Trade Smartly in the Fractal Stock Market with Machine Learning Power

motek 1This algorithmic article was written by Yutong Li – Analyst at I Know First, Master's candidate at Brandeis University.

Highlights:

  • Although Efficient Market Hypothesis has been a dominated financial theory for years, it fails to give a sensible reason and interpretation of the financial crashes and crises that occurred
  • A more comprehensive financial theory - Fractal Market Hypothesis is capable to explain these crises and provide a clear-cut description of the financial markets
  • Fractal Market Hypothesis puts forward the idea of self-similarity and stability in the market when it consists of investors from a wide range of investment horizons
  • FMH verifies the root of technical analysis under the idea that history can repeat, and this process of pattern-finding can be efficiently attained by machine learning

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The AI Book: Featuring I Know First’s Yaron Golgher, Dr. Lipa Roitman, and Denis Khoronenko

On December 30, 2019, I Know First published an article covering the continued work of the I Know Firsts team, Yaron Golgher, Dr. Lipa Roitman, and Denic Khoronenko, as they write a chapter to be published in The AI Book. This book aggregates multiple expertise through crowd-sourced experts into a uniform volume that enforces the significance of artificial intelligence and how it can be utilized amongst financial services. 

With great pleasure, we can announce the chapter titled “Finding Order In The Chaos: Investment Selection Using AI” has been published alongside various prominent

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Why Artificial Intelligence Will Always Beat the Market

motek 1This algorithmic article was written by Yutong Li – Analyst at I Know First, Master's candidate at Brandeis University.

Highlights:

  • Despite the controversial opinion on whether Artificial Intelligence could beat the market, AI could still win in many aspects
  • I Know First’s proprietary AI-powered algorithm can make accurate predictions and smartly approach the stock market uncertainty
  • Based on the 1-year evaluation summary, I Know First has predicted ^IXIC, SPY, and QQQ with 100% accuracy in a 1-year time horizon, and has a performance over 62% for for all time horizons

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In The News: Eduonix Article Features I Know First AI Predictive Algorithm

EDUONIX | LinkedIn
(Source: Edunix.Com)

An article on Eduonix Blog featured I Know First’s AI-powered predictive algorithm. The blog is owned by Eduonix learning Solutions Ltd, which is the premier training and skill development organization. It was started with a vision to bring world class training content, pedagogy and best learning practices to everyone’s doorsteps.

In this article, the author discusses methods to predict the stock market with artificial intelligence and machine learning. He gives I Know First as an example for that. The author features our stock market predictive algorithm and mentions the concept behind

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Making Sense of the Chaos: How Algorithmic Trading Increases Investor Returns

The article was written by Jessica Kremer - Analyst at I Know First.

Summary:

  • Human investors are prone to judgment errors while investing in the stock market.
  • Chaos theory allows I Know First to use artificial intelligence and a self learning algorithm to correctly model and predict the stock market.
  • There are multiple instances where chaos theory has enabled our algorithm to make correct decisions while other investors made losses. 

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Unpacking the Ins and Outs of a Chaotic System – How Can We Predict it

I Know First Research Team LogoThis article was written by the I Know First Research Team.

Summary:

  • What is Chaos Theory?
  • Earthquakes – An example of a Natural Chaotic System
  • Randomness vs Chaos 
  • What makes a Chaotic System a Chaotic System
  • Modeling a Chaotic System
  • Can We Really Predict the Stock Market? Psychology of Trading and Feedback Loops

What is Chaos Theory?

Source: Medium

In a chaotic system like weather, a tiny change can make a huge impact. Weather is predicted a few days in advance because small changes in input can produce dramatically different results. 

The most commonly used example to explain chaos theory is the butterfly effect. It says that a butterfly flapping its wings on one end of the world can give rise to a hurricane in another part of the world. It sounds bizarre but it illustrates the huge impact small changes in the factors can have on the outcome. 

Without going into too much mathematical details, I would like to briefly explain how

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