Spurious correlation #3,584 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Average Cost of a 30-Second Ad Commercial during the Academy Awards and the second variable is M&T Bank's stock price (MTB). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Average Cost of a 30-Second Ad Commercial during the Academy Awards and the second variable is M&T Bank's stock price (MTB). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As the Average Cost of a 30-Second Ad Commercial during the Academy Awards goes up, more companies are forced to dig deep into their vaults to afford the coveted airtime. This causes a surge in demand for loans and financial services, leading to increased profits for banks. M&T Bank, in particular, sees a boon as businesses flock to secure the necessary funds for their extravagant Oscar-worthy advertisements. In a twist of financial fate, it seems that M&T Bank has found a way to turn lights, camera, and action into cold, hard cash.

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a futuristic cityscape at night with neon lights and tall skyscrapers. In the center of the scene, a massive holographic billboard prominently displays the M&T Bank logo, casting a vibrant glow over the bustling street corner below. People are gathered around a sleek, high-tech storefront television screen, mesmerized by a dynamic 30-second ad for M&T Bank playing during a prestigious event. The electronic ticker displays a visually captivating representation of a stock price steadily rising as the city hums with vibrant energy. The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: Average Cost of a 30-Second Ad Commercial during the Academy Awards and M&T Bank's stock price (MTB). Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Data cyber art Steampunk Macabre Glitch art High-tech
ChatGPT: High-tech

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Average Cost of a 30-Second Ad Commercial during the Academy Awards and M&T Bank's stock price (MTB), in the following situation: Because the higher cost of advertising during the Academy Awards led to an increase in viewership and exposure, more people saw M&T Bank's commercials, which subliminally convinced them to "bank" on the company, resulting in an uptick in stock price.. Keep the description simple.
ChatGPT: In a bustling city, a gigantic billboard featuring the M&T Bank logo towers over a busy street corner. The electronic ticker below it displays a steadily rising stock price. Amidst the crowd, a group of people gather around a stylish storefront television screen, all captivated by a 30-second ad for M&T Bank playing during the Academy Awards. The ad showcases the bank's services and reliability, drawing the attention of passersby who pause to watch.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ High-tech ] and depicting this scene: In a bustling city, a gigantic billboard featuring the M&T Bank logo towers over a busy street corner. The electronic ticker below it displays a steadily rising stock price. Amidst the crowd, a group of people gather around a stylish storefront television screen, all captivated by a 30-second ad for M&T Bank playing during the Academy Awards. The ad showcases the bank's services and reliability, drawing the attention of passersby who pause to watch. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a futuristic cityscape at night with neon lights and tall skyscrapers. In the center of the scene, a massive holographic billboard prominently displays the M&T Bank logo, casting a vibrant glow over the bustling street corner below. People are gathered around a sleek, high-tech storefront television screen, mesmerized by a dynamic 30-second ad for M&T Bank playing during a prestigious event. The electronic ticker displays a visually captivating representation of a stock price steadily rising as the city hums with vibrant energy.

*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.
^{Show prompt for explanation} Model: gpt-3.5-turbo-1106 (fine-tuned)
System prompt: You provide humorous responses in the form of plausible sounding explanations for correlations. You assume the correlation is causative for the purpose of the explanation even if it is ridiculous. You do not chat with the user, you only reply with the causal connection explanation and nothing else.
User prompt: Please make up a funny explanation for how an increase in Average Cost of a 30-Second Ad Commercial during the Academy Awards caused M&T Bank's stock price (MTB) to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

The Ad Yields for MTB Shields Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price

The Journal of Advertising and Financial Analysis

Jan 2024

Reminder: This paper is AI-generated. Not real!

^{Show prompt used to generate this paper} Quick note: This sequence is long and repetitive. That's how the prompt engineering works for this one. I manage the output in Python to format it into this PDF.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft a literature review section of an academic research paper, that starts out dry for the first few sentences but then becomes hilarious and goofy.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a literature review section of an academic research paper presenting the findings of the connection between Average Cost of a 30-Second Ad Commercial during the Academy Awards and M&T Bank's stock price (MTB). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Speak in the present tense for this section (the authors find...), as is common in academic research paper literature reviews. Name the sources in a format similar to this: In "Book," the authors find lorem and ipsum.

Make up the lorem and ipsum part, but make it sound related to the topic at hand.

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then cite some social media posts you read that seem to be related.

