Commit 7c7c9fc7 authored by 吕先亚's avatar 吕先亚

动态调整UARC

parent b972442a
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:stable_prr3_t} # stable_prr3
injectable:
names:
backtest: robo_executor.BacktestExecutor
datum: basic.datum.DefaultDatum
hold-report: portfolios.holder.DivHoldReportor
mpt: portfolios.builder.RiskParityARCPortfoliosBuilder # 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:
- 'LCUAGAA ID Equity' # 美盛凱利美國積極成長基金 A 美元 累積
- 'TEMASAA LX Equity' # 富蘭克林坦伯頓全球投資系列-亞洲債券基金 美元A(acc)股
- 'TEMEMAU LX Equity' # 富蘭克林坦伯頓全球投資系列-新興國家固定收益基金 美元A(acc)股
- 'FTGBFAC LX Equity' # 富蘭克林坦伯頓全球投資系列-全球債券基金 美元A(acc)股
- 'TGTRFAA LX Equity' # 富蘭克林坦伯頓全球投資系列-全球債券總報酬基金 美元A(acc)股
- 'TGHYACU LX Equity' # 富蘭克林坦伯頓全球投資系列-全球非投資等級債券基金美元A(acc)股
- 'LEGOUAA ID Equity' # 美盛布蘭迪全球固定收益基金 A 美元 累積
- 'LGBOAAU ID Equity' # 美盛布蘭迪全球機會固定收益基金 A 美元 累積
# - 'TEMFHAC LX Equity' # 富蘭克林坦伯頓全球投資系列-公司債基金 美元A(acc)股 -> 20240722起可一般申购
real:
- 'LCUAGAA ID Equity' # 美盛凱利美國積極成長基金 A 美元 累積
- 'TEMASAA LX Equity' # 富蘭克林坦伯頓全球投資系列-亞洲債券基金 美元A(acc)股
- 'TEMEMAU LX Equity' # 富蘭克林坦伯頓全球投資系列-新興國家固定收益基金 美元A(acc)股
- 'FTGBFAC LX Equity' # 富蘭克林坦伯頓全球投資系列-全球債券基金 美元A(acc)股
- 'TGTRFAA LX Equity' # 富蘭克林坦伯頓全球投資系列-全球債券總報酬基金 美元A(acc)股
- 'TGHYACU LX Equity' # 富蘭克林坦伯頓全球投資系列-全球非投資等級債券基金美元A(acc)股
- 'LEGOUAA ID Equity' # 美盛布蘭迪全球固定收益基金 A 美元 累積
- 'LGBOAAU ID Equity' # 美盛布蘭迪全球機會固定收益基金 A 美元 累積
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: 4 #基金优选个数
annual-volatility-filter: #1各资产年化波动率末exclude位 2各资产年化波动率大于volatility
- customType: 2 # none
min-retain: 4
exclude: 0
volatility: 1000
- customType: 3 # none
min-retain: 4
exclude: 0
volatility: 1000
annual-volatility-section: # 波动率时间区间
- years: 1
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: 0.0 #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: [0.15, 0.00, 0.00, 0.00] #低阈值
UARC: [0.35, 0.75, 0.75, 0.75] #高阈值
fix-w: 0.01
fdtr-w: 0.02
cpiyoy-w: 0.1
cpi-expect: 2
max-w: 0.75
uarc-index: 3
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: [ 0.50 ] # 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
month-fund-filter: {4:['XXX ID Equity']} # 'LMAOMPU ID Equity' 根据月份删除某几档基金,51勞動節:美盛西方資產亞洲機會債券基金 A 增益配息 (M) 美元
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: SteadyFoF_prr3(實盤)-每月投組推薦
include-report:
# - daily-hold-report
- daily-signal-report
# - daily-mpt-report
email:
receives:
- brody_wu@chifufund.com
copies:
- wenwen.tang@thizgroup.com
subject:
# default: "SteadyFoF_prr3(實盤)-每日投組推薦_{today}"
rebalance: "SteadyFoF_prr3(實盤)-每月投組推薦_{today}"
content:
# default: "Dear All: 附檔為今日投資組合推薦,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 brody_wu@chifufund.com"
rebalance: "Dear All: 附檔為每月投資組合推薦,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 brody_wu@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:on} # 是否开启同步资料数据
backtest: # 回测执行器相关
start-date: 2023-10-02 # 回测起始日期
