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Spurious correlation #1,275 · View random

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is The distance between Neptune and Uranus and the second variable is SAP SE's stock price (SAP).  The chart goes from 2002 to 2023, and the two variables track closely in value over that time. Small Image
Download png
, svg

AI explanation

As the gap between the two far-off planets widened, it created a ripple effect in the cosmic energy market, leading to an unexpected boost in SAP SE's stock price on Earth's stock exchanges. It's a stellar reminder that even astronomical distances can't eclipse the power of stock market fluctuations!

Model: dalle-3
Prompt: Generate an image of a futuristic space scene with two large, luminous planets, Neptune and Uranus, elegantly retreating from each other in the cosmic expanse. In the middle, Saturn sits aligned with the diverging planets, forming an impeccable straight line. Glide through the vast void, a sleek spaceship representing SAP SE, glistening with advanced technology, navigates effortlessly between the celestial bodies, symbolizing the expansion of interstellar commerce and prosperity. The overall scene should exude a sense of awe-inspiring grandeur and technological advancement. 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 situation described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here is a situation: Because the increased distance caused Neptune and Uranus to align with Saturn, boosting SAP SE's profits with interplanetary business solutions.. Given that situation, which of the following image descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand and the tone of the explanation. Please respond with only one of the following potential descriptions: An image that looks like it is a scene from a Pixar movie Futuristic A scene from Skyrim Cute cartoon Cubism
ChatGPT: Futuristic

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated and the explanation described. Do not reference graphs or charts; describe physical objects.
User prompt: Please describe a visual scene that depicts the following situation. Keep the description simple. Because the increased distance caused Neptune and Uranus to align with Saturn, boosting SAP SE's profits with interplanetary business solutions.
ChatGPT: In the scene, we see two large planets, Neptune and Uranus, moving away from each other, creating an increased distance. Meanwhile, another planet, Saturn, is positioned in between them, forming a straight line. A spaceship representing SAP SE is shown traveling smoothly between the aligned planets, symbolizing the boost in profits from interplanetary business solutions.

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: [ Futuristic ] and depicting this scene: In the scene, we see two large planets, Neptune and Uranus, moving away from each other, creating an increased distance. Meanwhile, another planet, Saturn, is positioned in between them, forming a straight line. A spaceship representing SAP SE is shown traveling smoothly between the aligned planets, symbolizing the boost in profits from interplanetary business solutions. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a futuristic space scene with two large, luminous planets, Neptune and Uranus, elegantly retreating from each other in the cosmic expanse. In the middle, Saturn sits aligned with the diverging planets, forming an impeccable straight line. Glide through the vast void, a sleek spaceship representing SAP SE, glistening with advanced technology, navigates effortlessly between the celestial bodies, symbolizing the expansion of interstellar commerce and prosperity. The overall scene should exude a sense of awe-inspiring grandeur and technological advancement.

*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.

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 The distance between Neptune and Uranus caused SAP SE's stock price (SAP) to increase. Add a funny one-liner at the end.

AI academic paper

(Because p < 0.01)
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

Cosmic Finance Quarterly

Jan 2024

Reminder: This paper is AI-generated. Not real!
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 write titles and abstracts of goofy academic research papers.
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, and add unexpected twists in your writing.

Please draft the title and abstract of an academic research paper presenting the findings of the connection between The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns.

Make the title an alliteration.

Your research team used data from Caclculated using Astropy and LSEG Analytics (Refinitiv) to assess this nagging question. You found a correlation coefficient of 0.9256769 and p < 0.01 for 2002 to 2023.

Please respond in this format (replace "Lorem ipsum dolor sit" with your title and abstract)

[[TITLE]]
Lorem ipsum dolor sit

[[ABSTRACT]]
Lorem ipsum dolor sit



ChatGPT:
[[TITLE]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.


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 introduction 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 introduction section of an academic research paper presenting the findings of the connection between The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Here is the title and abstract of the paper:
[[TITLE]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

-------

Your response should start like this:

[[INTRODUCTION]]



ChatGPT:
[[INTRODUCTION]]

The relationship between celestial bodies and earthly matters has fascinated mankind for centuries. Despite the vast distances that separate them, the movements of planets have often been linked, both seriously and whimsically, to events on our own little blue planet. In this study, we delve into the whimsical side as we explore the potential connection between the distance between Neptune and Uranus and the stock price of SAP SE (SAP).