Here is the title and abstract of the paper:
[[TITLE]]
The "Ad Yields for MTB Shields" Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price

[[ABSTRACT]]
This study delves into the intriguing relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). We harnessed data from Statista and LSEG Analytics (Refinitiv), extracting insights from the period spanning 2002 to 2022. Utilizing rigorous statistical analysis, we uncovered a striking correlation coefficient of 0.9157765, with a p-value of less than 0.01.

Our findings not only unveil a robust and statistically significant connection between these seemingly disparate variables but also prompt the classic joke: "Why don't we ever tell secrets on a farm? Because the potatoes have eyes and the corn has ears!"

Through in-depth examination, we shed light on the potential implications of this correlation for both the advertising industry and the financial sector. The implications of our research may influence strategic decision-making related to advertising expenditures and financial investments. Furthermore, the disclosed connection adds a lighthearted twist to the phrase "banking on ads."

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The world of advertising and finance often intersect in unexpected ways, much like a punny economist and a dad joke. In this study, we explore the relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB), and the findings are nothing short of reel-y fascinating. We embarked on this investigation with the goal of shedding light on the underlying factors that may influence M&T Bank's stock performance, with a touch of glitz and glamour.
As economists, we are accustomed to analyzing complex data and drawing nuanced conclusions, but even we were surprised by the strength of the connection we uncovered. It's as surprising as finding a panda in a pantry - not something you'd expect, but undeniably captivating once discovered.
We present our findings not just as a means of academic inquiry, but also as a source of entertainment for those who appreciate the whimsy in the world of finance. After all, everyone loves a good surprise, much like finding a hidden treasure in a balance sheet.
So, with a sense of humor and a keen eye for patterns, we delve into the "Ad Yields for MTB Shields" to unravel the delightful connection between advertising costs and stock prices. Get ready to be captivated, and perhaps even amused, by the unexpected correlation we have uncovered.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The relationship between advertising expenditures and stock prices has been a subject of interest for researchers and practitioners alike. Smith and Doe (2008) examined the impact of advertising on firm value and found a positive association. Jones et al. (2015) further explored the temporal dynamics of advertising and stock prices, revealing intriguing patterns within the consumer goods industry.

Transitioning to the realm of finance, Henderson (2012) elucidated the factors affecting bank stock performance, emphasizing the role of macroeconomic indicators and regulatory environment. Similarly, Phillips (2016) investigated the impact of marketing activities on bank performance, offering valuable insights into the relationship between marketing investments and financial metrics.

Turning to the world of literature, "Ogilvy on Advertising" by David Ogilvy provides a comprehensive perspective on advertising strategies and their potential impact on brand equity and consumer behavior. In a more fictional realm, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams humorously explores the intricacies of interstellar travel and the importance of knowing where one's towel is, drawing unexpected parallels to the unpredictability of stock market movements.

Additionally, social media platforms have become hubs of informal discussions and anecdotal observations related to financial phenomena. A Twitter post by @MarketWizard42 quips, "Watching ad rates during Oscars is like watching a stock rise and shine – unexpected, yet oddly satisfying." This casual observation underscores the pervasive curiosity surrounding the correlation between advertising activities and financial markets.

It is within this interdisciplinary context that we endeavor to investigate the captivating nexus between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). As we embark on this journey, we encourage readers to embrace the levity in financial research, much like finding a dollar bill in a library book – a delightful surprise amidst scholarly pursuits.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the methodology section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the methodology section of an academic research paper presenting the findings of the connection between Average Cost of a 30-Second Ad Commercial during the Academy Awards and M&T Bank's stock price (MTB). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Statista and LSEG Analytics (Refinitiv) . You used data from 2002 to 2022

Make up the research methods you don't know. Make them a bit goofy and convoluted.

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
The "Ad Yields for MTB Shields" Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price

[[ABSTRACT]]
This study delves into the intriguing relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). We harnessed data from Statista and LSEG Analytics (Refinitiv), extracting insights from the period spanning 2002 to 2022. Utilizing rigorous statistical analysis, we uncovered a striking correlation coefficient of 0.9157765, with a p-value of less than 0.01.

Our findings not only unveil a robust and statistically significant connection between these seemingly disparate variables but also prompt the classic joke: "Why don't we ever tell secrets on a farm? Because the potatoes have eyes and the corn has ears!"

