Spurious correlation #3,406 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Sales of LP/Vinyl Albums and the second variable is Netflix's stock price (NFLX). The chart goes from 2003 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 Sales of LP/Vinyl Albums and the second variable is Netflix's stock price (NFLX). The chart goes from 2003 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As people dusted off their record players, the resulting increase in atmospheric nostalgia created a positive energy flux. This flux, in turn, was harvested by Netflix's hidden retro-entertainment receptors, leading to a surge in their stock price. It's like a cosmic boomerang effect, but for financial gains!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a cozy living room, with a person sitting on a well-worn armchair, flipping through a stack of LP/vinyl albums. The albums feature vibrant and varied artwork, and the person looks engrossed in admiring them. In the background, a TV displays the stock market ticker, with Netflix's stock price steadily rising. The vintage feel of the albums and the modern stock market display create an interesting contrast, symbolizing the interconnectedness of nostalgia and the surge in Netflix subscriptions and stock price. The scene should evoke a sense of nostalgia and simplicity, creating an intriguing visual that could be seen on Reddit. 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: Sales of LP/Vinyl Albums and Netflix's stock price (NFLX). 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: Celtic art Magic realism a funny image you would see on reddit Cybernetic art a funny image macro
ChatGPT: a funny image you would see on reddit

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 Sales of LP/Vinyl Albums and Netflix's stock price (NFLX), in the following situation: Because when people buy vinyl albums, they experience a surge of nostalgia that makes them yearn for the simpler times when Netflix was just a DVD-mailing service. This increased longing for the past causes a spike in subscribers and boosts Netflix's stock price - it's like going back in time, but with a much better selection of shows.. Keep the description simple.
ChatGPT: In a cozy living room, a person is seen flipping through a stack of LP/vinyl albums, admiring the vibrant album artwork. In the background, a TV displays the stock market ticker, showing Netflix's stock price steadily rising. The vintage feel of the albums evokes a sense of nostalgia and simplicity, mirroring the longing for the past that has led to the surge in Netflix subscriptions and its stock price.

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: [ a funny image you would see on reddit ] and depicting this scene: In a cozy living room, a person is seen flipping through a stack of LP/vinyl albums, admiring the vibrant album artwork. In the background, a TV displays the stock market ticker, showing Netflix's stock price steadily rising. The vintage feel of the albums evokes a sense of nostalgia and simplicity, mirroring the longing for the past that has led to the surge in Netflix subscriptions and its stock price. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cozy living room, with a person sitting on a well-worn armchair, flipping through a stack of LP/vinyl albums. The albums feature vibrant and varied artwork, and the person looks engrossed in admiring them. In the background, a TV displays the stock market ticker, with Netflix's stock price steadily rising. The vintage feel of the albums and the modern stock market display create an interesting contrast, symbolizing the interconnectedness of nostalgia and the surge in Netflix subscriptions and stock price. The scene should evoke a sense of nostalgia and simplicity, creating an intriguing visual that could be seen on Reddit.

*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 Sales of LP/Vinyl Albums caused Netflix's stock price (NFLX) to increase.\Make it sound serious until the end.

AI academic paper

(Because p < 0.01)

Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price

The Journal of Financial Fusions

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 Sales of LP/Vinyl Albums and Netflix's stock price (NFLX). 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 devolve ever further, and mention something completely ridiculous, like you conducted literature review by reading the backs of shampoo bottles.

Here is the title and abstract of the paper:
[[TITLE]]
Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price

[[ABSTRACT]]
This paper aims to explore the unexpected relationship between the sales of LP/vinyl albums and the stock price of Netflix (NFLX) using data from Statista and LSEG Analytics (Refinitiv) for the years 2003 to 2022. The analysis revealed a remarkably high correlation coefficient of 0.9824068 with a significance level of p < 0.01. The findings suggest a surprisingly strong positive association between the two seemingly unrelated variables.

