36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
# -*- coding: utf-8 -*-
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"""服务器调试：两级状态桶在 000993 上的真实分布"""
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import sys
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import warnings
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sys.path.insert(0, '/opt/a_stock_timeline')
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warnings.filterwarnings('ignore')
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from src.fetcher.kline_fetcher import KlineFetcher
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from src.quant.model import per_stock_expected, _bucket, rsi_series
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import numpy as np
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import pandas as pd
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DB = '/opt/a_stock_timeline/data/a_stock.db'
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kf = KlineFetcher(DB)
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k = kf.load('000993', 'day', 150)
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print('bars:', len(k))
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close = k['close'].reset_index(drop=True)
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ma20 = close.rolling(20).mean()
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rsi = rsi_series(close)
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for fine in (True, False):
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cur = _bucket(close.iloc[-1], ma20.iloc[-1], rsi.iloc[-1], fine)
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rets = []
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horizon = 5
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for t in range(30, len(close) - horizon):
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b = _bucket(close.iloc[t], ma20.iloc[t], rsi.iloc[t], fine)
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if b == cur:
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rets.append(close.iloc[t + horizon] / close.iloc[t] - 1)
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med = float(np.median(rets)) if rets else None
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print('fine={} 桶={} 样本={} 中位={}'.format(fine, cur, len(rets), med))
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med, n, bucket = per_stock_expected(k)
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print('per_stock_expected:', med, n, bucket)
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