While some may find the idea frivolous, we assure you that the calculations and analyses presented here are anything but. Utilizing data painstakingly collected and calculated using Astropy and LSEG Analytics (Refinitiv), we aim to bring light to this interstellar curiosity. Yes, you read that right – we are indeed bringing "light" into the mix, both figuratively and literally speaking.

Now, before you raise an eyebrow and think we've gone off into the deep end of the cosmos, rest assured that we are as grounded in statistical rigor as any reputable study should be. Our aim is not just to amuse but to uncover any potential patterns that may exist between the fluctuations of Neptune and Uranus and the swings of SAP stock prices. This inquiry is just as much a study in financial markets as it is a playful nod to the cosmic ballet that unfolds above us.

The pursuit of knowledge often takes us to unexpected places, and in this case, it has led us to the outer reaches of our solar system. Join us as we embark upon this celestial journey and see how the movements of planets may hold a clue to the movements of stocks. After all, in the vast sea of economics and astrophysics, perhaps there's room for a little cosmic whimsy.


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 The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns.

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 name a couple popular internet memes that are related to one of the topics.

Here is the title and abstract of the paper:
[[TITLE]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The relationship between celestial bodies and earthly matters has fascinated mankind for centuries. Despite the vast distances that separate them, the movements of planets have often been linked, both seriously and whimsically, to events on our own little blue planet. In this study, we delve into the whimsical side as we explore the potential connection between the distance between Neptune and Uranus and the stock price of SAP SE (SAP).
While some may find the idea frivolous, we assure you that the calculations and analyses presented here are anything but. Utilizing data painstakingly collected and calculated using Astropy and LSEG Analytics (Refinitiv), we aim to bring light to this interstellar curiosity. Yes, you read that right – we are indeed bringing "light" into the mix, both figuratively and literally speaking.
Now, before you raise an eyebrow and think we've gone off into the deep end of the cosmos, rest assured that we are as grounded in statistical rigor as any reputable study should be. Our aim is not just to amuse but to uncover any potential patterns that may exist between the fluctuations of Neptune and Uranus and the swings of SAP stock prices. This inquiry is just as much a study in financial markets as it is a playful nod to the cosmic ballet that unfolds above us.
The pursuit of knowledge often takes us to unexpected places, and in this case, it has led us to the outer reaches of our solar system. Join us as we embark upon this celestial journey and see how the movements of planets may hold a clue to the movements of stocks. After all, in the vast sea of economics and astrophysics, perhaps there's room for a little cosmic whimsy.

-------

Your response should start like this:

[[LITERATURE REVIEW]]



ChatGPT:
[[LITERATURE REVIEW]]

Previous studies have touched upon the interplay between celestial phenomena and human affairs, albeit in less conventional manners. Smith (2008) explored the implications of lunar phases on market sentiment, finding a curious link between the full moon and stock market performance. Doe (2015) delved into the astrological signs of CEOs, postulating that the alignment of stars at birth may influence executive decision-making. Jones (2017) took a different tack and studied the impact of sunspots on commodity prices, unearthing a connection that defies conventional economic theories.

Turning to more tangentially related literature, "Astrophysics for People in a Hurry" by Neil deGrasse Tyson offers a lucid distillation of cosmic concepts for the layperson, reminding us that even the most complex phenomena can be made accessible. In a similar vein, "Cosmos" by Carl Sagan provides a poetic journey through the universe, inspiring awe and wonder at our place in the cosmos.

Venturing into the realm of fiction, one encounters "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, a whimsical romp through space that showcases the absurdities of the universe. Meanwhile, the classic "Neuromancer" by William Gibson delves into a cyberpunk future where human consciousness intertwines with the digital realm, reminding us that even in the celestial expanse, technology and humanity intersect in unforeseen ways.

A more contemporary source of celestial amusement comes in the form of the "Distracted Boyfriend" meme, where a man's wandering eye invites playful interpretations. In this case, we can't help but draw a parallel to investors keeping an eye on alternative stocks while SAP's performance may be drifting away.

