capital += pnl
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for time, result in resultDict.items():
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capital += result.pnl
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maxCapital = max(capital, maxCapital)
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drawdown = capital - maxCapital
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pnlList.append(result.pnl)
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timeList.append(time)
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capitalList.append(capital)
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maxCapitalList.append(maxCapital)
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drawdownList.append(drawdown)
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totalResult += 1
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totalTurnover += result.turnover
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totalCommission += result.commission
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totalSlippage += result.slippage
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# 返回回测结果
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d = {}
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d['capital'] = capital
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d['maxCapital'] = maxCapital
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d['drawdown'] = drawdown
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d['totalResult'] = totalResult
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d['totalTurnover'] = totalTurnover
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d['totalCommission'] = totalCommission
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d['totalSlippage'] = totalSlippage
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d['timeList'] = timeList
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d['pnlList'] = pnlList
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d['capitalList'] = capitalList
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d['drawdownList'] = drawdownList
|
||||
return d
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def showBacktestingResult(self):
|
||||
"""显示回测结果"""
|
||||
d = self.calculateBacktestingResult()
|
||||
|
||||
# 输出
|
||||
self.output('-' * 50)
|
||||
self.output(u'第一笔交易时间：%s' % timeList[0])
|
||||
self.output(u'最后一笔交易时间：%s' % timeList[-1])
|
||||
self.output(u'总交易次数：%s' % len(pnlList))
|
||||
self.output(u'总盈亏：%s' % capitalList[-1])
|
||||
self.output(u'最大回撤: %s' % min(drawdownList))
|
||||
self.output('-' * 30)
|
||||
self.output(u'第一笔交易：\t%s' % d['timeList'][0])
|
||||
self.output(u'最后一笔交易：\t%s' % d['timeList'][-1])
|
||||
|
||||
self.output(u'总交易次数：\t%s' % formatNumber(d['totalResult']))
|
||||
self.output(u'总盈亏：\t%s' % formatNumber(d['capital']))
|
||||
self.output(u'最大回撤: \t%s' % formatNumber(min(d['drawdownList'])))
|
||||
|
||||
self.output(u'平均每笔盈利：\t%s' %formatNumber(d['capital']/d['totalResult']))
|
||||
self.output(u'平均每笔滑点：\t%s' %formatNumber(d['totalSlippage']/d['totalResult']))
|
||||
self.output(u'平均每笔佣金：\t%s' %formatNumber(d['totalCommission']/d['totalResult']))
|
||||
|
||||
# 绘图
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
pCapital = plt.subplot(3, 1, 1)
|
||||
pCapital.set_ylabel("capital")
|
||||
pCapital.plot(capitalList)
|
||||
pCapital.plot(d['capitalList'])
|
||||
|
||||
pDD = plt.subplot(3, 1, 2)
|
||||
pDD.set_ylabel("DD")
|
||||
pDD.bar(range(len(drawdownList)), drawdownList)
|
||||
pDD.bar(range(len(d['drawdownList'])), d['drawdownList'])
|
||||
|
||||
pPnl = plt.subplot(3, 1, 3)
|
||||
pPnl.set_ylabel("pnl")
|
||||
pPnl.hist(pnlList, bins=20)
|
||||
pPnl.hist(d['pnlList'], bins=50)
|
||||
|
||||
plt.show()
|
||||
|
||||
@ -531,7 +576,7 @@ class BacktestingEngine(object):
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def setSlippage(self, slippage):
|
||||
"""设置滑点"""
|
||||
"""设置滑点点数"""
|
||||
