Spurious correlation #2,146 · View random
A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Walker and the second variable is Lam Research's stock price (LRCX). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

A linear line chart with years as the X-axis and two variables on the Y-axis. The first variable is Popularity of the first name Walker and the second variable is Lam Research's stock price (LRCX). The chart goes from 2002 to 2022, and the two variables track closely in value over that time.

Download png, svg

AI explanation

More babies named Walker led to a surge in stroller sales, boosting the stock price of companies like Lam Research that supply the microchips for all the newfangled, high-tech baby strollers. It's a real baby boom for the tech industry!

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a high-tech cityscape with a modern coffee shop at the forefront. The coffee shop's menu board prominently features the name "Walker" as the top choice on the menu. Adjacent to the coffee shop, a sleek digital stock ticker displays Lam Research's stock price soaring high in the background. The city is alive with bustling streets and vibrant lights, capturing the energy of a thriving metropolis. 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: Popularity of the first name Walker and Lam Research's stock price. 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: Hyper-realistic a Polaroid photo High-tech Data cyber art Cyber folk
ChatGPT: High-tech

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both Popularity of the first name Walker and Lam Research's stock price together. Keep the description simple.
ChatGPT: In a bustling city, a coffee shop's menu board displays the name "Walker" as the most popular choice among customers. Meanwhile, a digital stock ticker above the shop showcases Lam Research's stock price soaring high in the background.

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ High-tech ] and depicting this scene: In a bustling city, a coffee shop's menu board displays the name "Walker" as the most popular choice among customers. Meanwhile, a digital stock ticker above the shop showcases Lam Research's stock price soaring high in the background. Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a high-tech cityscape with a modern coffee shop at the forefront. The coffee shop's menu board prominently features the name "Walker" as the top choice on the menu. Adjacent to the coffee shop, a sleek digital stock ticker displays Lam Research's stock price soaring high in the background. The city is alive with bustling streets and vibrant lights, capturing the energy of a thriving metropolis.

*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 Popularity of the first name Walker caused Lam Research's stock price (LRCX) to increase.

AI academic paper

(Because p < 0.01)

The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?

International Journal of Behavioral Economics and Finance

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 Popularity of the first name Walker and Lam Research's stock price (LRCX). Make lots of jokes, goofy observations, and puns.

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

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

Start by naming serious-sounding studies by authors like Smith, Doe, and Jones - but then quickly devolve. Name some real non-fiction books that would be related to the topic. Then name some real fiction books that sound like they could be related. Then you might move on to cartoons and children's shows that you watched for research.

Here is the title and abstract of the paper:
[[TITLE]]
The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?

[[ABSTRACT]]
This research paper investigates the peculiar correlation between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX). Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team delves into the whimsical world of baby names and stock market trends. Our findings reveal a remarkably high correlation coefficient of 0.9864042 and p < 0.01 for the time period spanning from 2002 to 2022, confounding conventional economic wisdom. The implications of this unexpected link between baby names and stock performance prompt a reevaluation of traditional forecasting models and provoke questions about the influence of pop culture on financial markets. As we untangle this enigmatic relationship, we offer a tongue-in-cheek glimpse into the sometimes surprising interplay of seemingly unrelated data sets.

-------

And here is the introduction section that led to this literature review:
[[INTRODUCTION]]
INTRODUCTION
The intersection of baby names and stock market performance may seem an unlikely area of research, but our investigation into the connection between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX) has yielded some intriguing and, dare I say, delightful findings.
While many investors and analysts turn to traditional economic indicators and financial reports to inform their market predictions, our team was drawn to the whimsical world of baby name popularity. After all, why wouldn't we look to the US Social Security Administration's treasure trove of data on baby names to gain insight into stock market trends? It's high time we recognize the potential impact of popular culture on financial markets. As the saying goes, "What's in a name? Apparently, quite a bit when it comes to stock prices."
The title of our paper, "The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?" may raise a few eyebrows, but rest assured, our exploration of this connection is rooted in rigorous analysis and statistical inquiry. We are not merely engaging in baby name banter; rather, we are diving headfirst, armed with regression analyses and correlation coefficients, into the sometimes surprising interplay of seemingly unrelated data sets.
As we embark on this scholarly escapade, we invite you to join us in unraveling the mystery of the "Walker Wave" and its impact on the LRCX stock price. Prepare yourself for a journey through the quirks and curiosities of financial markets, where baby names and stock performance converge in an unexpected, and perhaps even comical, manner. So, fasten your seatbelts and get ready for a ride that's more intriguing than a roller coaster named "Market Volatility."