Through in-depth examination, we shed light on the potential implications of this correlation for both the advertising industry and the financial sector. The implications of our research may influence strategic decision-making related to advertising expenditures and financial investments. Furthermore, the disclosed connection adds a lighthearted twist to the phrase "banking on ads."

[[INTRODUCTION]]
The world of advertising and finance often intersect in unexpected ways, much like a punny economist and a dad joke. In this study, we explore the relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB), and the findings are nothing short of reel-y fascinating. We embarked on this investigation with the goal of shedding light on the underlying factors that may influence M&T Bank's stock performance, with a touch of glitz and glamour.
As economists, we are accustomed to analyzing complex data and drawing nuanced conclusions, but even we were surprised by the strength of the connection we uncovered. It's as surprising as finding a panda in a pantry - not something you'd expect, but undeniably captivating once discovered.
We present our findings not just as a means of academic inquiry, but also as a source of entertainment for those who appreciate the whimsy in the world of finance. After all, everyone loves a good surprise, much like finding a hidden treasure in a balance sheet.
So, with a sense of humor and a keen eye for patterns, we delve into the "Ad Yields for MTB Shields" to unravel the delightful connection between advertising costs and stock prices. Get ready to be captivated, and perhaps even amused, by the unexpected correlation we have uncovered.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

To investigate the relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB), our research team employed a blend of quantitative analysis and a sprinkle of creativity, much like preparing a complex financial recipe with a dash of humor. The data collection process involved scouring various sources from the vast expanse of the internet, with a biased preference for Statista and LSEG Analytics (Refinitiv) due to their particularly appetizing data sets.

We gathered data from a period spanning 2002 to 2022, akin to patiently aging a fine wine until it was ripe for analysis. This timeframe allowed us to capture a comprehensive overview of the dynamic interplay between advertising costs and stock performance, resembling the meticulous craftsmanship of a seasoned vintner.

The first step in our methodology involved calculating the average cost of a 30-second advertisement during the Academy Awards for each year. This process required integrating data from multiple sources, much like assembling a puzzle with pieces scattered across different corners of the digital universe. Once this composite figure was derived, we had the essential ingredient to begin unraveling the relationship between advertising costs and stock price.

Next, we meticulously tracked the stock performance of M&T Bank (MTB) over the same period, applying advanced statistical techniques to discern patterns and fluctuations resembling the art of interpreting the subtle notes in a complex financial symphony.

To measure the correlation between the average ad cost and MTB's stock price, we employed the Pearson correlation coefficient, a staple statistical tool that functions as the compass guiding researchers through the tempestuous seas of data analysis. This coefficient allowed us to quantify the strength and direction of the relationship between the two variables, akin to demystifying the entwined flavors of a well-balanced dish.

Furthermore, we complemented this analysis with a series of robust regression models, including ordinary least squares (OLS) regression. These models served as the culinary alchemy, blending together the diverse ingredients of advertising expenditure and stock price to distill the essence of their relationship, much like the intricacies of crafting a multi-layered dessert.

Throughout this process, we remained mindful of potential confounding variables lurking in the shadows, much like the surprise flavor in a dish that demands careful consideration to ensure an accurate interpretation of the findings.

In the end, our methodology encapsulates the marriage of meticulous data analysis with a touch of whimsy, reflecting our commitment to unraveling complex relationships with both precision and a good-natured flair.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of an academic research paper.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up the discussion section of an academic research paper presenting the findings of the connection between Average Cost of a 30-Second Ad Commercial during the Academy Awards and M&T Bank's stock price (MTB). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 500 tokens.

Here are the title, abstract, literature review, and results sections. Please harken back to 1-2 of the goofy items in the literature review, but pretend to take them completely seriously. Discuss how your results supported the prior research.

Do not write a conclusion. I will add a conclusion after this.

[[TITLE]]
The "Ad Yields for MTB Shields" Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price

[[ABSTRACT]]
This study delves into the intriguing relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). We harnessed data from Statista and LSEG Analytics (Refinitiv), extracting insights from the period spanning 2002 to 2022. Utilizing rigorous statistical analysis, we uncovered a striking correlation coefficient of 0.9157765, with a p-value of less than 0.01.

Our findings not only unveil a robust and statistically significant connection between these seemingly disparate variables but also prompt the classic joke: "Why don't we ever tell secrets on a farm? Because the potatoes have eyes and the corn has ears!"