end-date: 2024-10-01 # 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:on} # 是否开启报告
start-date: 2023-05-08 # 实盘开始时间
include-date: []
web:
guid: AB088E61-FAB1-4466-B6AD-6E8AE253391E
port: 8081
......@@ -95,6 +95,7 @@ class PoemPortfoliosBuilder(MptPortfoliosBuilder):
portfolios = {}
for risk in PortfoliosRisk:
solver = self._factory.create_solver(risk, type)
self.__day = day
navs_group = solver.reset_navs(day)
for category, navs in navs_group.items():
solver.set_navs(navs)
......@@ -222,5 +223,3 @@ class RiskParityARCPortfoliosBuilder(MptPortfoliosBuilder):
'solve': SolveType.INFEASIBLE
}
return result
import math
import os
import statistics
import sys
from logging import DEBUG, getLogger
......@@ -196,7 +197,7 @@ class DefaultSolver(Solver):
model = self.create_model()
model.objective = Objective(expr=sum(
[(model.z[i] * model.w[i] * (self.risk_parity_sigma.iloc[i] @ model.w) - model.z[j] * model.w[j] * (
self.risk_parity_sigma.iloc[j] @ model.w)) ** 2
self.risk_parity_sigma.iloc[j] @ model.w)) ** 2
for i in model.indices for j in model.indices]), sense=minimize)
self._solver.solve(model)
return self.calc_port_weight(model)
......@@ -344,6 +345,26 @@ class ARCSolver(DefaultSolver):
count = self.get_config('asset-count')
return min(count[0] if isinstance(count, list) else count, len(self.rtn_annualized))
@property
def LARC(self):
return self._config['LARC']
@property
def UARC(self):
ecos = self._datum.get_datums(ticker=['CPI YOY Index', 'FDTR Index'])
cpi_id = [data['id'] for data in ecos if data['bloombergTicker'] == 'CPI YOY Index']
fdtr_id = [data['id'] for data in ecos if data['bloombergTicker'] == 'FDTR Index']
cpi = self._navs.get_last_eco_values(max_date=self.date, datum_id=cpi_id, count=2, by_release_date=True)
cpi = statistics.mean([c['indicator'] for c in cpi])
fdtr = self._navs.get_last_eco_values(max_date=self.date, datum_id=fdtr_id, by_release_date=True)['indicator']
cash_uarc = round(
self._config['fix-w'] + self._config['fdtr-w'] * fdtr + abs(cpi - self._config['cpi-expect']) *
self._config['cpiyoy-w'], 2)
cash_uarc = self._config['max-w'] if cash_uarc > self._config['max-w'] else cash_uarc
UARC = self._config['UARC']
UARC[self._config['uarc-index']] = cash_uarc
return UARC
def create_model(self):
low_weight = self.get_config('mpt.low-weight')
high_weight = self.get_config('mpt.high-weight')
......@@ -361,8 +382,8 @@ class ARCSolver(DefaultSolver):
model.cons_bounds_low = Constraint(model.indices, rule=lambda m, i: m.z[i] * low_weight <= m.w[i])
model.cons_bounds_up = Constraint(model.indices, rule=lambda m, i: m.z[i] * high_weight >= m.w[i])
if self._config['arc']:
LARC = self._config['LARC']
UARC = self._config['UARC']
LARC = self.LARC
UARC = self.UARC
numARC = len(LARC) # this is the M in the doc
numAsset = len(self.navs.columns)
......
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