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  What is python? Python is a high-level, interpreted programming language known for its simplicity and readability. It was created by Guido van Rossum and first released in 1991. Python is designed to be easy to learn and use, with a clear and concise syntax that emphasizes code readability. It has become one of the most popular programming languages in the world and is widely used for a variety of applications, including web development, scientific computing, data analysis, artificial intelligence, machine learning, automation, and more. What are the key Feature of Python? Readability: Python's syntax is designed to be easy to read and write, making it accessible to both beginners and experienced programmers. High-level language: Python abstracts many low-level details, allowing developers to focus on solving problems rather than managing system-specific details. Interpreted: Python is an interpreted language, which means you don't need to compile your code before running it...
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Stock Market's Big Data And Their 4 V's

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Stock Market's Big Data And Their 4 V's  Big Data: The Big Data is the mixture of structured and unstructured Data. It describe a collection of all kind of data like Traditional as well as Digital Data of all kind. But it is to extremely large and complex datasets that can not be easily managed, processed, or analyzed using traditional data processing technique. Stock's Market Big Data Stock market deals with a large number of data. It also generates data with a greater Velocity and having a larger Variety.  "Stock market big data" refers to the massive volume of structured and unstructured data generated in the financial markets, particularly related to stocks Market Data: This includes real-time and historical data on stock prices, trading volumes, bid-ask spreads, and other relevant metrics for individual securities and entire markets. News and Sentiment Analysis: Textual data from news articles, social media, and other sources are ...
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Predictive Analytics And Stock Market

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  Predictive Analytics: It is the practice of extracting information from historical data to make predictions about future events or outcomes. It involves applying statistical models, data mining techniques, machine learning algorithms, and other analytical methods to identify patterns and trends in data that can be used to forecast future behaviour. Predictive analysis can be applied to the stock market   to forecast future price movements, identify investment opportunities, and manage risk For the Stock Market, Predictive Analytics is all about analysing the  Fundamental And Technical properties  of company (stocks). Fundamental properties: Checking fundamental Properties means evaluate the intrinsic value of a stock by analyzing various fundamental factors related to the company, industry, and economy. It involves examining quantitative and qualitative factors to assess the financial health, performance, and prospects of a company and determine whether the stock i...
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Trading is Knowledge

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  DATA ANALYTICS FOR STOCK MARKET The stock market is influenced by a multitude of factors, including economic conditions, geopolitical events, and investor behaviours. Therefore, it is essential to combine data analytics with market knowledge and expertise for informed decision-making. These are a few ways to utilize data analytics for stock market analysis: o    Data Collection: Gather relevant data from various sources, including financial statements, news articles, social media, and market data providers. This data can include historical price and volume data, company financials, news sentiment, and macroeconomic indicators   o    Quantitative Analysis: Apply statistical and quantitative techniques to analyse the data. This can include calculating financial ratios, performing regression analysis, identifying patterns and correlations, and conducting time series analysis. These analyses help identify trends, relationships, and potential opp...
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