As we weave together these seemingly disparate threads of literature, we find ourselves poised for a cosmic collision of the celestial and the financial, steering us towards a nebula of possibilities in understanding the celestial connection to SAP stock prices.


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 The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Caclculated using Astropy and LSEG Analytics (Refinitiv) . You used data from 2002 to 2023

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]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

[[INTRODUCTION]]
The relationship between celestial bodies and earthly matters has fascinated mankind for centuries. Despite the vast distances that separate them, the movements of planets have often been linked, both seriously and whimsically, to events on our own little blue planet. In this study, we delve into the whimsical side as we explore the potential connection between the distance between Neptune and Uranus and the stock price of SAP SE (SAP).
While some may find the idea frivolous, we assure you that the calculations and analyses presented here are anything but. Utilizing data painstakingly collected and calculated using Astropy and LSEG Analytics (Refinitiv), we aim to bring light to this interstellar curiosity. Yes, you read that right – we are indeed bringing "light" into the mix, both figuratively and literally speaking.
Now, before you raise an eyebrow and think we've gone off into the deep end of the cosmos, rest assured that we are as grounded in statistical rigor as any reputable study should be. Our aim is not just to amuse but to uncover any potential patterns that may exist between the fluctuations of Neptune and Uranus and the swings of SAP stock prices. This inquiry is just as much a study in financial markets as it is a playful nod to the cosmic ballet that unfolds above us.
The pursuit of knowledge often takes us to unexpected places, and in this case, it has led us to the outer reaches of our solar system. Join us as we embark upon this celestial journey and see how the movements of planets may hold a clue to the movements of stocks. After all, in the vast sea of economics and astrophysics, perhaps there's room for a little cosmic whimsy.

-------

Your response should start like this:

[[METHODOLOGY]]



ChatGPT:

[[METHODOLOGY]]

To grapple with the enigmatic relationship between the cosmic dance of Neptune and Uranus and the capricious fluctuations of SAP SE's stock price, we employed a methodological approach that is as avant-garde as it is rigorously scientific. First, we harnessed the power of data mining techniques to extract celestial data on the positions of Neptune and Uranus from a variety of reputable sources, including but not limited to NASA and the European Space Agency. With this astronomical data in hand, we then meticulously cross-referenced it with stock price data for SAP SE extracted from the depths of known financial databases, including the illustrious archives of Financial Times and Bloomberg.

Our research team wielded the statistical weaponry of correlation analysis to unveil potential connections between the relative positions of Neptune and Uranus and the tempestuous temblors of SAP stock prices. We calculated the distance between the two planets and synchronized these values with the corresponding stock prices to unleash the power of Pearson's correlation coefficient. The resulting tidal wave of statistical significance flooded our analysis, revealing a correlation coefficient of 0.9256769 with p < 0.01, signifying a robust relationship that defies the gravitational pull of conventional expectations.

To ensure the robustness of our findings, we navigated the treacherous waters of time series analysis, employing both autoregressive integrated moving average (ARIMA) models and harmonic analysis to detect potential cyclical patterns in the interstellar-stock nexus. Our voyage through the spacetime continuum yielded compelling results, further reinforcing the profound intertwining of distant planets and earthly fortunes.

Moreover, mindful of potential spurious correlations, we conducted a battery of rigorous tests, including cross-validation procedures and Monte Carlo simulations, to pierce through the nebulous veil of chance and ascertain the authenticity of our celestial discoveries.

Our data, spanning the years from 2002 to 2023, were procured from a panoply of sources, including but not limited to Astropy and LSEG Analytics (Refinitiv). Through our intrepid efforts, we have spun a cosmic web that entwines the orbits of distant worlds with the haphazard leaps of stock prices, shedding light on a galaxy of financial insight that challenges the conventions of terrestrial causality.


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 results section of an academic research paper. You speak in the past tense (you found...).
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 results section of an academic research paper presenting the findings of the connection between The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

Your research team collected data from all across the internet, but mostly just used information from Caclculated using Astropy and LSEG Analytics (Refinitiv) .

For the time period 2002 to 2023, you found a correlation 0.9256769, r-squared of 0.8568777, and p < 0.01.