-------

Your response should start like this:

[[LITERATURE REVIEW]]

ChatGPT:
[[LITERATURE REVIEW]]

Over the years, researchers have delved into numerous aspects of stock market predictability, utilizing a wide array of data sources to uncover potential indicators of market performance. In "Smith et al.," the authors find correlations between economic indicators and stock prices, while "Doe and Roe" explore the influence of consumer confidence on market trends. However, our investigation takes a rather unconventional turn as we venture into the realm of baby names and their unexpected link to stock market behavior.

Turning to the world of literature, "The Random Walk Down Wall Street" by Burton Malkiel offers a comprehensive exploration of market efficiency, while "The Intelligent Investor" by Benjamin Graham provides insights into value investing strategies. These are undoubtedly esteemed works within the financial realm, but our study takes a more whimsical approach as we peer into the unconventional correlations between seemingly unrelated phenomena.

As we expand our purview to include fictional works, it is important to reflect on the potential influence of popular culture on market dynamics. Works such as "The Wolf of Wall Street" by Jordan Belfort and "Flash Boys" by Michael Lewis offer captivating tales of financial intrigue, but they fail to capture the sheer quirkiness of our own investigation.

Venturing even further into unexpected territories, we draw inspiration from childhood cartoons and shows, such as "SpongeBob SquarePants" and "Paw Patrol," where the interplay of seemingly unrelated characters and events often leads to unexpected outcomes. In a similar manner, our findings may evoke a sense of surprise and amusement, as we unravel the enigmatic connection between the first name "Walker" and the stock price of Lam Research.

In summary, while traditional economic analyses and financial literature offer valuable insights into market dynamics, our study offers a lighthearted and unexpected perspective on the potential influences of baby names and popular culture on stock performance. Stay tuned as we embark on a truly unconventional scholarly escapade into the world of "Walker Wave" and its impact on LRCX stock prices.

Model: gpt-3.5-turbo-1106
System prompt: You are a dry but witty academic researcher. You speak in the passive voice, and your writing sounds like it belongs in a medical or economics journal.You draft the 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 Popularity of the first name Walker and Lam Research's stock price (LRCX). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

Limit your response to 500 tokens.

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

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

[[TITLE]]
The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?

[[ABSTRACT]]
This research paper investigates the peculiar correlation between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX). Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team delves into the whimsical world of baby names and stock market trends. Our findings reveal a remarkably high correlation coefficient of 0.9864042 and p < 0.01 for the time period spanning from 2002 to 2022, confounding conventional economic wisdom. The implications of this unexpected link between baby names and stock performance prompt a reevaluation of traditional forecasting models and provoke questions about the influence of pop culture on financial markets. As we untangle this enigmatic relationship, we offer a tongue-in-cheek glimpse into the sometimes surprising interplay of seemingly unrelated data sets.

[[LITERATURE REVIEW]]
Over the years, researchers have delved into numerous aspects of stock market predictability, utilizing a wide array of data sources to uncover potential indicators of market performance. In "Smith et al.," the authors find correlations between economic indicators and stock prices, while "Doe and Roe" explore the influence of consumer confidence on market trends. However, our investigation takes a rather unconventional turn as we venture into the realm of baby names and their unexpected link to stock market behavior.
Turning to the world of literature, "The Random Walk Down Wall Street" by Burton Malkiel offers a comprehensive exploration of market efficiency, while "The Intelligent Investor" by Benjamin Graham provides insights into value investing strategies. These are undoubtedly esteemed works within the financial realm, but our study takes a more whimsical approach as we peer into the unconventional correlations between seemingly unrelated phenomena.
As we expand our purview to include fictional works, it is important to reflect on the potential influence of popular culture on market dynamics. Works such as "The Wolf of Wall Street" by Jordan Belfort and "Flash Boys" by Michael Lewis offer captivating tales of financial intrigue, but they fail to capture the sheer quirkiness of our own investigation.
Venturing even further into unexpected territories, we draw inspiration from childhood cartoons and shows, such as "SpongeBob SquarePants" and "Paw Patrol," where the interplay of seemingly unrelated characters and events often leads to unexpected outcomes. In a similar manner, our findings may evoke a sense of surprise and amusement, as we unravel the enigmatic connection between the first name "Walker" and the stock price of Lam Research.
In summary, while traditional economic analyses and financial literature offer valuable insights into market dynamics, our study offers a lighthearted and unexpected perspective on the potential influences of baby names and popular culture on stock performance. Stay tuned as we embark on a truly unconventional scholarly escapade into the world of "Walker Wave" and its impact on LRCX stock prices.

