Spurious correlation #3,108 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Hydopower energy generated in Kosovo and the second variable is The Home Depot's stock price (HD). The chart goes from 2008 to 2021, 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 Hydopower energy generated in Kosovo and the second variable is The Home Depot's stock price (HD). The chart goes from 2008 to 2021, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As Kosovo's hydropower output surged, it created a literal 'flood' of electricity, sparking a shocking demand for power tools and construction supplies. This surge in electrical potential sent a current of excitement through The Home Depot, leading to a power-packed boost in their stock price. It seems like their profits are certainly not going 'down the drain' with this electrifying connection to Kosovo's hydropower!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image that captures the juxtaposition between nature and commerce in Kosovo. Highlight a bustling hydroelectric plant with the rushing waters generating powerful energy, set against a scenic backdrop. In the distance, emphasize a Home Depot store standing boldly. The storefront features a vibrant, green stock price chart soaring upwards to epitomize the surge in sales and stock prices due to increased demand for plumbing supplies. The image should evoke a sense of the dynamic relationship between industry and the natural world, offering a striking, parallax-style representation of this scene. 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: Hydopower energy generated in Kosovo and The Home Depot's stock price (HD). 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: A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s Parallax art A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s a Polaroid photo A comic-book-style illustration with muted colors and a dotted halftone pattern from the 1960s
ChatGPT: Parallax art

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 Hydopower energy generated in Kosovo and The Home Depot's stock price (HD), in the following situation: Because as Kosovo generated more hydroelectric power, the increased water flow created a booming demand for Home Depot's plumbing supplies, boosting their sales and stock price.. Keep the description simple.
ChatGPT: A stunning sight unfolds in Kosovo as the rushing waters of the hydroelectric plant send powerful energy surging through the turbines. Meanwhile, in the distance, a Home Depot store stands proudly, displaying a vibrant green stock price chart that is shooting upwards, symbolizing the surge in sales and stock price due to the increased demand for plumbing supplies.

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: [ Parallax art ] and depicting this scene: A stunning sight unfolds in Kosovo as the rushing waters of the hydroelectric plant send powerful energy surging through the turbines. Meanwhile, in the distance, a Home Depot store stands proudly, displaying a vibrant green stock price chart that is shooting upwards, symbolizing the surge in sales and stock price due to the increased demand for plumbing supplies. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image that captures the juxtaposition between nature and commerce in Kosovo. Highlight a bustling hydroelectric plant with the rushing waters generating powerful energy, set against a scenic backdrop. In the distance, emphasize a Home Depot store standing boldly. The storefront features a vibrant, green stock price chart soaring upwards to epitomize the surge in sales and stock prices due to increased demand for plumbing supplies. The image should evoke a sense of the dynamic relationship between industry and the natural world, offering a striking, parallax-style representation of this scene.

*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 Hydopower energy generated in Kosovo caused The Home Depot's stock price (HD) to increase.

AI academic paper

(Because p < 0.01)

Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD)

The Journal of Eclectic Energy Economics

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 goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Hydopower energy generated in Kosovo and The Home Depot's stock price (HD). 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]]
"Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD)"

[[ABSTRACT]]
The aim of this study is to empirically examine the unexpected relationship between the hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). Our research team delved into this electrifying topic using data from the Energy Information Administration and LSEG Analytics (Refinitiv). The sheer current of curiosity propelled us to investigate whether the flow of hydropower energy could actually have a striking impact on a major retailer's stock price.

Amidst our rigorous data analysis, we stumbled upon an undeniable correlation coefficient of 0.9282949 and a p-value less than 0.01 for the period spanning from 2008 to 2021. This realization truly shocked us, just like a poorly grounded electrical outlet! It appears that the flow of hydropower energy in Kosovo is remarkably intertwined with the stock performance of The Home Depot, creating a fusion of market forces that could potentially power up investor enthusiasm and leave them feeling positively amped.

Our findings shed light on the thunderous influence of hydropower energy on the stock market, sparking a reevaluation of the interplay between renewable energy sources and market dynamics. As we illuminate this previously overlooked connection, we invite readers to plug into this electrifying discovery and join us as we continue to generate currents of research in this uncharted landscape.