self.slippage = slippage
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
@ -544,6 +589,137 @@ class BacktestingEngine(object):
|
||||
"""设置佣金比例"""
|
||||
self.rate = rate
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def runOptimization(self, strategyClass, optimizationSetting):
|
||||
"""优化参数"""
|
||||
# 获取优化设置
|
||||
settingList = optimizationSetting.generateSetting()
|
||||
targetName = optimizationSetting.optimizeTarget
|
||||
|
||||
# 检查参数设置问题
|
||||
if not settingList or not targetName:
|
||||
self.output(u'优化设置有问题，请检查')
|
||||
|
||||
# 遍历优化
|
||||
resultList = []
|
||||
for setting in settingList:
|
||||
self.clearBacktestingResult()
|
||||
self.output('-' * 30)
|
||||
self.output('setting: %s' %str(setting))
|
||||
self.initStrategy(strategyClass, setting)
|
||||
self.runBacktesting()
|
||||
d = self.calculateBacktestingResult()
|
||||
try:
|
||||
targetValue = d[targetName]
|
||||
except KeyError:
|
||||
targetValue = 0
|
||||
resultList.append(([str(setting)], targetValue))
|
||||
|
||||
# 显示结果
|
||||
resultList.sort(reverse=True, key=lambda result:result[1])
|
||||
self.output('-' * 30)
|
||||
self.output(u'优化结果：')
|
||||
for result in resultList:
|
||||
self.output(u'%s: %s' %(result[0], result[1]))
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def clearBacktestingResult(self):
|
||||
"""清空之前回测的结果"""
|
||||
# 清空限价单相关
|
||||
self.limitOrderCount = 0
|
||||
self.limitOrderDict.clear()
|
||||
self.workingLimitOrderDict.clear()
|
||||
|
||||
# 清空停止单相关
|
||||
self.stopOrderCount = 0
|
||||
self.stopOrderDict.clear()
|
||||
self.workingStopOrderDict.clear()
|
||||
|
||||
# 清空成交相关
|
||||
self.tradeCount = 0
|
||||
self.tradeDict.clear()
|
||||
|
||||
|
||||
########################################################################
|
||||
class TradingResult(object):
|
||||
"""每笔交易的结果"""
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def __init__(self, entry, exit, volume, rate, slippage, size):
|
||||
"""Constructor"""
|
||||
self.entry = entry # 开仓价格
|
||||
self.exit = exit # 平仓价格
|
||||
self.volume = volume # 交易数量（+/-代表方向）
|
||||
|
||||
self.turnover = (self.entry+self.exit)*size # 成交金额
|
||||
self.commission = self.turnover*rate # 手续费成本
|
||||
self.slippage = slippage*2*size # 滑点成本
|
||||
self.pnl = ((self.exit - self.entry) * volume * size
|
||||
- self.commission - self.slippage) # 净盈亏
|
||||
|
||||
|
||||
########################################################################
|
||||
class OptimizationSetting(object):
|
||||
"""优化设置"""
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def __init__(self):
|
||||
"""Constructor"""
|
||||
self.paramDict = OrderedDict()
|
||||
|
||||
self.optimizeTarget = '' # 优化目标字段
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def addParameter(self, name, start, end, step):
|
||||
"""增加优化参数"""
|
||||
if end <= start:
|
||||
print u'参数起始点必须小于终止点'
|
||||
return
|
||||
|
||||
if step <= 0:
|
||||
print u'参数布进必须大于0'
|
||||
return
|
||||
|
||||
l = []
|
||||
param = start
|
||||
|
||||
while param <= end:
|
||||
l.append(param)
|
||||
param += step
|
||||
|
||||
self.paramDict[name] = l
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def generateSetting(self):
|
||||
"""生成优化参数组合"""
|
||||
# 参数名的列表
|
||||
nameList = self.paramDict.keys()
|
||||
paramList = self.paramDict.values()
|
||||
|
||||
# 使用迭代工具生产参数对组合
|
||||
productList = list(product(*paramList))
|
||||
|
||||
# 把参数对组合打包到一个个字典组成的列表中
|
||||
settingList = []
|
||||
for p in productList:
|
||||
d = dict(zip(nameList, p))
|
||||
settingList.append(d)
|
||||
|
||||
return settingList
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def setOptimizeTarget(self, target):
|
||||
"""设置优化目标字段"""
|
||||
self.optimizeTarget = target
|
||||
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def formatNumber(n):
|
||||
"""格式化数字到字符串"""
|
||||
n = round(n, 2) # 保留两位小数
|
||||
return format(n, ',') # 加上千分符
|
||||
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
