CSIF I (Switzerland) Market Value
| 0P0000A2DS | 671.93 0.61 0.09% |
| Symbol | CSIF |
CSIF I '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 CSIF I's fund 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 CSIF I.
| 11/19/2024 |
| 12/19/2024 |
If you would invest 0.00 in CSIF I on November 19, 2024 and sell it all today you would earn a total of 0.00 from holding CSIF I Bond or generate 0.0% return on investment in CSIF I over 30 days.
CSIF I 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 CSIF I's fund 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 CSIF I Bond upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.2589 | |||
| Information Ratio | (0.07) | |||
| Maximum Drawdown | 1.35 | |||
| Value At Risk | (0.34) | |||
| Potential Upside | 0.5013 |
CSIF I Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for CSIF I's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as CSIF I's standard deviation. In reality, there are many statistical measures that can use CSIF I historical prices to predict the future CSIF I's volatility.| Risk Adjusted Performance | 0.015 | |||
| Jensen Alpha | 0.0018 | |||
| Total Risk Alpha | (0) | |||
| Sortino Ratio | (0.07) | |||
| Treynor Ratio | (0.21) |
CSIF I Bond Backtested Returns
At this point, CSIF I is very steady. CSIF I Bond secures Sharpe Ratio (or Efficiency) of 0.0514, which signifies that the fund had a 0.0514% return per unit of return volatility over the last 3 months. We have found twenty-seven technical indicators for CSIF I Bond, which you can use to evaluate the volatility of the entity. Please confirm CSIF I's Semi Deviation of 0.2023, risk adjusted performance of 0.015, and Mean Deviation of 0.1959 to double-check if the risk estimate we provide is consistent with the expected return of 0.0138%. The fund shows a Beta (market volatility) of -0.0082, which signifies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning CSIF I are expected to decrease at a much lower rate. During the bear market, CSIF I is likely to outperform the market.
Auto-correlation | 0.30 |
Below average predictability
CSIF I Bond has below average predictability. Overlapping area represents the amount of predictability between CSIF I time series from 19th of November 2024 to 4th of December 2024 and 4th of December 2024 to 19th 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 CSIF I Bond price movement. The serial correlation of 0.3 indicates that nearly 30.0% of current CSIF I price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.3 | |
| Spearman Rank Test | -0.01 | |
| Residual Average | 0.0 | |
| Price Variance | 2.1 |
CSIF I Bond lagged returns against current returns
Autocorrelation, which is CSIF I fund'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 CSIF I's fund expected returns. We can calculate the autocorrelation of CSIF I returns to help us make a trade decision. For example, suppose you find that CSIF I has exhibited high autocorrelation historically, and you observe that the fund 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 |
CSIF I 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 CSIF I fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if CSIF I fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in CSIF I fund over time.
Current vs Lagged Prices |
| Timeline |
CSIF I Lagged Returns
When evaluating CSIF I's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of CSIF I fund have on its future price. CSIF I 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, CSIF I autocorrelation shows the relationship between CSIF I fund current value and its past values and can show if there is a momentum factor associated with investing in CSIF I Bond.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.| Cryptocurrency Center Build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency | |
| ETFs Find actively traded Exchange Traded Funds (ETF) from around the world | |
| Insider Screener Find insiders across different sectors to evaluate their impact on performance | |
| Headlines Timeline Stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity |