# Advances in Financial Machine Learning ### Chapter 1 #### Factory Plan > "This book outlines the factory plan, where teamwork yields discoveries at a predictable rate, with no reliance on lucky strikes. This is how Berkeley Lab and other U.S. National Laboratories routinely make scientific discoveries, such as adding 16 elements to the periodic table, or laying out the groundwork for MRIs and PET scans. 1 No particular individual is responsible for these discoveries, as they are the outcome of team efforts where everyone contributes. Of course, setting up these financial laboratories takes time, and requires people who know what they are doing and have done it before." pg 5 ### Stations (roles) 1. Data Curators 2. Feature Analysts 3. Strategists 4. Backtesters 5. Deployment Team 6. Portfolio Oversight 1. Embargo phase 2. Paper trading 3. Graduation (production) 4. Reallocation 5. Decommission ### Meta Strategies > Problem: Amateurs develop individual strategies, believing that there is such a thing as a magical formula for riches. In contrast, professionals develop methods to mass-produce strategies. The money is not in making a car, it is in making a car factory. > > Your goal is to run a research lab like a factory, where true discoveries are not born out of inspiration, but out of methodic hard work. ### Overfitting > Problem: Standard cross-validation methods fail in finance. Most discoveries in finance are false, due to multiple testing and selection bias. > > Solution: Whatever you do, always ask yourself in what way you may be overfitting. Be skeptical about your own work, and constantly challenge yourself to prove that you are adding value. no one knows how to predict the real time (just look at the day ahead! It's all over the place)