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Commit 4a5dbfe8 authored by wenwen.tang's avatar wenwen.tang 😕
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新增投组校验，防止投组全为ft的情况

parent 992549c9
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Showing with 363 additions and 11 deletions
ai/EstimateMarketTrendV20.py
View file @ 4a5dbfe8
......@@ -2,6 +2,7 @@ from typing import List
from py_jftech import autowired
from ai.dao.robo_datas import get_base_info
from ai.data_access import DataAccess
from ai.model_trainer import ModelTrainer
from ai.noticer import upload_predict
......@@ -27,15 +28,17 @@ def sync(syncs: List[DataSync] = None):
s.do_sync()
def predictionFromMoel(the_model, scaledX_forecast, predict_item):
def predictionFromMoel(the_model, scaledX_forecast, predict_item, indexDict: dict):
prediction = the_model.predict(scaledX_forecast)
predictionStr = 'DOWN'
if (prediction > 0.5):
predictionStr = 'UP'
content = f"""\n On day {forecastDay.strftime("%m/%d/%Y")}, the model predicts {predict_item} to be {predictionStr} in {str(numForecastDays)} business days. \n"""
print(content)
# if predict_item == 'SPX':
# upload_predict(f'{predict_item} Index', forecastDay, predictionStr)
# 上传预测结果
# key = [k for k, v in indexDict.items() if v == predict_item]
# index_info = get_base_info(key)[0]
# upload_predict(index_info['ticker'], forecastDay, predictionStr)
# send(content)
return prediction
......@@ -113,4 +116,4 @@ if __name__ == '__main__':
ensemble_model = trainer.ensemble_model(rf_model, gbt_model, svc_model, X_train, y_train, X_test, y_test)
if (toForecast):
predictionFromMoel(ensemble_model, scaledX_forecast, indexDict[pid])
predictionFromMoel(ensemble_model, scaledX_forecast, indexDict[pid], indexDict)
api.py
View file @ 4a5dbfe8
......@@ -227,10 +227,10 @@ class AssetOptimize(ABC):
'''
@abstractmethod
def find_optimize(self, ids, day):
def find_optimize(self, fund_ids, day):
'''
从多id中，选出指定日期最优的id
:param ids: 待选id列表
:param fund_ids: 待选id列表
:param day: 指定日期
:return: 最优的id
'''
......@@ -305,6 +305,22 @@ class PortfoliosBuilder(ABC):
pass
class PortfoliosChecker(ABC):
'''
投组组合检测器
'''
@abstractmethod
def check(self, day=None, portfolios=None):
"""
检测避免出现最优投组同时出现全部是ft或美盛基金的情况，增加一步替换动作。
@param day:
@param portfolios:
@return:
"""
pass
class Solver(ABC):
'''
解算器
......
asset_pool/asset_optimize.py
View file @ 4a5dbfe8
......@@ -110,7 +110,7 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
sortino['score'] = sortino.apply(lambda r: sum([x['weight'] * r[x['name']] for x in self._config]), axis=1)
sortino.sort_values('score', ascending=False, inplace=True)
# 取得分数高的前optimize_count个
return pct_change.columns[sortino.index[0:self.optimize_count]].values
return pct_change.columns[sortino.index[0:self.optimize_count]].values,sortino['score']
def get_optimize_pool(self, day):
opt_pool = rop.get_one(day=day, type=AssetPoolType.OPTIMIZE)
......@@ -125,7 +125,7 @@ class FundDividendSortinoAssetOptimize(SortinoAssetOptimize):
for fund_group in self.get_groups():
fund_group = [x for x in fund_group if min_dates[x] <= max_incept_date]
if len(fund_group) > self.optimize_count:
pool.extend(self.find_optimize(tuple(fund_group), day))
pool.extend(self.find_optimize(tuple(fund_group), day)[0])
elif len(fund_group) <= self.optimize_count:
pool.extend(fund_group)
rop.insert(day, AssetPoolType.OPTIMIZE, sorted(pool))
......
config-svrobo4.yml
View file @ 4a5dbfe8
......@@ -107,6 +107,9 @@ portfolios: # 投组模块
# high-weight: [ 1 ] # 最高权重比例，可给一个值，也可以给多个值，当多个值时，第一个表示只有一个资产时权重，第二个表示只有两个资产时权重，以此类推，最后一个表示其他资产个数时的权重
poem: # poem相关
cvar-scale-factor: 0.1 # 计算时用到的系数
checker: #投组检测模块
switch: off #是否开启检查
custom-type-priority: [ 3,2,1,4 ] # 检测优先级
reports: # 报告模块相关
navs:
type: FUND
......