@ -562,7 +738,7 @@ if __name__ == '__main__':
|
||||
engine.setStartDate('20110101')
|
||||
|
||||
# 载入历史数据到引擎中
|
||||
engine.loadHistoryData(MINUTE_DB_NAME, 'IF0000')
|
||||
engine.setDatabase(MINUTE_DB_NAME, 'IF0000')
|
||||
|
||||
# 设置产品相关参数
|
||||
engine.setSlippage(0.2) # 股指1跳
|
||||
|
||||
@ -251,21 +251,29 @@ if __name__ == '__main__':
|
||||
# 设置回测用的数据起始日期
|
||||
engine.setStartDate('20120101')
|
||||
|
||||
# 载入历史数据到引擎中
|
||||
engine.loadHistoryData(MINUTE_DB_NAME, 'IF0000')
|
||||
|
||||
# 设置产品相关参数
|
||||
engine.setSlippage(0.2) # 股指1跳
|
||||
engine.setRate(0.3/10000) # 万0.3
|
||||
engine.setSize(300) # 股指合约大小
|
||||
|
||||
# 在引擎中创建策略对象
|
||||
engine.initStrategy(AtrRsiStrategy, {})
|
||||
# 设置使用的历史数据库
|
||||
engine.setDatabase(MINUTE_DB_NAME, 'IF0000')
|
||||
|
||||
# 开始跑回测
|
||||
engine.runBacktesting()
|
||||
## 在引擎中创建策略对象
|
||||
#d = {'atrLength': 11}
|
||||
#engine.initStrategy(AtrRsiStrategy, d)
|
||||
|
||||
# 显示回测结果
|
||||
engine.showBacktestingResult()
|
||||
## 开始跑回测
|
||||
#engine.runBacktesting()
|
||||
|
||||
## 显示回测结果
|
||||
#engine.showBacktestingResult()
|
||||
|
||||
# 跑优化
|
||||
setting = OptimizationSetting() # 新建一个优化任务设置对象
|
||||
setting.setOptimizeTarget('capital') # 设置优化排序的目标是策略净盈利
|
||||
setting.addParameter('atrLength', 11, 12, 1) # 增加第一个优化参数atrLength，起始11，结束12，步进1
|
||||
setting.addParameter('atrMa', 20, 30, 5) # 增加第二个优化参数atrMa，起始20，结束30，步进1
|
||||
engine.runOptimization(AtrRsiStrategy, setting) # 运行优化函数，自动输出结果
|
||||
|
||||
|
||||
@ -437,6 +437,7 @@ class CtpTdApi(TdApi):
|
||||
|
||||
self.posBufferDict = {} # 缓存持仓数据的字典
|
||||
self.symbolExchangeDict = {} # 保存合约代码和交易所的印射关系
|
||||
self.symbolSizeDict = {} # 保存合约代码和合约大小的印射关系
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def onFrontConnected(self):
|
||||
@ -637,10 +638,11 @@ class CtpTdApi(TdApi):
|
||||
|
||||
# 更新持仓缓存，并获取VT系统中持仓对象的返回值
|
||||
exchange = self.symbolExchangeDict.get(data['InstrumentID'], EXCHANGE_UNKNOWN)
|
||||
size = self.symbolSizeDict.get(data['InstrumentID'], 1)
|
||||
if exchange == EXCHANGE_SHFE:
|
||||
pos = posBuffer.updateShfeBuffer(data)
|
||||
pos = posBuffer.updateShfeBuffer(data, size)
|
||||
else:
|
||||
pos = posBuffer.updateBuffer(data)
|
||||
pos = posBuffer.updateBuffer(data, size)
|
||||
self.gateway.onPosition(pos)
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
@ -735,6 +737,7 @@ class CtpTdApi(TdApi):
|
||||
|
||||
# 缓存代码和交易所的印射关系
|
||||
self.symbolExchangeDict[contract.symbol] = contract.exchange
|
||||
self.symbolSizeDict[contract.symbol] = contract.size
|
||||
|
||||
# 推送
|
||||
self.gateway.onContract(contract)
|
||||
@ -1318,7 +1321,7 @@ class PositionBuffer(object):
|
||||
self.pos = pos
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def updateShfeBuffer(self, data):
|
||||
def updateShfeBuffer(self, data, size):
|
||||
"""更新上期所缓存，返回更新后的持仓数据"""
|
||||
# 昨仓和今仓的数据更新是分在两条记录里的，因此需要判断检查该条记录对应仓位
|
||||
# 因为今仓字段TodayPosition可能变为0（被全部平仓），因此分辨今昨仓需要用YdPosition字段
|
||||
@ -1336,7 +1339,7 @@ class PositionBuffer(object):
|
||||
# 如果手头还有持仓，则通过加权平均方式计算持仓均价
|
||||
if self.todayPosition or self.ydPosition:
|
||||
self.pos.price = ((self.todayPositionCost + self.ydPositionCost)/
|
||||
(self.todayPosition + self.ydPosition))
|
||||
((self.todayPosition + self.ydPosition) * size))
|
||||
# 否则价格为0
|
||||
else:
|
||||
self.pos.price = 0
|
||||
@ -1344,14 +1347,14 @@ class PositionBuffer(object):
|
||||
return copy(self.pos)
|
||||
|
||||
#----------------------------------------------------------------------
|
||||
def updateBuffer(self, data):
|
||||
def updateBuffer(self, data, size):
|
||||
"""更新其他交易所的缓存，返回更新后的持仓数据"""
|
||||
# 其他交易所并不区分今昨，因此只关心总仓位，昨仓设为0
|
||||
self.pos.position = data['Position']
|
||||
self.pos.ydPosition = 0
|
||||
|
||||
if data['Position']:
|
||||
self.pos.price = data['PositionCost'] / data['Position']
|
||||
self.pos.price = data['PositionCost'] / (data['Position'] * size)
|
||||
else:
|
||||
self.pos.price = 0
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user