Gone are the days of financial analyses solely focusing on traditional economic indicators. By delving into the world of music and streaming services, we uncovered a correlation that may leave some scratching their heads. Much like an old vinyl record, this relationship between LP sales and Netflix's stock price seems to spin and play a tune of its own.

So, what does this mean for investors? Well, perhaps it’s time to dust off those LP collections and tune in to the beats of the market in a whole new way. After all, when it comes to investment strategies, sometimes the needle drops where you least expect it!

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The financial markets have long been the subject of rigorous research and analysis probing into the causative factors of stock price movements. Traditional metrics such as earnings reports, economic indicators, and industry trends have dominated the landscape of financial analysis. However, in recent years, the advent of big data and novel approaches to data analysis have allowed for the examination of unexpected and unconventional relationships.
In this study, we explore the peculiar yet captivating link between the sales of LP/vinyl albums and the stock price of Netflix (NFLX). It seems that while LPs may be spinning on turntables, they may also be spinning the wheels of the stock market in ways previously unimagined. It's almost as if LP sales and stock prices are in a dance of their own - a tango between nostalgia and modernity.
While it may sound like we’re just riffing on old tunes, the correlation we have uncovered is backed by solid statistical analysis. Perhaps it’s time to think about LP sales as not just a dusty relic of the past, but as a groovy indicator of future stock prices. After all, it appears that the beat of LP sales might just be in sync with the rhythm of Netflix’s stock price.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "Smith et al.," the authors find that traditional economic indicators and industry trends have been the primary focus of financial analysis for decades. However, recent developments in data analytics have opened the door to the exploration of unconventional and surprising relationships in the financial markets. This shift in focus reflects a growing recognition of the potential influence of unexpected variables on stock price movements, challenging traditional notions of market analysis.

Dad Joke #1: Why did the investor bring string to the stock market? Because they wanted to tie up their portfolio!

In "Doe and Jones," the authors discuss the impact of cultural trends on financial markets, highlighting the intricate interplay between consumer behavior and stock prices. They emphasize the importance of considering non-traditional factors, such as cultural products and consumer preferences, in understanding market dynamics. The authors argue that cultural phenomena, including music trends and entertainment preferences, may have underappreciated effects on stock price movements.

Dad Joke #2: I told my wife she should embrace her mistakes. She gave me a hug.

Turning to non-fiction literature, books such as "The Sound of the City: The Rise of Rock and Roll" by Charlie Gillett offer insights into the social and cultural dimensions of music consumption. Similarly, "The Long Tail: Why the Future of Business is Selling Less of More" by Chris Anderson sheds light on the changing landscape of consumer behavior and its implications for market dynamics. These works underscore the multifaceted nature of cultural influences on consumer preferences, potentially extending to stock market trends.

Dad Joke #3: What do you call fake spaghetti? An "impasta"!

On a more fictional note, novels like "High Fidelity" by Nick Hornby and "The Vinyl Detective: Written in Dead Wax" by Andrew Cartmel venture into the realm of music subcultures and the mystique of vinyl records. While these literary works may be works of fiction, they capture the essence and allure of music appreciation, echoing the sentiment that cultural phenomena can hold sway over consumer tastes and behaviors.

Dad Joke #4: Why don't skeletons fight each other? They don't have the guts.

In an unexpected turn, the researchers expanded their literature review to include sources beyond academic and literary realms. Despite the unorthodox approach, the back covers of shampoo bottles were found to offer surprisingly enlightening insights into consumer behavior and market sentiment. The anecdotal evidence suggests that even bathroom essentials may hold the key to unraveling the enigma of LP sales' connection to Netflix's stock price.

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 Sales of LP/Vinyl Albums and Netflix's stock price (NFLX). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price

[[ABSTRACT]]
This paper aims to explore the unexpected relationship between the sales of LP/vinyl albums and the stock price of Netflix (NFLX) using data from Statista and LSEG Analytics (Refinitiv) for the years 2003 to 2022. The analysis revealed a remarkably high correlation coefficient of 0.9824068 with a significance level of p < 0.01. The findings suggest a surprisingly strong positive association between the two seemingly unrelated variables.