config-svrobo5.yml
View file @ 4a5dbfe8
......@@ -112,6 +112,9 @@ portfolios: # 投组模块
# high-weight: [ 1 ] # 最高权重比例，可给一个值，也可以给多个值，当多个值时，第一个表示只有一个资产时权重，第二个表示只有两个资产时权重，以此类推，最后一个表示其他资产个数时的权重
poem: # poem相关
cvar-scale-factor: 0.1 # 计算时用到的系数
checker: #投组检测模块
switch: off #是否开启检查
custom-type-priority: [ 3,2,1,4 ] # 检测优先级
reports: # 报告模块相关
navs:
type: FUND
......
config-svrobo6.yml
View file @ 4a5dbfe8
......@@ -111,6 +111,9 @@ portfolios: # 投组模块
high-weight: [ 0.35 ] # 最高权重比例，可给一个值，也可以给多个值，当多个值时，第一个表示只有一个资产时权重，第二个表示只有两个资产时权重，以此类推，最后一个表示其他资产个数时的权重
poem: # poem相关
cvar-scale-factor: 0.1 # 计算时用到的系数
checker: #投组检测模块
switch: on #是否开启检查
custom-type-priority: [ 3,2,1,4 ] # 检测优先级
reports: # 报告模块相关
navs:
type: FUND
......
config-svrobo_Mdiv_PRR3.yml 0 → 100644
View file @ 4a5dbfe8
py-jftech:
logger:
version: 1
formatters:
brief:
format: "%(asctime)s - %(levelname)s - %(message)s"
simple:
format: "%(asctime)s - %(filename)s - %(levelname)s - %(message)s"
handlers:
console:
class: logging.StreamHandler
formatter: simple
level: DEBUG
stream: ext://sys.stdout
file:
class: logging.handlers.TimedRotatingFileHandler
level: INFO
formatter: brief
filename: ${LOG_FILE:logs/info.log}
interval: 1
backupCount: 30
encoding: utf8
when: D
# loggers:
# basic.sync:
# level: DEBUG
# handlers: [console]
# propagate: no
root:
level: ${LOG_LEVEL:INFO}
handlers: ${LOG_HANDLERS:[ console ]}
database:
host: ${MYSQL_HOST:192.168.68.85}
port: ${MYSQL_PORT:3306}
user: ${MYSQL_USER:root}
password: ${MYSQL_PWD:changeit}
dbname: ${MYSQL_DBNAME:mdiv_prr3} # mdiv_prr3
injectable:
names:
backtest: robo_executor.BacktestExecutor
datum: basic.datum.DefaultDatum
hold-report: portfolios.holder.DivHoldReportor
mpt: portfolios.builder.PoemARCPortfoliosBuilder
dividend-holder: portfolios.holder.InvTrustPortfoliosHolder
navs-sync: basic.sync.FundNavSync
email:
server: smtphz.qiye.163.com
user: jft-ra@thizgroup.com
password: 5dbb#30ec6d3
mulit-process:
max-workers: ${MAX_PROCESS:1}
basic: # 基础信息模块
sync:
start-date: 1990-01-01 # 同步数据开始日期
datum: # 资料模块
change:
date: ${DATUM_CHANGE_DATE}
file: ${DATUM_CHANGE_FILE}
excludes: # 排除的资料彭博ticker
# backtest:
# - 'TEMDLRI LX Equity' # 富蘭克林坦伯頓全球投資系列-美元短期票券基金 美元A(Mdis)股
# - 'LMWADMU ID Equity' # 美盛西方資產全球藍籌債券基金 A 美元 配息
# - 'TGEIADI LX Equity' # 富蘭克林坦伯頓全球投資系列-全球股票收益基金 美元A穩定月配息股
real:
- 'FGFSACU LX Equity'
navs: # 净值模块
exrate: # 汇率，如果不开启，整个这块注释掉
- from: EUR # 需要转换的货币类型
ticker: EURUSD BGN Curncy # 汇率值的彭博ticker
asset-pool: # 资产池模块
asset-optimize: # 资产优选模块
sortino-weight: # sortino计算需要的权重，下面每一条为一次计算，e.g. months: 3, weight: 0.5 表示 3个月数据使用权重0.5来计算分值
- months: 3
weight: 0.5
- months: 6
weight: 0.3
- years: 1
weight: 0.2
asset-include: {'customType':[1,2,3,4]}
optimize-count: 3 #基金优选个数
portfolios: # 投组模块
holder: # 持仓投组相关
init-nav: 100 # 初始金额
min-interval-days: 10 # 两次实际调仓最小间隔期，单位交易日
dividend-rate: 0.0 #设定年化配息率
