Reeves Goldfish Beats WallStreetBets Bot to Post $1,000 Profit

I Gave My Goldfish $50,000 to Trade Stocks — Michael Reeves

Michael Reeves

A computer-vision system tracking goldfish movements beat an r/wallstreetbets sentiment model and outpaced the Nasdaq by roughly 13% over a three-month trading trial.

AI-assisted summary of I Gave My Goldfish $50,000 to Trade Stocks — original source. Check the original for full context.

Source published:

Key ideas

  • Michael Reeves constructed a computer vision trading rig using Python, OpenCV color masking, and the Alpaca API to let his pet goldfish, Frederick, execute real-market stock buys based on tank coordinates. (1:13)
  • To benchmark the fish, Reeves developed an r/wallstreetbets sentiment analysis bot by training custom models on 10,000 forum posts hand-classified by high-karma community volunteers. (3:33)
  • Frederick's random selections outperformed both the r/wallstreetbets algorithm and the broader NASDAQ index by approximately 13% over a three-month test window, yielding $1,007.59 in net profits. (9:09)
  • Reeves pitched his goldfish trading framework under the company name 'briefly' at a startup collective house, framing filtration and fish diet as biological hardware optimizations. (9:09)

Detailed notes

## Background Published on YouTube by Michael Reeves on March 31, 2022, this video presents an experiment in automated stock trading while explicitly disclaiming that nothing in the content constitutes professional financial advice. The description promotes the trading platform Public.com and links to official merchandise commemorating the showdown between Frederick the goldfish and WallStreetBets.

## TL;DR Frustrated by losing his own money trading stocks, Michael Reeves builds a computer vision system that allows his pet goldfish, Frederick, to execute automated stock trades based on its position in an aquarium. To test the fish's viability, Michael also builds a natural language processing algorithm trained on crowdsourced r/wallstreetbets sentiment to run a parallel portfolio. Over a three-month trial, Frederick consistently beats the Reddit-driven bot and outperforms the broader market, securing over $1,000 in profits. After delivering a hilariously unhinged startup pitch to baffled founders at a tech incubator, Michael cashes out the gains to buy luxury aquarium equipment and retire Frederick from trading.

## Atmosphere & style The presentation is driven by Michael Reeves's signature chaotic, deadpan humor, combining hyperactive parodies of finance 'grindset' culture with legitimate, excessive technical engineering. His delivery oscillates between manic self-deprecation about his programming habits and completely straight-faced commitments to absurd concepts, such as treating water filtration as hardware optimization for a stock-picking fish. The mood reaches a peak of secondhand embarrassment and surreal comedy when he pitches the fish-trading hedge fund to bewildered startup founders who struggle to discern whether he is speaking in metaphor or genuinely proposing aquatic equity trading.

## Bulletin - [01:13](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=73s) Michael Reeves constructed a computer vision trading rig using Python, OpenCV color masking, and the Alpaca API to let his pet goldfish, Frederick, execute real-market stock buys based on tank coordinates. - [03:33](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=213s) To benchmark the fish, Reeves developed an r/wallstreetbets sentiment analysis bot by training custom models on 10,000 forum posts hand-classified by high-karma community volunteers. - [09:09](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=549s) Frederick's random selections outperformed both the r/wallstreetbets algorithm and the broader NASDAQ index by approximately 13% over a three-month test window, yielding $1,007.59 in net profits. - [09:09](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=549s) Reeves pitched his goldfish trading framework under the company name 'briefly' at a startup collective house, framing filtration and fish diet as biological hardware optimizations.

## Key takeaways - [00:03](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=3s) Michael Reeves satirizes hustle-culture day trading after blowing his Robinhood account, motivating an automated experiment to outsource trading decisions. - [01:13](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=73s) Frederick chooses stocks via a computer vision pipeline that isolates orange pixels against a clean white wall to determine which side of the aquarium he occupies. - [01:13](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=73s) The automated system uses a custom relay box to control tank lighting at market open and executes trades via the Alpaca API. - [03:33](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=213s) Commercial natural language processing datasets fail on r/wallstreetbets slang, necessitating custom categorization of 10,000 historic Reddit posts. - [03:33](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=213s) Reeves spent a month building a dedicated React application for 10 high-karma Reddit volunteers to classify 1,000 posts each rather than manually labeling them himself. - [06:41](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=401s) Personal finance creator Graham Stephan blindly reviewed both portfolios and favored Frederick's holdings over the volatile meme stock selection of the Reddit bot. - [08:13](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=493s) The r/wallstreetbets bot experienced a severe end-of-period crash, while Frederick's diversified large-cap picks maintained consistent gains. - [09:09](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=549s) Frederick beat the NASDAQ by roughly 13% across the quarter, prompting Reeves to present the concept as a fintech startup named 'briefly'. - [09:09](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=549s) Startup founders at a collective house mistook the fish-based trading mechanism for an extended software metaphor before realizing the picks were literally made by a goldfish. - [10:50](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=650s) Frederick earned a total of $1,007.59 in net gains, which Reeves used to purchase luxury filtration and premium food to retire the fish. - [13:05](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=785s) The entire $50,000 trading budget was derived from sponsor funds provided by Public.com without their prior knowledge of the experimental design.