One figure will be included. The figure (Fig. 1) is a scatterplot showing the strong correlation between the two variables. You don't need to specify where; I will add the figure.

Here is the title and abstract of the paper:
[[TITLE]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

-------

And here is the methodology section that led to this result:
[[METHODOLOGY]]
The relationship between celestial bodies and earthly matters has fascinated mankind for centuries. Despite the vast distances that separate them, the movements of planets have often been linked, both seriously and whimsically, to events on our own little blue planet. In this study, we delve into the whimsical side as we explore the potential connection between the distance between Neptune and Uranus and the stock price of SAP SE (SAP).
While some may find the idea frivolous, we assure you that the calculations and analyses presented here are anything but. Utilizing data painstakingly collected and calculated using Astropy and LSEG Analytics (Refinitiv), we aim to bring light to this interstellar curiosity. Yes, you read that right – we are indeed bringing "light" into the mix, both figuratively and literally speaking.
Now, before you raise an eyebrow and think we've gone off into the deep end of the cosmos, rest assured that we are as grounded in statistical rigor as any reputable study should be. Our aim is not just to amuse but to uncover any potential patterns that may exist between the fluctuations of Neptune and Uranus and the swings of SAP stock prices. This inquiry is just as much a study in financial markets as it is a playful nod to the cosmic ballet that unfolds above us.
The pursuit of knowledge often takes us to unexpected places, and in this case, it has led us to the outer reaches of our solar system. Join us as we embark upon this celestial journey and see how the movements of planets may hold a clue to the movements of stocks. After all, in the vast sea of economics and astrophysics, perhaps there's room for a little cosmic whimsy.

-------

Your response should start like this:

[[RESULTS]]



ChatGPT:

[[RESULTS]]

The analysis of the data from 2002 to 2023 revealed a remarkably strong correlation (r = 0.9256769) between the distance separating Neptune and Uranus and the stock price of SAP SE (SAP). This finding suggests a striking relationship between the celestial dance of these two distant planets and the gyrations of the stock market. The coefficient of determination (r-squared = 0.8568777) further bolsters this observation, indicating that approximately 85.69% of the variation in SAP's stock price can be explained by the changing distance between Neptune and Uranus.

The p-value (p < 0.01) obtained from the statistical analysis indicates that the probability of observing such a strong correlation by chance alone is less than 1%. These results significantly support the alternative hypothesis that there is a meaningful association between the astronomical phenomenon under scrutiny and the performance of SAP's stock.

To visually depict the observed correlation, a scatterplot (Fig. 1) has been included. The scatterplot clearly illustrates the strong positive relationship between the measured variables, exuding a cosmic charm that is sure to draw attention from both financial and celestial enthusiasts alike.

The findings of this study not only hint at the potential impact of cosmic events on earthly financial systems but also serve as a reminder of the interconnectivity of seemingly disparate cosmic entities. While the results may seem out of this world, they provide an intriguing avenue for further investigation into the enigmatic interplay between the movements of celestial bodies and the movements of financial markets.


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 The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

[[LITERATURE REVIEW]]
Previous studies have touched upon the interplay between celestial phenomena and human affairs, albeit in less conventional manners. Smith (2008) explored the implications of lunar phases on market sentiment, finding a curious link between the full moon and stock market performance. Doe (2015) delved into the astrological signs of CEOs, postulating that the alignment of stars at birth may influence executive decision-making. Jones (2017) took a different tack and studied the impact of sunspots on commodity prices, unearthing a connection that defies conventional economic theories.
Turning to more tangentially related literature, "Astrophysics for People in a Hurry" by Neil deGrasse Tyson offers a lucid distillation of cosmic concepts for the layperson, reminding us that even the most complex phenomena can be made accessible. In a similar vein, "Cosmos" by Carl Sagan provides a poetic journey through the universe, inspiring awe and wonder at our place in the cosmos.
Venturing into the realm of fiction, one encounters "The Hitchhiker's Guide to the Galaxy" by Douglas Adams, a whimsical romp through space that showcases the absurdities of the universe. Meanwhile, the classic "Neuromancer" by William Gibson delves into a cyberpunk future where human consciousness intertwines with the digital realm, reminding us that even in the celestial expanse, technology and humanity intersect in unforeseen ways.
A more contemporary source of celestial amusement comes in the form of the "Distracted Boyfriend" meme, where a man's wandering eye invites playful interpretations. In this case, we can't help but draw a parallel to investors keeping an eye on alternative stocks while SAP's performance may be drifting away.
As we weave together these seemingly disparate threads of literature, we find ourselves poised for a cosmic collision of the celestial and the financial, steering us towards a nebula of possibilities in understanding the celestial connection to SAP stock prices.

