There are 5,000+ equities to pick from listed on NYSE, Nasdaq, and 40,000+ public stocks worldwide. With more than 10,000 funds are fishing in the same pound, finding the right investment with a unique edge is critical for consistent outperformance in the market.
"Price is what you pay, value is what you get." As long as the price is right, an investment could always be turned into profits. Having a system which can identify trading opportunities and market timing is essential in staying ahead of other investors.
Modern Portfolio Theory gives guidance for portfolio optimization but is too rigid to deal with irregular market changes. Constructing a portfolio with appropriate diversification and risk control plays a key role in long-term return and survival in the investing arena.
You could use Kai Score as an alpha signal by adding Kai Score to your own quantitative model to increase stable excessive return and reduce risks.
Kai Score has been proven to be an effective approach to AI-powered investment research. You could discover stock winners and avoid stock losers with Kai Score.
You could build portfolio with Kai Score or use intelligent strategies built by Kavout directly. With market timing and risk control, portfolios built on Kai Score could generate consistent excessive return.
For individuals investors who want to use our Kai Score to pick stocks, please check out Our Showcase
Smart Advisor could engineer the risk and return in a portfolio to fit your unique investment preference and meet your expectation.
Smart Advisor utilizes an intelligent and quantitative focus on asset selection and risk control to enhance both consistent excessive return and comprehensive protection from downside risks.
With quantitative analytics and machine learning technology, Smart Advisor tracks a number of underlying factors to discover outperforming asset classes in the market.
RoboChartist watch the market 24-7 for you, so you could get a complete picture of the market and discover valuable trading opportunities. Now, you can shift from following the market and analyzing data to making smarter and faster trading decision with confidence and ease.
RoboChartist measures the quality of each pattern and make prediction based on its learning experience of massive amount of data and multi-dimensional technical analysis. You could use its ranking as reference to make informed decisions.
Our AI-powered analysis model provides both statistics of historical performance and predictive ranking of each price pattern. You can review up to 5 years of analysis of frequency and winning ratio based on Bayesian Network to understand each pattern more thoroughly.
We believe that the best way to analyze a complex system is to integrate machine learning and human expertise. An AI co-pilot could provide data-driven, objective and constant insights, while experienced analysts are better at providing granular insights. The human-machine collaboration could maximize efficiency and bring stunning performance.
Inspired by the brain's ability to learn, deep learning models have performed unparalleled results in a number of applications. As we expose the algorithms to more data, they learn from their successes and failures to evolve, adapt and provide solutions for some of the most formidable challenges.
We develop and scale advanced neural network technologies that could intelligently interpret massive amount of data sets at a unprecedented scale. As we direct the power of deep learning to investment management, every step of your investment will get smarter and more effective.
We combine advanced machine learning techniques with financial expertise to create investment strategies with consistent excessive return. The predictive models aggregate unstructured data sets and peel back the layers of extraneous information to make fast and accurate prediction.
Alex Lu has over 17 years of experience in deep learning, artificial intelligence, and big data technology. Before launching Kavout, Alex served as the CTO at one of China’s largest financial information provider, was an Engineering Director at Baidu, a VP of Search Technology at SNDA, a Principal Program Manager at Microsoft, and a senior engineer at Google. He graduated from Tsinghua University, has a Master’s in Computer Science from University of Maryland, and a MBA from Columbia Business School.
Barry Bernstein has over 15 years of international financial services experience. Barry was previously Chief Operating Officer and Chief Compliance Officer of AlgoPartners. Prior to this, Barry was at Neonet, a financial services and technology firm that was recently purchased by Knight Capital Group. His positions over the years included President, Chief Compliance Officer, Chief Operating Officer and Head of Technology. During his career, Barry earned the "Top Fifty Growth Company" award and rang the Nasdaq Stock Market opening bell.
Tim Leung is an Applied Math Professor, Computational Finance Program Director at University of Washington, and has over 14 years of experience in Quantitative Finance and Algorithmic Trading. Previously, his research has been funded by industry and the National Science Foundation (NSF), and published in dozens of journal articles. He has written two books on, respectively, Optimal Mean Reversion Trading and ETFs. He has served as the Chair for the Institute for Operations Research and Management Sciences (INFORMS) Finance Section. He obtained his BS from Cornell University and PhD from Princeton University.
|10/09/2017 | Kavout|
|05/11/2017 | Benzinga|
Additional information: Fincon Startup Pitch ; FinTech Competition Awards10/24/2016 | Finconmedia