Five WealthTech Companies That You Should Know About

Five WealthTech Companies That You Should Know About

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The traditional understanding of what a financial institution does and the function it serves in wealth management is undoubtedly changing. In a modern landscape with data, AI and machine learning meeting with your portfolio manager on a regular basis seems a little too ‘old school’ and even time consuming. Along comes WealthTech companies that provide a holistic restructuring of traditional wealth management.

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Quantum Trading: Econophysics Can Help Predict Financial Markets

dr roitmanThis article was co-authored by Dr. Roitman, Co-Founder & CTO of I Know First Ltd. With over 35 years of research in AI and machine learning. Dr. Roitman earned a Ph.D  from the Weizmann Institute of Science.


This article was co-authored by David Shabotinsky, a Financial Analyst at I Know First, and enrolled at an undergraduate Finance program at the Interdisciplinary Center, Herzliya.  

Quantum Trading

Summary:
  • How Econophysics has shaped to become an important field of study for financial markets and policy makers
  • The uncertainty principle and how its used to predict the financial markets, such as bear and bull markets
  • What is phase transition in physics and how can it be applied to the financial market
  • Real applications of Econophysics in finance and policy making today
  • I Know First's self-learning predictive algorithm and its application of phase transition
  • Real differentiated competitive advantages offered by I Know First's algorithmic solutions

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Machine Learning Trading, Stock Market, and Chaos

taliTali Soroker is a Financial Analyst at I Know First.


Summary
  • There is a notable difference between chaos and randomness making chaotic systems predictable, while random ones are not
  • Modeling chaotic processes are possible using statistics, but it is extremely difficult
  • Machine learning can be used to model chaotic processes more effectively
  • I Know First has employed artificial intelligence and machine learning in order to make predictions in the stock market
  • Definitions for underlined words can be found in the Glossary at the end of the article

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Portfolio Strategies & Asset Allocation – 86.43% Expected Annual Return Using Algorithmic Allocation

 Summary
  • How to use an existing algorithmic signals system to allocate equity systematically.logo1
  • Building a sample portfolio based on stocks, interest rates and currencies.
  • Actual portfolio back test and returns.
Introduction:  Allocating your portfolio in a way that maximizes returns and minimizes risk can be tricky. In order to reduce volatility, high yield strategies are often ignored. In theory, if you were able to pick one stock a day you were most certain will go up - in order to maximize expected returns you would only invest in that stock. The downside of course is also maximizing your risk exposure.In this article I will go through a method of allocating funds using the I Know First artificial intelligence system. This will link between algorithmic signals, and actual market buy/sell decisions. Before you continue reading you should decide if any of these points don’t suit you well. The main advantage of this portfolio allocation is that it is a day trading model which is 100% systematic. Both the investment buy/sell decisions and allocation are based off the signal data; allowing any investor the peace of mind in separating emotion from trade decisions.

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Guide to Automated Trading Using Quant Platforms and I Know First Algorithmic signals: 48% Annual Return

This guide will cover how to begin designing a strategy using an open source quant platform (QuantConnect), which you can then use to design your algorithm and eventually execute it in live paper trading or real money trading in just a click. I will also share a large data set of historical picks based on the I Know first “Top 10 Stock Picks + S&P500” which you can use free of charge for back testing. Automated Trading

3 Ways To Cluster Data Using Unsupervised Learning

  This article was written by Julia Masch, a Financial Analyst at I Know First.



 

Highlights:

  • Understanding Unsupervised Learning
  • Types of Clustering and How To Implement Them
  • How I Know First Uses Clustering

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Arbitrage Trading: How Hedge Funds Should Use AI Based Algorithms For Arbitrage Trading

The article was written by David Shabotinsky, a Financial Analyst at I Know First, and enrolled at an undergraduate Finance program at the Interdisciplinary Center, Herzliya.

Arbitrage Trading

All things excellent are as difficult as they are rare.”-Benjamin Graham, The Intelligent Investor Free lunch, or riskless profit. The idea seems theoretically impossible, as any intro economics course will explain that free lunch is impossible. This article will come to explain; why seemingly riskless strategies should incorporate AI based algorithms. Summary:
  • Arbitrage opportunities are hard to locate but knowing which types exist can help investors watch for them
  • Hedge Funds today too many errors for the high costs that accompany them
  • I Know First Algorithm’s competitive advantages and usage in the market can subsitute/assist hedge funds
  • Barrier of entry for algorithmic trading firms

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