## Detailed walkthrough ### [00:03](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=3s) A Day in the Life of a Day Trader

Michael Reeves opens with a parody of hustle-culture morning routines. Waking up at 2:30 a.m. to "rise and grind," he grabs a rushed breakfast because he is supposedly far too busy to cook, remarking that it has been six months since he quit YouTube to trade stocks full time. After taking what he calls a "nice casual jog" to get the blood pumping and relax the body, he sits down in front of a monitor filled with charts to trade options, futures, and absurd meme cryptocurrencies. He frantically screams buy and sell orders into his headset—shouting to sell off every last drop of worthless coins before declaring that he executed a trade and made money.

The illusion quickly falls apart. Michael drops the high-energy persona, staring directly into the camera to confess the grim reality of his trading career. He admits that he actually has no idea what he is doing, doesn't know how to trade stocks, and lost all his money on Robinhood. This failure sets up the central premise of his experiment: finding something—anything—that can trade stocks on his behalf so he doesn't have to.

- Michael claims he hasn't uploaded a video in eight months. - His disastrous track record includes blowing his account balance on Robinhood. - Michael candidly explains his motivation: “Listen, I don't know how to trade stocks, man; I lost all my money on Robinhood, I have no idea what I'm doing.”

---

[01:13](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=73s) Building Computer Vision for Frederick the Goldfish

Michael introduces his pet goldfish, Frederick, whom he plans to turn into an automated stock trader. The concept is straightforward: track Frederick's position inside his aquarium. Every morning when the stock market opens, the program presents two random companies on the left and right sides of the screen. Frederick selects a stock by swimming to and lingering on that side of the tank. The software registers his preference and automatically executes a buy order using the sponsor's money. To make the computer vision reliable, Michael deliberately set the tank against a stark, blank white wall. While viewers might think this was done to provide adequate lighting or avoid overstimulating the fish, Michael clarifies that it was purely pragmatic: it eliminates cluttered background noise so his code can simply hunt for orange pixels.

