美股 研發成長股策略

In [ ]:

%%capture
!pip install finlab
!pip install ta-lib-bin

%%capture !pip install finlab !pip install ta-lib-bin

研發費用催化劑¶

投入較多資源進行研發的公司，會較受市場青睞而被給予較高的估值嗎？

In [ ]:

from finlab import data
from finlab.backtest import sim

close = data.get('us_price:close')
revenue = data.get('us_fundamental:revenue')
eps = data.get('us_fundamental:eps')
# 研發費用
rnd = data.get('us_fundamental:rnd')
# 投資人投入資本
invcap = data.get('us_fundamental:invcap')

# 選出研發費用成長為排名前10%個股
condition1 = rnd.pct_change() > rnd.pct_change().quantile_row(0.9)
condition2 =  eps > eps.average(2)
condition3 = invcap > invcap.average(2)
condition4 = close > close.average(250)

# 再以ESP及投資人投入資本增加、收盤價站上年線為濾網
position = condition1 & condition2 & condition3 & condition4

# 最後以營收成長率作為排序篩選出最大的前15名標的
revenue_growth = revenue.pct_change().index_str_to_date()
position *= revenue_growth
position = position.is_largest(10)
report = sim(position, resample='M', name='美股研發成長股策略', stop_loss=0.15, position_limit=0.2)
# report.display()

from finlab import data from finlab.backtest import sim close = data.get('us_price:close') revenue = data.get('us_fundamental:revenue') eps = data.get('us_fundamental:eps') # 研發費用 rnd = data.get('us_fundamental:rnd') # 投資人投入資本 invcap = data.get('us_fundamental:invcap') # 選出研發費用成長為排名前10%個股 condition1 = rnd.pct_change() > rnd.pct_change().quantile_row(0.9) condition2 = eps > eps.average(2) condition3 = invcap > invcap.average(2) condition4 = close > close.average(250) # 再以ESP及投資人投入資本增加、收盤價站上年線為濾網 position = condition1 & condition2 & condition3 & condition4 # 最後以營收成長率作為排序篩選出最大的前15名標的 revenue_growth = revenue.pct_change().index_str_to_date() position *= revenue_growth position = position.is_largest(10) report = sim(position, resample='M', name='美股研發成長股策略', stop_loss=0.15, position_limit=0.2) # report.display()

/usr/local/lib/python3.10/dist-packages/finlab/analysis/alphaBetaAnalysis.py:22: RuntimeWarning:

invalid value encountered in double_scalars

/usr/local/lib/python3.10/dist-packages/finlab/analysis/alphaBetaAnalysis.py:22: RuntimeWarning:

invalid value encountered in double_scalars

	annualized_rate_of_return	sharpe	max_drawdown	win_ratio
	25.17%	0.77	-34.71%	41.38%

	entry_date	exit_date	entry_sig_date	exit_sig_date	position	period	entry_index	exit_index	return	trade_price@entry_date	trade_price@exit_date	mae	gmfe	bmfe	mdd	pdays	weight	next_weights
stock_id
TIO TINGO GROUP INC	2023-06-01	2023-06-06	2023-05-31	2023-06-05	0.1	3.0	1613.0	1616.0	-0.580952	3.150	1.32	-0.580952	0.000000	0.000000	-0.580952	0.0	0.0	0.1
ALAR ALARUM TECHNOLOGIES LTD	2023-06-01	NaT	2023-05-31	2023-06-30	0.1	7.0	1613.0	-1.0	-0.133627	2.724	2.36	-0.137298	0.000000	0.000000	-0.137298	0.0	0.1	0.0
ASUR ASURE SOFTWARE INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	-0.026917	12.260	11.93	-0.026917	0.041599	0.041599	-0.065779	4.0	0.1	0.1
EH EHANG HOLDINGS LTD	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	0.030870	10.690	11.02	0.000000	0.035547	0.000000	-0.026388	6.0	0.1	0.1
GHSI GUARDION HEALTH SCIENCES INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	-0.018003	6.110	6.00	-0.018003	0.014730	0.014730	-0.032258	2.0	0.1	0.1
INVA INNOVIVA INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	0.014493	13.110	13.30	-0.003814	0.046529	0.006865	-0.030612	5.0	0.1	0.1
MRNS MARINUS PHARMACEUTICALS INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	0.443213	7.220	10.42	0.000000	0.443213	0.000000	0.000000	6.0	0.1	0.1
RXDX PROMETHEUS BIOSCIENCES INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	0.001712	198.650	198.99	0.000000	0.001712	0.000000	-0.000151	6.0	0.1	0.1
VTSI VIRTRA INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	0.078811	7.740	8.35	0.000000	0.078811	0.000000	-0.012706	6.0	0.1	0.1
WWD WOODWARD INC	2023-06-01	NaT	2023-05-31	NaT	0.1	7.0	1613.0	-1.0	0.040160	107.570	111.89	0.000000	0.053361	0.000000	-0.015708	6.0	0.1	0.1
UUUU ENERGY FUELS INC	NaT	NaT	2023-06-30	NaT	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.0	0.1

In [ ]: