Spurious correlation #4,005 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Global Rice Consumption and the second variable is Discover Financial Services' stock price (DFS). The chart goes from 2009 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Global Rice Consumption and the second variable is Discover Financial Services' stock price (DFS). The chart goes from 2009 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

As global rice consumption rose, more people were using chopsticks, sparking an interest in investments. This led to a surge in demand for Discover Financial Services stock, as investors realized it was time to stir up their portfolios and rice to the top in the financial market.

^{Show image generation prompt} Model: dalle-3
Prompt: [ A photo-realistic image ] In a bustling and vibrant marketplace, a diverse group of people can be seen enjoying hearty bowls of steaming rice, using colorful chopsticks with great skill and precision. Amidst the joyful chatter and laughter, a crowd gathers around a large digital screen displaying the stock prices, with the graph showing an upward trend for Discover Financial Services (DFS). The aroma of delicious food fills the air as the sound of clinking chopsticks accompanies the excited murmurs of successful investors, celebrating their wise investment decisions. The scene is filled with bright colors and lively energy, capturing the spirit of a dynamic marketplace. 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: Global Rice Consumption and Discover Financial Services' stock price (DFS). 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: Surrealism Macabre Data cyber art A photo-realistic image An image that looks like it is a scene from 'Star Wars'
ChatGPT: A photo-realistic image

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 Global Rice Consumption and Discover Financial Services' stock price (DFS), in the following situation: Because an increase in Global Rice Consumption leads to more people eating with chopsticks, and using chopsticks requires precision and dexterity, thereby boosting fine motor skills. This increase in fine motor skills translates to more precise stock trading, leading to better investment decisions, including an influx of investment in Discover Financial Services, driving up their stock price.. Keep the description simple.
ChatGPT: In a bustling and vibrant marketplace, a diverse group of people can be seen enjoying hearty bowls of steaming rice, using colorful chopsticks with great skill and precision. Amidst the joyful chatter and laughter, a crowd gathers around a large digital screen displaying the stock prices, with the graph showing an upward trend for Discover Financial Services (DFS). The aroma of delicious food fills the air as the sound of clinking chopsticks accompanies the excited murmurs of successful investors, celebrating their wise investment decisions.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ A photo-realistic image ] and depicting this scene: In a bustling and vibrant marketplace, a diverse group of people can be seen enjoying hearty bowls of steaming rice, using colorful chopsticks with great skill and precision. Amidst the joyful chatter and laughter, a crowd gathers around a large digital screen displaying the stock prices, with the graph showing an upward trend for Discover Financial Services (DFS). The aroma of delicious food fills the air as the sound of clinking chopsticks accompanies the excited murmurs of successful investors, celebrating their wise investment decisions. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: [ A photo-realistic image ] In a bustling and vibrant marketplace, a diverse group of people can be seen enjoying hearty bowls of steaming rice, using colorful chopsticks with great skill and precision. Amidst the joyful chatter and laughter, a crowd gathers around a large digital screen displaying the stock prices, with the graph showing an upward trend for Discover Financial Services (DFS). The aroma of delicious food fills the air as the sound of clinking chopsticks accompanies the excited murmurs of successful investors, celebrating their wise investment decisions. The scene is filled with bright colors and lively energy, capturing the spirit of a dynamic marketplace.

*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 Global Rice Consumption caused Discover Financial Services' stock price (DFS) to increase. Include one good pun.

AI academic paper

(Because p < 0.01)

Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price

The Journal of Quirky Quantitative Research

Jan 2024

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

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

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

Please make up a literature review section of an academic research paper presenting the findings of the connection between Global Rice Consumption and Discover Financial Services' stock price (DFS). 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. Perhaps you also got inspiration from some board games that are vaugely related.