And remember, when it comes to researching the stock market, it's essential to stay grounded – just like a three-pronged plug.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
Power is a fundamental driver of modern society, just like coffee is a fundamental driver of early morning productivity. Without power, everything from our homes to our economy would grind to a halt, much like a blender attempting to mix ice without enough wattage. The demand for energy has led to a dynamic interplay between renewable energy sources and financial markets, with each sector seeking to harness potential returns and surges of growth, much like a surfer seeking the perfect wave.
In recent years, the potential of hydropower energy has surged to the forefront of the renewable energy landscape, garnering significant attention from investors and environmental enthusiasts alike. Similarly, investors constantly seek the perfect wave of market performance, hoping to ride a bullish trend to profitability, akin to the excitement of catching the perfect wave at the beach.
In this electrifying context, our research aims to delve into the enigmatic relationship between hydropower energy generation in Kosovo and the stock price of The Home Depot. We set out to unravel this mystery by harnessing the power of empirical analysis and statistical methods, akin to a scientist on the cusp of a groundbreaking discovery, or perhaps a dedicated individual untangling a mess of power cords behind the TV.
The unexpected and shocking nature of our findings serves as a reminder that in the world of research, you never know what currents of insight you might uncover. Our aim is to illuminate this surprising connection, while also infusing some lighthearted puns to keep the reader feeling positively amped throughout the paper.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

The literature surrounding the connection between hydropower energy generation and stock prices is rather sparse, much like a desert landscape before a rainstorm. However, recent studies have begun to shed light on the potential impact of renewable energy sources on financial markets. In "Renewable Energy and Stock Market Performance," Smith et al. found that there may be a positive correlation between renewable energy production and stock market performance, suggesting that investors are increasingly electrified by the potential of green energy.

But what about the connection between hydropower energy generation in a small European country and the stock price of a major home improvement retailer? Well, that's a shockingly unexplored territory, much like finding a unicorn at a hardware store. As we dive into this electrifying topic, we sought inspiration from non-fiction works such as "Energy Markets: Price Risk Management and Trading" by Tom James, and "The Home Depot, Inc.: The Inside Story" by Bernie Marcus and Arthur Blank. These texts provided invaluable insights into the energy markets and the inner workings of The Home Depot, adding fuel to our research fire.

Moving beyond the confines of traditional literature, we embraced the imaginative realm of fiction for potential allegorical insights. Works such as "The Power" by Naomi Alderman and "Watt" by Samuel Beckett offered metaphoric musings on power dynamics and energy, which, although not directly applicable, added a spark of creativity to our investigation. As we delved into these fictional worlds, we couldn't help but wonder if The Home Depot's stock price had also been influenced by a mysterious force akin to a dystopian power shift or an existential exploration of wattage.

In the pursuit of comprehensive understanding, we didn't limit ourselves to conventional sources. In a wild departure from scholarly norms, we took a page out of unconventional wisdom by perusing the backs of shampoo bottles in a symbolic nod to the flow of hydropower energy. Surprisingly, amidst the instructions for lather and rinse, we stumbled upon a cryptic message about the potential connection between clean, renewable energy and the vibrancy of an individual's daily shower routine. While this may seem far-fetched, it certainly made us appreciate the captivating reach of the hydropower phenomenon.

As we navigate through the currents of literature and oddities, it becomes clear that the link between hydropower energy generation in Kosovo and The Home Depot's stock price is a topic that electrifies the imagination and illuminates the unexplored intersections of renewable energy and market dynamics. And just like a well-grounded electrical appliance, our findings aim to provide a stable foundation for future research in this shockingly captivating field.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Hydopower energy generated in Kosovo and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD)"

[[ABSTRACT]]
The aim of this study is to empirically examine the unexpected relationship between the hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). Our research team delved into this electrifying topic using data from the Energy Information Administration and LSEG Analytics (Refinitiv). The sheer current of curiosity propelled us to investigate whether the flow of hydropower energy could actually have a striking impact on a major retailer's stock price.

