Tesla Stock Forecast: A Future Tailwind From Electric Motorcycles

Tesla remains the leader in electric car sales in the United States. Two or three years from now, Tesla may also take over the electric motorcycle industry. There are much more affordable alternative to the Model 3 but Tesla’s brand power made it sell a lot more units than the Chevrolet Bolt and Nissan Leaf. Right now, car vendor Honda is selling more than 19 million units of regular motorcycles per year and Honda has upcoming electric motorcycles. However, Tesla brand power should extend into the electric motorcycle market too.



More than 130 million units of motorcycles are sold annually. Almost 109 million of them sold in the Asia Pacific Region. It is faster to assemble Tesla electric motorcycles than cars and trucks. Tesla can improve its bottom line by the quicker turnaround of selling motorcycles. TSLA has a very bullish one-year forecast from I Know First. It might be wise to load up on this stock while it trades below $370.

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SPY Trading Strategies Based On I Know First's Algorithmic Signals

I Know First employs a variety of trading strategies to maximize growth. In this article, we analyze the performance of SPY trading strategies developed using several ways of computing an S&P 500 forecast using I Know First’s daily market predictions. 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.



We focus on 3 different strategies that you can personalize: direst, weighted, aggregation, and a combination. All of I Know First’s SPY trading strategies significantly outperform the benchmark in terms of risk adjusted return (Sharpe Ratios up to 2.0 versus the benchmark’s 1.3) and register very strong alpha and beta statistics (annualized alpha up to 8.4% and betas around 0.5). Using these strategies can help you beat the benchmark!

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Treasury Yield Curves: An Indicator Of Economic Health

For a long time, yield curves have been a hot topic in the financial world. Many believe they are a good signal of a country's economic health. However, how each stock response to the changes in interest rate and the movement of the yield curve is still a big question that many human investors struggle with. I Know First has successfully built an Artificial Intelligence algorithm that factors yield curve and its relationship with other economic indicators to forecast the market movement. In this article, we discuss how to use yield curve as a market prediction indicator as well as how I Know First algorithms factor it.



So what even is a yield curve? A yield curve is a graphical depiction showing different interest rates or yields for different time periods ranging from 1 month to 30 years. Yield curves reflect the relationship between the yield of the interest rate on bonds and its maturity. Yield curves play an important role in the economy as a benchmark for bond pricing and standard yield for other bond sectors such as bank loans or corporate debt.



As we understand more about the yield curve, the question now is how to interpret the shape and movement of yield curves to predict the health of the economy. Over the last 50 years, the yield curve has proved itself as a good prediction indicator of an incoming financial crisis. A financial crisis normally follows an inverted yield curve. The last two times we saw an inverted yield curve is in 2000, right before the dot-com bubble burst, and 2007, right before the global financial crisis. To learn about the 4 types of yield curve, the type of stocks most affected by yield curve changes, and how I Know First algorithm implements yield curves in its forecast:

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Machine Learning Trading, Stock Market, and Chaos

Have you ever wondered how the I Know First Algorithm is so accurate when there's so many seemingly random and chaotic events happening all the time in the stock market? Well, the first thing to understand is there's a key difference between random and chaotic events. There is a notable difference between chaos and randomness making chaotic systems predictable, while random ones are not. Real world processes may seem random to the untrained eye, but upon closer examination, we see that such processes are in fact chaotic. Natural processes such as seismic events, population growth, and stock markets are all examples of such systems and can be predicted with reasonable accuracy. Chaotic processes are controlled by three competing paradigms: Stability, Memory, and Sudden and Drastic Change.



Stability is seen in the stock market as a stock trend either increases or decreases. While the share price of the stock changes over the given time period, the trend is unchanging. There is also a degree of instability here because of what is called a “tired trend.” As a stock is rising and continues to rise, there comes a point when investors start to question how long the trend can continue as it has. As people begin to lose confidence in the trend the stability decreases. Memory is the influence that past events have on a current trend. A stock that has been known to rise will likely continue to do so. Drastic and unforeseen changes can also occur, completely reversing a trend with little or no warning. Black Swan events, as they are referred to, are themselves unpredictable but are useful in making future predictions. The cycles of rising and falling trends that occur in chaotic processes have varying time periods, quiet periods can be followed by a large jump or vice versa. Together, these properties of chaotic processes make it possible to make predictions about the system using probability.

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How AI and I Know First Directly Impact Capital Market Forecasting





I Know First’s algorithm generates short, medium and long term daily market predictions for stocks, commodities, ETF’s, interest rates, currencies, and world indices for large financial institutions, banks, hedge funds and private investors. I Know First is currently tracking and predicting over 10,000 financial assets across multiple markets!

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