Storebrand ASA (Norway) Market Value
| STB Stock | NOK 106.70 0.30 0.28% |
| Symbol | Storebrand |
Storebrand ASA '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 Storebrand ASA's stock 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 Storebrand ASA.
| 08/04/2023 |
| 04/30/2024 |
If you would invest 0.00 in Storebrand ASA on August 4, 2023 and sell it all today you would earn a total of 0.00 from holding Storebrand ASA or generate 0.0% return on investment in Storebrand ASA over 270 days. Storebrand ASA is related to or competes with DnB ASA, Gjensidige Forsikring, Orkla ASA, Telenor ASA, and Yara International. Storebrand ASA, through its subsidiaries, primarily provides insurance products and services for private individuals, co... More
Storebrand ASA 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 Storebrand ASA's stock 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 Storebrand ASA upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.34 | |||
| Information Ratio | 0.0983 | |||
| Maximum Drawdown | 6.75 | |||
| Value At Risk | (1.84) | |||
| Potential Upside | 1.34 |
Storebrand ASA Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Storebrand ASA's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Storebrand ASA's standard deviation. In reality, there are many statistical measures that can use Storebrand ASA historical prices to predict the future Storebrand ASA's volatility.| Risk Adjusted Performance | 0.1052 | |||
| Jensen Alpha | 0.2238 | |||
| Total Risk Alpha | 0.0374 | |||
| Sortino Ratio | 0.1072 | |||
| Treynor Ratio | (20.45) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Storebrand ASA'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.
Storebrand ASA Backtested Returns
Storebrand ASA appears to be very steady, given 3 months investment horizon. Storebrand ASA owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.18, which indicates the firm had a 0.18% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Storebrand ASA, which you can use to evaluate the volatility of the company. Please review Storebrand ASA's Risk Adjusted Performance of 0.1052, semi deviation of 1.04, and Coefficient Of Variation of 627.4 to confirm if our risk estimates are consistent with your expectations. On a scale of 0 to 100, Storebrand ASA holds a performance score of 14. The entity has a beta of -0.0109, which indicates not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Storebrand ASA are expected to decrease at a much lower rate. During the bear market, Storebrand ASA is likely to outperform the market. Please check Storebrand ASA's expected short fall, day median price, and the relationship between the potential upside and accumulation distribution , to make a quick decision on whether Storebrand ASA's existing price patterns will revert.
Auto-correlation | 0.68 |
Good predictability
Storebrand ASA has good predictability. Overlapping area represents the amount of predictability between Storebrand ASA time series from 4th of August 2023 to 17th of December 2023 and 17th of December 2023 to 30th 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 Storebrand ASA price movement. The serial correlation of 0.68 indicates that around 68.0% of current Storebrand ASA price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.68 | |
| Spearman Rank Test | 0.63 | |
| Residual Average | 0.0 | |
| Price Variance | 17.67 |
Storebrand ASA lagged returns against current returns
Autocorrelation, which is Storebrand ASA stock'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 Storebrand ASA's stock expected returns. We can calculate the autocorrelation of Storebrand ASA returns to help us make a trade decision. For example, suppose you find that Storebrand ASA has exhibited high autocorrelation historically, and you observe that the stock 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 |
Storebrand ASA 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 Storebrand ASA stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Storebrand ASA stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Storebrand ASA stock over time.
Current vs Lagged Prices |
| Timeline |
Storebrand ASA Lagged Returns
When evaluating Storebrand ASA's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Storebrand ASA stock have on its future price. Storebrand ASA 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, Storebrand ASA autocorrelation shows the relationship between Storebrand ASA stock current value and its past values and can show if there is a momentum factor associated with investing in Storebrand ASA.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Check out Storebrand ASA Correlation, Storebrand ASA Volatility and Storebrand ASA Alpha and Beta module to complement your research on Storebrand ASA. Note that the Storebrand ASA information on this page should be used as a complementary analysis to other Storebrand ASA's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Money Flow Index module to determine momentum by analyzing Money Flow Index and other technical indicators.
Complementary Tools for Storebrand Stock analysis
When running Storebrand ASA's price analysis, check to measure Storebrand ASA'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 Storebrand ASA is operating at the current time. Most of Storebrand ASA's value examination focuses on studying past and present price action to predict the probability of Storebrand ASA's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Storebrand ASA's price. Additionally, you may evaluate how the addition of Storebrand ASA to your portfolios can decrease your overall portfolio volatility.
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Storebrand ASA technical stock 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, stock market cycles, or different charting patterns.