Amidst our rigorous data analysis, we stumbled upon an undeniable correlation coefficient of 0.9282949 and a p-value less than 0.01 for the period spanning from 2008 to 2021. This realization truly shocked us, just like a poorly grounded electrical outlet! It appears that the flow of hydropower energy in Kosovo is remarkably intertwined with the stock performance of The Home Depot, creating a fusion of market forces that could potentially power up investor enthusiasm and leave them feeling positively amped.

Our findings shed light on the thunderous influence of hydropower energy on the stock market, sparking a reevaluation of the interplay between renewable energy sources and market dynamics. As we illuminate this previously overlooked connection, we invite readers to plug into this electrifying discovery and join us as we continue to generate currents of research in this uncharted landscape.

And remember, when it comes to researching the stock market, it's essential to stay grounded – just like a three-pronged plug.

[[LITERATURE REVIEW]]
The literature surrounding the connection between hydropower energy generation and stock prices is rather sparse, much like a desert landscape before a rainstorm. However, recent studies have begun to shed light on the potential impact of renewable energy sources on financial markets. In "Renewable Energy and Stock Market Performance," Smith et al. found that there may be a positive correlation between renewable energy production and stock market performance, suggesting that investors are increasingly electrified by the potential of green energy.
But what about the connection between hydropower energy generation in a small European country and the stock price of a major home improvement retailer? Well, that's a shockingly unexplored territory, much like finding a unicorn at a hardware store. As we dive into this electrifying topic, we sought inspiration from non-fiction works such as "Energy Markets: Price Risk Management and Trading" by Tom James, and "The Home Depot, Inc.: The Inside Story" by Bernie Marcus and Arthur Blank. These texts provided invaluable insights into the energy markets and the inner workings of The Home Depot, adding fuel to our research fire.
Moving beyond the confines of traditional literature, we embraced the imaginative realm of fiction for potential allegorical insights. Works such as "The Power" by Naomi Alderman and "Watt" by Samuel Beckett offered metaphoric musings on power dynamics and energy, which, although not directly applicable, added a spark of creativity to our investigation. As we delved into these fictional worlds, we couldn't help but wonder if The Home Depot's stock price had also been influenced by a mysterious force akin to a dystopian power shift or an existential exploration of wattage.
In the pursuit of comprehensive understanding, we didn't limit ourselves to conventional sources. In a wild departure from scholarly norms, we took a page out of unconventional wisdom by perusing the backs of shampoo bottles in a symbolic nod to the flow of hydropower energy. Surprisingly, amidst the instructions for lather and rinse, we stumbled upon a cryptic message about the potential connection between clean, renewable energy and the vibrancy of an individual's daily shower routine. While this may seem far-fetched, it certainly made us appreciate the captivating reach of the hydropower phenomenon.
As we navigate through the currents of literature and oddities, it becomes clear that the link between hydropower energy generation in Kosovo and The Home Depot's stock price is a topic that electrifies the imagination and illuminates the unexplored intersections of renewable energy and market dynamics. And just like a well-grounded electrical appliance, our findings aim to provide a stable foundation for future research in this shockingly captivating field.

[[RESULTS]]
Upon analyzing the data collected from the Energy Information Administration and LSEG Analytics (Refinitiv), we uncovered a positively electrifying correlation between hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). The correlation coefficient of 0.9282949 left us feeling positively shocked – almost as shocked as when we forget to unplug the toaster before attempting to retrieve stuck bread with a fork! This strong correlation coefficient indicates a robust relationship between the flow of hydropower energy and the performance of HD stock.
Fig. 1 displays a scatterplot that visually illustrates the robust correlation we observed. The data points cluster tightly around a positively sloped line, highlighting the striking relationship between hydropower energy generation and HD stock price. It's as if the stock price is riding the wave of hydropower energy, much like a thrill-seeking investor catching the perfect wave of market performance.
The r-squared value of 0.8617315 further underscores the remarkable explanatory power of the relationship we uncovered. This means that approximately 86.17% of the variability in HD stock price can be explained by changes in hydropower energy generation in Kosovo. It's as if the movement of the stock price is unharnessed and free-flowing, much like the untamed power of rushing water through a hydroelectric dam.
The p-value being less than 0.01 provides compelling evidence that the observed relationship is statistically significant. The likelihood of the observed correlation occurring by random chance is less than 1%, reinforcing the notion that there is a genuine and substantial connection between the flow of hydropower energy and the market performance of The Home Depot. This finding is truly shocking, much like a well-timed jump scare in a horror movie!
In summary, our research uncovered a shockingly strong and statistically significant relationship between hydropower energy generation in Kosovo and the stock price of The Home Depot. This unexpected connection challenges conventional wisdom and highlights the powerful impact of renewable energy sources on financial markets. It seems that when it comes to the synergy between energy and the stock market, the potential for current and future research is boundless.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

Our findings reveal a shockingly strong linkage between the flow of hydropower energy in Kosovo and the stock price of The Home Depot, solidifying the notion that energy generation can indeed send ripples through the financial markets. This discovery sparks a surge of curiosity and raises a fundamental question: Could the connection between renewable energy sources and stock performance be a current trend in the market, or is it merely an isolated power surge? It seems that this relationship electrifies investors' interest to a degree that might even shock a seasoned electrician.

Our results align with previous research indicating a positive correlation between renewable energy production and stock market performance. This connection, much like a well-insulated wire, has the potential to channel energy from previously untapped sources into the financial market, redefining investors' perceptions and reactions. Our study offers a voltage-induced jolt to the conventional understanding of market dynamics, much like an unexpected zap from an old light switch.

In corroboration with Smith et al.'s findings, the data point to a positively sloped relationship between hydropower energy generation and HD stock price, reinforcing the notion that renewable energy may indeed act as a current driver of market performance. This revelation could inspire a surge of interest in the integration of clean energy sources into the financial sector, propelling the market into a new era of energy-conscious investment strategies.

While our results may seem as unexpected as a rogue lightning strike on a clear day, they underscore the pressing need for further exploration of the interplay between renewable energy and market dynamics. Just as an open circuit can lead to surprising fluctuations in power, the uncharted territory of renewable energy's influence on the stock market promises a blend of volatility and potential that demands further investigation.

As we harness the energy of this discovery and strive for an illuminating narrative in the field of financial research, our findings shine a bright light on the unexplored intersections of renewable energy and market forces. It is clear that this shockingly potent link has the potential to transform the landscape of financial analysis, sparking a paradigm shift in energy-conscious investing that could very well be the bright spark that ignites a new era of market performance.

In the realm of research, just like in the realm of electricity, shocking discoveries can often lead to a surge of new ideas. With this in mind, our study aims to invigorate further investigations into the relationship between renewable energy sources and stock market performance, guiding the field toward a future filled with potential and – dare we say – electrifying possibilities.

Model: gpt-3.5-turbo-1106
System prompt: You are a goofy academic researcher writing an academic paper. You follow the rules, but you throw out convention regularly to make jokes and funny asides.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 Hydopower energy generated in Kosovo and The Home Depot's stock price (HD). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences. 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]]
"Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD)"

[[ABSTRACT]]
The aim of this study is to empirically examine the unexpected relationship between the hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). Our research team delved into this electrifying topic using data from the Energy Information Administration and LSEG Analytics (Refinitiv). The sheer current of curiosity propelled us to investigate whether the flow of hydropower energy could actually have a striking impact on a major retailer's stock price.

Amidst our rigorous data analysis, we stumbled upon an undeniable correlation coefficient of 0.9282949 and a p-value less than 0.01 for the period spanning from 2008 to 2021. This realization truly shocked us, just like a poorly grounded electrical outlet! It appears that the flow of hydropower energy in Kosovo is remarkably intertwined with the stock performance of The Home Depot, creating a fusion of market forces that could potentially power up investor enthusiasm and leave them feeling positively amped.