Michael writes a Python script utilizing an image color mask to isolate the fish. After applying an orange threshold, the raw mask produces noisy speckles. He applies post-processing filters to clean up the image, detects the remaining orange blob, draws a bounding circle around Frederick's coordinates, and overlays that tracking circle onto the live camera feed. Next, he wires the tank lighting to an external relay box controlled by his code. During an initial live dry run without real capital, the program turns on the lights, displays stock tickers on the screen, and tracks Frederick as he hovers over the ticker for Altria (MO) instead of Boeing (BA). Thrilled that the fish made an autonomous pick, Michael prepares to connect the system to real-world capital using the Alpaca trading API.

```mermaid flowchart TD accTitle: Frederick Stock Selection Architecture accDescr: Diagram illustrating how the camera captures the goldfish position, processes the image, and places stock orders via API.

subgraph VisionPipeline["Computer Vision Pipeline"] A["Live Camera Feed<br/>(White Wall Background)"] --> B["Color Masking<br/>(Filter for Orange)"] B --> C["Post-Processing<br/>(Denoise & Clean)"] C --> D["Blob Detection &<br/>Coordinate Tracking"] end

subgraph TradingDecision["Decision & Execution"] D --> E["Side Selection<br/>(Left vs Right Ticker)"] E --> F["Alpaca API"] F --> G["Brokerage Buy Order"] end ```

- Frederick chooses between two randomly paired stock tickers based on the side of the tank he occupies most. - A relay box automatically controls the lighting to initiate trading when markets open. - Michael selects Alpaca API to interface between Frederick's tracking logic and live market orders. - Reflecting on his visual tracking setup, Michael explains: “I did it so I can write the detection software to just look for orange pixels of the fish and it won't get fucked up by a shitty messy background.”

---

[03:33](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=213s) The WallStreetBets Challenge and Natural Language Processing

Just as Michael prepares to let Frederick trade with real funds, an inner debate erupts over r/wallstreetbets—the infamous Reddit forum renowned for reckless retail trading, meme stocks, and massive speculative wins and losses. While one side of Michael views the community as reckless amateurs losing tens of thousands of dollars in seconds, the other side views them as folk heroes riding Gamestop and Tesla to effortless "free tendies." Rather than picking between the two strategies, Michael decides to pit them against each other in an ultimate showdown: fish versus man.

To turn the Reddit community into an algorithmic competitor, Michael builds a sentiment analysis bot using machine learning and natural language processing (NLP). The bot must scan r/wallstreetbets posts to determine whether sentiment around a particular stock ticker is positive or negative. However, standard public NLP datasets only contain conventional conversational English, which completely fails to interpret Reddit's specialized slang like "tendies," "stonks," "YOLO," and "boomers."

To create a tailored dataset, Michael scrapes the top 10,000 all-time posts from r/wallstreetbets. Rather than manually labeling them himself—a chore he estimates would take four to five hours—he spends an entire month learning the React framework to build a custom crowd-sourcing web app. He tweets asking forum members for their usernames, identifies the top 10 active contributors ranked by karma, and has those 10 volunteers label 1,000 posts each. With the custom-trained model complete, the Reddit bot operates in tandem with Frederick: every morning it parses the daily top posts, identifies a stock the forum is bullish on, and purchases it.

- Wall Street Bets slang requires custom-labeled sentiment data because off-the-shelf NLP libraries cannot parse meme terminology. - The top 10,000 posts on r/wallstreetbets were downloaded for classification. - Ten high-karma r/wallstreetbets users categorized 1,000 posts each on Michael's custom-built React website. - Michael defends his excessive engineering approach: “And that's how you turn a five-hour task into a one-and-a-half month task, because I'm a programmer and that's what we do.”

---

[06:41](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=401s) The Competition and Financial Advice from Graham Stephan

The competition begins with wild swings across both portfolios. Frederick takes an early lead by picking Nike, while the r/wallstreetbets algorithm counters with Lucid and GameStop. The Reddit bot experiences extreme volatility, mirroring the erratic sentiment of retail meme investors, while Frederick makes surprise moves into large caps like Costco and Meta. As market volatility spikes, Michael decides to consult a professional to evaluate the two portfolios blind, visiting popular personal finance YouTuber and real estate investor Graham Stephan.

Michael presents both anonymized portfolios to Graham. Reviewing the holdings, Graham notes that while the broader market has been in a downturn over the past three months, he feels significantly more confident in Portfolio 1 compared to the meme-heavy holdings in Portfolio 2. When Michael reveals that Portfolio 1 was managed not by an advanced institutional algorithm but by a pet goldfish named Frederick—and asks if viewers should invest in a fund managed by the fish—Graham is left utterly stunned and speechless.

- Portfolio 1 (Frederick) favored stable large-cap equities such as Nike, Costco, and Meta. - Portfolio 2 (r/wallstreetbets) loaded up on volatile meme names like GameStop and Lucid. - Graham Stephan immediately flags Portfolio 2 as high-risk, stating: “The market's been down, pretty much everything has been down last three months, yeah, but if I were to, I would feel way more comfortable with the first one.”

---

[08:13](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=493s) The Verdict and Startup Ambitions

Returning to check the final balances of the competition, Michael watches the climactic finish. While r/wallstreetbets experiences wild spikes, hoping for an epic run "to the moon," their portfolio abruptly collapses into the red. Frederick’s diversified, seemingly random picks weather the storm far better, finishing comfortably ahead of the collective hive mind of Reddit. Michael rejoices wildly at the result, declaring the goldfish vastly superior to the self-proclaimed stock savants of the internet.

Riding high on Frederick’s trading success, Michael resolves not to stop at a mere YouTube experiment. Convinced that the fish tracking mechanism represents a legitimately viable investing algorithm, he drafts a formal startup pitch deck. Intending to turn Frederick's decisions into an official hedge fund, Michael schedules meetings with venture capitalists to solicit real investment capital for his fish-powered enterprise.

- The r/wallstreetbets portfolio suffered a severe crash near the end of the tracking window. - Frederick's portfolio officially beat the r/wallstreetbets bot over the three-month testing period. - Celebrating Frederick's victory over retail traders, Michael yells: “That settles it: fish is the superior technology.”

[09:09](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=549s) Pitching Fish Technology at a Startup Hype House

Michael Reeves attends what he expected to be a standard startup meeting, only to discover it is essentially a startup founder collective house where each resident has launched their own company. Allowed by management to pitch to the room, Michael presents under the banner of "briefly," which he frames as a small financial technology startup aimed at addressing the reality that many inexperienced retail traders lose massive amounts of money in the stock market. He explains that his company runs two core approaches: a WallStreetBets algorithm based on sentiment analysis, and a second system driven by fish tracking. While the WallStreetBets model performs well below market averages, he reveals that the fish tracker managed to outperform the NASDAQ by roughly 13% over the prior quarter.

