{
  "id": 541599,
  "title": "Jane Street or Bust: Confessions of an Overambitious Newbie",
  "url": "/competitions/jane-street-real-time-market-data-forecasting/discussion/541599",
  "author_name": "Khaled Alghaish",
  "post_date": "2024-10-20T13:15:51.568000",
  "votes": -2,
  "comment_count": 0,
  "views": 0,
  "content": "<h1>Hello Everybody,</h1>\n<p>I know nothing about ML! My one strength is having a good temperament!<br>\nFresh from dipping my toes in the MCTS competition, after seeing this competition I bailed out. As an options trader, this challenge feels like hitting the jackpot! 🎰<br>\nAfter years of wins and losses, I am in love with probabilities, and that is why I committed to learning machine learning, it is the love for the probabilistic foundation behind its predictions! I am super excited! </p>\n<p>Thanks to Jane Street for this opportunity! I am grateful.</p>\n<p>Just to lay my cards: I'm no ML wizard (yet), but I'm here to learn, grow, and maybe surprise myself. My goal? To tinker super fast and understand the fundamentals deeply as needed so I can crack that leaderboard and land somewhere in the double digits. Ambitious? Maybe. Impossible? We'll see! 😉</p>\n<h6>Here's my game plan:</h6>\n<ol>\n<li>Master the Metric: That weighted zero-mean R-squared score looks tricky. Time to dive deep!</li>\n<li>Build a Bulletproof Validation System: Gotta make sure my local scores aren't just wishful thinking.</li>\n<li>Establish a Reliable Baseline: Aiming to understand what \"good\" looks like in this financial playground.</li>\n<li>iterate Rapidly: Quick experiments, fail fast, learn faster.</li>\n<li>Hunt for Hidden Edges: Time to put my trader instincts to work on those anonymized features.</li>\n<li>Optimize Relentlessly: Push my models (and my poor laptop) to the limit.</li>\n<li>Scrutinize the Gap: Keep a hawk-eye on the difference between local and public scores.</li>\n<li>Leverage the Community (Carefully): so far I learned a lot form <a href=\"https://www.kaggle.com/cdeotte\" target=\"_blank\">@cdeotte</a> , I'm here to learn from the best.</li>\n<li>Plan for the Endgame: Saving my best shots for when it counts.</li>\n<li>Document and Learn: Win or lose, I'm here to level up.</li>\n</ol>\n<p>I know I'm punching above my weight class here, but that's how I like it. If anyone's got tips for a e eager newbie, I'm all ears!</p>\n<p>May the best model win (and may mine at least not embarrass me too badly)! 📈🤞<br>\nCheers,</p>",
  "messages": [
    {
      "id": 3023343,
      "postDate": "2024-10-20T13:15:51.567Z",
      "content": "<h1>Hello Everybody,</h1>\n<p>I know nothing about ML! My one strength is having a good temperament!<br>\nFresh from dipping my toes in the MCTS competition, after seeing this competition I bailed out. As an options trader, this challenge feels like hitting the jackpot! 🎰<br>\nAfter years of wins and losses, I am in love with probabilities, and that is why I committed to learning machine learning, it is the love for the probabilistic foundation behind its predictions! I am super excited! </p>\n<p>Thanks to Jane Street for this opportunity! I am grateful.</p>\n<p>Just to lay my cards: I'm no ML wizard (yet), but I'm here to learn, grow, and maybe surprise myself. My goal? To tinker super fast and understand the fundamentals deeply as needed so I can crack that leaderboard and land somewhere in the double digits. Ambitious? Maybe. Impossible? We'll see! 😉</p>\n<h6>Here's my game plan:</h6>\n<ol>\n<li>Master the Metric: That weighted zero-mean R-squared score looks tricky. Time to dive deep!</li>\n<li>Build a Bulletproof Validation System: Gotta make sure my local scores aren't just wishful thinking.</li>\n<li>Establish a Reliable Baseline: Aiming to understand what \"good\" looks like in this financial playground.</li>\n<li>iterate Rapidly: Quick experiments, fail fast, learn faster.</li>\n<li>Hunt for Hidden Edges: Time to put my trader instincts to work on those anonymized features.</li>\n<li>Optimize Relentlessly: Push my models (and my poor laptop) to the limit.</li>\n<li>Scrutinize the Gap: Keep a hawk-eye on the difference between local and public scores.</li>\n<li>Leverage the Community (Carefully): so far I learned a lot form <a href=\"https://www.kaggle.com/cdeotte\" target=\"_blank\">@cdeotte</a> , I'm here to learn from the best.</li>\n<li>Plan for the Endgame: Saving my best shots for when it counts.</li>\n<li>Document and Learn: Win or lose, I'm here to level up.</li>\n</ol>\n<p>I know I'm punching above my weight class here, but that's how I like it. If anyone's got tips for a e eager newbie, I'm all ears!</p>\n<p>May the best model win (and may mine at least not embarrass me too badly)! 📈🤞<br>\nCheers,</p>",