Our findings shed light on the thunderous influence of hydropower energy on the stock market, sparking a reevaluation of the interplay between renewable energy sources and market dynamics. As we illuminate this previously overlooked connection, we invite readers to plug into this electrifying discovery and join us as we continue to generate currents of research in this uncharted landscape.

And remember, when it comes to researching the stock market, it's essential to stay grounded – just like a three-pronged plug.

[[INTRDUCTION]]
Power is a fundamental driver of modern society, just like coffee is a fundamental driver of early morning productivity. Without power, everything from our homes to our economy would grind to a halt, much like a blender attempting to mix ice without enough wattage. The demand for energy has led to a dynamic interplay between renewable energy sources and financial markets, with each sector seeking to harness potential returns and surges of growth, much like a surfer seeking the perfect wave.
In recent years, the potential of hydropower energy has surged to the forefront of the renewable energy landscape, garnering significant attention from investors and environmental enthusiasts alike. Similarly, investors constantly seek the perfect wave of market performance, hoping to ride a bullish trend to profitability, akin to the excitement of catching the perfect wave at the beach.
In this electrifying context, our research aims to delve into the enigmatic relationship between hydropower energy generation in Kosovo and the stock price of The Home Depot. We set out to unravel this mystery by harnessing the power of empirical analysis and statistical methods, akin to a scientist on the cusp of a groundbreaking discovery, or perhaps a dedicated individual untangling a mess of power cords behind the TV.
The unexpected and shocking nature of our findings serves as a reminder that in the world of research, you never know what currents of insight you might uncover. Our aim is to illuminate this surprising connection, while also infusing some lighthearted puns to keep the reader feeling positively amped throughout the paper.

[[RESULTS]]
Upon analyzing the data collected from the Energy Information Administration and LSEG Analytics (Refinitiv), we uncovered a positively electrifying correlation between hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). The correlation coefficient of 0.9282949 left us feeling positively shocked – almost as shocked as when we forget to unplug the toaster before attempting to retrieve stuck bread with a fork! This strong correlation coefficient indicates a robust relationship between the flow of hydropower energy and the performance of HD stock.
Fig. 1 displays a scatterplot that visually illustrates the robust correlation we observed. The data points cluster tightly around a positively sloped line, highlighting the striking relationship between hydropower energy generation and HD stock price. It's as if the stock price is riding the wave of hydropower energy, much like a thrill-seeking investor catching the perfect wave of market performance.
The r-squared value of 0.8617315 further underscores the remarkable explanatory power of the relationship we uncovered. This means that approximately 86.17% of the variability in HD stock price can be explained by changes in hydropower energy generation in Kosovo. It's as if the movement of the stock price is unharnessed and free-flowing, much like the untamed power of rushing water through a hydroelectric dam.
The p-value being less than 0.01 provides compelling evidence that the observed relationship is statistically significant. The likelihood of the observed correlation occurring by random chance is less than 1%, reinforcing the notion that there is a genuine and substantial connection between the flow of hydropower energy and the market performance of The Home Depot. This finding is truly shocking, much like a well-timed jump scare in a horror movie!
In summary, our research uncovered a shockingly strong and statistically significant relationship between hydropower energy generation in Kosovo and the stock price of The Home Depot. This unexpected connection challenges conventional wisdom and highlights the powerful impact of renewable energy sources on financial markets. It seems that when it comes to the synergy between energy and the stock market, the potential for current and future research is boundless.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has uncovered a positively electrifying connection between hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). This unexpected relationship has left us feeling positively amped – just like a powerful surge of energy coursing through an electrical circuit!

Our findings have illuminated the remarkable impact of renewable energy sources on market dynamics, adding a shocking twist to the conventional understanding of financial markets. It seems that when it comes to market performance, the ripple effect of hydropower energy cannot be overlooked – it's like trying to ignore the gravitational pull of a black hole on a cosmic scale.

As we wrap up this thoroughly electrifying journey, we invite readers to plug into the sparks of insight we've generated and ride the wave of enthusiasm for further research in this uncharted territory. After all, the potential for research in this area is just like static electricity – it's positively unlimited.