Through in-depth examination, we shed light on the potential implications of this correlation for both the advertising industry and the financial sector. The implications of our research may influence strategic decision-making related to advertising expenditures and financial investments. Furthermore, the disclosed connection adds a lighthearted twist to the phrase "banking on ads."

[[LITERATURE REVIEW]]
The relationship between advertising expenditures and stock prices has been a subject of interest for researchers and practitioners alike. Smith and Doe (2008) examined the impact of advertising on firm value and found a positive association. Jones et al. (2015) further explored the temporal dynamics of advertising and stock prices, revealing intriguing patterns within the consumer goods industry.
Transitioning to the realm of finance, Henderson (2012) elucidated the factors affecting bank stock performance, emphasizing the role of macroeconomic indicators and regulatory environment. Similarly, Phillips (2016) investigated the impact of marketing activities on bank performance, offering valuable insights into the relationship between marketing investments and financial metrics.
Turning to the world of literature, "Ogilvy on Advertising" by David Ogilvy provides a comprehensive perspective on advertising strategies and their potential impact on brand equity and consumer behavior. In a more fictional realm, "The Hitchhiker's Guide to the Galaxy" by Douglas Adams humorously explores the intricacies of interstellar travel and the importance of knowing where one's towel is, drawing unexpected parallels to the unpredictability of stock market movements.
Additionally, social media platforms have become hubs of informal discussions and anecdotal observations related to financial phenomena. A Twitter post by @MarketWizard42 quips, "Watching ad rates during Oscars is like watching a stock rise and shine – unexpected, yet oddly satisfying." This casual observation underscores the pervasive curiosity surrounding the correlation between advertising activities and financial markets.

It is within this interdisciplinary context that we endeavor to investigate the captivating nexus between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). As we embark on this journey, we encourage readers to embrace the levity in financial research, much like finding a dollar bill in a library book – a delightful surprise amidst scholarly pursuits.

[[RESULTS]]
The statistical analysis of the relationship between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price (MTB) from 2002 to 2022 yielded intriguing results. The correlation coefficient of 0.9157765 suggests a strong positive relationship between these two variables, akin to a dynamic duo on the red carpet. It's almost as if these numbers were destined to be co-stars, much like a classic Hollywood pairing.
With an r-squared value of 0.8386467, a substantial portion of the variability in M&T Bank's stock price can be explained by changes in the average cost of advertising during the Academy Awards. One might say this relationship is as solid as a bank vault or as steady as an award-winning film's plotline.
The p-value of less than 0.01 indicates that the observed correlation is statistically significant, further reinforcing the legitimacy of this association. This finding is as significant as a blockbuster movie's opening weekend, leaving an indelible mark on the audience.
The scatterplot (Fig. 1) visually depicts the strong positive correlation between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price. It is striking to see how these two variables move in harmonious tandem, much like a well-choreographed dance number.
The classic dad joke whispering from these results might say, "I asked the statistician if we should stop learning about correlation coefficients. He said, 'Covariance!'"
These results not only enhance our understanding of the intersection between advertising expenses and stock performance but also offer a lighthearted glimpse into the playful side of financial analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study corroborate the insights from prior research on the association between advertising expenditures and stock prices. The positive and statistically significant correlation between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price aligns with the conclusions drawn by Smith and Doe (2008) regarding the impact of advertising on firm value. It is as if our results and the previous literature were meant to be together, much like a perfect on-screen romance.

Moreover, the substantial proportion of the variability in M&T Bank's stock price explained by changes in the average cost of advertising during the Academy Awards is reminiscent of the temporal dynamics of advertising and stock prices explored by Jones et al. (2015) in the consumer goods industry. It's as if our study and prior research are in sync, like a well-coordinated dance routine at an awards show.

The statistically significant p-value further validates the robustness of the relationship uncovered in this study, echoing the emphasis on statistical significance in previous research by Henderson (2012) and Phillips (2016) in their analyses of factors affecting bank stock performance and the impact of marketing activities on bank performance, respectively. It's as if our results and the existing literature are delivering a punchline together, perfectly timed and executed.

The lighthearted twist offered by our findings fits seamlessly into the context of the levity in financial research, as previously encouraged within the interdisciplinary context. The unexpected similarity between casual observations and formal statistical results is akin to stumbling upon a punchline in a scholarly article.

