Machine Learning Hedge Funds: How AI Can Help Bolster Returns

Today, there are upwards of 10,000 hedge funds that are managing an estimated $3 trillion in assets. Hedge fund managers look at market data in two different ways. There are funds that are run using fundamental analysis and there are funds that are run based on quantitative analysis. The fundamental analysis aims to use market research on the value of different securities and determine which assets are “undervalued” and “overvalued”. Conversely, quantitative analysis involves the use of complex mathematical formulas and computer models to create time-series models of the market in order to identify ideal short and long-term positions on different assets.



Because of a lack of regulations from the SEC, it is unclear to investors how their money is being investors. However, companies like

I Know First

are breaking into the industry to provide this kind of technology to investors that can’t access it otherwise. This includes hedge funds and individual investors that are not a part of a large trading firms, as well. I Know First has a uniquely

customizable solution for hedge funds

that enables the fund manager to choose their preferred parameters.

NVDA Stock Forecast: Is Nvidia's Growth Sustainable?

Nvidia’s Q2 revenue reached $3.12 billion, up 40% from a year earlier and higher than the projected amount. Surprisingly, after the Q2 earnings announcement where Nvidia announced the new Turing developments, its shares dropped -8%. This caught investors off guard because Nvidia Q2 ER beat both revenue and EPS estimates. It was mostly because of the lower Q3 guidance despite high R&D fundings that went into developing Turing. The demand and adoption of these cards matter because Nvidia already has very high growth in the Gaming segment. For it to grow even more at the YoY pace of 52% and 57%, Turing needs to be something enthusiasts and professionals adopt.



However, following a SWOT analysis, it is clear NVDA has both short term and long term growth potential. Demand in the growing gaming industry will likely support continued growth. Other areas like AI technology and self-driving cars are much more forward-looking and would take many years to establish a strong customer base. At the moment, given high confidence in the new GeForce GTX 1180 and Turing, the new GPU generation should boost the continuing growth.

Winning AMD Forecast: Chip Market Continues To Surge The Market

The same outperformance can be seen for EPYC against the likes of Intel’s Xeon, and notably so. Since AMD’s launch of EPYC processors last year, they have gradually gained share within the server market space. They are also set to launch next-generation 7 nanometer products soon, well ahead of their competitors which aren’t scheduled to drop until 2020. This gives AMD a window to take a hold of even more market share in the coming year. Their avoidance of certain security issues that have hit competitors in recent moths may have been yet another factor in their recent uprise. Ryzen and EPYC, which brought this company back to life, are getting a ramp, which should be a good sign to shareholders.



I Know First was one of the first to give AMD a bullish outlook via our stock forecasting algorithm. On June 10 we publish this bullish outlook for AMD detailing 3 driving forces for this bullish outlook



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I Know First Forecast Evaluation: MSCI Stock Universe

In this article, we analyze the performance of I Know First’s AI Algorithm from the MSCI index universe for the period from January 1, 2018 to August 24, 2018. Based on the presented observations we record significant out-performance of the Top 30 stocks filtered by predictability for all time horizons for the considered asset universe, even without filtering by signal strength.



Applying our predictability indicator as an investment criterion coupled with filtering by our signal strength, results in even greater out-performance over the benchmarks comprised of stocks from the MSCI index and the ACWI stocks universe in general. Therefore, an investor who wants to critically improve the structure of his investments by adding stocks being traded on emerging markets to his portfolio can do so by simultaneously utilizing the I Know First predictability and signal indicators as criteria for picking stocks.



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Business Strategy and Machine Learning In The Financial Industry

Machine Learning in genera

l

is algorithmic based and utilizing the concept of self-learning, being able to learn from large amounts of data (without relying on specific rules). Thanks to cheap computer power and the digitalization era, scientists were able to adapt this with more ease.

Overall, Machine Learning can add significant competitive advantages to businesses’’ strategies if implemented correctly, especially in the financial industry. Originally, the inputs that Machine Learning carried were for structured data, Deep Learning Techniques were adapted so that businesses could begin to analyze unstructured data. In the financial industry, for these programs to accurately analyze the data with high-quality outputs, they need to be able to adapt to unstructured data.



However, if a firm simply adapts a specific program without setting aside a specific goal for it or merging the program into its business strategy, there is a huge risk the firm will lose the long-term value of the program and rather be used for a short-term gain i.e. customer retention. Deep Learning techniques have allowed banks to further excel in the adaptation of Machine Learning in many fields.



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