While generative AI is capturing most of the public’s attention today, rocket scientists have used machine learning to plan launches for many years. The solar system is complex, dynamic, and challenging to predict. If, for example, you are trying to launch a probe from Earth to peer below Jupiter’s dense clouds and observe the gas giant for the first time, as Professor Mike Hobson and his team did in 2016 with NASA’s Juno probe, you will need to take into consideration millions of data points and variables for the mission to be a success.
As Mahmood Noorani, CEO of Quant Insight, a quantitative macro analysis firm, described it: “When you are dealing with rocket missions, it is not about finding a single point in time to launch the rocket; it is about finding the optimal launch window.”
In this webinar, Professor Mike Hobson and Mahmood Noorani will discuss how they took rocket launch calculations and applied them to the stock market, allowing them to calculate “alpha windows”. They will also discuss why the China A-Share market is an ideal environment for an AI-powered machine learning strategy to be successful. KraneShares Investment Strategist Henry Greene will also provide an update on China’s capital markets.
What we will cover:
The link between astrophysics and AI-powered investing How using AI & machine learning to power investment decisions may benefit portfolios Why we believe China's A-Shares market may be best-suited to this strategy Overview of the KraneShares China Alpha Index ETF (Ticker: KCAI) Comprehensive Q&A
For KCAI standard performance, top 10 holdings, risks, and other fund information, please visit https://kraneshares.com/kcai.
This material contains the speakers’ opinions. It should not be regarded as investment advice or a recommendation of specific securities. Holdings are subject to change. Securities mentioned do not make up the entire portfolio and, in the aggregate, may represent a small percentage of the fund.
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