All That Glitters Is Not Gold: Comparing Backtest and Out-of-Sample Performance on a Large Cohort of Trading Algorithms-Reference-Cited by-同舟云学术

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All That Glitters Is Not Gold: Comparing Backtest and Out-of-Sample Performance on a Large Cohort of Trading Algorithms

Published:2016-08-31 Issue:3 Volume:25 Page:69-80
ISSN:1068-0896
Container-title:The Journal of Investing
language:en
Short-container-title:JOI

Author:

Wiecki Thomas,Campbell Andrew,Lent Justin,Stauth Jessica

Publisher

Pageant Media US

Subject

Management of Technology and Innovation,Strategy and Management,Finance

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Mean Absolute Directional Loss as a new loss function for machine learning problems in algorithmic investment strategies;Journal of Computational Science;2024-09

2. Open Innovation in Hedge Funds: Collective Intelligence Investing Using Crowdsourcing;SSRN Electronic Journal;2024

3. A discussion paper for possible approaches to building a statistically valid backtesting framework;2024

4. Mean Absolute Directional Loss as a New Loss Function for Machine Learning Problems in Algorithmic Investment Strategies;SSRN Electronic Journal;2023

5. Ensembling Arimax Model in Algorithmic Investment Strategies on Commodities Market;SSRN Electronic Journal;2023

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