Salesforce (Germany) Market Value
| FOO Stock | EUR 257.05 2.75 1.08% |
| Symbol | Salesforce |
Salesforce '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 Salesforce'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 Salesforce.
| 02/24/2024 |
| 04/24/2024 |
If you would invest 0.00 in Salesforce on February 24, 2024 and sell it all today you would earn a total of 0.00 from holding Salesforce or generate 0.0% return on investment in Salesforce over 60 days. Salesforce is related to or competes with Federal Home, Amkor Technology, ACCSYS TECHPLC, American Homes, Corporate Office, AAC TECHNOLOGHLDGADR, and Kingdee International. More
Salesforce 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 Salesforce'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 Salesforce upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.05 | |||
| Information Ratio | (0.05) | |||
| Maximum Drawdown | 10.92 | |||
| Value At Risk | (2.77) | |||
| Potential Upside | 2.89 |
Salesforce Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Salesforce's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Salesforce's standard deviation. In reality, there are many statistical measures that can use Salesforce historical prices to predict the future Salesforce's volatility.| Risk Adjusted Performance | 0.012 | |||
| Jensen Alpha | (0.06) | |||
| Total Risk Alpha | (0.24) | |||
| Sortino Ratio | (0.04) | |||
| Treynor Ratio | 0.0075 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Salesforce'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.
Salesforce Backtested Returns
We consider Salesforce very steady. Salesforce owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0089, which indicates the firm had a 0.0089% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Salesforce, which you can use to evaluate the volatility of the company. Please validate Salesforce's Coefficient Of Variation of 11274.96, risk adjusted performance of 0.012, and Semi Deviation of 1.88 to confirm if the risk estimate we provide is consistent with the expected return of 0.0156%. The entity has a beta of 0.75, which indicates possible diversification benefits within a given portfolio. As returns on the market increase, Salesforce's returns are expected to increase less than the market. However, during the bear market, the loss of holding Salesforce is expected to be smaller as well. Salesforce right now has a risk of 1.76%. Please validate Salesforce jensen alpha, potential upside, daily balance of power, as well as the relationship between the treynor ratio and expected short fall , to decide if Salesforce will be following its existing price patterns.
Auto-correlation | 0.09 |
Virtually no predictability
Salesforce has virtually no predictability. Overlapping area represents the amount of predictability between Salesforce time series from 24th of February 2024 to 25th of March 2024 and 25th of March 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 Salesforce price movement. The serial correlation of 0.09 indicates that less than 9.0% of current Salesforce price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.09 | |
| Spearman Rank Test | 0.01 | |
| Residual Average | 0.0 | |
| Price Variance | 125.75 |
Salesforce lagged returns against current returns
Autocorrelation, which is Salesforce 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 Salesforce's stock expected returns. We can calculate the autocorrelation of Salesforce returns to help us make a trade decision. For example, suppose you find that Salesforce 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 |
Salesforce 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 Salesforce stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Salesforce stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Salesforce stock over time.
Current vs Lagged Prices |
| Timeline |
Salesforce Lagged Returns
When evaluating Salesforce's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Salesforce stock have on its future price. Salesforce 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, Salesforce autocorrelation shows the relationship between Salesforce stock current value and its past values and can show if there is a momentum factor associated with investing in Salesforce.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Salesforce in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Salesforce's short interest history, or implied volatility extrapolated from Salesforce options trading.
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Try AI Portfolio ArchitectCheck out Salesforce Correlation, Salesforce Volatility and Salesforce Alpha and Beta module to complement your research on Salesforce. For more information on how to buy Salesforce Stock please use our How to Invest in Salesforce guide.You can also try the Equity Valuation module to check real value of public entities based on technical and fundamental data.
Complementary Tools for Salesforce Stock analysis
When running Salesforce's price analysis, check to measure Salesforce'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 Salesforce is operating at the current time. Most of Salesforce's value examination focuses on studying past and present price action to predict the probability of Salesforce's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Salesforce's price. Additionally, you may evaluate how the addition of Salesforce to your portfolios can decrease your overall portfolio volatility.
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Salesforce 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.