Real Estate (Vietnam) Market Value
| D11 Stock | 10,300 0.00 0.00% |
| Symbol | Real |
Real Estate '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 Real Estate'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 Real Estate.
| 06/08/2023 |
| 11/29/2024 |
If you would invest 0.00 in Real Estate on June 8, 2023 and sell it all today you would earn a total of 0.00 from holding Real Estate 11 or generate 0.0% return on investment in Real Estate over 540 days.
Real Estate 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 Real Estate'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 Real Estate 11 upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.13) | |||
| Maximum Drawdown | 10.63 | |||
| Value At Risk | (3.45) | |||
| Potential Upside | 2.7 |
Real Estate Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Real Estate's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Real Estate's standard deviation. In reality, there are many statistical measures that can use Real Estate historical prices to predict the future Real Estate's volatility.| Risk Adjusted Performance | (0.05) | |||
| Jensen Alpha | (0.13) | |||
| Total Risk Alpha | (0.44) | |||
| Treynor Ratio | 1.05 |
Real Estate 11 Backtested Returns
Real Estate 11 maintains Sharpe Ratio (i.e., Efficiency) of -0.081, which implies the firm had a -0.081% return per unit of risk over the last 3 months. Real Estate 11 exposes twenty-one different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check Real Estate's Risk Adjusted Performance of (0.05), variance of 3.74, and Coefficient Of Variation of (1,431) to confirm the risk estimate we provide. The company holds a Beta of -0.14, which implies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Real Estate are expected to decrease at a much lower rate. During the bear market, Real Estate is likely to outperform the market. At this point, Real Estate 11 has a negative expected return of -0.17%. Please make sure to check Real Estate's mean deviation, information ratio, potential upside, as well as the relationship between the standard deviation and total risk alpha , to decide if Real Estate 11 performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.63 |
Good predictability
Real Estate 11 has good predictability. Overlapping area represents the amount of predictability between Real Estate time series from 8th of June 2023 to 4th of March 2024 and 4th of March 2024 to 29th of November 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 Real Estate 11 price movement. The serial correlation of 0.63 indicates that roughly 63.0% of current Real Estate price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.63 | |
| Spearman Rank Test | 0.53 | |
| Residual Average | 0.0 | |
| Price Variance | 271.3 K |
Real Estate 11 lagged returns against current returns
Autocorrelation, which is Real Estate 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 Real Estate's stock expected returns. We can calculate the autocorrelation of Real Estate returns to help us make a trade decision. For example, suppose you find that Real Estate 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 |
Real Estate 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 Real Estate stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Real Estate stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Real Estate stock over time.
Current vs Lagged Prices |
| Timeline |
Real Estate Lagged Returns
When evaluating Real Estate's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Real Estate stock have on its future price. Real Estate 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, Real Estate autocorrelation shows the relationship between Real Estate stock current value and its past values and can show if there is a momentum factor associated with investing in Real Estate 11.
Regressed Prices |
| Timeline |
Pair Trading with Real Estate
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Real Estate position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Real Estate will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Real Estate could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Real Estate when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Real Estate - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Real Estate 11 to buy it.
The correlation of Real Estate is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Real Estate moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Real Estate 11 moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Real Estate can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.