Here is the title and abstract of the paper:
[[TITLE]]
Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price

[[ABSTRACT]]
This paper presents an analysis of the curious connection between global rice consumption and the stock price of Discover Financial Services (DFS). Using data from Statista and LSEG Analytics (Refinitiv), we conducted a longitudinal study from 2009 to 2022. Our findings revealed a striking correlation coefficient of 0.9753085 and p < 0.01, indicating a strong relationship between these seemingly disparate variables.

The relationship between global rice consumption and DFS stock price was not as plain as rice, leading to our investigation. Our analysis suggests that changes in global rice consumption may have a kernel of influence on the financial market, particularly the stock price of Discover Financial Services. As the saying goes, "You can't have your rice and eat it, too," but it seems that global rice consumption might have a hand in shaping stock market performance.

Despite the skeptics who may think the topic is just a bunch of hullabaloo, our research indicates that the influence of rice consumption on stock prices cannot be swept under the rug. There's no rice in denying the evidence - the symbiotic relationship between global rice consumption and financial markets is indeed a grain of truth.

In conclusion, it is clear that the stock market and global rice consumption have more in common than meets the eye. This research sheds light on a previously overlooked area of inquiry and underscores the importance of considering unconventional factors in financial market analysis.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
The intersection of global food consumption and financial markets has always been a fertile ground for research. Though it may seem like comparing apples and oranges, or perhaps in this case, rice and stocks, the relationship between these seemingly unrelated variables is ripe for exploration. As the stock market can often be a grainy subject, it's important to rice to the occasion and dig into the potential connections that may exist.
This study delves into the intriguing association between global rice consumption and the stock price of Discover Financial Services (DFS). As we wade through the data, one might say we are paddling into uncharted waters, seeking to uncover any kernels of truth that may be lurking beneath the surface. After all, "when it comes to stocks and rice, it's all about the grain."
The impetus for this research sprouted from the observation that rice, a staple food for a large portion of the world's population, may have a fuller impact on financial markets than previously thought. It was puzzling to ponder: could something as fundamental as rice consumption indeed have a stirring effect on stock prices? It's a conundrum that may have some investors feeling a bit fried, but as we shall see, there is more than meets the husk.

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

In "The Global Economy" by Smith, the relationship between food consumption patterns and financial markets is explored, emphasizing the intricate interplay of various commodities with stock prices. Doe's "Market Volatility and Macro Trends" examines the impact of external factors on market fluctuations, touching upon the potential influence of agricultural products on stock performance. Furthermore, Jones' "The Art of Financial Analysis" considers the broader implications of global consumer behavior on investment opportunities, hinting at the relevance of staple food consumption patterns on financial markets.

Turning to non-fiction works related to the topic at hand, "Rice as Self: Japanese Identities through Time" and "Golden Rice: The Imperfect Grain" supply valuable insights into the cultural, economic, and social significance of rice consumption, offering a deeper understanding of its potential influence on global markets. In the fictional realm, "The Rice Mother" by Rani Manicka and "A Grain of Wheat" by Ngũgĩ wa Thiong'o may not provide direct insights into financial market dynamics, but their evocative portrayal of rice as a symbol of sustenance and resilience speaks to the broader significance of this humble grain.

As we embark on this journey of unearthing the connection between global rice consumption and Discover Financial Services' stock price, we must also consider the unexpected sources of inspiration that may shed light on this peculiar relationship. Games such as "Agricola" and "Rice Dice" carry elements of strategic resource management and agricultural trade, offering unconventional perspectives that may inform our understanding of the interplay between food consumption and financial markets.

Now, onto the matter at hand with a stock-related dad joke: Why did the stock market break up with rice? It just couldn't handle the grains anymore!

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 Global Rice Consumption and Discover Financial Services' stock price (DFS). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Your research team collected data from all across the internet, but mostly just used information from Statista and LSEG Analytics (Refinitiv) . You used data from 2009 to 2022

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

Here is the title, abstract, and introduction of the paper:
[[TITLE]]
Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price

[[ABSTRACT]]
This paper presents an analysis of the curious connection between global rice consumption and the stock price of Discover Financial Services (DFS). Using data from Statista and LSEG Analytics (Refinitiv), we conducted a longitudinal study from 2009 to 2022. Our findings revealed a striking correlation coefficient of 0.9753085 and p < 0.01, indicating a strong relationship between these seemingly disparate variables.

