Consensus estimates

Obtain consensus expectations of non-cyclical indicators

Method name: get_consensus_nonperiod

Latest data only

Enter parameters

Field	Type	Description	Is it required
symbol	Optional[Union[str, List[str]]]	Stock code	Optional
fields	Optional[Union[str, List[str]]]	Return fields	Optional
market	str	Market, supports `hk`, `us`, default is `hk`	required

Response parameters

Note: For parameters other than symbol, currency, and indicator, the default is the prediction of the latest date, and there are historical dimension derived fields. The derived suffix is week, and 1month~12month constitutes a total of thirteen derived fields for each field, indicating the predicted value of the corresponding field one week, one month to twelve months ago. Example: mean_week represents the predicted mean one week ago, std_6month represents the predicted standard deviation six months ago.

Field	Type	Description
symbol	str	stock code
currency	str	currency unit
indicator	str	Indicator name: LTGROWTH is the long-term growth in the next 3 to 5 years, TP is the target price in the next 1 year
mean	double	predicted mean
median	double	predicted median
high	double	predicted highest value
low	double	predicted lowest value
std	double	forecast standard deviation
estimates_num	double	forecast number
included_estimates_num	double	Number of forecasts included in statistics

Usage examples

Obtain some consensus expectations of all Hong Kong stock non-cyclical indicators

import tqx_data
result = tqx_data.get_consensus_nonperiod(
    market='hk',
    symbol=[""],
    fields=["indicator","mean","std_6month","high_week"]
)
print(result)

Response Example

symbol indicator mean std_6month high_week
0001.HK LTGROWTH 4.60000 NaN 4.60
0001.HK TP 69.43333 1.50000 78.00
0002.HK LTGROWTH 2.70000 0.00000 2.70
0002.HK TP 77.02000 4.06262 86.64
0003.HK LTGROWTH 6.38000 0.00000 7.30
.. ... ... ... ... ...
9996.HK TP 9.43200 0.55741 10.66
9997.HK LTGROWTH NaN 0.00000 NaN
9997.HK TP NaN 0.00000 NaN
9999.HK LTGROWTH 4.80000 0.00000 4.80
9999.HK TP 235.88571 46.77894 289.00

Obtain consensus expectations for buying and selling recommendations

Method name: get_consensus_recommend

Latest data only

Enter parameters

Field	Type	Description	Is it required
symbol	Optional[Union[str, List[str]]]	Stock code	Optional
fields	Optional[Union[str, List[str]]]	Return fields	Optional
market	str	Market, supports `hk`, `us`, default is `hk`	required

Response parameters

Note 1: For parameters other than symbol and currency, the default is the prediction of the latest date, and there are historical dimension derived fields. The derived suffix is week, and 1month~12month constitutes a total of thirteen derived fields for each field, indicating the predicted value of the corresponding field one week, one month to twelve months ago. Example: mean_week represents the expected mean one week ago, and low_6month represents the expected lowest value 6 months ago. Note 2: Strong sell, sell, hold, buy, and strong buy are scored as 5, 4, 3, 2, and 1 in sequence.

Field	Type	Description
symbol	str	stock code
currency	str	currency unit
mean	double	expected mean
median	double	expected median
high	double	expected highest value
low	double	expected lowest value
strong_buy_num	double	Number of strong buy recommendations
buy_num	double	Number of buy recommendations
hold	double	recommended number of positions
sell_num	double	Sell recommendation number
strong_sell_num	double	Number of strong sell recommendations
no_opinion_num	double	No opinion number
recommendations_num	double	total number of recommendations

Usage examples

Obtain some consensus expectations for all Hong Kong stock trading recommendations

import tqx_data
result = tqx_data.get_consensus_recommend(
    market='hk',
    symbol=[""],
    fields=["strong_buy_num","buy_num_week"]
)
print(result)

Response Example

symbol strong_buy_num buy_num_week
0001.HK 2.0 5.0
0002.HK 1.0 2.0
0003.HK 1.0 2.0
0004.HK 0.0 2.0
0005.HK 3.0 6.0
.. ... ... ...
9992.HK 12.0 14.0
9995.HK 6.0 6.0
9996.HK 1.0 3.0
9997.HK NaN NaN
9999.HK 7.0 12.0

3. Financial and market factors 1. Obtain Hong Kong and US stock backtest factors

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Consensus estimates

Obtain consensus expectations of non-cyclical indicators

Method name: get_consensus_nonperiod

Enter parameters

Response parameters

Usage examples

Obtain some consensus expectations of all Hong Kong stock non-cyclical indicators

Obtain consensus expectations for buying and selling recommendations

Method name: get_consensus_recommend

Enter parameters

Response parameters

Usage examples

Obtain some consensus expectations for all Hong Kong stock trading recommendations