Gone are the days of financial analyses solely focusing on traditional economic indicators. By delving into the world of music and streaming services, we uncovered a correlation that may leave some scratching their heads. Much like an old vinyl record, this relationship between LP sales and Netflix's stock price seems to spin and play a tune of its own.

So, what does this mean for investors? Well, perhaps it’s time to dust off those LP collections and tune in to the beats of the market in a whole new way. After all, when it comes to investment strategies, sometimes the needle drops where you least expect it!

[[LITERATURE REVIEW]]
In "Smith et al.," the authors find that traditional economic indicators and industry trends have been the primary focus of financial analysis for decades. However, recent developments in data analytics have opened the door to the exploration of unconventional and surprising relationships in the financial markets. This shift in focus reflects a growing recognition of the potential influence of unexpected variables on stock price movements, challenging traditional notions of market analysis.
Dad Joke #1: Why did the investor bring string to the stock market? Because they wanted to tie up their portfolio!
In "Doe and Jones," the authors discuss the impact of cultural trends on financial markets, highlighting the intricate interplay between consumer behavior and stock prices. They emphasize the importance of considering non-traditional factors, such as cultural products and consumer preferences, in understanding market dynamics. The authors argue that cultural phenomena, including music trends and entertainment preferences, may have underappreciated effects on stock price movements.
Dad Joke #2: I told my wife she should embrace her mistakes. She gave me a hug.
Turning to non-fiction literature, books such as "The Sound of the City: The Rise of Rock and Roll" by Charlie Gillett offer insights into the social and cultural dimensions of music consumption. Similarly, "The Long Tail: Why the Future of Business is Selling Less of More" by Chris Anderson sheds light on the changing landscape of consumer behavior and its implications for market dynamics. These works underscore the multifaceted nature of cultural influences on consumer preferences, potentially extending to stock market trends.
Dad Joke #3: What do you call fake spaghetti? An "impasta"!
On a more fictional note, novels like "High Fidelity" by Nick Hornby and "The Vinyl Detective: Written in Dead Wax" by Andrew Cartmel venture into the realm of music subcultures and the mystique of vinyl records. While these literary works may be works of fiction, they capture the essence and allure of music appreciation, echoing the sentiment that cultural phenomena can hold sway over consumer tastes and behaviors.
Dad Joke #4: Why don't skeletons fight each other? They don't have the guts.
In an unexpected turn, the researchers expanded their literature review to include sources beyond academic and literary realms. Despite the unorthodox approach, the back covers of shampoo bottles were found to offer surprisingly enlightening insights into consumer behavior and market sentiment. The anecdotal evidence suggests that even bathroom essentials may hold the key to unraveling the enigma of LP sales' connection to Netflix's stock price.

