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You are here: Home » Machine Learning in Capital Markets : Part V

By Abhishek Ghosh February 19, 2020 6:39 am Updated on February 19, 2020

Machine Learning in Capital Markets : Part V

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This is the continuation of forth part of Machine Learning in Capital Markets in Capital Markets. The technical indicators are intended to help identify a trend as early as possible. The result of the various technical indicators is to provide a mathematical value that is determined from the price and trading data. It also tries to incorporate information from the past into future forecasts. Different algorithms can be used for this purpose. An algorithm helps the trader to recognize and evaluate short-term extreme situations. It warns the trader, for example, if a trend loses momentum before the actual situation or price movement occurs. Furthermore, divergences can be displayed with an oscillator, that a trend is nearing completion. The point in time at which the oscillator is used as a tool is of crucial importance here. An oscillator analysis is not very helpful at the beginning of a significant price movement. It only becomes helpful towards the end.

Price difference from a share price is continuously calculated for a fixed time interval. To determine the difference, the closing price is subtracted from the last interval from the current one. If the calculated value is greater than that 10 days back, then the prices have increased. The value is therefore entered above the zero line. If the value is less than 10 days ago, the prices have fallen. In this case, the value is entered below the zero line. If the value is above the zero line and increases, then there is an acceleration of the upward trend. If the value is above the zero line but there is also a trend towards it, the upward trend is still intact, but only with a declining slope. If the graph falls below the zero line, the current value of the share is lower than 10 days ago. The slowdown in the downward trend becomes apparent as soon as the line begins to rise again. The following illustration shows momentum with an interval of 10 days.

Another technical indicator is the Relative Strength Index (RSI). An advantage of RSI is that it provides between 0 and 100 for smoothing distortions and an n constant bandwidth value. One weakness of the “momentum” previously presented is that sudden changes in the stock can cause the momentum line to rise or fall sharply. By smoothing the RSI, this tear is brought to a constant value between 0 and 100. Furthermore, the Relative Strength Index can compare two securities or sectors. An objective benchmark is carried out with the securities or sectors seen in this way. A value above 70 is considered overbought, a value below 30 is considered an oversold market situation.

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The Aroon Oscillator was defined in 1995 and is used to react to the first signs of a turnaround. It is assumed that new highs will regularly be reached in upward trends and new lows in downward trends. Based on this assumption, the number of periods between the last two highs and lows is recorded in order to be able to make a prediction of a possible trend reversal. “Aroon-Up” and “Arron-Down” are essential components of the Aroon Oscillator. The past periods that have occurred since the last high are counted with “Aroon-Up” and the past periods since the last low with Aroon-Down. The Aroon Oscillator can be determined using the following formula.

Machine Learning in Capital Markets

When determining the metadata, exogenous variables are considered that cannot be traced back directly to the company to be analyzed or do not belong to its descriptive characteristics. The development of currency pairs is one example of this metadata. If a currency rises or falls in the exchange rate, this affects companies that generate a large part of their sales in the corresponding currency. The change in the value of a currency has a significant influence on the import prices or export sales of an international company. Companies such as “The Coca Cola Company”, which generate a large part of their sales abroad, can influence the development between the currencies EUR and US dollars, influence the company result and thus also the share price. In addition to currency differences, raw material prices such as oil prices also have an impact on price and sales trends for companies. Manufacturing companies are particularly affected. Raw material prices have an impact on production costs and these have to be adjusted to the customer either through a lower profit or a price adjustment. The price of gold can also influence the value of a share, even if the company does not process or trade gold. Inflation expectations or investor confidence can be derived from the gold price. For machine learning, the previously mentioned metadata must be added as a feature in the “metadata” feature category and taken into account Oil prices influence the price and sales development on companies. Manufacturing companies are particularly affected. Raw material prices have an impact on production costs and these have to be adjusted to the customer either through a lower profit or a price adjustment. The price of gold can also influence the value of a share, even if the company does not process or trade gold. Inflation expectations or investor confidence can be derived from the gold price. For machine learning, the previously mentioned metadata must be added as a feature in the “metadata” feature category and taken into account Oil prices influence the price and sales development on companies. Manufacturing companies are particularly affected. Raw material prices have an impact on production costs and these have to be adjusted to the customer either through a lower profit or a price adjustment. The price of gold can also influence the value of a share, even if the company does not process or trade gold. Inflation expectations or investor confidence can be derived from the gold price.

For machine learning, the previously mentioned metadata must be added as a feature in the “metadata” feature category and taken into account Raw material prices have an impact on production costs and these have to be adjusted to the customer either through a lower profit or a price adjustment. The price of gold can also influence the value of a share, even if the company does not process or trade gold. Inflation expectations or investor confidence can be derived from the gold price.

To be continued.

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Abhishek Ghosh

About Abhishek Ghosh

Abhishek Ghosh is a Businessman, Surgeon, Author and Blogger. You can keep touch with him on Twitter - @AbhishekCTRL.

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About This Article

Cite this article as: Abhishek Ghosh, "Machine Learning in Capital Markets : Part V," in The Customize Windows, February 19, 2020, July 4, 2022, https://thecustomizewindows.com/2020/02/machine-learning-in-capital-markets-part-v/.

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