Ekobot AB (Sweden) Analysis

Ekobot Stock Analysis Notes

About 36.0% of the company shares are held by company insiders. The company has price-to-book (P/B) ratio of 1.3. Some equities with similar Price to Book (P/B) outperform the market in the long run. Ekobot AB recorded a loss per share of 3.27. The entity had not issued any dividends in recent years. The firm had 1404:1219 split on the 27th of April 2022. Ekobot AB develops, manufactures, and sells autonomous agricultural robots that help farmers and growers in weeding crops in Europe. The company was incorporated in 2017 and is based in lvsj, Sweden. Ekobot AB is traded on Stockholm Stock Exchange in Sweden. To learn more about Ekobot AB call Erik Jonuks at 46 7 03 85 08 90 or check out https://www.ekobot.se.

Ekobot AB Investment Alerts

Ekobot Market Capitalization

The company currently falls under 'Micro-Cap' category with a current market capitalization of 16.31 M. Market capitalization usually refers to the total value of a company's stock within the entire market. To calculate Ekobot AB's market, we take the total number of its shares issued and multiply it by Ekobot AB's current market price. To manage market risk and economic uncertainty, many investors today build portfolios that are diversified across equities with different market capitalizations. However, as a general rule, conservative investors tend to hold large-cap stocks, and those looking for more risk prefer small-cap and mid-cap equities.

Technical Drivers

As of the 2nd of December, Ekobot AB shows the Variance of 26.12, mean deviation of 2.92, and Standard Deviation of 5.11. Ekobot AB technical analysis allows you to utilize historical prices and volume patterns in order to determine a pattern that computes the direction of the firm's future prices.

Ekobot AB Price Movement Analysis

Ekobot AB Outstanding Bonds

Ekobot AB Predictive Daily Indicators

Ekobot AB Forecast Models

Ekobot AB's time-series forecasting models are one of many Ekobot AB's stock analysis techniques aimed at predicting future share value based on previously observed values. Time-series forecasting models ae widely used for non-stationary data. Non-stationary data are called the data whose statistical properties e.g. the mean and standard deviation are not constant over time but instead, these metrics vary over time. These non-stationary Ekobot AB's historical data is usually called time-series. Some empirical experimentation suggests that the statistical forecasting models outperform the models based exclusively on fundamental analysis to predict the direction of the market movement and maximize returns from investment trading.

Stock analysis is the technique used by a trader or investor to examine and evaluate how Ekobot AB prices is reacting to, or reflecting on a current market direction and economic conditions. It can be used to make informed decisions about market timing, and when buying or selling Ekobot shares will generate the highest return on investment. We also built our stock analysis module to help investors to gain an insight into the world economy as a whole, the stock market, thematic ideas. a specific sector, or an individual Stock such as Ekobot AB. By using and applying Ekobot Stock analysis, traders can create a robust methodology for identifying Ekobot entry and exit points for their positions.

When running Ekobot AB's price analysis, check to measure Ekobot AB's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy Ekobot AB is operating at the current time. Most of Ekobot AB's value examination focuses on studying past and present price action to predict the probability of Ekobot AB's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Ekobot AB's price. Additionally, you may evaluate how the addition of Ekobot AB to your portfolios can decrease your overall portfolio volatility.