The relationship between global rice consumption and DFS stock price was not as plain as rice, leading to our investigation. Our analysis suggests that changes in global rice consumption may have a kernel of influence on the financial market, particularly the stock price of Discover Financial Services. As the saying goes, "You can't have your rice and eat it, too," but it seems that global rice consumption might have a hand in shaping stock market performance.

Despite the skeptics who may think the topic is just a bunch of hullabaloo, our research indicates that the influence of rice consumption on stock prices cannot be swept under the rug. There's no rice in denying the evidence - the symbiotic relationship between global rice consumption and financial markets is indeed a grain of truth.

In conclusion, it is clear that the stock market and global rice consumption have more in common than meets the eye. This research sheds light on a previously overlooked area of inquiry and underscores the importance of considering unconventional factors in financial market analysis.

[[INTRODUCTION]]
The intersection of global food consumption and financial markets has always been a fertile ground for research. Though it may seem like comparing apples and oranges, or perhaps in this case, rice and stocks, the relationship between these seemingly unrelated variables is ripe for exploration. As the stock market can often be a grainy subject, it's important to rice to the occasion and dig into the potential connections that may exist.
This study delves into the intriguing association between global rice consumption and the stock price of Discover Financial Services (DFS). As we wade through the data, one might say we are paddling into uncharted waters, seeking to uncover any kernels of truth that may be lurking beneath the surface. After all, "when it comes to stocks and rice, it's all about the grain."
The impetus for this research sprouted from the observation that rice, a staple food for a large portion of the world's population, may have a fuller impact on financial markets than previously thought. It was puzzling to ponder: could something as fundamental as rice consumption indeed have a stirring effect on stock prices? It's a conundrum that may have some investors feeling a bit fried, but as we shall see, there is more than meets the husk.

-------

Your response should start like this:

[[METHODOLOGY]]

ChatGPT:

[[METHODOLOGY]]

The methodology employed in this research involved gathering data on global rice consumption and Discover Financial Services' stock price from 2009 to 2022. Data on global rice consumption was obtained from Statista and LSEG Analytics (Refinitiv), while DFS stock price data was collected from the same sources. The purpose of this data collection was to sift through the mountain of information, like a rice farmer separating grains from chaff, in order to discern any discernible patterns or connections.

To establish a comprehensive understanding of the potential relationship between global rice consumption and DFS stock price, a multi-faceted approach was adopted. This involved utilizing advanced statistical techniques to cautiously separate the "rice" from the "chaff" in the data, ensuring that only the most relevant and high-quality information was included. It was crucial to handle the data with care, as one would handle a delicate rice paper, to avoid skewing the results.

We employed a complex econometric model that was as intricate as a well-woven basket to analyze the collected data. This involved employing time-series analysis and regression models to capture the intricacies of the relationship between global rice consumption and DFS stock price. The models were configured to account for various potential confounding variables, thus ensuring that the relationship between the variables under investigation was not obscured by extraneous factors. It was imperative to ensure the statistical methods were as robust as a hardy rice plant, capable of withstanding the turbulent winds of the financial market.

To validate the findings and enhance the rigor of the analysis, we also conducted sensitivity analyses and robustness checks. This multi-pronged approach was as thorough as combing through a field of ripe rice, ensuring that the conclusions drawn were not mere chaff, but rather substantial grains of truth.

The data from the two sources were cleaned and pre-processed to ensure that inconsistencies and errors were minimized. Various transformations and adjustments were applied to the data, akin to the process of milling and refining rice to improve its quality and extract the most valuable components.

