I Know First Review: Getting to Know I Know First

taliTali Soroker is a Financial Analyst at I Know First.

 

I Know First Review: Getting to Know I Know First

Summary

  • Intro to I Know First
  • About our team members
  • More about the algorithm
  • Who are our clients?
  • Quick glance into algorithmic trading strategies

About The Company

I Know First is a financial tech start-up that provides daily investment forecasts based on a state of the art machine-learning algorithm. The technology behind the algorithmic system is based on artificial intelligence and deep learning, incorporating elements of artificial neural networks and genetic algorithms. It was developed to analyze and predict financial markets to be used to discover new investment opportunities or to be integrated an existing investment process. The company offers a subscription-based service to its clients, with investors receiving forecasts from relevant packages before the market opens each day.

I Know First

About the Team

I Know First’s head of R&D is our CTO and Co-Founder, Dr. Lipa Roitman. Dr. Roitman earned his Ph.D. from the Weizmann Institute of Science and has more than 20 years of research and experience in artificial intelligence and machine-learning fields. The concept behind I Know First’s algorithmic system has crystallized as a result of his years of prior research into the inherent qualities of chaotic systems. The R&D team is a group of dedicated professionals with backgrounds in computer science, applied mathematics, and finance.

Our operations team is led by CEO and Co-Founder, Yaron Golgher, who has 15 years of experience in leading and managing projects for innovative costing, budgeting, and planning systems in industrial and financial institutions. He received his Bachelor of Science in Industrial Engineering from Tel Aviv University and his EMBA from Ben Gurion University.

About the Algorithm

I Know First’s algorithm analyzes, models and predicts over 3,000 securities, and identifies the best daily opportunities in the market in accordance with investor preferences. The system utilizes artificial intelligence and machine learning with artificial neural networks and genetic algorithms to evolve each day as new data comes in. The algorithm is self-learning, and thus adaptable to new market conditions, as well as scalable, meaning that additional markets can be integrated into the system.

The algorithm has the unique ability to create, modify, and delete relationships between financial assets and markets. Forecasts are then derived from recognized patterns within the 15-year history of market data, with more weight on the most recent data. With the algorithm’s ability to learn from each forecast and to adapt previously determined relationships, it adjusts quickly to changing market circumstances. The system is 100% empirical, and is derived entirely from historical data and does not rely on any human assumptions or written “rules”. It separates the predictable information from “random noise” generated within the markets and then models the future arc of the given market.

I Know First

Projections of security trends are outputted as a number, positive or negative, called the signal. The signal indicates both the direction and the magnitude of the asset’s predicted trend. In addition to the asset’s signal, the algorithmic forecast also includes a number representing predictability. The predictability is the fitness function of the algorithm; this correlation-based quality measure of the signal is useful in seeing the likelihood that the prediction will be correct. The predictability is useful in separating predictable markets and securities from those that are unpredictable in order to focus the investment process.

I Know First

Algorithmic forecasts are produced daily and each package consists of 6 time horizons. Investors receive daily forecasts for 3 day, 7 day, 14 day, 1 month, 3 month, and 1 year periods. Depending on the package, algorithmic forecasts can include stocks (both U.S. and international), world indices, ETFs/funds, interest rates, and more.

About Our Clients

Until recently, the only people on Wall Street that had access to predictive algorithmic technology were those at large hedge funds and investment banks. Now, I Know First is introducing the machine-learning algorithm to retail clients as well. The company services and collaborates with family offices, wealth management companies, investment managers, and financial advisors, in addition to private investors.

Clients subscribe to forecast packages that are filtered by criteria such as asset class, sector or industry, local markets/exchanges, market capitalization, and dividend paying stocks. For example, investors interested in the energy sector have a package suited to their specific investing needs. Other filtering criteria used to identify market opportunities include fundamental key ratios such as P/E ratios and EPS growth. These filters can also be further customized for our institutional clients.

i know first

For institutional clients, I Know First has specialized solutions and is able to create customized filters to tailor predictive solutions to the client’s investment focus. There are individual approaches that are customizable for hedge funds, financial advisors, family offices, and other wealth management companies specifically and the R&D team also recently introduced the new What-If Scenario analysis tool for institutional investors. The What-If Scenarios tool can be used to simulate various market conditions in order to analyze potential results of actions made by public policy makers and other key market players.

About Different Investment Approaches

Systematic Trading

Investors use computer models and systems that focus mainly on performing technical analysis of market data. The system is used to identify market opportunities, and in some cases make trades, with little intervention. With I Know First’s systematic trading system, assets are assigned signals by the algorithm along with a unique predictability indicator. Investors can use these in combination to determine which stocks and assets are promising in either the long position or the short position.

i know first

Below is a chart of I Know First’s recent performance for short-term trading strategies compared with the performance of the S&P 500. Read more about I Know First’s recent performance by clicking here or by clicking on the photo below.

i know first

Bottom-Up Approach

In a bottom-up investing approach, the analysis is focused on individual stocks. Investors perform fundamental analysis on individual companies and stocks to determine if the given company is strong and if it’s stock is likely to see future growth. I Know First’s algorithmic solutions can be integrated into this approach by targeting additional investment opportunities and/or by performing algorithmic screening in parallel to the investor’s own analysis. For example, the Fundamentals package includes predictions for companies screened with respect to specific fundamental key ratios which can be specified by the investor/client.

Top-Down Approach

For other investors, a top-down investment approach is more suitable. In this approach, analysis examines the economy as a whole to determine which sector/industry is likely to see the most growth. Once an industry is selected, top companies for the industry are examined. Investors engaging in the top-down approach also use ByIndustry merged forecasts and World Indices forecasts within the first steps of the approach, then individual sector/industry packages such as the Energy, Biotech, and Basic Industry Stocks to go deeper. Once the most promising industries are identified, investors can focus on those sub-universes by integrating individual stock forecasts into their decision-making process in term of investments.

I Know First

Getting to Know I Know First – Presentation

[slideshare id=62997071&doc=iknowfirstpresentation-160613082512]

 


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