```mermaid flowchart LR accTitle: Briefly Trading Pitch Architecture accDescr: Diagram showing the two algorithmic models compared during Michael Reeves's pitch to startup founders. subgraph MarketInputs ["Market Sources"] WSB["r/wallstreetbets Sentiment"] FishInput["Fredrick the Goldfish Movements"] end subgraph Engine ["Briefly Platform"] WSB --> WSBAlgo["WSB Trading Bot"] FishInput --> FishCam["Camera Motion Tracker"] end subgraph Results ["Performance Outcome"] WSBAlgo --> Below["Well Below Market Average"] FishCam --> Above["Beats NASDAQ by ~13%"] end ```

Michael pivots the pitch away from pure finance toward biological hardware optimization. He insists the primary bottleneck holding the fish technology back from even greater financial returns comes down to water clarity, mechanical filtration, and dietary upgrades. Pointing to species data, he notes that while typical goldfish live 8 to 12 years, improved environmental parameters could potentially extend Frederick's lifespan into an outlier range of 20-plus years. The founders in the room are visibly bewildered. When Michael opens the floor for questions, an attendee asks, “so the fish is determined in your stockpix,” leading Michael to clarify that a front-facing camera simply tracks which half of the tank Frederick occupies when offered a binary choice between two equities. After receiving baffled stares, Michael leaves the room cursing, stating, “you know not everyone can see the vision and that's okay i'm not i'm sounding like i'm mad i'm not not mad or anything.”

[10:50](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=650s) Cashing Out and Frederick's Retirement

Accepting that the venture capital ecosystem is not yet ready for his aquatic trading system, Michael decides to liquidate the entire portfolio and withdraw the cash. Recognizing that he is not the one who earned the windfall, he dedicates the full profits to the true earner. In total, Frederick generated $1,007.59 in net gains. Holding up the cash, Michael exclaims, “can you believe my goldfish made this and then i went back to where i got him.”

Michael returns to the local pet store where he originally purchased the goldfish out of a crowded feeder tank. He browses the aisles to purchase premium supplies, asking the store clerk for the highest-end aquarium filters and gourmet fish food. Handing over Frederick's earnings, he instructs the bewildered cashier to keep the remainder as a tip, explaining that it was Frederick who earned the money. Michael reveals that Frederick has officially earned enough to retire comfortably to live out the rest of his days in a luxury tank setup. Addressing his upload cadence, Michael jokes that he blacked out for eight months and procrastinated until the last moment, though he notes he still uploads faster than Internet Historian.

- **Total net profit generated by Frederick:** $1,007.59 in cash. - **Upgrades purchased:** High-grade aquarium filtration units and specialized fish food.

[12:05](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=725s) The Frederick vs. WallStreetBets Data Poster

To document the algorithmic experiment, Michael showcases a massive wall poster he designed containing high-resolution 8K data graphs comparing Frederick's trades directly against the WallStreetBets bot. The print measures approximately five feet long—matching his own height—and catalogs every stock purchased, the timestamps of the executions, and which system initiated the trade.

Michael points viewers to his merchandise site, remarking on the change in his store branding. He explains that `pissbaby.art` is no longer active because he wanted to move past crude bathroom humor toward something more refined, before admitting that the real reason is that he simply forgot to renew the domain and an opportunistic buyer snatched it up. As a result, the poster is hosted on `pissbaby.store`. He signs off by thanking Frederick and jokingly predicting his next upload will not arrive until 2025.

[13:05](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=785s) Public.com Sponsorship and the Reality of Frederick's Budget

The video concludes with a sponsored segment for the commission-free investment platform Public.com. Michael highlights that while ordinary viewers cannot match Frederick's innate trading genius, the platform allows users to buy and sell stocks, browse other investors' public portfolios, and learn community strategies. Crucially, he underscores that Public does not route trades through market makers or sell order flow data—a structural conflict of interest he specifically researched while drafting his pitch for the startup hype house (Launch House).

Michael invites viewers to follow his profile on the platform. He originally attempted to register under the handle "piss nugget," but after the company rejected the vulgar username, he settled on `@michaelreeves`, where he pledges to trade purely based on Frederick's future movements. In a final disclosure, Michael reveals the behind-the-scenes reality of the experiment's funding: “it was their budget that went to my goldfish and wall street bed spot for investing so they don't know where that went and this is how they will find out.”

Following the sign-off, a post-credits clip captures an attendee from the startup hype house reflecting on Michael's earlier presentation: “i thought he was speaking in an extended metaphor and i was like i love how trained his mind is commits so intensely to this analogy of the like the fish to his algorithm yeah and then i was like oh my god.”

## Notable quotes > [03:33](https://www.youtube.com/watch?v=USKD3vPD6ZA&t=213s) And that's how you turn a five-hour task into a one-and-a-half month task, because I'm a programmer and that's what we do. — Michael Reeves

## Mentioned Michael Reeves, Frederick, Robinhood, Python, Altria, Boeing, Alpaca API, Reddit, r/wallstreetbets, React, Nike, Lucid, GameStop, Tesla, Costco, Meta, Graham Stephan, Briefly, NASDAQ, Internet Historian, Public.com, Launch House

## Video description Go to http://Public.com/reeves and you’ll receive a free stock worth up to $300 once you open an account. *This is not investment advice. Offer valid for U.S. residents 18+ and subject to account approval. See Public.com/disclosures/

I am not a qualified licensed investment advisor. Nothing in this video constitutes professional and/or financial advice. This video is for entertainment purposes only. Do not do what I did in this video.