In addition, we undertook a comparative analysis of rice consumption patterns across different regions and their potential effects on DFS stock price. This involved exploring the nuanced variations in rice consumption and their plausible impacts on a financial institution like Discover Financial Services. It was important to capture the regional subtleties, just like the distinct flavors of different rice varieties.

Ultimately, the approach undertaken in this research was designed to be as exhaustive as sifting through a sack of rice to ensure that the insights gleaned were as nourishing as a bowl of steaming hot rice on a cold day.

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 Global Rice Consumption and Discover Financial Services' stock price (DFS). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

Limit your response to 500 tokens.

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

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

[[TITLE]]
Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price

[[ABSTRACT]]
This paper presents an analysis of the curious connection between global rice consumption and the stock price of Discover Financial Services (DFS). Using data from Statista and LSEG Analytics (Refinitiv), we conducted a longitudinal study from 2009 to 2022. Our findings revealed a striking correlation coefficient of 0.9753085 and p < 0.01, indicating a strong relationship between these seemingly disparate variables.

The relationship between global rice consumption and DFS stock price was not as plain as rice, leading to our investigation. Our analysis suggests that changes in global rice consumption may have a kernel of influence on the financial market, particularly the stock price of Discover Financial Services. As the saying goes, "You can't have your rice and eat it, too," but it seems that global rice consumption might have a hand in shaping stock market performance.

Despite the skeptics who may think the topic is just a bunch of hullabaloo, our research indicates that the influence of rice consumption on stock prices cannot be swept under the rug. There's no rice in denying the evidence - the symbiotic relationship between global rice consumption and financial markets is indeed a grain of truth.

In conclusion, it is clear that the stock market and global rice consumption have more in common than meets the eye. This research sheds light on a previously overlooked area of inquiry and underscores the importance of considering unconventional factors in financial market analysis.

[[LITERATURE REVIEW]]
In "The Global Economy" by Smith, the relationship between food consumption patterns and financial markets is explored, emphasizing the intricate interplay of various commodities with stock prices. Doe's "Market Volatility and Macro Trends" examines the impact of external factors on market fluctuations, touching upon the potential influence of agricultural products on stock performance. Furthermore, Jones' "The Art of Financial Analysis" considers the broader implications of global consumer behavior on investment opportunities, hinting at the relevance of staple food consumption patterns on financial markets.
Turning to non-fiction works related to the topic at hand, "Rice as Self: Japanese Identities through Time" and "Golden Rice: The Imperfect Grain" supply valuable insights into the cultural, economic, and social significance of rice consumption, offering a deeper understanding of its potential influence on global markets. In the fictional realm, "The Rice Mother" by Rani Manicka and "A Grain of Wheat" by Ngũgĩ wa Thiong'o may not provide direct insights into financial market dynamics, but their evocative portrayal of rice as a symbol of sustenance and resilience speaks to the broader significance of this humble grain.
As we embark on this journey of unearthing the connection between global rice consumption and Discover Financial Services' stock price, we must also consider the unexpected sources of inspiration that may shed light on this peculiar relationship. Games such as "Agricola" and "Rice Dice" carry elements of strategic resource management and agricultural trade, offering unconventional perspectives that may inform our understanding of the interplay between food consumption and financial markets.
Now, onto the matter at hand with a stock-related dad joke: Why did the stock market break up with rice? It just couldn't handle the grains anymore!

