Quant Hedge Fund: Why Hedge Funds Should Adapt AI Technology To Continue

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.

Quant Hedge Fund

The punches you miss are the ones that wear you out”. —Boxing trainer Angelo Dundee -The Intelligent Investor, by Benjamin Graham. Active Investors have over the past years been experiencing large losses, as a result of volatile markets and recent market bubbles. The losses result in human error, that greatly hurts returns. This article will explain how hedge funds and investors alike, should begin to utilize machine-learning AI algorithms in their trading strategies. Summary:
  • Background of Hedge Funds and their role in the market
  • Hedge fund and investor issues and how it affects the financial world today
  • Development of AI based algorithms and their advantages
  • I Know First Algorithm’s competitive advantages and usage in the market

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ETF Trading Strategies Based on I Know First’s Aggregated Algorithmic Forecasts

In the following article we update a set of ETF trading strategies based on I Know First’s aggregated investment signals for the individual stocks contained within the funds. In this article, the ETF forecast is generated by using a weighted aggregation of stock-level forecasts and the performance of this method is tested on the SPDR Sector ETFs. We show that these aggregated forecasts result in ETF Trading strategies which outperform the benchmark and present excellent performance and risk statistics.

Building an AI fund Using I Know First’s Algorithmic Investment Signals

In the following article we update the performance of mid-term oriented algorithmic trading strategies built on I Know First’s AI-based forecasting signals geared at collaborations with institutional investors to bring an AI fund to the marketplace.

Stock Market Forecast: Chaos Theory Revealing How the Market Works

I Know First Research | May 8th 2014

How Can We Predict the Financial Markets by Using Algorithms? Common fallacies about markets claim markets are unpredictable. However, chaos theory together with powerful algorithms proves such statements are wrong. Markets are chaotic systems with complex dynamics, yet to a certain extent we can make valid stock market forecasts. Using these forecasts generated by cutting-edge predictive algorithms together with a careful risk management strategy may give a trader a significant competitive advantage.

Markets Are Complex Systems

Looking at the common fallacies about stock markets, we can see two major groups. The first group is connected to the classical economic theory, which claims that markets are 100% efficient, and as such unpredictable. However, trying to make predictions regarding the markets is useless anyway, as no stock can be possibly be a better deal than another. Both of them are efficient and everybody in the market has perfect information available to them. From our daily lives it is obvious that this does not truly reflect reality. There are people who actually profit trading stocks, which should not be possible in this idealistic market of economy theories.

Micron Stock Forecast: Micron (MU) Shares Show Consistent Algorithm Results

This article was written by Esther Hanon, a Financial Analyst at I Know First

“I can’t change the direction of the wind, but I can adjust my sails to always reach my destination”

—Jimmy Dean

Summary:­­­­

  • Memory-chip maker Micron Technology continued its skyward climb, following a breakout last week
  • Micron shares jumped 8.8% to close at 59.37 on the stock market on Monday, March 12 Micron stock broke out of a 14-week consolidation period with a buy point of 49.99 on March 5th.
  • Analysts are maintaining its outperform rating while many others are shifting towards a buy rating in the recent days.
  • Catalysts for Micron stock include higher DRAM chip pricing, margin expansion in NAND chips, and expectations for increased capital returns. Micron can also be an acquisition target as chip-industry merger activity intensifies.

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S&P 500 Forecast Based On AI: SPY Trading Strategies based on I Know First’s algorithmic signals

In the following article we analyze the performance of SPY trading strategies developed using I Know First’s stock market forecasts. We show different ways such strategies can be built using the algorithmic forecasts and that they result in ETF portfolios with excellent performance and risk statistics.

ETF Predictions Based Trading Strategies Using I Know First’s Aggregated ETF Forecast

We continue our series of articles analyzing the performance of ETF predictions computed by aggregating I Know First’s algorithmic forecasts for the individual stocks contained within the funds. In this article, a new method to generate an ETF forecast by using a weighted aggregation of stock-level predictions is presented and the performance of this method is tested using Sector ETFs. We show that the computed ETF predictions result in strategies which outperform the benchmark and present excellent performance and risk statistics both on an individual ETF level and for portfolios of ETFs.
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