finlab.analysis

finlab.analysis.liquidityAnalysis.LiquidityAnalysis

LiquidityAnalysis(required_volume=200000, required_turnover=1000000)

Bases: Analysis

分析台股策略流動性風險項目的機率

Note

參考VIP限定文章更了解流動性檢測內容細節。

Args: required_volume (int): 要求進出場時的單日成交股數至少要多少？ required_turnover (int): 要求進出場時的單日成交金額至少要多少元？避免成交股數夠，但因低價股因素，造成胃納量仍無法符合資金需求。

Examples:

# better syntax
report.run_analysis('LiquidityAnalysis', required_volume=100000)

# original syntax
from finlab.analysis.liquidityAnalysis import LiquidityAnalysis
report.run_analysis(LiquidityAnalysis(required_volume=100000))

is_market_supported

is_market_supported(market)

Check if the market is supported for liquidity analysis.

Currently only Taiwan stock market is supported, as it has unique features like disposal stocks, warning stocks, full delivery stocks, and price limit regulations.

策略流動性檢測

finlab.analysis.inequalityAnalysis.InequalityAnalysis

InequalityAnalysis(name, df=None, date_type='entry_sig_date', target='return')

Bases: Analysis

Analyze return of trades with condition inequality

PARAMETER	DESCRIPTION
`name`	name of the condition TYPE: `str`
`df`	value used in condition. If df is None, `data.get(name)` will be automatically perform to fetch the values. TYPE: `DataFrame or None` DEFAULT: `None`
`date_type`	can be either `entry_date`, `entry_sig_date`, `exit_date`, `exit_sig_date`. TYPE: `str` DEFAULT: `'entry_sig_date'`
`target`	the target to optimize. Any column name in report.get_trades() TYPE: `str` DEFAULT: `'return'`

Examples:

report.run_analysis('InequalityAnalysis', name='price_earning_ratio:股價淨值比')

策略不等式因子分析

finlab.analysis.periodStatsAnalysis.PeriodStatsAnalysis

PeriodStatsAnalysis()

Bases: Analysis

分析台股策略的不同時期與大盤指標作比較

Examples:

可以執行以下程式碼來產生分析結果：

report.run_analysis('PeriodStatsAnalysis')

產生的結果：

	benchmark	strategy
('overall_daily', 'calmar_ratio')	0.149192	0.0655645
('overall_daily', 'sortino_ratio')	0.677986	0.447837
('overall_daily', 'sharpe_ratio')	0.532014	0.306351
('overall_daily', 'profit_factor')	1.20022	1.07741
('overall_daily', 'tail_ratio')	0.914881	0.987751
('overall_daily', 'return')	0.0835801	0.0478957
('overall_daily', 'volatility')	0.182167	0.312543
('overall_monthly', 'calmar_ratio')	0.155321	0.0731378
('overall_monthly', 'sortino_ratio')	0.697382	0.439003
('overall_monthly', 'sharpe_ratio')	0.524943	0.307292
('overall_monthly', 'profit_factor')	1.75714	1.27059
('overall_monthly', 'tail_ratio')	1.03322	0.903335
('overall_monthly', 'return')	0.0836545	0.0479377
('overall_monthly', 'volatility')	0.186989	0.316178
('overall_yearly', 'calmar_ratio')	0.436075	0.127784
('overall_yearly', 'sortino_ratio')	0.738327	0.694786
('overall_yearly', 'sharpe_ratio')	0.407324	0.350986
('overall_yearly', 'profit_factor')	2.2	1.66667
('overall_yearly', 'tail_ratio')	1.71647	1.359
('overall_yearly', 'return')	0.0814469	0.0663674
('overall_yearly', 'volatility')	0.284742	0.419087

假如希望開發交易分析系統，可以繼承 finlab.analysis.Analysis 來實做分析。

finlab.analysis.Analysis

Bases: ABC

analyze

analyze(report)

Analyze trading report.

One could assume self.caluclate_trade_info will be executed before self.analyze, so the report.get_trades() will contain the required trade info.

calculate_trade_info

calculate_trade_info(report)

Additional trade info can be calculated easily.

User could override this function if additional trade info is required for later anlaysis.

Examples:

from finlab.analysis import Analysis

class SomeAnalysis(Analysis):
  def calculate_trade_info(self, report):
    return [
      ['股價淨值比', data.get('price_earning_ratio:股價淨值比'), 'entry_sig_date']
    ]

report.run_analysis(SomeAnalysis())
trades = report.get_trades()

assert '股價淨值比@entry_sig_date' in trades.columns

print(trades)

display

display()

Display result

When implement this function, returning Plotly figure instance is recommended.

is_market_supported

is_market_supported(market)

Check if market info is supported

RETURNS	DESCRIPTION
`bool`	True, support. False not support.