[[RESULTS]]
An analysis of the data collected from 2009 to 2022 revealed a remarkably strong correlation coefficient of 0.9753085 between global rice consumption and the stock price of Discover Financial Services (DFS). This suggests a robust relationship between these variables, resembling a well-cooked risotto - perfectly blended.
The r-squared value of 0.9512267 further conveys that a substantial portion of the variance in DFS stock price can be explained by changes in global rice consumption. It's as if the stock market has a hankering for rice, with each grain of consumption leaving its mark on stock prices.
The p-value of less than 0.01 indicates that the observed correlation is statistically significant, providing ample evidence to reject the null hypothesis that there is no relationship between global rice consumption and DFS stock price. It seems the bond between rice consumption and stock prices is as strong as the adhesive on a rice paper wrapper.
The scatterplot in Fig. 1 visually represents the strong positive correlation between global rice consumption and DFS stock price. Each point on the plot is like a grain of rice, contributing to the robust pattern linking these two variables. One might say the relationship is as clear as black rice.
As the analysis of the data rice, a dad-joke-worthy conclusion becomes apparent: the influence of global rice consumption on the stock price of Discover Financial Services is nothing to sneeze at. In fact, someone might say it's a-PECK-ting the financial markets in ways previously unbeknownst.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The findings of the present study bolster the existing body of research, shedding light on the intricate connection between global rice consumption and the stock price of Discover Financial Services (DFS). The substantial correlation coefficient mirrors the assertions made by Smith in "The Global Economy" and Doe in "Market Volatility and Macro Trends," both of which hinted at the potential influence of agricultural products on stock market performance. It appears that the impact of staple food consumption on financial markets is not just a flash in the pan but rather a simmering reality.

Moreover, the r-squared value's indication that a noteworthy portion of the variance in DFS stock price can be elucidated by changes in global rice consumption lends further credence to the notion espoused by Jones in "The Art of Financial Analysis." Indeed, our findings imply that staple food consumption patterns may serve as a tasty indicator of investment opportunities. As Jones might say, "When it comes to the stock market, follow the grain."

The statistically significant p-value supports the premise put forth by "Rice as Self: Japanese Identities through Time" and "Golden Rice: The Imperfect Grain," aligning with their insights into the economic and social significance of rice consumption. This empirical evidence suggests that the influence of global rice consumption on financial markets is not just a figment of scholarly imagination but rather a palpable reality that cannot be rice-isted.

The robust visual representation of the positive correlation between global rice consumption and DFS stock price in the scatterplot further underscores the resonance of our findings with the unconventional perspectives offered by games such as "Agricola" and "Rice Dice." It seems that these games, akin to a pound of jasmine rice, offer unexpected yet insightful kernels of wisdom that inform our understanding of food consumption's impact on financial markets.

In sum, the results of this study affirm the relevance of global rice consumption as an influential factor in shaping the stock price of Discover Financial Services. It appears that the stock market may indeed have a soft spot for rice, and the notion of the market breaking up with rice seems as inconceivable as trading stocks for chaff. Our findings stand as a testament to the unexpectedly grainy relationship between global rice consumption and stock prices, serving as a robust foundation for further inquiry into the uncharted territory of culinary influences on 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 Global Rice Consumption and Discover Financial Services' stock price (DFS). You can't resist a good dad joke. Add a relevant dad joke related to the content every couple of sentences.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price

[[ABSTRACT]]
This paper presents an analysis of the curious connection between global rice consumption and the stock price of Discover Financial Services (DFS). Using data from Statista and LSEG Analytics (Refinitiv), we conducted a longitudinal study from 2009 to 2022. Our findings revealed a striking correlation coefficient of 0.9753085 and p < 0.01, indicating a strong relationship between these seemingly disparate variables.

The relationship between global rice consumption and DFS stock price was not as plain as rice, leading to our investigation. Our analysis suggests that changes in global rice consumption may have a kernel of influence on the financial market, particularly the stock price of Discover Financial Services. As the saying goes, "You can't have your rice and eat it, too," but it seems that global rice consumption might have a hand in shaping stock market performance.

Despite the skeptics who may think the topic is just a bunch of hullabaloo, our research indicates that the influence of rice consumption on stock prices cannot be swept under the rug. There's no rice in denying the evidence - the symbiotic relationship between global rice consumption and financial markets is indeed a grain of truth.

In conclusion, it is clear that the stock market and global rice consumption have more in common than meets the eye. This research sheds light on a previously overlooked area of inquiry and underscores the importance of considering unconventional factors in financial market analysis.

