Vinci Shopping (Brazil) Market Value
| VISC11 Fund | BRL 120.29 1.02 0.86% |
| Symbol | Vinci |
Vinci Shopping '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 Vinci Shopping'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 Vinci Shopping.
| 04/02/2024 |
| 05/02/2024 |
If you would invest 0.00 in Vinci Shopping on April 2, 2024 and sell it all today you would earn a total of 0.00 from holding Vinci Shopping Centers or generate 0.0% return on investment in Vinci Shopping over 30 days. More
Vinci Shopping 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 Vinci Shopping'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 Vinci Shopping Centers upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.16) | |||
| Maximum Drawdown | 1.69 | |||
| Value At Risk | (0.81) | |||
| Potential Upside | 0.7373 |
Vinci Shopping Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Vinci Shopping's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Vinci Shopping's standard deviation. In reality, there are many statistical measures that can use Vinci Shopping historical prices to predict the future Vinci Shopping's volatility.| Risk Adjusted Performance | (0.02) | |||
| Jensen Alpha | (0.02) | |||
| Total Risk Alpha | (0.05) | |||
| Treynor Ratio | (3.75) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Vinci Shopping'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.
Vinci Shopping Centers Backtested Returns
We consider Vinci Shopping very steady. Vinci Shopping Centers owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0037, which indicates the fund had a 0.0037% return per unit of risk over the last 3 months. We have found twenty-four technical indicators for Vinci Shopping Centers, which you can use to evaluate the volatility of the fund. Please validate Vinci Shopping's Coefficient Of Variation of (5,182), risk adjusted performance of (0.02), and Variance of 0.1879 to confirm if the risk estimate we provide is consistent with the expected return of 0.0015%. The entity has a beta of 0.0049, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Vinci Shopping's returns are expected to increase less than the market. However, during the bear market, the loss of holding Vinci Shopping is expected to be smaller as well.
Auto-correlation | -0.32 |
Poor reverse predictability
Vinci Shopping Centers has poor reverse predictability. Overlapping area represents the amount of predictability between Vinci Shopping time series from 2nd of April 2024 to 17th of April 2024 and 17th of April 2024 to 2nd of May 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 Vinci Shopping Centers price movement. The serial correlation of -0.32 indicates that nearly 32.0% of current Vinci Shopping price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.32 | |
| Spearman Rank Test | 0.4 | |
| Residual Average | 0.0 | |
| Price Variance | 0.63 |
Vinci Shopping Centers lagged returns against current returns
Autocorrelation, which is Vinci Shopping 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 Vinci Shopping's fund expected returns. We can calculate the autocorrelation of Vinci Shopping returns to help us make a trade decision. For example, suppose you find that Vinci Shopping 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 |
Vinci Shopping 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 Vinci Shopping fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Vinci Shopping fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Vinci Shopping fund over time.
Current vs Lagged Prices |
| Timeline |
Vinci Shopping Lagged Returns
When evaluating Vinci Shopping's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Vinci Shopping fund have on its future price. Vinci Shopping 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, Vinci Shopping autocorrelation shows the relationship between Vinci Shopping fund current value and its past values and can show if there is a momentum factor associated with investing in Vinci Shopping Centers.
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 Vinci Shopping 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, Vinci Shopping's short interest history, or implied volatility extrapolated from Vinci Shopping options trading.
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Check out Vinci Shopping Correlation, Vinci Shopping Volatility and Vinci Shopping Alpha and Beta module to complement your research on Vinci Shopping. You can also try the Aroon Oscillator module to analyze current equity momentum using Aroon Oscillator and other momentum ratios.
Vinci Shopping technical fund 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, fund market cycles, or different charting patterns.