<\/p>\n
Dissertation title<\/u><\/b>: The Intersection Structure:<\/span><\/u><\/b> Master Reference Models: The The excel file with the models and the R script must *Please professor comments and my master thesis <\/span><\/b><\/p>\n Professor Comments:<\/span><\/b><\/p>\n 1. The motivation is interesting. However, it would be 2. References could be better; you should not use 3.You want to include the investor sentiment by using 4. Consider using other indexes besides NASDAQ and <\/span><\/b><\/p>\n <\/span><\/b><\/p>\n <\/span><\/b><\/p>\n <\/span><\/b><\/p>\n Master thesis Proposal <\/span>(Revised after professor comments)<\/span><\/b><\/p>\n <\/span><\/b><\/p>\n The Intersection of AI and Stock Markets: Performance <\/span><\/b><\/p>\n Research Area of Interest:<\/span><\/b><\/p>\n My research interest lies in exploring the intersection In addition to analyzing indices, I will conduct a comparative <\/span><\/div>\n Objectives:<\/span><\/b><\/p>\n <\/span><\/div>\n Data Sources and Platforms:<\/span><\/b><\/p>\n <\/span><\/div>\n Methodology:<\/span><\/b><\/p>\n <\/span><\/div>\n Expected Outcomes:<\/span><\/b><\/p>\n <\/span><\/div>\n Limitations:<\/span><\/b><\/p>\n <\/span><\/div>\n Reference List:<\/span><\/b><\/p>\n
\nof AI and Stock Markets: Performance Analysis of the Nasdaq, S&P 500, and
\ntech giants Nvidia, Intel, Amazon, Microsoft, and Meta<\/span><\/p>\n
\nThesis<\/b> The dissertation <\/u><\/b>will be split into 3 chapters: 1)
\nIntroduction\/Problem statement\/research questions and objectives and literature
\nreview. <\/span>2) research phlisophic,research approach,
\ndata collection and analysis of the models (strategy) and limitations of the
\nresearch 3) discussion and results of the models, research
\nextension\/improvements and conclusion.<\/span><\/p>\n
\nstyle:<\/span><\/u> Harvard Style \u2013
\nuse only academic reputable books and journal and not websites and AI content. <\/span>Deadline: 18.11.2024
\nis my preferred delivery time for at least the 2 chapters<\/b><\/span><\/p>\n
\ndata can be attached by me, I have Bloomberg and Refinitiv access. <\/span><\/b><\/span><\/p>\n
\nbe shared.<\/span><\/b><\/p>\n
\nrevised proposal for better understanding!<\/span><\/b><\/span><\/p>\n
\nquite difficult to attribute Nasdaq’s evolution to the “AI factor”.
\nJust so you know, many other factors are present, and these other factors will
\nblur any effect (you are aware of this, eg. “limitations”) . Still,
\nit is interesting to analyze what you mention. You focussed on two companies,
\none indisputably linked to AI but the other not (you correctly highlight this
\nby mentioning the bandwagon effect); maybe it could be interesting to include
\nother firms such as Amazon, Microsoft, and Meta…(i.e., the “seven
\nmagnificent”) and see what you find.<\/span><\/b><\/p>\n
\ngeneral references as Miller or Tsay but academic papers directly linked to
\nyour research. Please also beware of formal aspects, there are no page
\nnumbers, <\/span><\/b><\/p>\n
\nVIX but note that this does not give you an idea of the polarity but on the
\nintensity. Moreover, you should provide some hint of how you are going to
\ncollect “AI news”, this point is crucial, you can not simply select a
\nbunch of news because you consider them relevant, you should do something
\nsystematic.<\/span><\/b><\/p>\n
\n-possibly- SP500 (e.g. technology indexes or AI specific Index)<\/span><\/b><\/p>\n
\nAnalysis of the Nasdaq, S&P 500, and tech giants Nvidia, Intel, Amazon,
\nMicrosoft, and Meta<\/span><\/b><\/p>\n