[[INTRDUCTION]]
The intersection of global food consumption and financial markets has always been a fertile ground for research. Though it may seem like comparing apples and oranges, or perhaps in this case, rice and stocks, the relationship between these seemingly unrelated variables is ripe for exploration. As the stock market can often be a grainy subject, it's important to rice to the occasion and dig into the potential connections that may exist.
This study delves into the intriguing association between global rice consumption and the stock price of Discover Financial Services (DFS). As we wade through the data, one might say we are paddling into uncharted waters, seeking to uncover any kernels of truth that may be lurking beneath the surface. After all, "when it comes to stocks and rice, it's all about the grain."
The impetus for this research sprouted from the observation that rice, a staple food for a large portion of the world's population, may have a fuller impact on financial markets than previously thought. It was puzzling to ponder: could something as fundamental as rice consumption indeed have a stirring effect on stock prices? It's a conundrum that may have some investors feeling a bit fried, but as we shall see, there is more than meets the husk.

[[RESULTS]]
An analysis of the data collected from 2009 to 2022 revealed a remarkably strong correlation coefficient of 0.9753085 between global rice consumption and the stock price of Discover Financial Services (DFS). This suggests a robust relationship between these variables, resembling a well-cooked risotto - perfectly blended.
The r-squared value of 0.9512267 further conveys that a substantial portion of the variance in DFS stock price can be explained by changes in global rice consumption. It's as if the stock market has a hankering for rice, with each grain of consumption leaving its mark on stock prices.
The p-value of less than 0.01 indicates that the observed correlation is statistically significant, providing ample evidence to reject the null hypothesis that there is no relationship between global rice consumption and DFS stock price. It seems the bond between rice consumption and stock prices is as strong as the adhesive on a rice paper wrapper.
The scatterplot in Fig. 1 visually represents the strong positive correlation between global rice consumption and DFS stock price. Each point on the plot is like a grain of rice, contributing to the robust pattern linking these two variables. One might say the relationship is as clear as black rice.
As the analysis of the data rice, a dad-joke-worthy conclusion becomes apparent: the influence of global rice consumption on the stock price of Discover Financial Services is nothing to sneeze at. In fact, someone might say it's a-PECK-ting the financial markets in ways previously unbeknownst.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our research has rice-n above the rest, revealing a surprisingly close connection between global rice consumption and the stock price of Discover Financial Services (DFS). The data speak louder than words, and the statistical analysis yields a spicy correlation coefficient of 0.9753085 and a p-value of less than 0.01, indicating a significant relationship. It's clear that when it comes to financial markets, the influence of rice consumption cannot be grain-ored.

The results of this study have stirred up a pot of curiosity, suggesting that perhaps there is more to financial market analysis than meets the husk. It's a reminder that when it comes to stocks, one must always keep an eye on the grain. As they say, "don't put all your rice in one stock portfolio."

This investigation sheds light on a previously unexplored aspect of market dynamics, emphasizing the need to broaden our perspective when considering factors that may impact stock prices. It's a timely reminder that in the financial world, it pays to be rice-eptive to unconventional influences.

Having pecked through the data and seasoned our analysis with robust statistical methods, we can confidently affirm that the relationship between global rice consumption and DFS stock price is no mere grain of salt. It's a reminder that in the world of finance, no connection should be rice-smissed.

In conclusion, it is evident that further research in this field is akin to beating a dead horse, or as they say in the rice fields, "beating a dead paddy." We can confidently say that no more research is needed in this area.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price. Respond only with the name of a fictional academic journal.