[[RESULTS]]
The results of our investigation into the relationship between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX) yielded a remarkably high correlation coefficient of 0.9864042 and an r-squared value of 0.9729931 for the time period from 2002 to 2022. This association between the name "Walker" and LRCX stock price is quite striking, to say the least.
The correlation coefficient of 0.9864042 indicates an extremely strong positive linear relationship between the popularity of the name "Walker" and the stock price of LRCX., which suggests that as the popularity of the name "Walker" has trended, so has the stock price of LRCX. It truly makes one wonder, could the birth announcements in the local newspaper be the newest leading indicator for stock market movements? Perhaps it's time to add baby names to the list of economic indicators alongside inflation rates and GDP growth. Who would have thought that your name could have such an impact on the stock market? Maybe it's time for investors to start checking the baby name trends before making their next trade!
Additionally, the r-squared value of 0.9729931 indicates that a significant proportion of the variability in LRCX stock price can be explained by the variability in the popularity of the name "Walker." This finding implies that there is a strong explanatory power in the relationship between these two seemingly unrelated variables. One might even say that the popularity of the name "Walker" provides significant insight into the fluctuations of LRCX stock price. It seems that in the world of finance and economics, surprises can come in all shapes, sizes, and yes, names.
Furthermore, the p < 0.01 indicates that the correlation is statistically significant, providing substantial evidence to reject the null hypothesis that there is no relationship between the popularity of the name "Walker" and LRCX stock price. This means that we can be quite confident in the strength of the relationship observed in our data, and gives us all the more reason to consider the impact of baby names on the stock market with a raised eyebrow and a smirk.
The scatterplot (Fig. 1) included in this paper visually illustrates the strong positive correlation between the popularity of the name "Walker" and the stock price of LRCX for the period under investigation. It's a sight to behold - who knew that a simple graph could reveal such an unexpectedly delightful connection between a popular baby name and stock performance?
In conclusion, our findings suggest that there is indeed a noteworthy association between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX). This peculiar correlation challenges traditional economic conventions and invites us to ponder the possibility of integrating unconventional data sources such as baby names into our predictive models. As we continue to scrutinize the whimsical world of baby names and stock market trends, we encourage fellow researchers and market analysts to consider the broader implications of this unexpected correlation with a blend of curiosity and caution. Let's not be too hasty in naming our next investment strategy after a popular baby name, but let's also not entirely dismiss the potential influence of the "Walker Wave" on financial markets. After all, in economics, as in life, one shouldn't be too quick to dismiss the unexpected and the amusing.

-------

Your response should start like this:

[[DISCUSSION]]

ChatGPT:

[[DISCUSSION]]

The striking correlation between the popularity of the name "Walker" and the stock price of Lam Research (LRCX) has left many market analysts scratching their heads and pondering the whimsical nature of this unexpected relationship. Our findings not only support prior research on the influence of unconventional data sources on market behavior, but also open the door to a novel approach in economic forecasting.

Drawing from the established literature on stock market predictability, our study ventures into uncharted territory by uncovering the peculiar connection between baby names and stock performance. The correlation coefficient of 0.9864042 and the r-squared value of 0.9729931 for the period from 2002 to 2022 have surpassed even our most lighthearted expectations, underscoring the robustness of the relationship between the name "Walker" and LRCX stock price. This further emphasizes the need to consider non-traditional indicators in financial analysis, as they may hold valuable insights that elude conventional economic wisdom.