In summary, our study provides compelling empirical evidence supporting the correlation between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price, adding a touch of humor to the otherwise serious realm of financial research—almost like finding a dollar bill in a library book, providing a joyful surprise amidst scholarly pursuits.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the discussion section of goofy academic research papers that sounds like it belongs based on the title and abstract provided.
User prompt:
Pretend you are an academic researcher. Your writing sounds like it belongs in a medical or economics journal. However, you frequently crack jokes, make puns, or add unexpected twists in your writing.

Please make up a short conclusion of an academic research paper presenting the findings of the connection between Average Cost of a 30-Second Ad Commercial during the Academy Awards and M&T Bank's stock price (MTB). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 300 tokens. At the very end, assert that no more research is needed in this area.

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The "Ad Yields for MTB Shields" Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price

[[ABSTRACT]]
This study delves into the intriguing relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). We harnessed data from Statista and LSEG Analytics (Refinitiv), extracting insights from the period spanning 2002 to 2022. Utilizing rigorous statistical analysis, we uncovered a striking correlation coefficient of 0.9157765, with a p-value of less than 0.01.

Our findings not only unveil a robust and statistically significant connection between these seemingly disparate variables but also prompt the classic joke: "Why don't we ever tell secrets on a farm? Because the potatoes have eyes and the corn has ears!"

Through in-depth examination, we shed light on the potential implications of this correlation for both the advertising industry and the financial sector. The implications of our research may influence strategic decision-making related to advertising expenditures and financial investments. Furthermore, the disclosed connection adds a lighthearted twist to the phrase "banking on ads."

[[INTRDUCTION]]
The world of advertising and finance often intersect in unexpected ways, much like a punny economist and a dad joke. In this study, we explore the relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB), and the findings are nothing short of reel-y fascinating. We embarked on this investigation with the goal of shedding light on the underlying factors that may influence M&T Bank's stock performance, with a touch of glitz and glamour.
As economists, we are accustomed to analyzing complex data and drawing nuanced conclusions, but even we were surprised by the strength of the connection we uncovered. It's as surprising as finding a panda in a pantry - not something you'd expect, but undeniably captivating once discovered.
We present our findings not just as a means of academic inquiry, but also as a source of entertainment for those who appreciate the whimsy in the world of finance. After all, everyone loves a good surprise, much like finding a hidden treasure in a balance sheet.
So, with a sense of humor and a keen eye for patterns, we delve into the "Ad Yields for MTB Shields" to unravel the delightful connection between advertising costs and stock prices. Get ready to be captivated, and perhaps even amused, by the unexpected correlation we have uncovered.

[[RESULTS]]
The statistical analysis of the relationship between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price (MTB) from 2002 to 2022 yielded intriguing results. The correlation coefficient of 0.9157765 suggests a strong positive relationship between these two variables, akin to a dynamic duo on the red carpet. It's almost as if these numbers were destined to be co-stars, much like a classic Hollywood pairing.
With an r-squared value of 0.8386467, a substantial portion of the variability in M&T Bank's stock price can be explained by changes in the average cost of advertising during the Academy Awards. One might say this relationship is as solid as a bank vault or as steady as an award-winning film's plotline.
The p-value of less than 0.01 indicates that the observed correlation is statistically significant, further reinforcing the legitimacy of this association. This finding is as significant as a blockbuster movie's opening weekend, leaving an indelible mark on the audience.
The scatterplot (Fig. 1) visually depicts the strong positive correlation between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price. It is striking to see how these two variables move in harmonious tandem, much like a well-choreographed dance number.
The classic dad joke whispering from these results might say, "I asked the statistician if we should stop learning about correlation coefficients. He said, 'Covariance!'"
These results not only enhance our understanding of the intersection between advertising expenses and stock performance but also offer a lighthearted glimpse into the playful side of financial analysis.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our study has shed light on the intriguing relationship between the average cost of a 30-second advertisement during the Academy Awards and M&T Bank's stock price (MTB). The statistically significant correlation coefficient of 0.9157765 and the p-value of less than 0.01 have unveiled a connection as strong as a vault door and as enduring as a classic movie's legacy.

The implications of our research are as real as a bank statement, and they prompt us to reconsider the phrase "putting all your money where your ads are." This correlation between advertising costs and stock prices redefines the notion of "show me the money" in a delightfully unexpected way.

Furthermore, our findings add a touch of glamour to the world of finance, providing evidence that financial analysis can indeed be as captivating as a riveting film. It's as if we've uncovered the hidden stars of the financial galaxy – and they're shining as brightly as the Hollywood sign.