ChatGPT:

The Journal of Quirky Quantitative Research

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 Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Economic Culinary 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 Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price with an abstract of This paper presents an analysis of the curious connection between global rice consumption and the stock price of Discover Financial Services (DFS). Using data from Statista and LSEG Analytics (Refinitiv), we conducted a longitudinal study from 2009 to 2022. Our findings revealed a striking correlation coefficient of 0.9753085 and p < 0.01, indicating a strong relationship between these seemingly disparate variables.
The relationship between global rice consumption and DFS stock price was not as plain as rice, leading to our investigation. Our analysis suggests that changes in global rice consumption may have a kernel of influence on the financial market, particularly the stock price of Discover Financial Services. As the saying goes, "You can't have your rice and eat it, too," but it seems that global rice consumption might have a hand in shaping stock market performance.
Despite the skeptics who may think the topic is just a bunch of hullabaloo, our research indicates that the influence of rice consumption on stock prices cannot be swept under the rug. There's no rice in denying the evidence - the symbiotic relationship between global rice consumption and financial markets is indeed a grain of truth.
In conclusion, it is clear that the stock market and global rice consumption have more in common than meets the eye. This research sheds light on a previously overlooked area of inquiry and underscores the importance of considering unconventional factors in financial market analysis.

ChatGPT:

"global rice consumption, stock price, Discover Financial Services, correlation coefficient, financial market analysis, rice consumption influence on stock prices, longitudinal study, global rice consumption impact on financial market, unconventional factors in financial market analysis"

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

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Data details

Global Rice Consumption
Source: Statista
See what else correlates with Global Rice Consumption

Discover Financial Services' stock price (DFS)
Detailed data title: Opening price of Discover Financial Services (DFS) 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 Discover Financial Services' stock price (DFS)

Correlation r = 0.9753085 (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 = 0.9512267 (Coefficient of determination)
This means 95.1% of the change in the one variable (i.e., Discover Financial Services' stock price (DFS)) is predictable based on the change in the other (i.e., Global Rice Consumption) over the 14 years from 2009 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 3.1E-9.^Show 0.0000000031022978985644450000
The p-value is a measure of how probable it is that we would randomly find a result this extreme.^Note More specifically the p-value is a measure of how probable it is that we would randomly find a result this extreme if we had only tested one pair of variables one time.

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

Who is going to stop me? p-value reporting doesn't require me to report how many calculations I had to go through in order to find a low p-value!
On average, you will find a correaltion as strong as 0.98 in 3.1E-7% of random cases. Said differently, if you correlated 322,341,707 random variables^Note You don't actually need 322 million variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

Just to be clear: I'm being completely transparent about the calculations. There is no math trickery. This is just how statistics shakes out when you calculate hundreds of millions of random correlations.
with the same 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.

[ 0.92, 0.99 ] 95% correlation confidence interval (using the Fisher z-transformation)
^{Read more about the confidence interval} The confidence interval is an estimate the range of the value of the correlation coefficient, using the correlation itself as an input. The values are meant to be the low and high end of the correlation coefficient with 95% confidence.

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

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

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

	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Global Rice Consumption (Thousand Metric Tons)	437179	438338	445084	460825	462623	473878	474845	468882	483817	481678	485064	493953	503437	519895
Discover Financial Services' stock price (DFS) (Stock price)	9.69	14.87	18.75	24.34	39.39	55.79	65.93	52.53	72.9	77.24	57.92	85.11	91.99	116.93

Why this works

Data dredging: I have 25,213 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 635,695,369 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.
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. ^Note 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. ^{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([437179,438338,445084,460825,462623,473878,474845,468882,483817,481678,485064,493953,503437,519895,])
array_2 = np.array([9.69,14.87,18.75,24.34,39.39,55.79,65.93,52.53,72.9,77.24,57.92,85.11,91.99,116.93,])
array_1_name = "Global Rice Consumption"
array_2_name = "Discover Financial Services' stock price (DFS)"

# 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 Global Rice Consumption
Line chart for only Discover Financial Services' stock price (DFS)
AI-generated correlation image
The spurious research paper: Stalking the Stock Market: The Grainy Relationship Between Global Rice Consumption and Discover Financial Services' Stock Price

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Correlation ID: 4005 · Black Variable ID: 437 · Red Variable ID: 1894


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