dividend-date: 15 #配息日，每月15号
dividend-adjust-day: [1,4,7,10] #每年的首个季度调整配息
warehouse-frequency: 1 #每隔1个月调一次仓
warehouse-transfer-date: 1 #调仓日
redeem-list: [ 'TEUSAAU LX Equity', 'LIGTRAA ID Equity', 'TEMFHAC LX Equity', 'LUSHUAA ID Equity' ] #从持仓中的低风险资产“直接”按序赎回
solver: # 解算器相关
model: prr # 结算模型 ARC ,PRR, ~ 标准解算器
arc: on #是否开启ARC
brr: 0.02 #误差补偿值
trr: 3
tol: 1E-10 # 误差满足条件
navs: # 净值要求
range: # 需要净值数据的区间, days: 90 表示90自然日，months: 3 表示3个自然月
days: 90
max-nan: # 最大缺失净值条件
asset: 8 # 单一资产最多缺少多少交易日数据，则踢出资产池
day: 0.5 # 单一交易日最多缺少百分之多少净值，则删除该交易日
risk: [] # 资产风险等级要求，可分开写也可以合并写，e.g. risk：[ 2, 3 ] 则表示 所有投组资产风险等级都是 2 或 3
LARC: [0.30, 0.00, 0.00] #低阈值
UARC: [0.70, 0.70, 0.70] #高阈值
matrix-rtn-days: 20 # 计算回报率矩阵时，回报率滚动天数
asset-count: [5,5] # 投组资产个数。e.g. count 或 [min, max] 分别表示 最大最小都为count 或 最小为min 最大为max，另外这里也可以类似上面给不同风险等级分别配置
mpt: # mpt计算相关
cvar-beta: 0.2 # 计算Kbeta 需要用到
quantile: 0.9 # 分位点，也可以给不同风险等级分别配置
low-weight: 0.05 # 最低权重
high-weight: [ 0.35 ] # 最高权重比例，可给一个值，也可以给多个值，当多个值时，第一个表示只有一个资产时权重，第二个表示只有两个资产时权重，以此类推，最后一个表示其他资产个数时的权重
poem: # poem相关
cvar-scale-factor: 0.1 # 计算时用到的系数
checker: #投组检测模块
switch: on #是否开启检查
custom-type-priority: [3,2,1,4] # 检测优先级
reports: # 报告模块相关
navs:
type: FUND
tickers:
- TEMTECI LX Equity
- TEPLX US Equity
- FRDPX US Equity
- FKRCX US Equity
- FTNRACU LX Equity
benchmark: # benchmark报告
ft:
init-amount: 100 # 初始金额
stock-rate: # stock型基金比例
RR3: 0.3
RR4: 0.5
RR5: 0.7
fixed-range: # 固定区间收益率
range-dates: # 固定起始截止日期
- start: 2008-01-01
end: 2008-10-27
- start: 2011-05-02
end: 2011-10-04
- start: 2013-05-08
end: 2013-06-24
- start: 2014-09-03
end: 2014-12-16
- start: 2015-04-28
end: 2016-01-21
- start: 2018-01-26
end: 2018-10-29
- start: 2020-01-20
end: 2020-03-23
relative-range: # 相对区间收益率
range-dates: # 相对时间周期
- days: 1
name: '一天'
- weeks: 1
name: '一周'
- months: 1
name: '一月'
- months: 3
name: '三月'
- months: 6
name: '六月'
- years: 1
name: '一年'
- years: 2
name: '两年'
- years: 3
name: '三年'
- years: 5
name: '五年'
- years: 10
name: '十年'
- dates: ~
name: '成立以来'
exports:
backtest: # 回测导出曹策略
save-path: ${EXPORT_PATH:excels} # 导出报告文件存放路径，如果以./或者../开头，则会以执行python文件为根目录，如果以/开头，则为系统绝对路径，否则，以项目目录为根目录
file-name: ${EXPORT_FILENAME:real} # 导出报告的文件名
save-config: ${EXPORT_CONFIG:off} # 是否保存配置文件
include-report: # 需要导出的报告类型列表，下面的顺序，也代表了excel中sheet的顺序
# - funds-report # 基金资料
# - navs-report # 净值报告
- hold-report # 持仓报告
- signal-report # 信号报告
- benckmark-report # benckmark报告
- combo-report # 持仓对比
- indicators-report # 各种特殊指标报告
- fixed-range-report # 固定区间收益报告
- relative-range-report # 相对区间收益报告
- year-range-report # 单年区间业绩报告
- month-div-rate-report # 月度配息率比较
- year-div-rate-report # 年度配息率比较
real-daily:
file-name: svROBO6_portfolios
include-report:
- daily-hold-report
- daily-signal-report
email:
receives:
- wenwen.tang@thizgroup.com
copies: ${DAILY_EMAIL_COPIES}
subject:
default: "ROBO6_TAIBEI-实盘版-每日投組推薦_{today}"