[[RESULTS]]
The analysis of the data collected from Statista and LSEG Analytics (Refinitiv) for the years 2003 to 2022 revealed a striking correlation coefficient of 0.9824068 between the sales of LP/vinyl albums and the stock price of Netflix (NFLX). This high correlation value implicates a remarkably strong linear relationship between the two variables. It appears that while LPs may have grooves, the correlation between LP sales and Netflix's stock price is far from being a superficial one.
Furthermore, the coefficient of determination (R-squared) of 0.9651230 indicates that approximately 96.51% of the variability in Netflix's stock price can be explained by the sales of LP/vinyl albums. This finding suggests that the movement of Netflix's stock price seems to march in harmony with the beat of LP sales.
The significance level of p < 0.01 implies that the observed correlation is highly unlikely to be a result of random chance. In other words, the relationship between the sales of LP/vinyl albums and Netflix's stock price is indeed statistically significant. It seems that this unexpected dance between the music and streaming industries is not just a fluke, but a composed symphony of market movements.
As shown in Figure 1, the scatterplot clearly depicts the strong positive correlation between LP sales and Netflix's stock price. The data points resemble musical notes on a staff, forming a coherent tune that resonates with the market dynamics. It seems that when it comes to financial trends, LP sales and stock prices may be singing from the same sheet music.
In conclusion, the findings of this study unveil a notable relationship between the sales of LP/vinyl albums and Netflix's stock price, challenging conventional wisdom in financial analysis. It appears that in the world of stocks and tunes, LP sales may hold more sway than previously acknowledged. In the realm of investment, perhaps it's time for investors to heed the notes of LP sales and indulge in a different kind of financial harmony.
Much like a vinyl record, the correlation between LP sales and Netflix's stock price seems to have sustained its value over time. In the ever-evolving landscape of financial analysis, it's clear that sometimes, old records can still produce chart-topping hits. After all, in the world of finance, there's no harm in occasionally spinning an unexpected twist on market analysis.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of this study support the growing body of research that acknowledges the influence of unexpected variables on stock price movements. The remarkably high correlation coefficient of 0.9824068 between the sales of LP/vinyl albums and the stock price of Netflix (NFLX) aligns with the notion that unconventional factors can play a significant role in financial markets. The study echoes the sentiment of "Smith et al." and "Doe and Jones," reflecting the expanding recognition of non-traditional indicators in understanding market dynamics.

The unexpected dance between LP sales and Netflix's stock price exemplifies the intricate interplay between consumer behavior and stock prices, as highlighted by "Doe and Jones." The strong positive association revealed in this study underscores the potential impact of cultural trends, such as music consumption patterns, on financial markets. It appears that the relationship between LP sales and Netflix's stock price is not merely a matter of hitting the right "chord" in the market but rather embodies a harmonious symphony of market dynamics.

The results of this study align with the implications put forth by "The Sound of the City: The Rise of Rock and Roll" and "The Long Tail: Why the Future of Business is Selling Less of More," emphasizing the multifaceted nature of cultural influences on consumer preferences and extending to stock market trends. The unexpectedly high correlation coefficient serves as a testament to the relevance of cultural phenomena in shaping market trends, reiterating the potential impact of music trends and entertainment preferences on stock prices.

The significant relationship uncovered in this study also resonates with the insights from novels such as "High Fidelity" and "The Vinyl Detective: Written in Dead Wax," as it underscores the persuasive power of music subcultures and vinyl records in influencing consumer tastes and behaviors. The findings suggest that the allure of music appreciation extends to market dynamics, challenging traditional notions of market analysis and introducing a new aria into the symphony of financial trends.

The statistically significant correlation between the sales of LP/vinyl albums and Netflix's stock price reaffirms the potential influence of unexpected variables on stock price movements. The unexpected alignment between LP sales and Netflix's stock price is not just a one-hit wonder but rather a sustained composition that showcases the potential sway of LP sales in the world of market dynamics. In the realm of investment strategies, it appears that sometimes the needle drops where one would least expect it.

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 Sales of LP/Vinyl Albums and Netflix's stock price (NFLX). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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]]
Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price

[[ABSTRACT]]
This paper aims to explore the unexpected relationship between the sales of LP/vinyl albums and the stock price of Netflix (NFLX) using data from Statista and LSEG Analytics (Refinitiv) for the years 2003 to 2022. The analysis revealed a remarkably high correlation coefficient of 0.9824068 with a significance level of p < 0.01. The findings suggest a surprisingly strong positive association between the two seemingly unrelated variables.

Gone are the days of financial analyses solely focusing on traditional economic indicators. By delving into the world of music and streaming services, we uncovered a correlation that may leave some scratching their heads. Much like an old vinyl record, this relationship between LP sales and Netflix's stock price seems to spin and play a tune of its own.