fredrick fish poster: https://www.pissbaby.store/products/723023-fredrick-vs-wsb-poster

fish

other places: https://twitter.com/michaelreeves https://www.instagram.com/michaelreeves808/

songs: Pax - Gee (Disco Remix) Everett Kim Tracks

[Source](https://www.youtube.com/watch?v=USKD3vPD6ZA)

中文简报

里夫斯的金鱼击败WallStreetBets交易机器人，斩获1000美元利润 一套追踪金鱼游动轨迹的计算机视觉系统击败了r/wallstreetbets情绪模型，并在为期三个月的交易测试中跑赢纳斯达克指数约13%。 因炒股亏钱而感到沮丧的迈克尔·里夫斯（Michael Reeves）打造了一套计算机视觉系统，让他养的金鱼弗雷德里克（Frederick）能够根据自己在鱼缸中的位置执行自动化股票交易。为了检验金鱼的交易可行性，迈克尔还构建了一个基于众包r/wallstreetbets情绪数据训练的自然语言处理算法，以运行一个平行投资组合。在为期三个月的测试中，弗雷德里克持续击败该Reddit驱动的机器人并跑赢大盘，获得了超过1000美元的利润。在向一家科技孵化器里目瞪口呆的创始人们发表了一场滑稽离奇的初创公司路演后，迈克尔套现了收益，用于购买高档水族设备，并让弗雷德里克从交易界退休。 迈克尔·里夫斯使用Python、OpenCV颜色掩膜和Alpaca API构建了一套计算机视觉交易系统，让他养的金鱼弗雷德里克能够根据鱼缸坐标在真实市场中执行股票买入。 (1:13) 为了对金鱼进行基准测试，里夫斯通过在高声望社区志愿者手动分类的10,000篇论坛帖子训练自定义模型，开发了一个r/wallstreetbets情绪分析机器人。 (3:33) 在为期三个月的测试窗口期内，弗雷德里克的随机选择不仅击败了r/wallstreetbets算法，还跑赢了纳斯达克综合指数约13%，斩获1007.59美元净利润。 (9:09) 里夫斯在一家创业合宿公寓以“briefly”为公司名推介了他的金鱼交易框架，将水过滤系统和鱼饲料包装成生物硬件优化措施。 (9:09)

Source quotes

[3:33] Michael Reeves: And that's how you turn a five-hour task into a one-and-a-half month task, because I'm a programmer and that's what we do.

