Investment methods are diversifying day by day. For example, Bitcoin and various commodities have become very popular recently. However, the stock exchange is one of the most popular investment tools that has remained unchanged for years. For many years, investors and businesses have shaped their investments with real-time and historical stock data. Stock Historic data provides them with past values of currencies.
Analyzing stock historical data can provide valuable insights for making investment decisions. These data are an important element that affects traders’ current investment decisions. In this article, we will look closer at the importance of historical and real-time stock data for investors. Then, we will show you the best way to obtain stock data with Python.
What is the Importance of Historical and Real-Time Stock Data for Investors
For investors, historical and real-time stock data offers them a valuable treasure trove to make informed decisions in the financial markets. While historical data helps them understand past price movements and market trends of stocks, live data allows them to follow real-time stock market data. This data provides investors with valuable information to predict future stock performance and manage risks. Therefore, historical and real-time stock data is indispensable in the investment world.
Some advantages of using historical and real-time stock data are as follows:
- Trend Analysis Opportunity: Historical data allows investors to examine past price movements. Thus, investors can make predictions in identifying market trends and possible future price changes.
- Providing Risk Management: Historical data provides information about how stocks have changed prices during political and economic crises in the past. This is very important for investors to manage their risks and develop appropriate strategies.
- Speeding Up the Decision Process: Real-time data offers investors the chance to monitor real-time market data and update their decisions more quickly. This provides the ability to move quickly.
Best Way to Get Stock Data in Python: Stock Data API
There are many ways to obtain stock data with Python. For example, scraping data from NASDAQ, S&P 500, and New York stock exchanges with Python’s unique web scraping libraries. However, many methods like this are not preferred due to the development cost and the little data obtained.
Nowadays, using a stock data API is the best way to obtain historical and real-time stock market data with Python and many other languages. Many stock data APIs in the market offer both real-time and stock market historical data to their users with a single endpoint. The marketstack API, which is used by global companies such as Amazon, Uber, and Accenture, offers a wide data set to its users. This API provides 170,000+ stock tickers and 750+ market indices while supporting 70+ global exchanges. It also provides up to 30 years of free historical stock data.
The easiest and most cost-effective way to obtain stock data with Python is to use a stock data API such as the marketstack API. Now, let’s integrate this API into the Python programming language step by step.
Get an API Key
The marketstack API is a free stock data API. That free plan supports both live and historical stock data. We need an API key to use this API and obtain data. For this, let’s sign up for the free subscription plan offered by the marketstack and get an API key.
Code
After obtaining the API key, we can now integrate the marketstack API into the Python programming language. To do this, let’s open a file named ‘stock-data-with-api.py’ in the file path where we will develop the application and put the following codes in it:
import requests
base_url= “http://api.marketstack.com/v1/eod”;
access_key = “MARKETSTACK-API-KEY”;
live_params = (
(“access_key”, access_key),
(“symbols”,“AAPL”),
(“limit”,“1”)
);
historical_params = (
(“access_key”, access_key),
(“symbols”,“AAPL”),
(“date_from”,“2023-10-01”),
(“date_to”,“2023-10-03”)
);
live_response = requests.get(base_url, params=live_params);
historical_response = requests.get(base_url, params=historical_params);
print(“Live data for APPL: “)
print(live_response.text)
print(“Historical data for APPL: “)
print(historical_response.text)
If we examine the codes below one by one, we first import the ‘requests’ library into the project, where we will send the HTTP request.
import requests
Then, we kept the marketstack API URL and its API key in variables.
base_url= “http://api.marketstack.com/v1/eod”;
access_key = “MARKETSTACK-API-KEY”;
Afterward, we created parameters to query both real-time and historical stock data from the marketstack endpoint.
live_params = (
(“access_key”, access_key),
(“symbols”,“AAPL”),
(“limit”,“1”)
);
historical_params = (
(“access_key”, access_key),
(“symbols”,“AAPL”),
(“date_from”,“2023-10-01”),
(“date_to”,“2023-10-03”)
);
Finally, we sent 2 separate API calls with these parameters and printed the results on the console screen of the application.
live_response = requests.get(base_url, params=live_params);
historical_response = requests.get(base_url, params=historical_params);
print(“Live data for AAPL: “)
print(live_response.text)
print(“Historical data for AAPL: “)
print(historical_response.text)
Test
Before running the application, let’s put our API key in the ‘MARKETSTACK-API-KEY’ field and run the application with the command below.
python stock-data-with-api.py
After running the application, both live and historical stock data in JSON format for AAPL stock printed on the application console are as follows:
Conclusion
In summary, stock investments have always been a popular investment method from the past to the present. It is the favorite investment tool of millions of people around the world. For these reasons, the accuracy of the stock data provided by the platforms that offer their users the opportunity to invest is very important. The way to obtain the most accurate stock data, especially in the Python programming language, which is frequently used in the processing and analysis of stock data, is to use a reliable stock data API.
FAQs
Q: How To Get Historical Stock Data?
A: There are many options for accessing historical stock data. Some of the popular options are using a reliable stock data API and using a web scraping tool.
Q: Where Can I Find Historical Stock Data API?
A: If you want to obtain historical stock data as an API, various official financial data providers and platforms offer stock data API services. You can also find reliable stock market historical data APIs from popular API marketplaces such as APILayer.
Q: What is the Stock History?
A: Stock history is data containing previous price movements of a particular stock. This historical data helps investors and businesses analyze the past performance of stocks and predict future trends.
Q: How Can I Get Real-Time Stock Data For Free?
A: The best way to get real-time stock data for free is to use a free stock data API. Nowadays, popular APIs such as the marketstack API offer a free subscription plan to their users.
