Bkw Ag Stock Technical Analysis

BKWAF Stock  USD 180.00  5.00  2.86%   
As of the 16th of March 2025, BKW AG shows the mean deviation of 0.0853, and Risk Adjusted Performance of 0.0924. BKW AG technical analysis gives you the methodology to make use of historical prices and volume patterns to determine a pattern that approximates the direction of the firm's future prices. Please confirm BKW AG coefficient of variation, as well as the relationship between the total risk alpha and skewness to decide if BKW AG is priced some-what accurately, providing market reflects its regular price of 180.0 per share. Given that BKW AG has variance of 0.1237, we suggest you to validate BKW AG's prevailing market performance to make sure the company can sustain itself at some point in the future.

BKW AG Momentum Analysis

Momentum indicators are widely used technical indicators which help to measure the pace at which the price of specific equity, such as BKW, fluctuates. Many momentum indicators also complement each other and can be helpful when the market is rising or falling as compared to BKW
  
BKW AG's Momentum analyses are specifically helpful, as they help investors time the market using mark points where the market can reverse. The reversal spots are usually identified through divergence between price movement and momentum.
BKW AG technical pink sheet analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, pink sheet market cycles, or different charting patterns.
A focus of BKW AG technical analysis is to determine if market prices reflect all relevant information impacting that market. A technical analyst looks at the history of BKW AG trading pattern rather than external drivers such as economic, fundamental, or social events. It is believed that price action tends to repeat itself due to investors' collective, patterned behavior. Hence technical analysis focuses on identifiable price trends and conditions. More Info...

BKW AG Technical Analysis

Indicator
Time Period
Execute Indicator
The output start index for this execution was fifty with a total number of output elements of eleven. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of BKW AG volatility. High ATR values indicate high volatility, and low values indicate low volatility.
JavaScript chart by amCharts 3.21.15Dec2025FebFebFeb 10Feb 17Feb 24MarMar 10175176177178179180 0.20.40.60.81.0 0.0920.0940.0960.0980.100 41K41.5K42K42.5K43K43.5K44K44.5K Show all
JavaScript chart by amCharts 3.21.15BKW AG Volume BKW AG Closing Prices Dow Jones Industrial Closing Prices - Benchmark BKW AG Average True Range

BKW AG Trend Analysis

Use this graph to draw trend lines for BKW AG. You can use it to identify possible trend reversals for BKW AG as well as other signals and approximate when it will take place. Remember, you need at least two touches of the trend line with actual BKW AG price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.
JavaScript chart by amCharts 3.21.15
JavaScript chart by amCharts 3.21.15Dec2025FebMar175175.5176176.5177177.5178178.5179179.5
JavaScript chart by amCharts 3.21.15Dec2025Feb

BKW AG Best Fit Change Line

The following chart estimates an ordinary least squares regression model for BKW AG applied against its price change over selected period. The best fit line has a slop of   0.04  , which means BKW AG will continue generating value for investors. It has 122 observation points and a regression sum of squares at 71.99, which is the sum of squared deviations for the predicted BKW AG price change compared to its average price change.
JavaScript chart by amCharts 3.21.15 Prediction Change
JavaScript chart by amCharts 3.21.15Dec2025FebMar0.0%0.5%1.0%1.5%2.0%2.5%3.0%
JavaScript chart by amCharts 3.21.15Dec2025Feb

About BKW AG Technical Analysis

The technical analysis module can be used to analyzes prices, returns, volume, basic money flow, and other market information and help investors to determine the real value of BKW AG on a daily or weekly bases. We use both bottom-up as well as top-down valuation methodologies to arrive at the intrinsic value of BKW AG based on its technical analysis. In general, a bottom-up approach, as applied to this company, focuses on BKW AG price pattern first instead of the macroeconomic environment surrounding BKW AG. By analyzing BKW AG's financials, daily price indicators, and related drivers such as dividends, momentum ratios, and various types of growth rates, we attempt to find the most accurate representation of BKW AG's intrinsic value. As compared to a bottom-up approach, our top-down model examines the macroeconomic factors that affect the industry/economy before zooming in to BKW AG specific price patterns or momentum indicators. Please read more on our technical analysis page.

BKW AG March 16, 2025 Technical Indicators

Most technical analysis of BKW help investors determine whether a current trend will continue and, if not, when it will shift. We provide a combination of tools to recognize potential entry and exit points for BKW from various momentum indicators to cycle indicators. When you analyze BKW charts, please remember that the event formation may indicate an entry point for a short seller, and look at different other indicators across different periods to confirm that a breakdown or reversion is likely to occur.

BKW AG March 16, 2025 Daily Trend Indicators

Traders often use several different daily volumes and price technical indicators to supplement a more traditional technical analysis when analyzing securities such as BKW stock. With literally thousands of different options, investors must choose the best indicators for them and familiarize themselves with how they work. We suggest combining traditional momentum indicators with more near-term forms of technical analysis such as Accumulation Distribution or Daily Balance Of Power. With their quantitative nature, daily value technical indicators can also be incorporated into your automated trading systems.

Complementary Tools for BKW Pink Sheet analysis

When running BKW AG's price analysis, check to measure BKW AG'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 BKW AG is operating at the current time. Most of BKW AG's value examination focuses on studying past and present price action to predict the probability of BKW AG's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move BKW AG's price. Additionally, you may evaluate how the addition of BKW AG to your portfolios can decrease your overall portfolio volatility.
Risk-Return Analysis
View associations between returns expected from investment and the risk you assume
Portfolio Manager
State of the art Portfolio Manager to monitor and improve performance of your invested capital
Portfolio Analyzer
Portfolio analysis module that provides access to portfolio diagnostics and optimization engine
My Watchlist Analysis
Analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like
Bollinger Bands
Use Bollinger Bands indicator to analyze target price for a given investing horizon
Theme Ratings
Determine theme ratings based on digital equity recommendations. Macroaxis theme ratings are based on combination of fundamental analysis and risk-adjusted market performance
Idea Analyzer
Analyze all characteristics, volatility and risk-adjusted return of Macroaxis ideas
Correlation Analysis
Reduce portfolio risk simply by holding instruments which are not perfectly correlated
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm