Closed wickenden-g closed 4 years ago
- Is there a way to specify past x days, or specify the date on which I want the intraday data for?
I too would much like to see this since even though panda df slicing isnt a problem, trying to download a mass of data for one data point is quite expensive. This the most anticipated prospective feature of the Alpha Vantage API for me.
@sanjes1 @mark100net Can confirm. I have reached out to them several times with this^ inquiry (dating weeks back) but received no response... Maybe if we all send a request? haha
Ok, so they will talk, but you need to pay them. I subscribed to their monthly plan. They responded pretty quick. Also for my question they provide last 1 week~ of intraday 1 min data. I dont see any interface to request for a particular date
@sanjes1 The "~" 1 week of intraday depends on how many days the market is open out of the that last 7 I believe. I would use your premium status to request features such as that if you haven't already.
@SterlingButters I tried, They said, they are working on it to get more data and dont have any dates :)
Hi, Is there any way where we can get information of the corresponding sector for the stocks we get the data or any way we can pull the stock performance(API available) along with corresponding industries. i am working on stock predictions so checking i may get any help on this
What's the split coefficient supposed to be? I checked for some stocks that split and it was always 1.00
For me it has worked, using this formel for symbol, for european stocks:
Fingerprint Cards (STO: FING-B) == FING-B.STO Novo Nordisk (CPH: NOVO-B) == NOVO-B.CPH BMW (DE: BMW) == BMW.DE
I think you got the point ;)
If AlphaVantage are rearranging the letters in the acronyms of the stocks on different stock exchanges(for their API calls), they have to have a list clarifying the logic behind that. There IS no logic otherwise.
NSE:TITAN
@RomelTorres @thecodeflash, are you guys getting the correct timestamp for NSE:TITAN or any other NSE stock, i think it should show till 3:30 PM or something, it is showing 4:59.
NSE:TITAN
@RomelTorres @thecodeflash, are you guys getting the correct timestamp for NSE:TITAN or any other NSE stock, i think it should show till 3:30 PM or something, it is showing 4:59.
If you look at the time zone, it's in 6. Time Zone: "US/Eastern"
you'll have to convert it to IST if that's what you're looking for.
Check out this thread in StackOverflow that answers the question.
Hello,
I know this is a long thread with a lot of questions. I should not add another comment, but I will do now, because there is a repeated question without a real question.
To get the symbol of the instrument, you can search using ISIN. For example https://www.alphavantage.co/query?function=SYMBOL_SEARCH&keywords=FR0000120172&apikey=demo
{
"bestMatches": [
{
"1. symbol": "CA.PAR",
"2. name": "Carrefour SA",
"3. type": "Equity",
"4. region": "Paris",
"5. marketOpen": "09:00",
"6. marketClose": "17:30",
"7. timezone": "UTC+01",
"8. currency": "EUR",
"9. matchScore": "0.1667"
}
]
}
how to fetch data for nifty 50?can anyone help me with the url which fetch nifty 50 data
Hi @spateltc,
Currently, Alpha Vantage has support for stocks, crypto, TIs, sector, and FX. Index data you can get from pulling the individual stocks in the nifty 50.
how to fetch data for nifty 50?can anyone help me with the url which fetch nifty 50 data
The symbol is NFTY
. Use the search function as I pointed out in the previous comment to find the symbol. The first result is the correct one.
https://www.alphavantage.co/query?function=SYMBOL_SEARCH&keywords=NIFTY&apikey=${"apikey"}
{
"bestMatches": [
{
"1. symbol": "NFTY",
"2. name": "First Trust India NIFTY 50 Equal Weight ETF",
"3. type": "ETF",
"4. region": "United States",
"5. marketOpen": "09:30",
"6. marketClose": "16:00",
"7. timezone": "UTC-05",
"8. currency": "USD",
"9. matchScore": "0.8889"
},
{
"1. symbol": "ICICINIFTY.BSE",
"2. name": "ICICI Prudential Nifty ETF",
"3. type": "Equity",
"4. region": "India/Bombay",
"5. marketOpen": "09:15",
"6. marketClose": "15:30",
"7. timezone": "UTC+5.5",
"8. currency": "INR",
"9. matchScore": "0.5556"
}
]
}
Then fetch the data:
https://www.alphavantage.co/query?function=GLOBAL_QUOTE&symbol=NFTY&apikey=${"apikey"}
{
"Global Quote": {
"01. symbol": "NFTY",
"02. open": "34.8600",
"03. high": "34.8600",
"04. low": "34.8600",
"05. price": "34.8600",
"06. volume": "6",
"07. latest trading day": "2020-01-06",
"08. previous close": "34.9252",
"09. change": "-0.0652",
"10. change percent": "-0.1867%"
}
}
Please ignore my previous comment. It was about an ETF. As per @PatrickAlphaVantage 's answer, to calculate an index, calculate the components is a solution.
Thanks @jcisio for the info on the ETF
@PatrickAlphaVantage I was looking for an alternative to my costly provider and alphavantage was one of the candiates but it has some blocking problems. Now I've just found out another big problem: no index data :( I've just searching a few examples and it really does not have index data. We can also use maths to calculate, but then it adds extra complexity.
Hi folks, I am the OP of this Github issue. Appreciate the responses to my post (my inbox is exploding!), but frankly I don't feel comfortable seeing my review article morphing into tangential discussions. This issue is for reviewing the Alpha Vantage APIs, not for technical support or marketing campaigns.
Can the moderators do something about the off-topic posts?
Alpha Vantage API Review from a Python Developer
@RomelTorres congratulations on your wonderful python library for Alpha Vantage!
I am a full-stack python developer who uses the Alpha Vantage API to develop trading strategies for stocks, ETFs, and OTCs. I am wondering whether you are affiliated with Alpha Vantage, and whether this is a good place for me to leave a 360° review on their API service for future reference by the developer community.
So technically this is not a bug report or feature request - hope it's OK with you :)
The Experience
I was one of the "yahoo refugees" who stumbled upon Alpha Vantage via Google search. My first interactions with their website could be summarized by the good-old term WYSIWYG (what-you-see-is-what-you-get). Their documentation promised three things: (1) time series data with various resolutions, (2) over 50 technical signals, (3) sector data, and they kept their promise by providing demo URLs for all the said API functions.
They promised free API keys, and they also delivered. They promised "no promotional materials to your inbox," and indeed the only email I got from them so far was the announcement email for their new CSV feature.
This being said, there are a couple areas they could optimize upon.
The Data
Of the thousands of US-based equities I have analyzed so far, their historical data and technical indicators seem to match other reputable data sources. Their intraday data is realtime up to the current minute, which is fine for my research purposes but may not satisfy users who want to beat the market with millisecond precision. Perhaps a premium feature for this down the road?
Their JSON output is easily readable and python-parsable. For the daily time series, however, I understand that their most recent data point is the cumulative information of the current trading day (updated realtime), but why is the first timestamp in YYYY-MM-DD HH:MM:SS format while all the others are in the normal YYYY-MM-DD format typical of the EOD data?
I would love to see a consistent YYYY-MM-DD format across all the timestamps. The "last refreshed" timestamp can be specified in Meta Data instead:
In addition to the data presentation aspects, below are couple other data-related proposals:
In Summary
It is always a pleasure to have an API service that is well documented, platform/language-agnostic, and easily integratable. The fact that we have several third-party libraries built on top of Alpha Vantage on GitHub is in a sense testament to its developer-friendly nature. While there is still room for them to become a better version of themselves, I hope they thrive and stay true to the description on their home page - "driven by rigorous research, cutting edge technology, and a disciplined focus on democratizing access to data."