Danske Bank As Stock Market Value
| DNSKF Stock | USD 29.33 0.00 0.00% |
| Symbol | Danske |
Danske Bank 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Danske Bank's pink sheet what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Danske Bank.
| 03/25/2024 |
| 04/24/2024 |
If you would invest 0.00 in Danske Bank on March 25, 2024 and sell it all today you would earn a total of 0.00 from holding Danske Bank AS or generate 0.0% return on investment in Danske Bank over 30 days. Danske Bank is related to or competes with Bank Rakyat, Lloyds Banking, Western Alliance, JAPAN POST, Piraeus Bank, PT Bank, and Eurobank Ergasias. Danske Bank AS provides various banking products and services to corporate, institutional, and international clients More
Danske Bank Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Danske Bank's pink sheet current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Danske Bank AS upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | 0.0379 | |||
| Maximum Drawdown | 13.99 | |||
| Value At Risk | (0.37) | |||
| Potential Upside | 1.62 |
Danske Bank Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Danske Bank's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Danske Bank's standard deviation. In reality, there are many statistical measures that can use Danske Bank historical prices to predict the future Danske Bank's volatility.| Risk Adjusted Performance | 0.0716 | |||
| Jensen Alpha | 0.1423 | |||
| Total Risk Alpha | (0.05) | |||
| Treynor Ratio | (2.99) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Danske Bank's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Danske Bank AS Backtested Returns
We consider Danske Bank out of control. Danske Bank AS secures Sharpe Ratio (or Efficiency) of 0.0949, which denotes the company had a 0.0949% return per unit of risk over the last 3 months. We have found eighteen technical indicators for Danske Bank AS, which you can use to evaluate the volatility of the firm. Please confirm Danske Bank's Standard Deviation of 1.4, mean deviation of 0.5114, and Variance of 1.96 to check if the risk estimate we provide is consistent with the expected return of 0.14%. Danske Bank has a performance score of 7 on a scale of 0 to 100. The firm shows a Beta (market volatility) of -0.0463, which means not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Danske Bank are expected to decrease at a much lower rate. During the bear market, Danske Bank is likely to outperform the market. Danske Bank AS right now shows a risk of 1.44%. Please confirm Danske Bank AS variance, value at risk, as well as the relationship between the Value At Risk and rate of daily change , to decide if Danske Bank AS will be following its price patterns.
Auto-correlation | 0.00 |
No correlation between past and present
Danske Bank AS has no correlation between past and present. Overlapping area represents the amount of predictability between Danske Bank time series from 25th of March 2024 to 9th of April 2024 and 9th of April 2024 to 24th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Danske Bank AS price movement. The serial correlation of 0.0 indicates that just 0.0% of current Danske Bank price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.0 | |
| Spearman Rank Test | 0.1 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Danske Bank AS lagged returns against current returns
Autocorrelation, which is Danske Bank pink sheet's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Danske Bank's pink sheet expected returns. We can calculate the autocorrelation of Danske Bank returns to help us make a trade decision. For example, suppose you find that Danske Bank has exhibited high autocorrelation historically, and you observe that the pink sheet is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Danske Bank regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Danske Bank pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Danske Bank pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Danske Bank pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Danske Bank Lagged Returns
When evaluating Danske Bank's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Danske Bank pink sheet have on its future price. Danske Bank autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Danske Bank autocorrelation shows the relationship between Danske Bank pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Danske Bank AS.
Regressed Prices |
| Timeline |
Pair Trading with Danske Bank
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Danske Bank position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Danske Bank will appreciate offsetting losses from the drop in the long position's value.Moving together with Danske Pink Sheet
| 0.8 | CIHHF | China Merchants Bank | PairCorr |
Moving against Danske Pink Sheet
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| 0.76 | SRBBF | VPN Technologies | PairCorr |
| 0.56 | IMHC | Imperalis Holding Corp | PairCorr |
| 0.49 | CHHE | China Health Industries | PairCorr |
The ability to find closely correlated positions to Danske Bank could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Danske Bank when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Danske Bank - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Danske Bank AS to buy it.
The correlation of Danske Bank is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Danske Bank moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Danske Bank AS moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Danske Bank can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Check out Danske Bank Correlation, Danske Bank Volatility and Danske Bank Alpha and Beta module to complement your research on Danske Bank. You can also try the Portfolio Analyzer module to portfolio analysis module that provides access to portfolio diagnostics and optimization engine.
Complementary Tools for Danske Pink Sheet analysis
When running Danske Bank's price analysis, check to measure Danske Bank'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 Danske Bank is operating at the current time. Most of Danske Bank's value examination focuses on studying past and present price action to predict the probability of Danske Bank's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Danske Bank's price. Additionally, you may evaluate how the addition of Danske Bank to your portfolios can decrease your overall portfolio volatility.
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Danske Bank 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.