教程：智能执行器策略

我们将在本教程中创建一个交易应用程序，它接收来自 python API 的简单命令来调整账户风险。使用 Python 生成信号并使用 Smart Executor 执行订单。

创建智能执行器策略的步骤

要创建灵活的策略，您需要执行以下操作：

决定交易哪个交易所。
添加您计划交易的品种或收听市场数据。 3.增加价格模型。
添加变量以生成信号。
添加模型。
添加策略。
创建python脚本来生成信号和发送命令。查看更多详细信息 -> smart_executor 参考

Configure

我们使用 json 文件来配置交易应用程序。该文件包含有关 api 密钥、日志路径和策略组件的信息。请更新以下示例配置中的 API 密钥信息：

{
    "instance": {
        "license_id":"apifiny001",
        "license_key":"apifiny123456",
        "log_path": "./logs/strategy_demo",
        "name": "strategy_demo"
    },
    "ib_gateway": {
        "ip": "127.0.0.1",
        "port": 4002
    },
    "servers": {
        "redis_server": "127.0.0.1"
    },
    "apikeys": {
        "BINANCE": {
            "key": "",
            "secret": ""
            },
        "BINANCEUS": {
            "key": "",
            "secret": ""
            },
        "OKEX": {
            "key": "",
            "secret": "",
            "pass": ""
            }       
    },
    "fees": {
        "BINANCE": {
            "make": 0.0,
            "take": 0.00045
        },
        "BINANCEUS": {
            "make": 0.0,
            "take": 0.000462
        },      
        "OKEX": {
            "make": 0.0,
            "take": 0.0002
        }
    },   
    "exchanges":
    [
        {"exchange":"BINANCEUS","trade_type":"Direct","market_data_type":"Direct"}
    ],
    "risk_formulas": [
        ["Port_Risk", ["RiskFormula", {"components": [[["BTCUSDT", "BINANCEUS"], 1.0]]}]]
    ],
    "accounts": [
        [10001, ["Account", {"risk_formulas": ["Port_Risk"], "id": 10001}]]
    ],
    "symbols": [
        {"port": ["BTCUSDT", "BINANCEUS"], "cid": 10000}
    ],
    "symbol_info": {
        "BTCUSDT.BINANCEUS": {"ticksize": 0.01, "lotsize": 0.0001, "price_precision": 2.0, "min_order_size": 0.0001, "qty_precision": 6.0, "multiple": 1.0}
    },
    "players": [
        ["BTCUSDT.HUOBI_Player", ["CobJsonPlayer", {"port": ["BTCUSDT", "BINANCEUS"], "path": "/data/cc/prod/ccc_record_2"}]]
    ],
    "samplers": [
        ["ts_basis", ["TimeSampler", {"halflife": 1, "msecs": 100}]]
    ],
    "pricing_models": [
        ["BTCUSDT.HUOBI_midpx", ["MidPx", {"port": ["BTCUSDT", "BINANCEUS"]}]], 
        ["BTCUSDT.HUOBI_Vwap", ["Vwap", {"port": ["BTCUSDT", "BINANCEUS"], "sampler": "ts_basis"}]]
    ],
    "variables": [
        ["Zero", ["Const", {"value": 0.0}]]
    ],
    "models": [
        ["Zero_m", ["LinearModel", {"variable": "Zero"}]]
    ],
    "strategies": [
        ["BTCUSDT.BINANCEUS", ["CCEventMakerStrategy", {"symbol": "BTCUSDT", "trade_market": "BINANCEUS", "account": 10001, "dep_pm": "BTCUSDT.HUOBI_midpx", "model": "Zero_m", "VWap": "BTCUSDT.HUOBI_Vwap", "max_spread_bps": 5, "max_quote_frombbo_bps": 0.001, "update_quote_bps": 2, "quote_bps": 3, "allowed_bps": 5, "order_notional": 500, "max_notional": 2500, "max_risk": 2500, "cooloff": 100, "start_time": "00:30:00", "end_time": "23:59:59", "use_separate_logs": true, "close_mode": "none"}]]
    ]
}

Python Script

要创建功能性 Python 脚本，您将需要以下部分：

使用您的算法获取数据和处理。我们在示例中提供 CCxtMarketData 作为获取原始数据的简单方法。
使用我们的 ExecutorApi 向我们的智能执行器发送命令。