Echoing the playful spirit of our literature review, we must acknowledge that our discovery of the "Walker Wave" aligns with the unexpected yet meaningful connections observed in childhood cartoons and shows. Just as the amalgamation of seemingly unrelated characters in these narratives often leads to unexpected outcomes, the fusion of baby names and stock prices has unmasked a novel avenue for market analysis. This reinforces the eclectic and capricious nature of economic phenomena, reminding us that unconventional sources may encode valuable signals amidst the noise of market data.

Furthermore, our results corroborate the potential influence of popular culture on market dynamics, as alluded to in our literature review. The unexpected correlation between the name "Walker" and LRCX stock price exemplifies the interplay of societal trends with financial markets, inviting us to consider the broader implications of cultural phenomena on economic behavior. It seems that the pulse of pop culture, reflected in the popularity of baby names, may indeed resonate with the movements of stock prices, challenging traditional economic models with its eerily prescient trend.

In addition, the statistical significance of the correlation, underscored by the p < 0.01, provides robust evidence for the relationship between the name "Walker" and LRCX stock price. This prompts not only a reevaluation of traditional forecasting models, but also a reimagining of the diverse array of data sources that may hold predictive power in market analysis. The traditional economic paradigm, which may have once dismissed the influence of baby names on financial markets as mere child's play, must now contend with the compelling evidence presented by our study.

As we look to the future, it's essential for market analysts and researchers to approach the "Walker Wave" with a blend of curiosity and caution. While the unexpected nature of this correlation may elicit a sense of amusement, the potential implications for market predictability warrant a sober examination of the broader ramifications. Our findings encourage fellow scholars to integrate a dash of whimsy into their analyses, reminding us that even in the realm of dry economic research, surprises can come in all shapes, sizes, and yes, names.

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 Popularity of the first name Walker and Lam Research's stock price (LRCX). Make lots of jokes, goofy observations, and puns. Stay serious and dry most of the time, but then occasionally let your wit shine through.

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

Here are the title, abstract, introduction, and results sections.
[[TITLE]]
The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?

[[ABSTRACT]]
This research paper investigates the peculiar correlation between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX). Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team delves into the whimsical world of baby names and stock market trends. Our findings reveal a remarkably high correlation coefficient of 0.9864042 and p < 0.01 for the time period spanning from 2002 to 2022, confounding conventional economic wisdom. The implications of this unexpected link between baby names and stock performance prompt a reevaluation of traditional forecasting models and provoke questions about the influence of pop culture on financial markets. As we untangle this enigmatic relationship, we offer a tongue-in-cheek glimpse into the sometimes surprising interplay of seemingly unrelated data sets.

[[INTRDUCTION]]
INTRODUCTION
The intersection of baby names and stock market performance may seem an unlikely area of research, but our investigation into the connection between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX) has yielded some intriguing and, dare I say, delightful findings.
While many investors and analysts turn to traditional economic indicators and financial reports to inform their market predictions, our team was drawn to the whimsical world of baby name popularity. After all, why wouldn't we look to the US Social Security Administration's treasure trove of data on baby names to gain insight into stock market trends? It's high time we recognize the potential impact of popular culture on financial markets. As the saying goes, "What's in a name? Apparently, quite a bit when it comes to stock prices."
The title of our paper, "The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?" may raise a few eyebrows, but rest assured, our exploration of this connection is rooted in rigorous analysis and statistical inquiry. We are not merely engaging in baby name banter; rather, we are diving headfirst, armed with regression analyses and correlation coefficients, into the sometimes surprising interplay of seemingly unrelated data sets.
As we embark on this scholarly escapade, we invite you to join us in unraveling the mystery of the "Walker Wave" and its impact on the LRCX stock price. Prepare yourself for a journey through the quirks and curiosities of financial markets, where baby names and stock performance converge in an unexpected, and perhaps even comical, manner. So, fasten your seatbelts and get ready for a ride that's more intriguing than a roller coaster named "Market Volatility."

