Stay Ahead Of The Curve: AI Weekly. Algorithmic Trading with AI: Two Heads Better Than One S&P500 (^GSPC) and 10-year Treasuries will go down in a month’s time, Bloomberg reported in early July, citing a very unorthodox analyst. The forecast in question was delivered by an AI algorithm trained by JPMorgan Chase, one of the world’s top investment banks. This AI is just one of the many cases which highlight the interest that the big players have for the technology. As algorithmic trading becomes the word of the day, the giants seek to ride the AI tide. And at least one of their incentives for doing so is also relevant for retail traders. It sounds simple; in fact, it is a simple truth that greatly pre-dates the era of AI. What is it, you may ask? It’s just the good old two heads are better than one. And this is where AI market prediction tools come in. What they do is give the investor a way to cross-reference their own calculations by looking at the AI output and comparing it to their own plans. In terms of pure statistics, this gives them a better measure of certainty in their decisions. If a human analyst utilizing a strategy and an AI, both with known accuracy rates (through assessment of prior performance) converge in their assessment of a specific stock, it is reasonable to expect that the probability of its price following the predicted course is higher than for that on which AI and human analysts disagree.



Read more. AI-driven Algorithmic Trading: Self-Driving Car for Stock Markets



We have heard of a virtual car navigating a virtual city and learning from the process. Now, let us change gears a bit and envision something different. Instead of a city, our new algorithmic trading AI would navigate the stock market. First, we will train it on a historical dataset that would cover years worth of trading. In doing so, it would pick up the patterns in the data, learning the market behavior and training to predict its future swings. But that is not it: we will also use reinforcement learning in our design. How? The idea would be to make the algorithmic trading AI assess its own performance. Precision makes for an intuitively good point of reference here: if we want the AI to be able to predict the market dynamics, the correlation between its predictions and the actual price movements is a sensible measure of its success. From there, we follow pretty much the same logic. With new data coming in every day and a clear benchmark for measuring the performance, our algorithm will be able to not just predict the market dynamics, but also improve its own accuracy with every new forecast delivered. Read more.

How to Identify the Best Small Cap Stocks By Using Algorithms Small cap trading has 3 main benefits. The first is that there is huge growth potential. Everyone wants to invest in the next Apple or Microsoft and even those companies started out small. Likewise, the small cap stock that you invest in today could end up being a huge corporation and your investment could have a large payoff. The second benefit is that with small cap stocks, there are more opportunities for the private investor, as opposed to investment firms. Mutual funds are unlikely to invest in small cap stocks because the payoff is unlikely to alter their fund’s performance. This is due to SEC regulations that control how large of a position a mutual fund can hold in a company. Therefore, an individual investor has the potential to recognize and invest in a promising company before large investment firms invest and push up the price. Lastly, small cap stocks are often under-recognized. Because these companies are so small, they are often unheard of or not reported on and therefore may be improperly priced, with each share costing less than it should.



Despite all of these benefits, it is important to note that small cap stocks are much riskier and volatile than mid or large cap stocks. Additionally, there is much more research involved in the investment decisions that come along with small cap stocks being that there is little to no analyst coverage on them and ratios are often not reported so potential investors would have to do the tedious math themselves to make an educated decision. Read more. NVDA Stock Forecast: Nvidia Driving Profits in Q2 2019 Nvidia announced a partnership with Microsoft to give Minecraft a massive graphics overhaul. The chipmaker would bring support for “ray tracing” technology to “Minecraft.” Microsoft purchased “Minecraft” studio Mojang in 2014, and the game remains among the most popular in the world, with more than 91 million monthly users as of October. The addition of ray tracing serves as one of the game’s biggest updates since its release in May 2009. Ray tracing will first arrive on PCs equipped with Nvidia’s RTX graphics cards. In June, a new partnership with the Volvo Group to develop AI autonomous trucks was announced, utilizing NVIDIA’s end to end AI platform for training, simulation and in vehicle computing. The strategic partnership will enable Volvo Group to develop a wide range of autonomous driving solutions for freight transport, recycling collection, public transport, construction, mining, forestry and more. This collaboration is a great validation of Nvidia’s long-held position that every vehicle will have autonomous capability one day. Investors can expect growth in this area. Read more.

News Reel Hub Report: I Know First AI Algorithm Shows Up to 95% Accuracy on Predicting Facebook Price Movements The deep learning predictive AI algorithm developed by I Know First, a Fintech company that provides state of the art self-learning AI-based algorithmic stock market forecast solutions to uncover the best investment opportunities, has shown an accuracy of up to 95% in its predictions for Facebook (FB). That is according to a Facebook stock forecast evaluation report published by the company on August 25, 2019. The algorithm has demonstrated a higher accuracy rate for longer-term forecasts, as is often the case for predictive AI.



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Other Top I Know Evaluation Reports: Top ETFs Forecast Package : The top 5 predictability and signal filtered assets beat the benchmark in all time horizons, with the best outperformance being for the 2 weeks time horizon, where the top 5 assets beat the benchmark by over 87%

Russell 2000 Index Predictions : 91% Hit Ratio for 3-months time period for Russell 2000 predictions allowing our clients to be able to invest their money with significant less risk

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