{"title":"关于基本统计边缘原理","authors":"Tommaso Gastaldi","doi":"arxiv-2404.14252","DOIUrl":null,"url":null,"abstract":"This paper establishes that conditioning the probability of execution of new\norders on the self-generated historical trading information (HTI) of a trading\nstrategy is a necessary condition for a statistical trading edge. It is shown,\nin particular, that, given any trading strategy S that does not use its own\nHTI, it is always possible to construct a new strategy S* that yields a\nsystematically increasing improvement over S in terms of profit and loss (PnL)\nby using the self-generated HTI. This holds true under rather general\nconditions that are frequently met in practice, and it is proven through a\ndecision mechanism specifically designed to formally prove this idea.\nSimulations and real-world trading evidence are included for validation and\nillustration, respectively.","PeriodicalId":501045,"journal":{"name":"arXiv - QuantFin - Portfolio Management","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On a fundamental statistical edge principle\",\"authors\":\"Tommaso Gastaldi\",\"doi\":\"arxiv-2404.14252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper establishes that conditioning the probability of execution of new\\norders on the self-generated historical trading information (HTI) of a trading\\nstrategy is a necessary condition for a statistical trading edge. It is shown,\\nin particular, that, given any trading strategy S that does not use its own\\nHTI, it is always possible to construct a new strategy S* that yields a\\nsystematically increasing improvement over S in terms of profit and loss (PnL)\\nby using the self-generated HTI. This holds true under rather general\\nconditions that are frequently met in practice, and it is proven through a\\ndecision mechanism specifically designed to formally prove this idea.\\nSimulations and real-world trading evidence are included for validation and\\nillustration, respectively.\",\"PeriodicalId\":501045,\"journal\":{\"name\":\"arXiv - QuantFin - Portfolio Management\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Portfolio Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2404.14252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Portfolio Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2404.14252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本文证明,以交易策略的历史交易信息(HTI)作为新订单执行概率的条件,是统计交易优势的必要条件。本文特别指出,在给定任何不使用自身历史交易信息的交易策略 S 的情况下,总是有可能构建出一种新的策略 S*,通过使用自创的历史交易信息,在盈亏(PnL)方面比 S 得到系统性的提升。这一点在实践中经常遇到的一般条件下是成立的,并通过专门为正式证明这一观点而设计的决策机制得到了证明。模拟和实际交易证据分别用于验证和说明。
This paper establishes that conditioning the probability of execution of new
orders on the self-generated historical trading information (HTI) of a trading
strategy is a necessary condition for a statistical trading edge. It is shown,
in particular, that, given any trading strategy S that does not use its own
HTI, it is always possible to construct a new strategy S* that yields a
systematically increasing improvement over S in terms of profit and loss (PnL)
by using the self-generated HTI. This holds true under rather general
conditions that are frequently met in practice, and it is proven through a
decision mechanism specifically designed to formally prove this idea.
Simulations and real-world trading evidence are included for validation and
illustration, respectively.