      "rawMarkdown": "# Hello Everybody,  \n\nI know nothing about ML! My one strength is having a good temperament!\nFresh from dipping my toes in the MCTS competition, after seeing this competition I bailed out. As an options trader, this challenge feels like hitting the jackpot! 🎰\nAfter years of wins and losses, I am in love with probabilities, and that is why I committed to learning machine learning, it is the love for the probabilistic foundation behind its predictions! I am super excited! \n\nThanks to Jane Street for this opportunity! I am grateful.\n \n\nJust to lay my cards: I'm no ML wizard (yet), but I'm here to learn, grow, and maybe surprise myself. My goal? To tinker super fast and understand the fundamentals deeply as needed so I can crack that leaderboard and land somewhere in the double digits. Ambitious? Maybe. Impossible? We'll see! 😉\n\n###### Here's my game plan:\n1. Master the Metric: That weighted zero-mean R-squared score looks tricky. Time to dive deep!\n2. Build a Bulletproof Validation System: Gotta make sure my local scores aren't just wishful thinking.\n3. Establish a Reliable Baseline: Aiming to understand what \"good\" looks like in this financial playground.\n4. iterate Rapidly: Quick experiments, fail fast, learn faster.\n5. Hunt for Hidden Edges: Time to put my trader instincts to work on those anonymized features.\n6. Optimize Relentlessly: Push my models (and my poor laptop) to the limit.\n7. Scrutinize the Gap: Keep a hawk-eye on the difference between local and public scores.\n8. Leverage the Community (Carefully): so far I learned a lot form @cdeotte , I'm here to learn from the best.\n9. Plan for the Endgame: Saving my best shots for when it counts.\n10. Document and Learn: Win or lose, I'm here to level up.\n\nI know I'm punching above my weight class here, but that's how I like it. If anyone's got tips for a e eager newbie, I'm all ears!\n\nMay the best model win (and may mine at least not embarrass me too badly)! 📈🤞\nCheers,",
      "votes": -2
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "3023343": "# Hello Everybody,  \n\nI know nothing about ML! My one strength is having a good temperament!\nFresh from dipping my toes in the MCTS competition, after seeing this competition I bailed out. As an options trader, this challenge feels like hitting the jackpot! 🎰\nAfter years of wins and losses, I am in love with probabilities, and that is why I committed to learning machine learning, it is the love for the probabilistic foundation behind its predictions! I am super excited! \n\nThanks to Jane Street for this opportunity! I am grateful.\n \n\nJust to lay my cards: I'm no ML wizard (yet), but I'm here to learn, grow, and maybe surprise myself. My goal? To tinker super fast and understand the fundamentals deeply as needed so I can crack that leaderboard and land somewhere in the double digits. Ambitious? Maybe. Impossible? We'll see! 😉\n\n###### Here's my game plan:\n1. Master the Metric: That weighted zero-mean R-squared score looks tricky. Time to dive deep!\n2. Build a Bulletproof Validation System: Gotta make sure my local scores aren't just wishful thinking.\n3. Establish a Reliable Baseline: Aiming to understand what \"good\" looks like in this financial playground.\n4. iterate Rapidly: Quick experiments, fail fast, learn faster.\n5. Hunt for Hidden Edges: Time to put my trader instincts to work on those anonymized features.\n6. Optimize Relentlessly: Push my models (and my poor laptop) to the limit.\n7. Scrutinize the Gap: Keep a hawk-eye on the difference between local and public scores.\n8. Leverage the Community (Carefully): so far I learned a lot form @cdeotte , I'm here to learn from the best.\n9. Plan for the Endgame: Saving my best shots for when it counts.\n10. Document and Learn: Win or lose, I'm here to level up.\n\nI know I'm punching above my weight class here, but that's how I like it. If anyone's got tips for a e eager newbie, I'm all ears!\n\nMay the best model win (and may mine at least not embarrass me too badly)! 📈🤞\nCheers,"
  }
}