COMPUTER MODELLING (Germany) Volatility

Moving together with COMPUTER Stock

Moving against COMPUTER Stock

COMPUTER MODELLING Market Sensitivity And Downside Risk

3 Months Beta |Analyze COMPUTER MODELLING Demand TrendCheck current 90 days COMPUTER MODELLING correlation with market (Dow Jones Industrial)

COMPUTER Beta

-0.0172

Standard Deviation

0.17

COMPUTER MODELLING Stock Volatility Analysis

COMPUTER MODELLING Projected Return Density Against Market

Assuming the 90 days trading horizon COMPUTER MODELLING has a beta of -0.0172 . This suggests as returns on the benchmark increase, returns on holding COMPUTER MODELLING are expected to decrease at a much lower rate. During a bear market, however, COMPUTER MODELLING is likely to outperform the market. COMPUTER MODELLING has an alpha of 0.0104, implying that it can generate a 0.0104 percent excess return over Dow Jones Industrial after adjusting for the inherited market risk (beta). COMPUTER MODELLING's volatility is measured either by using standard deviation or beta. Standard deviation will reflect the average amount of how computer stock's price will differ from the mean after some time.To get its calculation, you should first determine the mean price during the specified period then subtract that from each price point.

What Drives a COMPUTER MODELLING Price Volatility?

Several factors can influence a stock's market volatility:

Industry

Specific events can influence volatility within a particular industry. For instance, a significant weather upheaval in a crucial oil-production site may cause oil prices to increase in the oil sector. The direct result will be the rise in the stock price of oil distribution companies. Similarly, any government regulation in a specific industry could negatively influence stock prices due to increased regulations on compliance that may impact the company's future earnings and growth.

Political and Economic environment

When governments make significant decisions regarding trade agreements, policies, and legislation regarding specific industries, they will influence stock prices. Everything from speeches to elections may influence investors, who can directly influence the stock prices in any particular industry. The prevailing economic situation also plays a significant role in stock prices. When the economy is doing well, investors will have a positive reaction and hence, better stock prices and vice versa.

The Company's Performance

Sometimes volatility will only affect an individual company. For example, a revolutionary product launch or strong earnings report may attract many investors to purchase the company. This positive attention will raise the company's stock price. In contrast, product recalls and data breaches may negatively influence a company's stock prices.

COMPUTER MODELLING Stock Risk Measures

COMPUTER MODELLING Stock Return Volatility

COMPUTER MODELLING historical daily return volatility represents how much of COMPUTER MODELLING stock's daily returns swing around its mean - it is a statistical measure of its dispersion of returns. The firm assumes 0.1721% volatility of returns over the 90 days investment horizon. By contrast, Dow Jones Industrial accepts 0.8133% volatility on return distribution over the 90 days horizon.

Volatility is a rate at which the price of COMPUTER MODELLING or any other equity instrument increases or decreases for a given set of returns. It is measured by calculating the standard deviation of the annualized returns over a given period of time and shows the range to which the price of COMPUTER MODELLING may increase or decrease. In other words, similar to COMPUTER's beta indicator, it measures the risk of COMPUTER MODELLING and helps estimate the fluctuations that may happen in a short period of time. So if prices of COMPUTER MODELLING fluctuate rapidly in a short time span, it is termed to have high volatility, and if it swings slowly in a more extended period, it is understood to have low volatility.

The analysis of COMPUTER MODELLING's secondary risk indicators is one of the essential steps in making a buy or sell decision. The process involves identifying the amount of risk involved in COMPUTER MODELLING's investment and either accepting that risk or mitigating it. Along with some common measures of COMPUTER MODELLING stock's risk such as standard deviation, beta, or value at risk, we also provide a set of secondary indicators that can assist in the individual investment decision or help in hedging the risk of your existing portfolios.

Please note, the risk measures we provide can be used independently or collectively to perform a risk assessment. When comparing two potential stocks, we recommend comparing similar stocks with homogenous growth potential and valuation from related markets to determine which investment holds the most risk.

Pair trading is one of the very effective strategies used by professional day traders and hedge funds capitalizing on short-time and mid-term market inefficiencies. The approach is based on the fact that the ratio of prices of two correlating shares is long-term stable and oscillates around the average value. If the correlation ratio comes outside the common area, you can speculate with a high success rate that the ratio will return to the mean value and collect a profit.

The effect of pair diversification on risk is to reduce it, but we should note this doesn't apply to all risk types. When we trade pairs against COMPUTER MODELLING as a counterpart, there is always some inherent risk that will never be diversified away no matter what. This volatility limits the effect of tactical diversification using pair trading. COMPUTER MODELLING's systematic risk is the inherent uncertainty of the entire market, and therefore cannot be mitigated even by pair-trading it against the equity that is not highly correlated to it. On the other hand, COMPUTER MODELLING's unsystematic risk describes the types of risk that we can protect against, at least to some degree, by selecting a matching pair that is not perfectly correlated to COMPUTER MODELLING.

When running COMPUTER MODELLING's price analysis, check to measure COMPUTER MODELLING'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 COMPUTER MODELLING is operating at the current time. Most of COMPUTER MODELLING's value examination focuses on studying past and present price action to predict the probability of COMPUTER MODELLING's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move COMPUTER MODELLING's price. Additionally, you may evaluate how the addition of COMPUTER MODELLING to your portfolios can decrease your overall portfolio volatility.