[[RESULTS]]
The analysis of the data from 2002 to 2023 revealed a remarkably strong correlation (r = 0.9256769) between the distance separating Neptune and Uranus and the stock price of SAP SE (SAP). This finding suggests a striking relationship between the celestial dance of these two distant planets and the gyrations of the stock market. The coefficient of determination (r-squared = 0.8568777) further bolsters this observation, indicating that approximately 85.69% of the variation in SAP's stock price can be explained by the changing distance between Neptune and Uranus.
The p-value (p < 0.01) obtained from the statistical analysis indicates that the probability of observing such a strong correlation by chance alone is less than 1%. These results significantly support the alternative hypothesis that there is a meaningful association between the astronomical phenomenon under scrutiny and the performance of SAP's stock.
To visually depict the observed correlation, a scatterplot (Fig. 1) has been included. The scatterplot clearly illustrates the strong positive relationship between the measured variables, exuding a cosmic charm that is sure to draw attention from both financial and celestial enthusiasts alike.
The findings of this study not only hint at the potential impact of cosmic events on earthly financial systems but also serve as a reminder of the interconnectivity of seemingly disparate cosmic entities. While the results may seem out of this world, they provide an intriguing avenue for further investigation into the enigmatic interplay between the movements of celestial bodies and the movements of financial markets.

-------

Your response should start like this:

[[DISCUSSION]]



ChatGPT:

[[DISCUSSION]]

The findings of this research provide a celestial twist to the understanding of financial markets. The remarkably strong correlation identified between the distance separating Neptune and Uranus and the stock price of SAP SE (SAP) corroborates prior studies that have explored unorthodox connections between cosmic phenomena and human affairs.

Indeed, while some may consider the study of celestial bodies in relation to financial markets as "Neptunian Nonsense," the results suggest a tangible association that is truly out of this world. This celestial connection adds a cosmic humor to the world of finance, infusing a touch of whimsy into the typically serious realm of stock analysis.

The previous work of Smith (2008), which delved into the implications of lunar phases on market sentiment, and Doe's (2015) investigation of the astrological signs of CEOs, hint at the broader influence of celestial bodies on financial activities. The findings of this study align with these earlier works, providing further evidence of the surprising ways in which cosmic events can influence earthly affairs.

Moreover, as Jones (2017) revealed the impact of sunspots on commodity prices, our research adds to the growing body of literature that defies conventional economic theories by incorporating celestial variables into market analysis. It is fascinating to imagine the cosmos exerting an unseen pull on the movements of stock prices, echoing the gravitational forces that govern the celestial bodies themselves.

The unexpected correlation coefficient of 0.9256769 and the statistically significant p-value reinforce the argument that there is a meaningful association between the distance between Neptune and Uranus and the performance of SAP's stock. These results not only raise eyebrows but also raise the specter of further research into the cosmic influences on stock market dynamics.

The scatterplot included in this study (Fig. 1) visualizes this celestial journey, demonstrating the strong positive relationship between the measured variables. It is a graphic representation that is sure to draw nods of cosmic approval from both financial and celestial enthusiasts alike, serving as a reminder of the interconnectedness of seemingly disparate cosmic entities.

In conclusion, while this study may have started with Neptunian Nonsense, it has navigated through the celestial expanse to shed light on a potential interplanetary influence on the stock market. The implications of this discovery are as far-reaching as the celestial bodies that inspired it, opening the floodgates for further investigation into the enigmatic interplay between the movements of cosmic bodies and the movements of financial markets.


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 The distance between Neptune and Uranus and SAP SE's stock price (SAP). Make lots of jokes, goofy observations, and puns. Sneak in some jokes and clever puns about science, research, statistics, and the variables.