rebalance: "ROBO6_TAIBEI-实盘版-每日投組推薦_{today}_今日有調倉信號！！！"
content:
default: "Dear All: 附件是今天生成的推薦組合，請驗收，謝謝！ 注>：該郵件為自動發送，如有問題請聯繫矽谷團隊 telan_qian@chifufund.com"
rebalance: "Dear All: 附件是今天生成的推薦組合以及調倉信號，請驗收，謝謝！ 注>：該郵件為自動發送，如有問題請聯繫矽谷團隊 telan_qian@chifufund.com"
daily-monitor:
file-name: svROBO6_monitor
include-report:
- name: relative-range-report # 相对区间收益报告
min-date: ~
- name: contribution-report # 贡献率报告
min-date: {days: 30}
- name: high-weight-report # 高风险资产占比
min-date: {days: 30}
- name: asset-pool-report # 基金池
min-date: {days: 30}
- name: combo-report # 持仓报告
min-date: {days: 40}
- name: mpt-report
min-date: {days: 30}
- name: signal-report
min-date: ~
- name: crisis-one-report
min-date: {days: 30}
- name: crisis-two-report
min-date: {days: 30}
- name: market-right-report
min-date: {days: 30}
- name: drift-buy-report
min-date: {days: 30}
email:
receives:
- wenwen.tang@thizgroup.com
copies: ${MONITOR_EMAIL_COPIES}
subject: "SVROBO6-实盘版-每日监测_{today}"
content: "Dear All: 附件是今天生成的监测数据，請驗收，謝謝！ 注>：該郵件為自動發送，如有問題請聯繫矽谷團隊 telan_qian@chifufund.com"
robo-executor: # 执行器相关
use: ${ROBO_EXECUTOR:backtest} # 执行哪个执行器，优先取系统环境变量ROBO_EXECUTOR的值，默认backtest
sync-data: ${SYNC_DATA:off} # 是否开启同步资料数据
backtest: # 回测执行器相关
start-date: 2023-01-02 # 回测起始日期
end-date: 2023-10-31 # 回测截止日期
sealing-period: 10 #调仓封闭期
start-step: ${BACKTEST_START_STEP:1} # 回测从哪一步开始执行 1:计算资产池；2:计算最优投组：3:计算再平衡信号以及持仓投组
end-step: ${BACKTEST_END_STEP:3} # 回测从哪一步执行完成后结束执行 1:计算资产池；2:计算最优投组：3:计算再平衡信号以及持仓投组
clean-up: off
real: # 实盘执行器
export: ${EXPORT_ENABLE:off} # 是否开启报告
start-date: 2023-05-08 # 实盘开始时间
include-date: []
portfolios/builder.py
View file @ 4a5dbfe8
......@@ -4,7 +4,8 @@ import logging
from py_jftech import component, autowired, format_date
from pymysql import IntegrityError, constants
from api import PortfoliosBuilder, PortfoliosRisk, AssetPool, Navs, PortfoliosType, Datum, SolveType, SolverFactory
from api import PortfoliosBuilder, PortfoliosRisk, AssetPool, Navs, PortfoliosType, Datum, SolveType, SolverFactory, \
PortfoliosChecker
from portfolios.dao import robo_mpt_portfolios as rmp
logger = logging.getLogger(__name__)
......@@ -14,11 +15,13 @@ logger = logging.getLogger(__name__)
class MptPortfoliosBuilder(PortfoliosBuilder):
@autowired
def __init__(self, assets: AssetPool = None, navs: Navs = None, datum: Datum = None, factory: SolverFactory = None):
def __init__(self, assets: AssetPool = None, navs: Navs = None, datum: Datum = None, factory: SolverFactory = None,
checker: PortfoliosChecker = None):
self._assets = assets
self._navs = navs
self._datum = datum
self._factory = factory
self._checker = checker
def get_portfolios(self, day, risk: PortfoliosRisk, type: PortfoliosType = PortfoliosType.NORMAL):
try:
......@@ -26,6 +29,7 @@ class MptPortfoliosBuilder(PortfoliosBuilder):
if not portfolio:
result = self.build_portfolio(day, type)