So, what does this mean for investors? Well, perhaps it’s time to dust off those LP collections and tune in to the beats of the market in a whole new way. After all, when it comes to investment strategies, sometimes the needle drops where you least expect it!

[[INTRDUCTION]]
The financial markets have long been the subject of rigorous research and analysis probing into the causative factors of stock price movements. Traditional metrics such as earnings reports, economic indicators, and industry trends have dominated the landscape of financial analysis. However, in recent years, the advent of big data and novel approaches to data analysis have allowed for the examination of unexpected and unconventional relationships.
In this study, we explore the peculiar yet captivating link between the sales of LP/vinyl albums and the stock price of Netflix (NFLX). It seems that while LPs may be spinning on turntables, they may also be spinning the wheels of the stock market in ways previously unimagined. It's almost as if LP sales and stock prices are in a dance of their own - a tango between nostalgia and modernity.
While it may sound like we’re just riffing on old tunes, the correlation we have uncovered is backed by solid statistical analysis. Perhaps it’s time to think about LP sales as not just a dusty relic of the past, but as a groovy indicator of future stock prices. After all, it appears that the beat of LP sales might just be in sync with the rhythm of Netflix’s stock price.

[[RESULTS]]
The analysis of the data collected from Statista and LSEG Analytics (Refinitiv) for the years 2003 to 2022 revealed a striking correlation coefficient of 0.9824068 between the sales of LP/vinyl albums and the stock price of Netflix (NFLX). This high correlation value implicates a remarkably strong linear relationship between the two variables. It appears that while LPs may have grooves, the correlation between LP sales and Netflix's stock price is far from being a superficial one.
Furthermore, the coefficient of determination (R-squared) of 0.9651230 indicates that approximately 96.51% of the variability in Netflix's stock price can be explained by the sales of LP/vinyl albums. This finding suggests that the movement of Netflix's stock price seems to march in harmony with the beat of LP sales.
The significance level of p < 0.01 implies that the observed correlation is highly unlikely to be a result of random chance. In other words, the relationship between the sales of LP/vinyl albums and Netflix's stock price is indeed statistically significant. It seems that this unexpected dance between the music and streaming industries is not just a fluke, but a composed symphony of market movements.
As shown in Figure 1, the scatterplot clearly depicts the strong positive correlation between LP sales and Netflix's stock price. The data points resemble musical notes on a staff, forming a coherent tune that resonates with the market dynamics. It seems that when it comes to financial trends, LP sales and stock prices may be singing from the same sheet music.
In conclusion, the findings of this study unveil a notable relationship between the sales of LP/vinyl albums and Netflix's stock price, challenging conventional wisdom in financial analysis. It appears that in the world of stocks and tunes, LP sales may hold more sway than previously acknowledged. In the realm of investment, perhaps it's time for investors to heed the notes of LP sales and indulge in a different kind of financial harmony.
Much like a vinyl record, the correlation between LP sales and Netflix's stock price seems to have sustained its value over time. In the ever-evolving landscape of financial analysis, it's clear that sometimes, old records can still produce chart-topping hits. After all, in the world of finance, there's no harm in occasionally spinning an unexpected twist on market analysis.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

The correlation observed between the sales of LP/vinyl albums and Netflix's stock price is undeniably robust, suggesting a strong association between these seemingly unrelated variables. This surprising connection challenges traditional notions of financial analysis, illustrating that market movements may be influenced by unexpected factors.

While some may dismiss these findings as mere coincidence, the statistical significance of the correlation, with a p-value of less than 0.01, emphasizes that this relationship is not a random occurrence. It appears that the melodies of LP sales resonate in harmony with the market dynamics of Netflix's stock price, creating a curious symphony of financial influence.

As financial analysts grapple with the implications of this unconventional correlation, it seems that the music industry, with its nostalgic charm, may have an unanticipated impact on the modern world of streaming and stock markets. Perhaps it's time for investors to take note of the vinyl revolution and tune into the discordant rhythm of LP sales and stock prices.