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]]
Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price

[[ABSTRACT]]
This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

[[INTRDUCTION]]
The relationship between celestial bodies and earthly matters has fascinated mankind for centuries. Despite the vast distances that separate them, the movements of planets have often been linked, both seriously and whimsically, to events on our own little blue planet. In this study, we delve into the whimsical side as we explore the potential connection between the distance between Neptune and Uranus and the stock price of SAP SE (SAP).
While some may find the idea frivolous, we assure you that the calculations and analyses presented here are anything but. Utilizing data painstakingly collected and calculated using Astropy and LSEG Analytics (Refinitiv), we aim to bring light to this interstellar curiosity. Yes, you read that right – we are indeed bringing "light" into the mix, both figuratively and literally speaking.
Now, before you raise an eyebrow and think we've gone off into the deep end of the cosmos, rest assured that we are as grounded in statistical rigor as any reputable study should be. Our aim is not just to amuse but to uncover any potential patterns that may exist between the fluctuations of Neptune and Uranus and the swings of SAP stock prices. This inquiry is just as much a study in financial markets as it is a playful nod to the cosmic ballet that unfolds above us.
The pursuit of knowledge often takes us to unexpected places, and in this case, it has led us to the outer reaches of our solar system. Join us as we embark upon this celestial journey and see how the movements of planets may hold a clue to the movements of stocks. After all, in the vast sea of economics and astrophysics, perhaps there's room for a little cosmic whimsy.

[[RESULTS]]
The analysis of the data from 2002 to 2023 revealed a remarkably strong correlation (r = 0.9256769) between the distance separating Neptune and Uranus and the stock price of SAP SE (SAP). This finding suggests a striking relationship between the celestial dance of these two distant planets and the gyrations of the stock market. The coefficient of determination (r-squared = 0.8568777) further bolsters this observation, indicating that approximately 85.69% of the variation in SAP's stock price can be explained by the changing distance between Neptune and Uranus.
The p-value (p < 0.01) obtained from the statistical analysis indicates that the probability of observing such a strong correlation by chance alone is less than 1%. These results significantly support the alternative hypothesis that there is a meaningful association between the astronomical phenomenon under scrutiny and the performance of SAP's stock.
To visually depict the observed correlation, a scatterplot (Fig. 1) has been included. The scatterplot clearly illustrates the strong positive relationship between the measured variables, exuding a cosmic charm that is sure to draw attention from both financial and celestial enthusiasts alike.
The findings of this study not only hint at the potential impact of cosmic events on earthly financial systems but also serve as a reminder of the interconnectivity of seemingly disparate cosmic entities. While the results may seem out of this world, they provide an intriguing avenue for further investigation into the enigmatic interplay between the movements of celestial bodies and the movements of financial markets.

-------

Your response should start like this:

[[CONCLUSION]]



ChatGPT:

[[CONCLUSION]]

In conclusion, our research has revealed a celestial connection that is truly "out of this world" - the distance between Neptune and Uranus seems to have a cosmic influence on the stock price of SAP SE (SAP). This correlation coefficient of 0.9256769 and p-value < 0.01 is quite a "stellar" finding, indicating a strong link between these seemingly unrelated phenomena. With a coefficient of determination of 0.8568777, approximately 85.69% of SAP's stock price variation can be "astronomically" explained by the changing distance between these distant planets.

The scatterplot (Fig. 1) not only depicts this strong positive relationship but also exudes a cosmic charm that is sure to "eclipse" other financial analyses. It's safe to say that our results are quite "celestial" and may come as a "shock-wave" to the finance world.

While our findings may seem like they're from a different "orbit," they highlight the interconnectedness of the cosmic ballet and earthly financial systems. A playful nod to the whimsical side of research, this study adds a dash of cosmic humor and reminds us that even in the world of finance, there's always room for a little "space oddity."

We believe that our research sheds "starlight" on the interplay between distant celestial bodies and the movements of financial markets. However, no more research is needed in this area. It's time for us to "planet" and move on to new frontiers of inquiry.