\nof artificial intelligence (AI) and financial markets<\/b>, with a particular
\nfocus on how the widespread adoption of AI has influenced the performance of major
\nstock indices<\/b> like the Nasdaq<\/b> (representing US technology and
\ninnovation sectors), the S&P 500<\/b> (representing the US overall
\neconomy), and potentially other technology-focused or AI indices<\/b>. I aim
\nto understand how AI has influenced market behavior<\/b>, investor
\nsentiment<\/b>, and stock price movements<\/b> within these indices over the
\nlong term (5 years).<\/span><\/p>\n
\nanalysis of key tech companies<\/b> that are deeply involved in AI, such as Nvidia,
\nIntel, Amazon, Microsoft, and Meta<\/b>. While Nvidia is indisputably linked to
\nAI, Intel is a latecomer to the AI race, and this contrast makes for an
\ninteresting comparison. Expanding the analysis to other tech giants (Amazon,
\nMicrosoft, Meta) will help provide a broader view of how AI influences both
\nindividual companies and stock market indices. My goal is to address the
\nbroader implications of AI adoption<\/b> on the stock market and to draw
\nconclusions on AI’s importance in driving stock market performance.<\/span><\/p>\n
\n\n
\n the performance<\/span><\/b> of Nasdaq, S&P 500, and
\n other relevant technology-focused indices<\/b> over the past 5 years,
\n during a period of AI boom, using stock prices, returns, and volatility measures.<\/span><\/li>\n
\n the correlation<\/span><\/b> between the performance of
\n indices and AI-related companies, including Nvidia, Intel, Amazon,
\n Microsoft, and Meta, to assess how AI adoption has influenced their stock
\n performance.<\/span><\/li>\n
\n and contrast<\/span><\/b> the macro market results
\n (indices) with the micro market results of Nvidia, Intel, Amazon,
\n Microsoft, and Meta.<\/span><\/li>\n
\n market behavior<\/span><\/b> (bullish vs. bearish,
\n volatility) and investor sentiment<\/b> (using both VIX and other
\n alternative measures) in response to AI-related announcements, and observe
\n their short-term impact on stock prices.<\/span><\/li>\n
\n collect and analyze AI-related news<\/span><\/b> to
\n study its correlation with stock movements across both indices and
\n individual companies.<\/span><\/li>\n<\/ol>\n
\n\n
\n stock price data<\/span><\/b>, returns, liquidity, VIX,
\n trading volume, and relevant company\/market news will be sourced from
\n platforms such as Bloomberg, Reuters, Investing.com, Yahoo Finance, Google
\n Finance, and company-specific press releases.<\/span><\/li>\n
\n and R-Studio will be used for data analysis and statistical modeling<\/b>.<\/span><\/li>\n
\n collection process<\/b> for AI-related news will be systematized<\/b> by
\n using news agencies’ archives and AI-related keyword filters on financial
\n news platforms. This will ensure a consistent and unbiased selection of
\n news articles.<\/span><\/li>\n<\/ul>\n
\n\n
\n Collection<\/span><\/b>:<\/span><\/li>\n\n
\n historical data on stock prices, returns, and volatility for the Nasdaq,
\n S&P 500, and other technology-focused indices (e.g., Dow Jones
\n U.S. Technology Index<\/b>).<\/span><\/li>\n
\n financial data and news on Nvidia, Intel, Amazon, Microsoft, and Meta,
\n focusing on AI-related developments over the past 5 years.<\/span><\/li>\n<\/ul>\n
\n Series Analysis<\/span><\/b>:<\/span><\/li>\n\n
\n time series analysis<\/b> on the collected data using R or Excel,
\n ensuring that the data is cleaned and preprocessed appropriately (Tsay,
\n 2002).<\/span><\/li>\n