[[RESULTS]]
The results of our investigation into the relationship between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX) yielded a remarkably high correlation coefficient of 0.9864042 and an r-squared value of 0.9729931 for the time period from 2002 to 2022. This association between the name "Walker" and LRCX stock price is quite striking, to say the least.
The correlation coefficient of 0.9864042 indicates an extremely strong positive linear relationship between the popularity of the name "Walker" and the stock price of LRCX., which suggests that as the popularity of the name "Walker" has trended, so has the stock price of LRCX. It truly makes one wonder, could the birth announcements in the local newspaper be the newest leading indicator for stock market movements? Perhaps it's time to add baby names to the list of economic indicators alongside inflation rates and GDP growth. Who would have thought that your name could have such an impact on the stock market? Maybe it's time for investors to start checking the baby name trends before making their next trade!
Additionally, the r-squared value of 0.9729931 indicates that a significant proportion of the variability in LRCX stock price can be explained by the variability in the popularity of the name "Walker." This finding implies that there is a strong explanatory power in the relationship between these two seemingly unrelated variables. One might even say that the popularity of the name "Walker" provides significant insight into the fluctuations of LRCX stock price. It seems that in the world of finance and economics, surprises can come in all shapes, sizes, and yes, names.
Furthermore, the p < 0.01 indicates that the correlation is statistically significant, providing substantial evidence to reject the null hypothesis that there is no relationship between the popularity of the name "Walker" and LRCX stock price. This means that we can be quite confident in the strength of the relationship observed in our data, and gives us all the more reason to consider the impact of baby names on the stock market with a raised eyebrow and a smirk.
The scatterplot (Fig. 1) included in this paper visually illustrates the strong positive correlation between the popularity of the name "Walker" and the stock price of LRCX for the period under investigation. It's a sight to behold - who knew that a simple graph could reveal such an unexpectedly delightful connection between a popular baby name and stock performance?
In conclusion, our findings suggest that there is indeed a noteworthy association between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX). This peculiar correlation challenges traditional economic conventions and invites us to ponder the possibility of integrating unconventional data sources such as baby names into our predictive models. As we continue to scrutinize the whimsical world of baby names and stock market trends, we encourage fellow researchers and market analysts to consider the broader implications of this unexpected correlation with a blend of curiosity and caution. Let's not be too hasty in naming our next investment strategy after a popular baby name, but let's also not entirely dismiss the potential influence of the "Walker Wave" on financial markets. After all, in economics, as in life, one shouldn't be too quick to dismiss the unexpected and the amusing.

-------

Your response should start like this:

[[CONCLUSION]]

ChatGPT:

[[CONCLUSION]]

In conclusion, our investigation into the connection between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX) has provided compelling evidence of a remarkably high correlation. This peculiar correlation challenges traditional economic conventions and invites us to ponder the possibility of integrating unconventional data sources such as baby names into our predictive models. It seems that when it comes to stock prices, what's in a name might be more significant than we previously thought. And here we thought "baby boom" only referred to demographic trends!

The strong positive linear relationship observed between the popularity of the name "Walker" and the stock price of LRCX raises intriguing questions about the potential impact of pop culture on financial markets. It seems that the market may not only have bull and bear trends but perhaps also a "Walker walk" that investors need to keep an eye on! Who knew that the stroller set could hold such sway over the stock market? It's enough to make one rethink the role of unconventional indicators in economic forecasting.

Our findings also highlight the need for a diversified approach to market analysis. While we're not suggesting that investors start reading the tea leaves from their favorite baby name books, it may be time to broaden our perspectives and consider the influence of unexpected factors on stock performance. As the saying goes, "Never underestimate the power of a popular name – or a curious correlation" (Shakespeare, if he were an economist).

We must acknowledge that our research has its limitations, and further studies to validate and delve deeper into this unexpected connection would be beneficial. However, for now, we can confidently assert that there is indeed a noteworthy association between the popularity of the first name "Walker" and the stock price of LRCX. As we close this chapter of our research, we urge fellow scholars and market observers to maintain a sense of open-mindedness and curiosity when exploring the quirky interplay of seemingly unrelated data sets. After all, in the delightful dance of economics, one never knows who – or what – may lead the next waltz.

In light of our findings, we assert that no further research is needed in this area. The connection between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX) has been sufficiently, and humorously, explored.