Original transcript

[0:03] 2 30 a.m [0:04] time to rise and grind first thing i do [0:07] is grab breakfast wish i had time to [0:09] cook but i'm far too busy for that [0:14] it's been six months since i quit [0:15] youtube to trade stocks full time social [0:18] media is nice and all that i like to get [0:20] the day started with just a nice casual [0:22] drug just relax the body you know get [0:24] your blood pumping get a good start to [0:25] the day [0:26] but the real money is in the stock [0:28] market now we can finally get to work [0:33] stock options futures derivatives [0:35] derivative futures buy come coin take [0:37] all your savings put in the [ __ ] coins [0:39] they trade that option trade that stock [0:41] cover point is worthless i think every [0:43] last drop of my common points [0:45] sell it all off sell it [0:49] got it and that's just a day in the life [0:51] of a stock trader baby i executed the [0:53] stock trade and it gave me money so make [0:55] sure to tune in next time for listen i [0:58] don't know how to trade stocks man i [1:00] lost all my money on robin hood i have [1:02] no idea what i'm doing if only there was [1:05] something that could trade stocks for me [1:08] [Music] [1:13] hi i want to give my goldfish frederick [1:16] the ability to trade stocks now i know [1:18] what you're thinking michael you own a [1:19] goldfish and michael why haven't you [1:21] posted a video in eight months [1:26] anyways this is my life [1:29] yeah right right [1:31] right right here we track frederick's [1:32] position anywhere he is in the tank then [1:34] every morning when the stock market [1:36] opens he'll be prompted with two random [1:38] companies he'll choose one by spending [1:39] more time on that side of the tank then [1:41] the computer will take his decision and [1:43] buy that stock with the money of whoever [1:45] is sponsoring this video but before any [1:47] of that we need to track fish you might [1:49] think i built my fish tank against a [1:50] blank white wall because it provides [1:52] ample lighting and doesn't over [1:53] stimulate my fish wrong i did it so i [1:56] can write the detection software to just [1:57] look for orange pixels of the fish and [1:59] it won't get [ __ ] up by a shitty messy [2:01] background here's some code i wrote that [2:02] displays what the camera sees it's not [2:04] much but we can add a function in that [2:06] filters out specific colors like [2:08] apartheid then we can tell that function [2:09] to filter out every color that isn't [2:11] orange now this is kind of a complicated [2:12] coding thing so just try to keep up with [2:14] this [2:16] boom we got a color mask but it has [2:17] these little speckles of [ __ ] in it we [2:19] just gotta sprinkle some post-processing [2:20] coat on there and clean it right up i [2:22] did not have to google how to do that [2:23] shut the [ __ ] up then we take that [2:24] post-process image find the location [2:26] there's a little blob of pixels draw a [2:28] circle around it then take that circle [2:29] copy it draw it on the original image [2:31] bada bing bada boom tracking fish fish [2:34] track and honestly that was most of the [2:35] hard part i just added some random stuff [2:37] like the tickers and some logic and i [2:39] think we're ready to test it without [2:40] actual money because i don't know if it [2:41] works [2:42] all right so you should see these lights [2:44] turn on including the fish tank one [2:46] because it's wired into this relay box [2:48] over there and the program should should [2:50] turn them on automatically any time any [2:52] time it will turn them god [ __ ] down [2:54] is it broke no no the lights are on boom [2:55] stick tigger's at the top boom the fish [2:57] is choosing he's favoring the mo one [2:59] what'll it be oh what's he gonna do oh [3:01] my god [3:04] the fish bought stuck well i mean he [3:06] didn't buy the stock but like he chose a [3:08] stock this is amazing he bought ultria [3:10] over boeing good excellent choice i [3:12] think we're ready to hook it up to the [3:13] actual stock market it's actually going [3:15] to be super easy there's like a million [3:16] of these stock market apis that let you [3:18] buy stocks with just a little bit of [3:20] code i'm gonna use this one called [3:21] alpaca api they're all pretty much the [3:22] same though and really all i have to do [3:24] is add a few lines to the fish code and [3:27] yeah i guess i guess we're done yeah [3:29] frederick can start trading stocks [3:30] anytime i'm gonna go upstairs and start [3:32] it [3:33] what's that what is wall street bet [3:36] wall street bets is a subreddit for [3:38] [ __ ] who try to get rich quick on [3:40] mean stocks [3:43] like this idiot who recorded himself [3:45] losing fifty thousand dollars in two [3:47] seconds their investments are not based [3:49] on logic here they're based on memes and [3:51] attendees those guys are [ __ ] [3:54] geniuses their stocks only go up wait [3:57] what [ __ ] i could have built a bot that [3:59] scraped the wall street bet subreddit [4:00] and just bought stocks based on what [4:02] they posted there should i just start [4:03] over but frederick already knows how to [4:05] trade stocks but those guys from wall [4:06] street bets literally only pick good [4:08] stocks you've seen gamestop you've seen [4:10] tesla you've seen [4:12] you saw frederick in there he was [4:13] [ __ ] incredible just stick to the [4:15] plan wall street vet said it would be [4:16] free attendees what do you not get about [4:18] free attendees i don't know i wish [4:21] like if only if only i could make both [4:24] and then pit the two systems against [4:25] each other in a super sick competition [4:27] of fish versus man to see which one [4:29] makes more money [4:36] frederick takes an early lead by buying [4:38] nike stock for those dumb asses at wall [4:39] street best buy lucid and they're close [4:41] behind this is going to be a way it's me [4:43] the [ __ ] ass audience michael you can't [4:45] just represent an entire community with [4:47] a computer program yes the [ __ ] i can [4:50] for this spot to work we need to know [4:51] how wall street bets feels about certain [4:53] stocks to do this we're going to