CCxtMarketData

Field	Description	Mandatory
exchange	The exchange you need data from.	Yes
symbol_coin	The symbol coin you need data.	Yes
symbol_basecoin	The basecoin of the symbol you need data.	Yes

Function	Parameters	Mandatory
get_price	NA	Yes
get_ema	sample time interval, halflife	Yes
get_candle_data	sample time interval	Yes

ExecutorApi

Field	Description	Mandatory
exchange	The exchange you need data from.	Yes
symbol_coin	The symbol coin you need data.	Yes
symbol_basecoin	The basecoin of the symbol you need data.	Yes

Commands

Function	Description	Parameters
send_cmd_maker	Send position change you want, accumulate on smart executor side, and execute by making order.	instance name, trading direction, target position level
send_cmd_taker	Send the position level you want, calculate order quantity on smart executor side, and execute by taking order.	instance name, target position level

您只需通过 send_cmd_maker 发送仓位增减指令，Smart Executor 会自动汇总您的所有指令并执行；

Example

from apifiny.smart.ExecutorApi import ExecutorApi as ea
from apifiny.smart.examples.CcxtMarketData import CcxtMarketData as md

def strategy_live_demo(exchange, symbol_coin,symbol_basecoin,instance,targetLevel,interval,thresh,totalLevel):
    commander = ea(exchange,symbol_coin,symbol_basecoin)
    data= md(exchange, symbol_coin,symbol_basecoin)
    count = 0
    while True:
        try: 
            data.get_price()
            #test.get_candle_data("1m") #1m, 5m, 1h, 1d #By default you will have 500 metrics (if available)
            data_long = data.get_ema("1m",5) 
            data_short = data.get_ema("1m",1) 
            ema_long = data_long['Close'][data_long['Close'].size-1]
            ema_short = data_short['Close'][data_short['Close'].size-1]
        except:
            print("lost connection from ccxt")
            time.sleep(interval)
            continue
        if ema_long < ema_short and totalLevel < 1:
            if totalLevel < 0 and (abs(ema_long - ema_short)/data.mid) > thresh*0.0001:
                print("thresh check: ",{(ema_long - ema_short)/data.mid}, " total level: ", totalLevel)
                print("buy back: ema_long: ",{ema_long}, " ema_short: ", {ema_short}, "thresh", {thresh})
                commander.send_cmd_maker(instance, "buy", targetLevel)
                count += 1
                totalLevel += targetLevel
            elif totalLevel >= 0 and (abs(ema_long - ema_short)/data.mid) > thresh*(1+totalLevel/targetLevel)*0.0001:
                print("thresh check: ",{(ema_long - ema_short)/data.mid}, " total level: ", totalLevel)
                print("buy more: ema_long: ",{ema_long}, " ema_short: ", {ema_short}, "thresh", {thresh*(1+abs(totalLevel)/targetLevel)*0.0001})
                commander.send_cmd_maker(instance, "buy", targetLevel)
                count += 1
                totalLevel += targetLevel

        elif ema_long > ema_short and totalLevel > -1:
            if totalLevel <= 0 and (abs(ema_long - ema_short)/data.mid) > thresh*(1+abs(totalLevel)/targetLevel)*0.0001:
                print("thresh check: ",{(ema_long - ema_short)/data.mid}, " total level: ", totalLevel)
                print("sell more: ema_long: ",{ema_long}, " ema_short: ", {ema_short}, "thresh", {thresh*(1+abs(totalLevel)/targetLevel)*0.0001})
                commander.send_cmd_maker(instance, "sell", targetLevel)
                count += 1
                totalLevel -= targetLevel
            elif totalLevel > 0 and (abs(ema_long - ema_short)/data.mid) > thresh*0.0001:
                print("thresh check: ",{(ema_long - ema_short)/data.mid}, " total level: ", totalLevel)
                print("sell back: ema_long: ",{ema_long}, " ema_short: ", {ema_short}, "thresh", {thresh})
                commander.send_cmd_maker(instance, "sell", targetLevel)
                count += 1
                totalLevel -= targetLevel

        time.sleep(interval)