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of academic journals. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding research, scientific, or academic journal that would publish a paper entited The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?. Respond only with the name of a fictional academic journal.

ChatGPT:

International Journal of Behavioral Economics and Finance

Model: gpt-3.5-turbo-1106
System prompt: You provide fictional names of nonprofit research organizations and associations. You say nothing else, and you do not chat with the user.
User prompt: Please provide the name of a funny but plausible sounding nonprofit, academic, or scientific association or organization that would sponsor research that resulted in a paper entited The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?. Respond only with the name of a fictional organization.

ChatGPT:

The Institute for Applied Linguistic Finance

Model: gpt-3.5-turbo-1106
System prompt: You provide potential search keywords separated by commas. You say nothing else, and you do not chat with the user.
User prompt: Please provide potential search keywords for a paper titled The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions? with an abstract of This research paper investigates the peculiar correlation between the popularity of the first name "Walker" and the stock price of Lam Research (LRCX). Utilizing data from the US Social Security Administration and LSEG Analytics (Refinitiv), our research team delves into the whimsical world of baby names and stock market trends. Our findings reveal a remarkably high correlation coefficient of 0.9864042 and p < 0.01 for the time period spanning from 2002 to 2022, confounding conventional economic wisdom. The implications of this unexpected link between baby names and stock performance prompt a reevaluation of traditional forecasting models and provoke questions about the influence of pop culture on financial markets. As we untangle this enigmatic relationship, we offer a tongue-in-cheek glimpse into the sometimes surprising interplay of seemingly unrelated data sets.

ChatGPT:

"Walker" popularity, stock price correlation, Lam Research, LRCX, US Social Security Administration data, LSEG Analytics, Refinitiv, baby names, stock market trends, correlation coefficient, forecasting models, pop culture influence, financial markets, unconventional correlations

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

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Data details

Popularity of the first name Walker
Detailed data title: Babies of all sexes born in the US named Walker
Source: US Social Security Administration
See what else correlates with Popularity of the first name Walker

Lam Research's stock price (LRCX)
Detailed data title: Opening price of Lam Research (LRCX) 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 Lam Research's stock price (LRCX)

Correlation r = 0.9864042 (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 = 0.9729931 (Coefficient of determination)
This means 97.3% of the change in the one variable (i.e., Lam Research's stock price (LRCX)) is predictable based on the change in the other (i.e., Popularity of the first name Walker) over the 21 years from 2002 through 2022.

p < 0.01, which is statistically significant(Null hypothesis significance test)
The p-value is 2.3E-16.^Show 0.0000000000000002297348481045
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 0.99 in 2.3E-14% of random cases. Said differently, if you correlated 4,352,844,195,170,284 random variables^Note You don't actually need 4 quadrillion variables to find a correlation like this one. I don't have that many variables in my database. You can also correlate variables that are not independent. I do this a lot.

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

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

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

[ 0.97, 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.

	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022
Popularity of the first name Walker (Babies born)	628	638	740	812	708	609	559	595	656	686	715	857	1064	1028	1062	1119	1368	1675	1907	2983	4389
Lam Research's stock price (LRCX) (Stock price)	23.39	10.98	32.64	28.7	36.09	50.95	42.96	21.47	39.7	51.69	37.72	37.02	54.04	79.87	77.77	106.68	185.15	133.46	295.78	478.15	721.13

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([628,638,740,812,708,609,559,595,656,686,715,857,1064,1028,1062,1119,1368,1675,1907,2983,4389,])
array_2 = np.array([23.39,10.98,32.64,28.7,36.09,50.95,42.96,21.47,39.7,51.69,37.72,37.02,54.04,79.87,77.77,106.68,185.15,133.46,295.78,478.15,721.13,])
array_1_name = "Popularity of the first name Walker"
array_2_name = "Lam Research's stock price (LRCX)"

# 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 Popularity of the first name Walker
Line chart for only Lam Research's stock price (LRCX)
AI-generated correlation image
The spurious research paper: The Walker Wave: Will Lam Research's LRCX Look to Baby Names for Stock Price Predictions?

View another random correlation

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Correlation ID: 2146 · Black Variable ID: 2876 · Red Variable ID: 1652


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