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 Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

Cosmic Finance Quarterly


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 Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Society for Speculative Space Studies


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 Neptunian Nonsense: Navigating the Nexus between Neptune's Nearness and SAP SE Stock Price with an abstract of This study navigates through the celestial realm to investigate the potential link between the distance between Neptune and Uranus and the stock price of SAP SE (SAP). Utilizing data meticulously gathered from calculated using Astropy and LSEG Analytics (Refinitiv), we explore the truly astronomical question at hand. Surprisingly, we uncover a correlation coefficient of 0.9256769 and p < 0.01 during the time period of 2002 to 2023, suggesting a connection that is truly out of this world. Our findings not only shed light on the interplanetary influence on the stock market but also add a dash of cosmic humor to the world of finance.

ChatGPT:

Neptune, Uranus, SAP stock price, celestial influence, interplanetary correlation, Astropy data, LSEG Analytics, Refinitiv data, finance, stock market, correlation coefficient, cosmic humor, Neptune's distance, SAP SE, astronomical question

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



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Data details

The distance between Neptune and Uranus
Detailed data title: The average distance between Neptune and Uranus as measured on the first day of each month
Source: Caclculated using Astropy
Additional Info: I wrote a Python script using Astropy to calculate the distance between the named planets on the first day of each month for every year.

See what else correlates with The distance between Neptune and Uranus

SAP SE's stock price (SAP)
Detailed data title: Opening price of SAP SE (SAP) on the first trading day of the year
Source: LSEG Analytics (Refinitiv)
Additional Info: Via Microsoft Excel Stockhistory function

See what else correlates with SAP SE's stock price (SAP)

Correlation r = 0.9256769 (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 = 0.8568777 (Coefficient of determination)
This means 85.7% of the change in the one variable (i.e., SAP SE's stock price (SAP)) is predictable based on the change in the other (i.e., The distance between Neptune and Uranus) over the 22 years from 2002 through 2023.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 6.8E-10. 0.0000000006813504984717255000
The p-value is a measure of how probable it is that we would randomly find a result this extreme. 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 0.93 in 6.8E-8% of random cases. Said differently, if you correlated 1,467,673,396 random variables You don't actually need 1 billion 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 21 degrees of freedom, Degrees of freedom is a measure of how many free components we are testing. In this case it is 21 because we have two variables measured over a period of 22 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.

[ 0.83, 0.97 ] 95% correlation confidence interval (using the Fisher z-transformation)
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: 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.
2002200320042005200620072008200920102011201220132014201520162017201820192020202120222023
The distance between Neptune and Uranus (Planetary distance (AU))12.394712.811913.257913.727514.21814.72715.253215.792516.343816.90617.479118.059718.647619.242319.844320.450721.061621.676822.297322.920423.546524.1757
SAP SE's stock price (SAP) (Stock price)32.4520.2242.7544.5645.6153.751.7935.6547.2350.6654.2882.0584.9769.7976.7486.25111.2398.57135.42131.66140.32104.04




Why this works

  1. 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.
  2. Lack of causal connection: There is probably 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.
  3. 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 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.
  4. Y-axis doesn't start at zero: I truncated the Y-axes of the graph above. I also used a line graph, which makes the visual connection stand out more than it deserves. Nothing against line graphs. They are great at telling a story when you have linear data! But visually it is deceptive because the only data is at the points on the graph, not the lines on the graph. In between each point, the data could have been doing anything. Like going for a random walk by itself!
    Mathematically what I showed is true, but it is intentionally misleading. Below is the same chart but with both Y-axes starting at zero.




Try it yourself

You can calculate the values on this page on your own! Try running the Python code to see the calculation results. 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([12.3947,12.8119,13.2579,13.7275,14.218,14.727,15.2532,15.7925,16.3438,16.906,17.4791,18.0597,18.6476,19.2423,19.8443,20.4507,21.0616,21.6768,22.2973,22.9204,23.5465,24.1757,])
array_2 = np.array([32.45,20.22,42.75,44.56,45.61,53.7,51.79,35.65,47.23,50.66,54.28,82.05,84.97,69.79,76.74,86.25,111.23,98.57,135.42,131.66,140.32,104.04,])
array_1_name = "The distance between Neptune and Uranus"
array_2_name = "SAP SE's stock price (SAP)"

# 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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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.

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Correlation ID: 1275 · Black Variable ID: 1967 · Red Variable ID: 1590
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