As for future research directions, we daresay that delving further into this correlation would be as unnecessary as taking an umbrella to a bank, for our findings have already provided a delightful and unexpected twist to the world of finance and advertising. The classic dad joke in the room whispers, "Why did the statistician break up with the chemist? There was no 'reaction'."

No more research is needed in this area.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Ad Yields for MTB Shields Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Advertising and Financial Analysis

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Ad Yields for MTB Shields Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Economic Entertainment Research

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Ad Yields for MTB Shields Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price with an abstract of This study delves into the intriguing relationship between the average cost of a 30-second advertisement during the Academy Awards and the stock price of M&T Bank (MTB). We harnessed data from Statista and LSEG Analytics (Refinitiv), extracting insights from the period spanning 2002 to 2022. Utilizing rigorous statistical analysis, we uncovered a striking correlation coefficient of 0.9157765, with a p-value of less than 0.01.
Our findings not only unveil a robust and statistically significant connection between these seemingly disparate variables but also prompt the classic joke: "Why don't we ever tell secrets on a farm? Because the potatoes have eyes and the corn has ears!"
Through in-depth examination, we shed light on the potential implications of this correlation for both the advertising industry and the financial sector. The implications of our research may influence strategic decision-making related to advertising expenditures and financial investments. Furthermore, the disclosed connection adds a lighthearted twist to the phrase "banking on ads.

ChatGPT:

Academy Awards, advertisement costs, M&T Bank, MTB stock price, stock price correlation, advertising expenditures, relationship analysis, financial investments, Statista, LSEG Analytics, Refinitiv, advertising industry, financial sector, correlation coefficient, p-value, advertising impact, strategic decision-making

*There is a bunch of Python happening behind the scenes to turn this prompt sequence into a PDF.

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Data details

Average Cost of a 30-Second Ad Commercial during the Academy Awards
Source: Statista
See what else correlates with Average Cost of a 30-Second Ad Commercial during the Academy Awards

M&T Bank's stock price (MTB)
Detailed data title: Opening price of M&T Bank (MTB) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: ^{See full details} Via Microsoft Excel Stockhistory function

See what else correlates with M&T Bank's stock price (MTB)

Correlation r = 0.9157765 (Pearson correlation coefficient)
Correlation is a measure of how much the variables move together. If it is 0.99, when one goes up the other goes up. If it is 0.02, the connection is very weak or non-existent. If it is -0.99, then when one goes up the other goes down. If it is 1.00, you probably messed up your correlation function.

r² = 0.8386467 (Coefficient of determination)
This means 83.9% of the change in the one variable (i.e., M&T Bank's stock price (MTB)) is predictable based on the change in the other (i.e., Average Cost of a 30-Second Ad Commercial during the Academy Awards) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 5.8E-9.^Show 0.0000000058217381771963445000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

But I am a p-villain. I absolutely did not test only one pair of variables one time. I correlated hundreds of millions of pairs of variables. I threw boatloads of data into an industrial-sized blender to find this correlation.

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.92 in 5.8E-7% of random cases. Said differently, if you correlated 171,770,006 random variables^Note You don't actually need 171 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

p-value calculations are useful for understanding the probability of a result happening by chance. They are most useful when used to highlight the risk of a fluke outcome. For example, if you calculate a p-value of 0.30, the risk that the result is a fluke is high. It is good to know that! But there are lots of ways to get a p-value of less than 0.01, as evidenced by this project.

In this particular case, the values are so extreme as to be meaningless. That's why no one reports p-values with specificity after they drop below 0.01.

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 20 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 20 because we have two variables measured over a period of 21 years. It's just the number of years minus ( the number of variables minus one ), which in this case simplifies to the number of years minus one.
you would randomly expect to find a correlation as strong as this one.

[ 0.8, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

This one is a bit more complciated than the other calculations, but I include it because many people have been pushing for confidence intervals instead of p-value calculations (for example: NEJM. However, if you are dredging data, you can reliably find yourself in the 5%. That's my goal!

All values for the years included above: ^Note If I were being very sneaky, I could trim years from the beginning or end of the datasets to increase the correlation on some pairs of variables. I don't do that because there are already plenty of correlations in my database without monkeying with the years.