\n statistical models<\/b> to analyze relationships between stock\/index
\n performance and AI-related factors, using methods such as correlation<\/b>
\n and regression \u2013 multi regression<\/b><\/span><\/li>\n<\/ul>\n
\n Statistics and Visualizations<\/span><\/b>:<\/span><\/li>\n\n
\n descriptive statistics<\/b> and charts<\/b> to visualize the patterns
\n and relationships between indices and AI-related companies over time.<\/span><\/li>\n
\n and or Implied Volatilit<\/b>y to capture the intensity of investor
\n sentiment and explore alternative measures (e.g., sentiment analysis
\n of news articles<\/b>) to gauge the polarity of sentiments toward
\n AI-related announcements.<\/span><\/li>\n<\/ul>\n
\n Analysis<\/span><\/b>:<\/span><\/li>\n\n
\n a systematic approach<\/b> to collect AI-related news by using
\n predefined search filters on platforms like Bloomberg, Reuters, and
\n Google News.<\/span><\/li>\n
\n sentiment analysis on AI-related news to assess how it impacts stock
\n prices and indices.<\/span><\/li>\n<\/ul>\n
\n Analysis<\/span><\/b>:<\/span><\/li>\n\n
\n the performance of Nvidia and Intel, examining how their differing AI
\n strategies have influenced their market valuation.<\/span><\/li>\n
\n the comparison to Amazon, Microsoft, and Meta to provide a broader
\n perspective on AI’s impact within the tech sector.<\/span><\/li>\n<\/ul>\n
\n and Revenue Analysis<\/span><\/b>:<\/span><\/li>\n\n
\n earnings reports<\/b> and financial statements<\/b> of Nvidia, Intel,
\n Amazon, Microsoft, and Meta to determine the contribution of AI-related
\n product lines to their revenue growth.<\/span><\/li>\n<\/ul>\n<\/ol>\n
\n\n
\n expect to find positive correlations<\/b> between AI announcements and
\n stock\/index movements, particularly among tech giants like Nvidia, Amazon,
\n and Microsoft.<\/span><\/li>\n
\n is anticipated to outperform the S&P 500<\/b>, given its heavy
\n weighting toward AI-driven companies.<\/span><\/li>\n
\n expected to show the most significant gains, while Intel<\/b> may
\n underperform, as it has been slower in adopting AI technologies.<\/span><\/li>\n
\n inclusion of other AI leaders such as Amazon, Microsoft, and Meta<\/b>
\n will provide a more comprehensive picture of AI’s impact across the tech
\n sector.<\/span><\/li>\n
\n likely to have been a significant driver<\/b> of stock market
\n performance over the past 5 years, but the analysis will also account for
\n other macroeconomic factors such as interest rates.<\/span><\/li>\n<\/ul>\n
\n\n
\n difficult to isolate AI’s impact<\/b> on stock performance due to the
\n presence of other factors such as interest rates, inflation, and global
\n economic events. Therefore, while AI may be a significant factor, it is
\n not the sole driver of stock market trends.<\/span><\/li>\n
\n measures the intensity of investor sentiment and not its polarity;
\n alternative methods will be explored to capture the positive vs.
\n negative sentiment<\/b> surrounding AI-related news.<\/span><\/li>\n
\n inclusion of additional indices and companies may add complexity to the
\n analysis, which will be carefully managed to ensure the scope remains
\n feasible.<\/span><\/li>\n<\/ul>\n
\n\n
\n S. (2023). The Impact of AI on Company Stock Returns<\/i>. <\/span>SSRN. <\/span>https:\/\/ssrn.com\/abstract=4595946<\/span><\/a>.<\/span><\/li>\n
\n J., & Malik, M. (2021). Artificial intelligence and semiconductor
\n firms: A comparative analysis of Nvidia and Intel<\/i>. Journal of
\n Technology Management & Innovation, 16(2), 23-35.<\/span><\/li>\n