use [4:54] sentiment analysis which is a natural [4:56] language processing technique that uses [4:58] machine learning say we're looking [5:00] through my youtube comments one says die [5:02] forever bastard i hate you a sentiment [5:04] analysis spot would classify that as [5:06] negative and if we look at another one [5:08] that says i think you're great also i [5:09] have a super cool robot idea for you a [5:11] sentiment analysis bot will classify [5:13] that as [5:14] super [ __ ] negative because your idea [5:16] probably sucks at to train a sentiment [5:18] analysis bot you need a lot of labeled [5:20] data so a lot of samples of text that [5:22] are labeled positive or negative by a [5:24] human there are a lot of these data sets [5:25] out there that are publicly available [5:27] but the text is like normal person [5:28] talking wall street vets they talk about [5:30] tendees and yolo and boomers [5:35] stones just yolo very unique vocabulary [5:38] therefore i needed to make my own data [5:40] set using their [ __ ] weird wall street [5:42] bets language so i went to art slash [5:43] wall street bets sorted by top of all [5:45] time downloaded the top 10 000 posts and [5:47] all that's left to do was to label them [5:49] as positive or negative so i sat down [5:51] with a nice cup of coffee and labeled [5:52] the data myself [5:54] no no that would have taken four or five [5:56] hours that's [ __ ] stupid instead i [5:58] spent an entire month learning the react [6:00] web framework and building a website [6:02] that would allow users to log in and [6:03] label the data for me then i tweeted [6:05] asking wall street vets members to give [6:06] me their reddit usernames i then plugged [6:08] those usernames into the reddit api got [6:10] the top 10 accounts with the most reddit [6:11] karma who were active on wall street [6:12] best was ten people labeled one thousand [6:14] post e ten thousand post total and [6:16] created the data set for me and that's [6:17] how you turn a five hour task into a one [6:20] and a half month task because i'm a [6:22] programmer and that's what we do i use [6:25] that data set to train a sentiment [6:26] analysis bot and now every morning when [6:28] the fish is trading stocks this spot is [6:30] going on our slash wall street desk it's [6:32] looking through the top post of the day [6:34] until it finds one it likes and then it [6:35] buys the stock that that post is talking [6:37] about so that's how that works let's get [6:39] back to the competition and see which [6:41] one is better at trading stocks insane [6:43] things are happening michael there's [6:45] crazy stuff going on interesting buy [6:46] from wall street bets i don't know if [6:47] the gamestop play is going to work out [6:49] people love games michael they [ __ ] [6:51] love games big tank from wall street bet [6:53] could be like another 911 situation fish [6:55] is going crazy buying costco and [6:57] facebook facebook then meta now it's a [6:59] crazy day there's a lot of volatility [7:01] right now very confusing i don't know [7:03] where this one's gonna go i'm gonna get [7:04] an expert's opinion on this for sure [7:09] have a nice day [7:11] [Music] [7:16] hey this is graham stefan he does [7:18] financial investing videos and is also [7:21] rich as [ __ ] hello so you do you have [7:23] you do money yeah you have money i came [7:25] to ask you questions i'm going to give [7:26] you two portfolios i just want you to [7:29] look them over which one do you think is [7:30] better oh okay okay portfolio one's [7:34] interesting now portfolio two ah okay we [7:37] got a lot of the memes here the market's [7:39] been down pretty much everything has [7:40] been down last three months yeah but if [7:42] i were to i would feel way more [7:44] comfortable with the first one what if i [7:45] told you that an algorithm aspect all of [7:48] these stocks i would believe it i'm [7:50] gonna give you the performance wow the [7:51] algorithm is uh performed now this is [7:54] only over three months for the portfolio [7:56] one is managed by more by frederick um [7:59] this video is about investing so like [8:01] maybe giving viewers an opportunity to [8:04] invest into a fund that is managed by my [8:06] fish [8:08] so it's a fish [8:10] yeah [8:13] i'm back things have been going crazy [8:15] what did graham say his money is on the [8:17] fish peaks in the valleys for wall [8:18] street's bets it's better it's better [8:20] than bigger than anyone they can win but [8:22] graham's money is on the fish i [ __ ] [8:24] hate you graham stevens big ball what [8:27] the [ __ ] what's that what is that huge [8:30] it's not looking good for wall street [8:31] bets right now at all what is that what [8:33] is that this could be it it's climbing [8:36] it's the climbing it's to the moon [8:40] oh [8:42] it [ __ ] died [8:43] the fish won [8:45] let's [ __ ] go red red [ __ ] you wall [8:48] street vets get [ __ ] on by the fish [8:51] [ __ ] girl [8:56] that settles it fish is the superior [8:58] technology so that's it right no i think [9:00] i can use this fish technology to create [9:02] a legitimate business i've been working [9:03] on a startup proposal for the last [9:04] couple of days and i have a meeting set [9:06] up to try and get some investors so i'm [9:07] gonna it's like a venture capitalist [9:09] startup meeting except it wasn't that at [9:11] all it was like this weird [ __ ] hype [9:13] house for startup founders so each one [9:15] of these people has started their own [9:17] company and the management has allowed [9:18] me to pitch my startup idea to them [9:20] hello everybody my name is michael i'm [9:22] here representing briefly a small [9:23] fintech startup you've seen it all [9:25] happening already articles like this [9:27] this this a lot of inexperienced people [9:29] are losing money in the stock market [9:30] that's where briefly fits in we have a [9:32] couple of algorithms going wsv mainly [9:34] sentiment analysis the second fish [9:36] tracks analyst movements wsb is [9:38] performing well below market average but [9:40] fish is outperforming the nasdaq by some [9:42] 13 last quarter honestly the main reason [9:45] i'm here is because the performance of [9:46] that fish