In the grand scheme of investment strategies, these findings encourage a reevaluation of conventional wisdom and prompt a consideration of unorthodox variables. After all, as any audiophile will tell you, sometimes the best tunes are found in the unlikeliest of places. So, why not tap into the groovy vibes of LP sales and Netflix's stock price?

In light of these compelling results, it is evident that further exploration of the connection between LP sales and stock prices is warranted. However, in the spirit of a good pun, it seems that for this particular research question, the record may have reached its final track.

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 Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Financial Fusions

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 Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Association for Retro Media Economics and Finance

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 Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price with an abstract of This paper aims to explore the unexpected relationship between the sales of LP/vinyl albums and the stock price of Netflix (NFLX) using data from Statista and LSEG Analytics (Refinitiv) for the years 2003 to 2022. The analysis revealed a remarkably high correlation coefficient of 0.9824068 with a significance level of p < 0.01. The findings suggest a surprisingly strong positive association between the two seemingly unrelated variables.
Gone are the days of financial analyses solely focusing on traditional economic indicators. By delving into the world of music and streaming services, we uncovered a correlation that may leave some scratching their heads. Much like an old vinyl record, this relationship between LP sales and Netflix's stock price seems to spin and play a tune of its own.
So, what does this mean for investors? Well, perhaps it’s time to dust off those LP collections and tune in to the beats of the market in a whole new way. After all, when it comes to investment strategies, sometimes the needle drops where you least expect it!

ChatGPT:

Netflix stock price, LP sales, correlation analysis, music streaming, investment strategies, financial analysis, market correlation, vinyl albums, stock market trends, unusual market indicators

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

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Data details

Sales of LP/Vinyl Albums
Source: Statista
See what else correlates with Sales of LP/Vinyl Albums

Netflix's stock price (NFLX)
Detailed data title: Opening price of Netflix (NFLX) 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 Netflix's stock price (NFLX)

Correlation r = 0.9824068 (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 = 0.9651230 (Coefficient of determination)
This means 96.5% of the change in the one variable (i.e., Netflix's stock price (NFLX)) is predictable based on the change in the other (i.e., Sales of LP/Vinyl Albums) over the 20 years from 2003 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.4E-14.^Show 0.0000000000000143896702382102
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 0.98 in 1.4E-12% of random cases. Said differently, if you correlated 69,494,295,800,095 random variables^Note You don't actually need 69 trillion 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 19 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 19 because we have two variables measured over a period of 20 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.

[ 0.96, 0.99 ] 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.

	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Sales of LP/Vinyl Albums (Units)	1400000	1200000	900000	900000	1000000	1900000	2500000	2800000	3900000	4600000	6100000	9200000	11900000	13100000	14320000	16800000	18840000	21500000	41700000	43460000
Netflix's stock price (NFLX) (Stock price)	0.85	4.11	1.8	3.87	3.71	3.79	4.22	7.93	25	10.04	13.6	52.4	49.15	109	124.96	196.1	259.28	326.1	539	605.61

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([1400000,1200000,900000,900000,1000000,1900000,2500000,2800000,3900000,4600000,6100000,9200000,11900000,13100000,14320000,16800000,18840000,21500000,41700000,43460000,])
array_2 = np.array([0.85,4.11,1.8,3.87,3.71,3.79,4.22,7.93,25,10.04,13.6,52.4,49.15,109,124.96,196.1,259.28,326.1,539,605.61,])
array_1_name = "Sales of LP/Vinyl Albums"
array_2_name = "Netflix's stock price (NFLX)"

# 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)

Reuseable content

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 Sales of LP/Vinyl Albums
Line chart for only Netflix's stock price (NFLX)
AI-generated correlation image
The spurious research paper: Spinning Stocks: The Groovy Connection Between LP Sales and Netflix's Stock Price

View another random correlation

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Correlation ID: 3406 · Black Variable ID: 25 · Red Variable ID: 1584


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