for build_risk, datas in result.items():
datas['portfolio'] = self._checker.check(day, json.loads(datas['portfolio']))
try:
rmp.insert({
**datas,
......@@ -44,7 +48,7 @@ class MptPortfoliosBuilder(PortfoliosBuilder):
return None
except Exception as e:
logger.exception(
f"build protfolio of type[{type.name}] and risk[{risk.name}] with date[{format_date(day)}] failure.", e)
f"build portfolio of type[{type.name}] and risk[{risk.name}] with date[{format_date(day)}] failure.", e)
raise e
def build_portfolio(self, day, type: PortfoliosType):
......@@ -119,6 +123,7 @@ class MptARCPortfoliosBuilder(MptPortfoliosBuilder):
if not portfolio:
result, detail = self.build_portfolio(day, type)
for build_risk, datas in result.items():
datas['portfolio'] = self._checker.check(day, json.loads(datas['portfolio']))
try:
rmp.insert({
**datas,
......
portfolios/checker.py 0 → 100644
View file @ 4a5dbfe8
import logging
from py_jftech import autowired, component, get_config
from api import AssetOptimize, PortfoliosChecker, Datum, Navs, DatumType
logger = logging.getLogger(__name__)
@component(bean_name='checker')
class DefaultPortfoliosChecker(PortfoliosChecker):
@autowired
def __init__(self, asset: AssetOptimize = None, navs: Navs = None, datum: Datum = None):
self._asset = asset
self._navs = navs
self._datum = datum
self._config = get_config(__name__)
def check(self, day=None, portfolios: dict = None):
if not self._config.get('switch'):
return portfolios
funds = self._datum.get_datums(type=DatumType.FUND)
company = {f"{fund['id']}": fund['companyType'] for fund in funds}
customType = {f"{fund['id']}": fund['customType'] for fund in funds}
companies = set(company[key] for key in portfolios.keys())
# 同时出现全部是ft或美盛基金的情况
if len(companies) == 1:
# step1: 检查原始投组的customType。检查顺序用列表呈现，依序进行
priority = self._config.get('custom-type-priority')
for p in priority:
keys = [key for key in portfolios.keys() if customType[key] == p]
# 若存在匹配值则执行后跳出循环
if len(keys) > 0:
ids = [fund['id'] for fund in funds if fund['companyType'] != list(companies)[0]]
best = self.find_highest_score(ids, day)
# 若刚好有一个匹配，直接替换
if len(keys) == 1:
portfolios[best] = portfolios[keys[0]]
# 删除原始键
del portfolios[keys[0]]
else:
# 算分，把分低的替换掉
scores = self.do_score(keys, day)
weight_scores = {key: scores[key]*portfolios[key] for key in keys}
lowest = min(scores, key=lambda k: weight_scores[k])
portfolios[best] = portfolios[lowest]
# 删除原始键
del portfolios[lowest]
break
return portfolios
def do_score(self, ids, day):
optimize = self._asset.find_optimize(fund_ids=ids, day=day)
scores = optimize[1].to_dict()
id_score = {}
for k, v in scores.items():
id_score[f'{ids[k]}'] = v
return id_score
def find_highest_score(self, ids, day):
optimize = self._asset.find_optimize(fund_ids=ids, day=day)
return optimize[0][0]
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