Algorithmic Trading:

“Eighty percent of daily volume in the U.S. is done by machines” – Guy De Blonay, fund manager at Jupiter Asset Management

Summary:

• New long-term strategies are being built around algorithmic trading and machine trading is now slowly eating further into long term investments.
• The volume of trades in the USA done by machines can be up to 80% according to recent claims.
• Blackrock are set to give a number of their financial analysts the boot in favour of a more updated trading strategy that draws on machines and Artificial Intelligence.
• I Know First’s state of the art algorithm, uses Artificial Intelligence and self-learning capabilities to predict asset price movements in the market today.

Source: Flickr

The volume of trades in the USA done by machines can be up to 80% according to recent claims. Obviously, this percentage fluctuates but it certainly increases during periods of prolonged volatility for short term trades. The days of having an investor pour over a company’s 401(k) and then strategically making an investment seems to be rapidly coming to an end. This is especially true as new long-term strategies are being built around algorithmic trading and machine trading is now slowly eating further into long term investments.

HedgeFunds and Investment Banks are Upgrading

When it comes to machine trading it is important to note that these figures do not account for those that use software to assist them in the decision-making process. To put this in perspective even the remaining 20% of human trades will not be solely relying on their own analysis but utilise algorithms and software to provide data recommendations.

Blackrock are set to give a number of their financial analysts the boot in favour of a more updated trading strategy that draws on machines and artificial intelligence.  While many other firms have adopted such strategies for a while not Blackrock doing so seems to be the writing on the wall for what is to come.

In an extended interview with CNBC Guy De Blonay, fund manager at Jupiter Asset Management expounds on just how the market crash flashes and volatility do not prevent the trends towards machine trading. He goes on to explain how: “Eighty percent of daily volume in the U.S. is done by machines, so what you get is a lack of focus on earnings, a lack of focus on outlooks and you just get short-term movements based on very specific data that is released every day and that creates noise,”

Source: Pixabay

I Know First algorithm and it how it assists in the modern trading world

I Know First’s state of the art algorithm, uses Artificial Intelligence and self-learning capabilities to predict asset price movements in the market today. In the following link the results of the deep learning strategies that use the I Know First algorithm’s predictability filter are used to determine those assets that are predictable and have high expected returns and construct a portfolio of those assets. In some strategies, selection is focused on the S&P 500 stocks with the strongest three-month forecasts and high predictability levels. Initial portfolio size is 10 stocks for all strategies and positions are adjusted based on the daily updated forecasts, where shorter term signals are used as time elapses resulting in a maximum holding period of 63 trading days.

Source: Pixabay

The I Know First daily forecasts consists of two indicators, the signal and the predictability. The latter is a measure of the forecast performance in the recent past. By monitoring the performance of each stock and of the aggregate of stocks over time one can judge the stability of the market. The signal is an indicator which represents the predicted movement direction/trend; not a percentage or specific target price. The signal strength indicates how much the current price deviates from what the system considers an equilibrium or “fair” price. The predictability is a separate indicator that is obtained by calculating the correlation between the prediction and the actual asset movement for each discrete time period. The algorithm then averages the results of all the prediction points, while giving more weight to recent performance. As the machine keeps learning, the predictability values generally increase, but then stabilise. By monitoring the predictability over time, one can detect the potential paradigm shift. This is a part of the competitive advantage offered by I Know First, allowing investors to more successfully differentiate themselves in the market.

These outputs can then be utilised by a trader as a decision support system and assist them in the trading process especially given that modern trades are increasingly computerised making it even more difficult for a human to be making to correct decisions. Tools like the I Know First algorithm allow humans to continue to trade and keep up with the fast-paced computerised trading without compromise in the more detailed and personal aspect behind investment trading.

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