hw03

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University of California, Berkeley *

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61B

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Economics

Date

Apr 3, 2024

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pdf

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6

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0.0.1 Question 1d Suppose we are interested in using the news to predict future stock values. What additional data would we need to predict stock prices, and how could we connect that data to news articles? In addition, what attributes or characteristics of the news might help predict the stock value? Additional data we would need to predict stock prices would be historical stock trends, company-specific financial data, and reports on economic trends. We could connect that data to news articles because news articles can inform changes in a company and their stock’s performance, provide timestamps for major occurances, and sentiment/topic analysis can identify trends and sentiment towards stocks, supporting our data analysis. Attributes of the news that might predict stock value could be sentiment trends, market condition indicators, keywords on stock prices (ex. spike, increase, rise, plummet), company event patterns, etc. 1
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Question 2d, Part ii Given your code in the previous part is correct, after running the cell below, you should be able to see the number of articles released mentioning companies for each year. The plot should look like this: In [52]: plt . figure(figsize = ( 6 , 4 )) for company in companies: sns . lineplot(data = year_news . reset_index(), x = "Year" , y = company, label = company) plt . legend(fontsize = "12" ) plt . xticks(np . arange( 2010 , 2014 ), np . arange( 2010 , 2014 )) plt . ylabel( "Number of Articles" ) plt . xlabel( "Year" ) plt . title( "Number of Articles Released (2010-2013)" ); What trends do you notice in the plot above? Feel free to reference or Google any events to explain the trends seen in the graph. What are some limitations of using data and the corresponding plot to analyze the performance of different companies or trends? 3
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