{
  "id": 284910,
  "title": "Papers on Short Term Trading and Returns",
  "url": "/competitions/g-research-crypto-forecasting/discussion/284910",
  "author_name": "",
  "post_date": "2021-11-02T20:20:06.399601700Z",
  "votes": 13,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Hey everyone!</p>\n<p>I wanted to start a papers thread and build on it, and hope others share as well, papers to gain domain knowledge. I have no domain knowledge in this area so I have downloaded papers that appeared to be relevant after reading their abstracts. I'll be reading these over the coming days and commenting more as I go through all of them. Hope this helps!</p>\n<p><strong>Research Papers:</strong></p>\n<ul>\n<li><p><a href=\"https://arxiv.org/abs/2109.07835\" target=\"_blank\">Incentives in Two-sided Matching Markets with Prediction-enhanced Preference-formation</a> - The present work shows that at the intersection of the two lies a previously unexplored type of strategic behavior: agents returning to the market (e.g., schools) can attack future predictions by interacting short-term non-optimally with their matches. </p></li>\n<li><p><a href=\"https://arxiv.org/abs/2107.06659\" target=\"_blank\">Financial Return Distributions: Past, Present, and COVID-19</a> - We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017--2020, we model tails of the return distributions at different time scales by using power-law, stretched exponential, and q-Gaussian functions.</p></li>\n</ul>",
  "messages": [
    {
      "id": "1568527",
      "postDate": "11/02/2021 20:20:06",
      "content": "<p>Hey everyone!</p>\n<p>I wanted to start a papers thread and build on it, and hope others share as well, papers to gain domain knowledge. I have no domain knowledge in this area so I have downloaded papers that appeared to be relevant after reading their abstracts. I'll be reading these over the coming days and commenting more as I go through all of them. Hope this helps!</p>\n<p><strong>Research Papers:</strong></p>\n<ul>\n<li><p><a href=\"https://arxiv.org/abs/2109.07835\" target=\"_blank\">Incentives in Two-sided Matching Markets with Prediction-enhanced Preference-formation</a> - The present work shows that at the intersection of the two lies a previously unexplored type of strategic behavior: agents returning to the market (e.g., schools) can attack future predictions by interacting short-term non-optimally with their matches. </p></li>\n<li><p><a href=\"https://arxiv.org/abs/2107.06659\" target=\"_blank\">Financial Return Distributions: Past, Present, and COVID-19</a> - We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017--2020, we model tails of the return distributions at different time scales by using power-law, stretched exponential, and q-Gaussian functions.</p></li>\n</ul>",
      "rawMarkdown": "Hey everyone!\n\nI wanted to start a papers thread and build on it, and hope others share as well, papers to gain domain knowledge. I have no domain knowledge in this area so I have downloaded papers that appeared to be relevant after reading their abstracts. I'll be reading these over the coming days and commenting more as I go through all of them. Hope this helps!\n\n**Research Papers:**\n\n- [Incentives in Two-sided Matching Markets with Prediction-enhanced Preference-formation](https://arxiv.org/abs/2109.07835) - The present work shows that at the intersection of the two lies a previously unexplored type of strategic behavior: agents returning to the market (e.g., schools) can attack future predictions by interacting short-term non-optimally with their matches. \n\n- [Financial Return Distributions: Past, Present, and COVID-19](https://arxiv.org/abs/2107.06659) - We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017--2020, we model tails of the return distributions at different time scales by using power-law, stretched exponential, and q-Gaussian functions.",
      "votes": null
    },
    {
      "id": "1568535",
      "postDate": "11/02/2021 20:31:22",
      "content": "<p>The one that includes COVID-19 is really interesting! </p>",
      "rawMarkdown": "The one that includes COVID-19 is really interesting!",
      "votes": null
    },
    {
      "id": "1573608",
      "postDate": "11/06/2021 19:09:24",
      "content": "<p>Why does everyone just hop to an LSTM, XGBoost, or LGBM lmaoo. Also, that is not how HFT prediction works and those papers are going to be wildly inaccurate. No, I will not elaborate! I want that prize money…</p>",
      "rawMarkdown": "Why does everyone just hop to an LSTM, XGBoost, or LGBM lmaoo. Also, that is not how HFT prediction works and those papers are going to be wildly inaccurate. No, I will not elaborate! I want that prize money...",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1568535,
      "author_name": "",
      "author_url": "",
      "post_date": "11/02/2021 20:31:22",
      "content": "<p>The one that includes COVID-19 is really interesting! </p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1573608,
      "author_name": "infernapespeed",
      "author_url": "",
      "post_date": "11/06/2021 19:09:24",
      "content": "<p>Why does everyone just hop to an LSTM, XGBoost, or LGBM lmaoo. Also, that is not how HFT prediction works and those papers are going to be wildly inaccurate. No, I will not elaborate! I want that prize money…</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1568527": "Hey everyone!\n\nI wanted to start a papers thread and build on it, and hope others share as well, papers to gain domain knowledge. I have no domain knowledge in this area so I have downloaded papers that appeared to be relevant after reading their abstracts. I'll be reading these over the coming days and commenting more as I go through all of them. Hope this helps!\n\n**Research Papers:**\n\n- [Incentives in Two-sided Matching Markets with Prediction-enhanced Preference-formation](https://arxiv.org/abs/2109.07835) - The present work shows that at the intersection of the two lies a previously unexplored type of strategic behavior: agents returning to the market (e.g., schools) can attack future predictions by interacting short-term non-optimally with their matches. \n\n- [Financial Return Distributions: Past, Present, and COVID-19](https://arxiv.org/abs/2107.06659) - We analyze the price return distributions of currency exchange rates, cryptocurrencies, and contracts for differences (CFDs) representing stock indices, stock shares, and commodities. Based on recent data from the years 2017--2020, we model tails of the return distributions at different time scales by using power-law, stretched exponential, and q-Gaussian functions.",
    "1568535": "The one that includes COVID-19 is really interesting!",
    "1573608": "Why does everyone just hop to an LSTM, XGBoost, or LGBM lmaoo. Also, that is not how HFT prediction works and those papers are going to be wildly inaccurate. No, I will not elaborate! I want that prize money..."
  },
  "source": "meta"
}