Swiss Leader (Switzerland) Market Value
| SLI Index | 1,856 17.79 0.97% |
| Symbol | Swiss |
Swiss Leader '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 Swiss Leader's index 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 Swiss Leader.
| 03/28/2024 |
| 04/27/2024 |
If you would invest 0.00 in Swiss Leader on March 28, 2024 and sell it all today you would earn a total of 0.00 from holding Swiss Leader Price or generate 0.0% return on investment in Swiss Leader over 30 days.
Swiss Leader 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 Swiss Leader's index 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 Swiss Leader Price upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6548 | |||
| Information Ratio | (0.03) | |||
| Maximum Drawdown | 3.81 | |||
| Value At Risk | (1.00) | |||
| Potential Upside | 1.01 |
Swiss Leader Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Swiss Leader's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Swiss Leader's standard deviation. In reality, there are many statistical measures that can use Swiss Leader historical prices to predict the future Swiss Leader's volatility.| Risk Adjusted Performance | 0.0664 | |||
| Total Risk Alpha | (0.02) | |||
| Sortino Ratio | (0.03) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Swiss Leader'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.
Please note, it is not enough to conduct a financial or market analysis of a single entity such as Swiss Leader. Your research has to be compared to or analyzed against Swiss Leader's peers to derive any actionable benefits. When done correctly, Swiss Leader's competitive analysis will give you plenty of quantitative and qualitative data to validate your investment decisions or develop an entirely new strategy toward taking a position in Swiss Leader Price.
Swiss Leader Price Backtested Returns
Swiss Leader Price owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0522, which indicates the index had a 0.0522% return per unit of risk over the last 3 months. We have found twenty-five technical indicators for Swiss Leader Price, which you can use to evaluate the volatility of the index. The entity has a beta of 0.0, which indicates not very significant fluctuations relative to the market. the returns on MARKET and Swiss Leader are completely uncorrelated.
Auto-correlation | 0.13 |
Insignificant predictability
Swiss Leader Price has insignificant predictability. Overlapping area represents the amount of predictability between Swiss Leader time series from 28th of March 2024 to 12th of April 2024 and 12th of April 2024 to 27th 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 Swiss Leader Price price movement. The serial correlation of 0.13 indicates that less than 13.0% of current Swiss Leader price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.13 | |
| Spearman Rank Test | 0.14 | |
| Residual Average | 0.0 | |
| Price Variance | 180.77 |
Swiss Leader Price lagged returns against current returns
Autocorrelation, which is Swiss Leader index'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 Swiss Leader's index expected returns. We can calculate the autocorrelation of Swiss Leader returns to help us make a trade decision. For example, suppose you find that Swiss Leader has exhibited high autocorrelation historically, and you observe that the index 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 |
Swiss Leader 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 Swiss Leader index is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Swiss Leader index is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Swiss Leader index over time.
Current vs Lagged Prices |
| Timeline |
Swiss Leader Lagged Returns
When evaluating Swiss Leader's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Swiss Leader index have on its future price. Swiss Leader 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, Swiss Leader autocorrelation shows the relationship between Swiss Leader index current value and its past values and can show if there is a momentum factor associated with investing in Swiss Leader Price.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
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Swiss Leader technical index 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, index market cycles, or different charting patterns.