SBI Insurance (Germany) Market Value
| EEW Stock | 6.25 0.20 3.31% |
| Symbol | SBI |
SBI Insurance '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 SBI Insurance'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 SBI Insurance.
| 06/05/2024 |
| 12/02/2024 |
If you would invest 0.00 in SBI Insurance on June 5, 2024 and sell it all today you would earn a total of 0.00 from holding SBI Insurance Group or generate 0.0% return on investment in SBI Insurance over 180 days. SBI Insurance is related to or competes with Richardson Electronics, Methode Electronics, HOCHSCHILD MINING, Benchmark Electronics, Scientific Games, Penn National, and UMC Electronics. More
SBI Insurance 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 SBI Insurance'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 SBI Insurance Group upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 1.82 | |||
| Information Ratio | (0.06) | |||
| Maximum Drawdown | 6.29 | |||
| Value At Risk | (2.63) | |||
| Potential Upside | 2.7 |
SBI Insurance Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for SBI Insurance's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as SBI Insurance's standard deviation. In reality, there are many statistical measures that can use SBI Insurance historical prices to predict the future SBI Insurance's volatility.| Risk Adjusted Performance | 0.0305 | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.20) | |||
| Sortino Ratio | (0.05) | |||
| Treynor Ratio | 0.11 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of SBI Insurance'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.
SBI Insurance Group Backtested Returns
Currently, SBI Insurance Group is not too volatile. SBI Insurance Group owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0433, which indicates the company had a 0.0433% return per unit of volatility over the last 3 months. We have found twenty-seven technical indicators for SBI Insurance Group, which you can use to evaluate the volatility of the entity. Please validate SBI Insurance's Market Risk Adjusted Performance of 0.12, downside deviation of 1.82, and Risk Adjusted Performance of 0.0305 to confirm if the risk estimate we provide is consistent with the expected return of 0.0618%. SBI Insurance has a performance score of 3 on a scale of 0 to 100. The firm has a beta of 0.35, which indicates possible diversification benefits within a given portfolio. As returns on the market increase, SBI Insurance's returns are expected to increase less than the market. However, during the bear market, the loss of holding SBI Insurance is expected to be smaller as well. SBI Insurance Group now has a risk of 1.43%. Please validate SBI Insurance jensen alpha, semi variance, price action indicator, as well as the relationship between the maximum drawdown and daily balance of power , to decide if SBI Insurance will be following its existing price patterns.
Auto-correlation | 0.13 |
Insignificant predictability
SBI Insurance Group has insignificant predictability. Overlapping area represents the amount of predictability between SBI Insurance time series from 5th of June 2024 to 3rd of September 2024 and 3rd of September 2024 to 2nd of December 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 SBI Insurance Group price movement. The serial correlation of 0.13 indicates that less than 13.0% of current SBI Insurance price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.13 | |
| Spearman Rank Test | 0.41 | |
| Residual Average | 0.0 | |
| Price Variance | 0.03 |
SBI Insurance Group lagged returns against current returns
Autocorrelation, which is SBI Insurance 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 SBI Insurance's stock expected returns. We can calculate the autocorrelation of SBI Insurance returns to help us make a trade decision. For example, suppose you find that SBI Insurance 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 |
SBI Insurance 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 SBI Insurance stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if SBI Insurance stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in SBI Insurance stock over time.
Current vs Lagged Prices |
| Timeline |
SBI Insurance Lagged Returns
When evaluating SBI Insurance's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of SBI Insurance stock have on its future price. SBI Insurance 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, SBI Insurance autocorrelation shows the relationship between SBI Insurance stock current value and its past values and can show if there is a momentum factor associated with investing in SBI Insurance Group.
Regressed Prices |
| Timeline |
Thematic Opportunities
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Additional Tools for SBI Stock Analysis
When running SBI Insurance's price analysis, check to measure SBI Insurance'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 SBI Insurance is operating at the current time. Most of SBI Insurance's value examination focuses on studying past and present price action to predict the probability of SBI Insurance's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move SBI Insurance's price. Additionally, you may evaluate how the addition of SBI Insurance to your portfolios can decrease your overall portfolio volatility.