For any company (e.g. Tesla) the API returns
- price targets calculated from analyst estimates: mean, median, highest, lowest, number of estimates
- news sentiment data (bullish vs bearish) based on published articles in the last week
It also returns trending stocks.
{
"symbol": "TSLA",
"priceTargets": {
"mean": 297.3333333333333,
"median": 300,
"highest": 500,
"lowest": 54,
"numberOfEstimates": 21
}
}{
"symbol": "TSLA",
"sentiment": {
"bullishPercent": 0.4062,
"bearishPercent": 0.5938
},
"buzz": {
"articlesInLastWeek": 143,
"weeklyAverage": 147.25,
"buzz": 0.9711
},
"sectorAverageBullishPercent": 0.6204,
"sectorAverageNewsScore": 0.52,
"companyNewsScore": 0.3969
}[
{
"ticker": "HAL",
"popularity": 10,
"sentiment": 10,
"consensusScore": 1,
"operations": null,
"sector": "BASIC MATERIALS",
"sectorID": 17343,
"marketCap": 18394572000,
"buy": 10,
"sell": 0,
"hold": 0,
"priceTarget": 32.42,
"rating": 5,
"companyName": "Halliburton",
"quarterlyTrend": 5,
"lastRatingDate": "2019年07月24日T00:00:00"
},
{
"ticker": "XLNX",
"popularity": 9,
"sentiment": 6,
"consensusScore": 1.6666666666666667,
"operations": null,
"sector": "CONSUMER GOODS",
"sectorID": 18731,
"marketCap": 27832018900,
"buy": 6,
"sell": 0,
"hold": 3,
"priceTarget": 131.6,
"rating": 4,
"companyName": "Xilinx Inc",
"quarterlyTrend": 4,
"lastRatingDate": "2019年07月26日T00:00:00"
}
]- Install Node.js (which includes
npm) if you haven't already. On Mac in the command line typebrew install node. More information here: nodejs.org - Set up a new Node.js project. In the command line type
mkdir my-new-project && cd my-new-projectto create a new foldernpm initto scaffold the Node.js projecttouch index.jsto create the fileindex.jsnpm install tipranks-api-v2to install the library to access the API- Copy/paste the example code below inside the
index.jsfile
const tipranksApi = require('tipranks-api-v2'); tipranksApi.getPriceTargets('MU').then(result => console.log(result)); tipranksApi.getNewsSentimentData('MU').then(result => console.log(result)); tipranksApi.getTrendingStocks().then(trending => console.log(trending));
node index.jsto run the code inside theindex.jsfile- Done! Now you should see the price targets and the news sentiment for the ticker
MU
The API supports the following commands:
.getPriceTargets(ticker)tickeris a string representing the company ticker, e.g.TSLA.- This method returns the mean price target, median target, highest target, lowest target, and the number of analyst estimates. See below for an example.
Note: The price calculator (e.g. mean price) only considers analyst price estimates given in the last 3 months. The API intentionally excludes estimates given more than three months ago as analysts seem to review/update their estimates in a quarterly interval. The result: under "Analyst ratings" on the website the "average price" for MU was 46.5 and the script displayed 46.77 for "mean" price.
-
.getNewsSentimentData(ticker)tickeris a string representing the company ticker, e.g.TSLA.- This method returns the bullish and bearish sentiment in percent, the number of articles published last week, sector average bullish percent, sector average news score, and the company's news score. See example below.
-
.getTrendingStocks()- Returns an array of trending stocks listed on tipranks.com/trending-stocks
- Copy the code below into the
index.jsfile node index.jsto run the code
const tipranksApi = require('tipranks-api-v2'); tipranksApi.getPriceTargets('TSLA').then(result => console.log(result));
{
"symbol": "TSLA",
"priceTargets": {
"mean": 297.3333333333333,
"median": 300,
"highest": 500,
"lowest": 54,
"numberOfEstimates": 21
}
}- Copy the code below into the
index.jsfile node index.jsto run the code
const tipranksApi = require('tipranks-api-v2'); tipranksApi.getNewsSentimentData('TSLA').then(result => console.log(result));
{
"symbol": "TSLA",
"sentiment": {
"bullishPercent": 0.4062,
"bearishPercent": 0.5938
},
"buzz": {
"articlesInLastWeek": 143,
"weeklyAverage": 147.25,
"buzz": 0.9711
},
"sectorAverageBullishPercent": 0.6204,
"sectorAverageNewsScore": 0.52,
"companyNewsScore": 0.3969
}