I Know First Live Forecast Evaluation for Eastern Markets Based On New Global Volatility Adjusted Approach

Executive Summary

As of December 2018, I Know First finished a performance evaluation of the live AI-based predictive forecasts for the new East stock strategy sent to customers. This evaluation clearly demonstrates the consistent out-performance of I Know First’s forecasts vs. the entirety of stocks within the East Market. The East Market is comprised of stocks in Eastern countries such as China, Japan, Australia, and New Zealand. This evaluation is part of our continuous studies of live I Know First’s AI predictive algorithm performance.

East Market Highlights:

  • Selecting the East Market stocks with the top 5 signal adjusted strength provides the highest return consistently beating other filters for each time horizon with the exception of the top 10 signal, which provide the highest return for the 3-month time horizon
  • There is a clear correlation between the length of the time horizon and the return as the length increases the accuracy and performance of the I Know First algorithm dramatically improves
  • For the 3-day, 1-week, 2-week, 1-month, and 3-month time horizons all signal filters outperform the benchmark with the top 10 signal on the 3-month horizon providing the largest return of 13.88%

Evaluation Period and Universe

In this Live Forecast Evaluation Report, we will examine the performance

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Day Trading Strategy: An In-depth Analysis of Realistic Back-Tests

Daniel Tal is a Quantitative Analyst at I Know First. He is currently a candidate for his bachelor's degree in Computer Science and Business Management at Columbia University.

  • Implementation of IKF strategy in intraday trading environment
  • Quantopian slippage and commissions models used to simulate real-time trading
  • Data and statistical Analysis of the methods used to gain day trading returns

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Artificial Intelligence Stock Market: Algorithmic Analysis of Humans and Their Behavior

taliTali Soroker is a Financial Analyst at I Know First.
  • Algorithms are being used every day to analyze human behavior and decision-making
  • Companies use these algorithms to reach relevant customers and expand their reach
  • AI could prove to be beneficial to employers seeking a diverse and successful company
  • Using Algorithms to analyze human thought process can help investors make profitable stock trades
  • Companies are using AI and algorithmic systems to analyze human behavior in the stock market to make accurate forecasts of stock trends

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Deep Learning Finance: Artificial Neural Networks, Deep Learning and Applications of Deep Learning in Finance

taliTali Soroker is a Financial Analyst at I Know First. She holds a B.S. Mathematics from Northeastern University

Deep Learning Finance

  • Artificial Neural Networks Overview
  • ANNs Vs. Conventional Computing
  • Structure and Backpropagation
  • Deep Learning
  • Applications in Finance and Other Areas

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Algorithmic Trading: Machines Account for Upwards of 80% of Trades in the USA

Algorithmic Trading:

“Eighty percent of daily volume in the U.S. is done by machines” - Guy De Blonay, fund manager at Jupiter Asset Management


  • New long-term strategies are being built around algorithmic trading and machine trading is now slowly eating further into long term investments.
  • The volume of trades in the USA done by machines can be up to 80% according to recent claims.
  • Blackrock are set to give a number of their financial analysts the boot in favour of a more updated trading strategy that draws on machines and Artificial Intelligence.
  • I Know First’s state of the art algorithm, uses Artificial Intelligence and self-learning capabilities to predict asset price movements in the market today.

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Algorithmic Trading With I Know First Versus High Frequency Trading

Algorithmic Trading

Competition between investment firms is more intense than ever before as firms are expected to be able to beat the S&P 500 on a regular basis to retain and attract new investors. The market is evolving beyond previously established theories however investors still expect strong and consistent returns. Traditional tools and fundamental analysis are no longer enough to stay competitive in the contemporary market. Investment firms need to stay one step ahead in order to be the first to recognize trends and take advantage of opportunities. To stay competitive they are looking to employ the most advanced tools to enhance performance. Algorithmic trading is now a growing trend filling this void. Algorithmic “Buy” and “Sell” orders account for 60%-70% of the US equity market volume. Previously, only large investment firms and hedge funds were able to utilize these advanced mathematical models but I Know First: Daily Market Forecast, a financial start-up, has developed an advanced self-learning algorithm that is being employed by professionals and retail investors alike.

Stock Filtering by the I Know First Signal and Predictability Indicators

Dario Biasini is a Research Analyst at I Know First.

We expand on research performed in previous articles by further exploring the effect and interpretation of the I Know First prediction measures and how these can be used for stock filtering. We show that as predictability and signal strength increase the average trade returns based on these indicators grow in a consistent, significant, and robust manner and that by daily selecting stocks with the highest predictabilities and signals average returns significantly above those of S&P500 Index can be achieved.
  • Analysis of the Returns Generated by Filtering S&P500 Stocks using the I Know First Signal and Predictability Indicators
  • Comparison of the Compounded Returns Generated by using the I Know First Signal and Predictability Indicators against those of the whole S&P500 Stock Universe

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