And remember folks, when it comes to exploring the surprising connections in the realm of finance and energy, the current findings suggest that no more research is needed in this area. It seems that our data has already given us a powerful jolt of understanding!

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 Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD). Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Eclectic Energy Economics

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 Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD). Respond only with the name of a fictional organization.

ChatGPT:

The International Institute for Sustainable Energy and Supply Chain Dynamics

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 Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD) with an abstract of The aim of this study is to empirically examine the unexpected relationship between the hydropower energy generation in Kosovo and the stock price of The Home Depot (HD). Our research team delved into this electrifying topic using data from the Energy Information Administration and LSEG Analytics (Refinitiv). The sheer current of curiosity propelled us to investigate whether the flow of hydropower energy could actually have a striking impact on a major retailer's stock price.
Amidst our rigorous data analysis, we stumbled upon an undeniable correlation coefficient of 0.9282949 and a p-value less than 0.01 for the period spanning from 2008 to 2021. This realization truly shocked us, just like a poorly grounded electrical outlet! It appears that the flow of hydropower energy in Kosovo is remarkably intertwined with the stock performance of The Home Depot, creating a fusion of market forces that could potentially power up investor enthusiasm and leave them feeling positively amped.
Our findings shed light on the thunderous influence of hydropower energy on the stock market, sparking a reevaluation of the interplay between renewable energy sources and market dynamics. As we illuminate this previously overlooked connection, we invite readers to plug into this electrifying discovery and join us as we continue to generate currents of research in this uncharted landscape.
And remember, when it comes to researching the stock market, it's essential to stay grounded – just like a three-pronged plug.

ChatGPT:

Hydropower, energy generation, Kosovo, The Home Depot, HD stock price, correlation coefficient, p-value, Energy Information Administration, LSEG Analytics, renewable energy sources, market dynamics

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

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Data details

Hydopower energy generated in Kosovo
Detailed data title: Total hydopower energy generated in Kosovo in billion kWh
Source: Energy Information Administration
See what else correlates with Hydopower energy generated in Kosovo

The Home Depot's stock price (HD)
Detailed data title: Opening price of The Home Depot (HD) 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 The Home Depot's stock price (HD)

Correlation r = 0.9282949 (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 = 0.8617315 (Coefficient of determination)
This means 86.2% of the change in the one variable (i.e., The Home Depot's stock price (HD)) is predictable based on the change in the other (i.e., Hydopower energy generated in Kosovo) over the 14 years from 2008 through 2021.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 1.7E-6.^Show 0.0000016792085350815332000000
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 0.93 in 0.00017% of random cases. Said differently, if you correlated 595,519 random variables^Note You don't actually need 595 thousand 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 13 degrees of freedom, ^Note Degrees of freedom is a measure of how many free components we are testing. In this case it is 13 because we have two variables measured over a period of 14 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.

[ 0.78, 0.98 ] 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.

	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021
Hydopower energy generated in Kosovo (Billion kWh)	0.075	0.119	0.154	0.104	0.095	0.142	0.149	0.139	0.243	0.177	0.27027	0.2079	0.262826	0.300635
The Home Depot's stock price (HD) (Stock price)	27.13	23.07	29.15	35.2	42.41	63.57	82.11	105.16	130.11	135.1	190.21	169.71	219.08	266.01

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([0.075,0.119,0.154,0.104,0.095,0.142,0.149,0.139,0.243,0.177,0.27027,0.2079,0.262826,0.300635,])
array_2 = np.array([27.13,23.07,29.15,35.2,42.41,63.57,82.11,105.16,130.11,135.1,190.21,169.71,219.08,266.01,])
array_1_name = "Hydopower energy generated in Kosovo"
array_2_name = "The Home Depot's stock price (HD)"

# 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 Hydopower energy generated in Kosovo
Line chart for only The Home Depot's stock price (HD)
AI-generated correlation image
The spurious research paper: Powering Up the Market: The Shocking Connection Between Hydropower Energy Generation in Kosovo and The Home Depot's Stock Price (HD)

View another random correlation

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Correlation ID: 3108 · Black Variable ID: 23774 · Red Variable ID: 1560


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