Still, sometimes one of the variables has more years of data available than the other. This page only shows the overlapping years. To see all the years, click on "See what else correlates with..." link above.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Average Cost of a 30-Second Ad Commercial during the Academy Awards (Dollars)	1290000	1360000	1500000	1500000	1650000	1690000	1700000	1310000	1400000	1550000	1610000	1650000	1760000	1830000	1720000	1910000	2090000	1980000	2150000	2000000	2200000
M&T Bank's stock price (MTB) (Stock price)	73.25	79.8	98.1	107.84	109.05	121.94	82.17	58.74	67.63	87.67	77.85	100.33	116.38	126.42	119.24	158.2	172.48	141.11	170.36	128.63	155.77

Why this works

Data dredging: I have 25,153 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 632,673,409 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
p-value calculation does not take this into account, so mathematically it appears less probable than it really is.

Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. ^{Show the steps to do this.} Step 1: Download and install Python on your computer.

Step 2: Open a plaintext editor like Notepad and paste the code below into it.

Step 3: Save the file as "calculate_correlation.py" in a place you will remember, like your desktop. Copy the file location to your clipboard. On Windows, you can right-click the file and click "Properties," and then copy what comes after "Location:" As an example, on my computer the location is "C:\Users\tyler\Desktop"

Step 4: Open a command line window. For example, by pressing start and typing "cmd" and them pressing enter.

Step 5: Install the required modules by typing "pip install numpy", then pressing enter, then typing "pip install scipy", then pressing enter.

Step 6: Navigate to the location where you saved the Python file by using the "cd" command. For example, I would type "cd C:\Users\tyler\Desktop" and push enter.

Step 7: Run the Python script by typing "python calculate_correlation.py"

If you run into any issues, I suggest asking ChatGPT to walk you through installing Python and running the code below on your system. Try this question:

"Walk me through installing Python on my computer to run a script that uses scipy and numpy. Go step-by-step and ask me to confirm before moving on. Start by asking me questions about my operating system so that you know how to proceed. Assume I want the simplest installation with the latest version of Python and that I do not currently have any of the necessary elements installed. Remember to only give me one step per response and confirm I have done it before proceeding."

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([1290000,1360000,1500000,1500000,1650000,1690000,1700000,1310000,1400000,1550000,1610000,1650000,1760000,1830000,1720000,1910000,2090000,1980000,2150000,2000000,2200000,])
array_2 = np.array([73.25,79.8,98.1,107.84,109.05,121.94,82.17,58.74,67.63,87.67,77.85,100.33,116.38,126.42,119.24,158.2,172.48,141.11,170.36,128.63,155.77,])
array_1_name = "Average Cost of a 30-Second Ad Commercial during the Academy Awards"
array_2_name = "M&T Bank's stock price (MTB)"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

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You may re-use the images on this page for any purpose, even commercial purposes, without asking for permission. The only requirement is that you attribute Tyler Vigen. ^Note Attribution can take many different forms. If you leave the "tylervigen.com" link in the image, that satisfies it just fine. If you remove it and move it to a footnote, that's fine too. You can also just write "Charts courtesy of Tyler Vigen" at the bottom of an article.

You do not need to attribute "the spurious correlations website," and you don't even need to link here if you don't want to. I don't gain anything from pageviews. There are no ads on this site, there is nothing for sale, and I am not for hire.

For the record, I am just one person. Tyler Vigen, he/him/his. I do have degrees, but they should not go after my name unless you want to annoy my wife. If that is your goal, then go ahead and cite me as "Tyler Vigen, A.A. A.A.S. B.A. J.D." Otherwise it is just "Tyler Vigen."

When spoken, my last name is pronounced "vegan," like I don't eat meat.

Full license details.
For more on re-use permissions, or to get a signed release form, see tylervigen.com/permission.

Download images for these variables:

High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.

If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.

Alternatively you can use a tool like Inkscape.
High resolution line chart, optimized for mobile
Alternative high resolution line chart
Scatterplot
Portable line chart (png)
Portable line chart (png), optimized for mobile
Line chart for only Average Cost of a 30-Second Ad Commercial during the Academy Awards
Line chart for only M&T Bank's stock price (MTB)
AI-generated correlation image
The spurious research paper: The Ad Yields for MTB Shields Revealed: The Relationship Between Academy Awards Ad Costs and M&T Bank's Stock Price

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Correlation ID: 3584 · Black Variable ID: 30 · Red Variable ID: 1912


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