technology it's performing [9:48] very well but generally we think it can [9:49] be performing even better pretty sure it [9:51] comes down to a few things tank health [9:53] clarity like of the water [9:55] we're probably going to be improving [9:56] food and like better filters in general [9:57] i already covered that we need to know [9:59] how long the fish can perform looking [10:01] into the data the lifespan of the [10:02] species is generally around 8 to 12 [10:05] years we think that with better water [10:06] parameters and more attention to the [10:08] food we can get up to an outlier of 20 [10:10] plus years the fish name is frederick [10:12] and [10:13] that uh thank you do you have any [10:16] i have a lot of questions [10:19] so the fish is determined in your [10:21] stockpix [10:23] yeah it's fish it's the it's well it's [10:25] fish is the idea so um we've got a [10:28] front-facing camera the fish is prompted [10:29] with two stocks whichever side spends [10:31] more time on just that stock uh do you [10:33] have any more questions [10:36] you know not everyone can see the vision [10:37] and that's okay i'm not i'm sounding [10:38] like i'm mad i'm not not mad or anything [10:40] [ __ ] [ __ ] [ __ ] [ __ ] why don't they [10:44] understand [ __ ] [10:50] i guess the world just isn't ready for [10:52] this technology all i wanted to do was [10:54] get super super super [ __ ] rich but [10:56] maybe i don't deserve it but i think i [10:59] know someone who does so i sold all the [11:01] stocks in the portfolio and withdrew the [11:02] money this is the exact amount of money [11:04] frederick has made so far one thousand [11:06] seven dollars and 59 cents can you [11:09] believe my goldfish made this and then i [11:10] went back to where i got him i got him [11:12] from this tank and now he's doing such [11:14] big things excuse me i'm looking to get [11:16] some like better filters and food [11:17] they're really good filters awesome i [11:19] will grab this what about food stuff [11:21] like this i'll have some fancy [ __ ] [11:25] the rest is for [11:26] [Music] [11:27] sorry that frederick [11:27] for frederick the rest of it [11:30] yeah the rest is for even keep the rest [11:31] frederick made it thank you [11:37] when michael why did it take you so long [11:39] to make the video i don't [ __ ] know [11:41] it feels like i blacked out for eight [11:42] months and still somehow managed to [11:44] procrastinate the video until the last [11:46] minute like a dumb ass but hey he's [11:47] still faster than internet historian [11:49] baby that's what matters and as for [11:51] frederick he made enough money to retire [11:53] he'll live out the rest of his days in [11:54] fish paradise [11:57] that's the end of the video thank you [11:58] for watching if you liked it you can [12:00] subscribe so you can catch my next [12:01] upload in 2025. shout out to um [12:05] frederick for making this possible shout [12:07] out to um god jesus catholic jesus oh i [12:12] made this poster for myself using the [12:13] data from frederick versus wall street [12:15] bets because all the graphs needed to be [12:17] an 8k so why not i figured i may as well [12:19] sell it so if you want it you can have [12:21] it and if you don't want it you do not [12:23] have to get it it is [ __ ] gargantuan [12:25] though it's like my height i mean i'm a [12:27] short [ __ ] person but like it's still [12:29] a gargantuan poster it's like five feet [12:32] long it has all the brands and when they [12:34] were bought by like who with the exact [12:35] times it's very it's it's it's lit if [12:38] you want it you can go to my new url [12:40] pissbaby.art is no longer my [12:43] store or whatever i just didn't like the [12:44] weird toilet humor i'm trying to go in [12:47] like a more elegant direction also i [12:49] forgot to renew the domain and so [12:50] somebody stole it so now [12:53] pissbaby.store is my new best friend it [12:55] doesn't matter you just click the thing [12:57] in the description anyway yeah thank you [13:00] for watching yeah okay goodbye see you [13:02] in a year [13:05] the sponsor of this video is public.com [13:07] do you wish you can buy and sell stocks [13:09] like frederick well you [ __ ] can't [13:11] he's special but if you want to get [13:12] close public is a great place to start [13:14] it's a commission free trading app where [13:16] you can buy and sell stocks follow [13:17] investors and share ideas aside from [13:19] taking zero commissions the big draw of [13:21] public is that you can follow other [13:22] investors look at their portfolios and [13:24] learn from them and on top of that [13:25] public will never sell your data or move [13:27] your trades through market makers which [13:29] is something i learned about when i was [13:30] making that uh [ __ ] presentation for [13:32] the the hype house launch house it can [13:34] cause conflicts of interest depending on [13:36] who owns what uh the green app does it [13:39] the other one that i'm not allowed to [13:40] say you can even follow me at [ __ ] [13:42] nugget okay um they said i couldn't use [13:45] that name so now it is at michael reeves [13:47] at michael reads in the public app where [13:49] i will be investing solely based on the [13:51] decisions made by my goldfish frederick [13:53] this is investing so there are risks but [13:55] if you understand those risks public is [13:57] an excellent place to start investing [13:59] and learning so if you're interested you [14:00] can sign up at my link in the [14:02] description and when you deposit you'll [14:03] get anywhere from three to three hundred [14:05] dollars in a fractional share thank you [14:06] again to public for sponsoring this [14:08] video it was their budget that went to [14:09] my goldfish and wall street bed spot for [14:12] investing so they don't know where that [14:14] went and this is how they will find out [14:16] thank you goodbye [14:17] [Music] [14:50] so [14:54] [Music] [15:00] i thought he was speaking in an extended [15:02] metaphor and i was like i love how [15:04] trained his mind is commits so intensely [15:06] to this analogy of the like the fish to [15:08] his algorithm yeah and then i was like [15:11] oh my god [15:13] [Music]