{
  "annotation_id": "35743684-8707-4352-911a-7af6e93ddf2f",
  "date_created": "2026-03-02T18:00:56.379000Z",
  "date_modified": "2026-03-02T18:00:56.379000Z",
  "file_hash": "f3471845ca1ab9ab369b503f0d1a0e13e3a48a36f1f7edc041105d232dc15708",
  "private": false,
  "record": {
    "abstract": "Automated trading systems on developed and emerging capital markets are\nstudied in this paper. The standard for developed market is automated trading\nsystem with 40-days simple moving average. We tested it for the index SIX\nIndustrial for 1000 and 730 trading days of the slovak emerging capital market.\nThe Buy and Hold trading system was 7.80 times more profitable than this etalon\ntrading system for active trading. Taking of profitable standard trading system\nfrom a developed capital market does not lead to optimal results on the\nemerging capital markets. We then studied optimized standard trading system\nbased on the simple moving average. The parameter of optimization was the\nnumber of weeks. An optimal system was that with 5 weeks. This trading system\nhas some of its characteristics comparable with the etalon trading system on\nthe NYSE Composite Index. The emerging market is more risky than the developed\nmarket. The profit on the emerging market is also higher. The range of\noptimized system parameter is quite robust. Observed was increase of number of\ntrades in the range from the 21 weeks to the 25 weeks. This indicates creation\nof a new optimal middle range trading system. Results of testing for liquid\nshares are quantitatively similar.",
    "arxiv_id": "physics/0505032",
    "authors": [
      "Ondrej Hudak",
      "Jana Tothova"
    ],
    "categories": [
      "physics.soc-ph",
      "physics.data-an",
      "q-fin.TR"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "Automated Trading Systems: Developed and Emerging Capital Markets",
    "url": "https://arxiv.org/abs/physics/0505032"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "7aa254cc-961a-421a-a696-b48e1c2e6687",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}