Warehouses (Belgium) Market Value
| WDP Stock | EUR 20.72 0.60 2.98% |
| Symbol | Warehouses |
Warehouses '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 Warehouses' 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 Warehouses.
| 09/26/2024 |
| 11/25/2024 |
If you would invest 0.00 in Warehouses on September 26, 2024 and sell it all today you would earn a total of 0.00 from holding Warehouses de Pauw or generate 0.0% return on investment in Warehouses over 60 days. Warehouses is related to or competes with Aedifica, Cofinimmo, VGP NV, Sofina Socit, and Montea CVA. WDP develops and invests in logistics property More
Warehouses 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 Warehouses' 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 Warehouses de Pauw upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.27) | |||
| Maximum Drawdown | 7.36 | |||
| Value At Risk | (2.57) | |||
| Potential Upside | 1.91 |
Warehouses Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Warehouses' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Warehouses' standard deviation. In reality, there are many statistical measures that can use Warehouses historical prices to predict the future Warehouses' volatility.| Risk Adjusted Performance | (0.13) | |||
| Jensen Alpha | (0.27) | |||
| Total Risk Alpha | (0.49) | |||
| Treynor Ratio | 12.84 |
Warehouses de Pauw Backtested Returns
Warehouses de Pauw shows Sharpe Ratio of -0.17, which attests that the company had a -0.17% return per unit of risk over the last 3 months. Warehouses de Pauw exposes twenty-four different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check out Warehouses' Mean Deviation of 1.07, standard deviation of 1.42, and Market Risk Adjusted Performance of 12.85 to validate the risk estimate we provide. The firm maintains a market beta of -0.0209, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Warehouses are expected to decrease at a much lower rate. During the bear market, Warehouses is likely to outperform the market. At this point, Warehouses de Pauw has a negative expected return of -0.23%. Please make sure to check out Warehouses' kurtosis, daily balance of power, and the relationship between the skewness and accumulation distribution , to decide if Warehouses de Pauw performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.79 |
Good predictability
Warehouses de Pauw has good predictability. Overlapping area represents the amount of predictability between Warehouses time series from 26th of September 2024 to 26th of October 2024 and 26th of October 2024 to 25th 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 Warehouses de Pauw price movement. The serial correlation of 0.79 indicates that around 79.0% of current Warehouses price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.79 | |
| Spearman Rank Test | 0.75 | |
| Residual Average | 0.0 | |
| Price Variance | 0.42 |
Warehouses de Pauw lagged returns against current returns
Autocorrelation, which is Warehouses 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 Warehouses' stock expected returns. We can calculate the autocorrelation of Warehouses returns to help us make a trade decision. For example, suppose you find that Warehouses 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 |
Warehouses 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 Warehouses stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Warehouses stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Warehouses stock over time.
Current vs Lagged Prices |
| Timeline |
Warehouses Lagged Returns
When evaluating Warehouses' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Warehouses stock have on its future price. Warehouses 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, Warehouses autocorrelation shows the relationship between Warehouses stock current value and its past values and can show if there is a momentum factor associated with investing in Warehouses de Pauw.
Regressed Prices |
| Timeline |
Pair Trading with Warehouses
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 Warehouses 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 Warehouses will appreciate offsetting losses from the drop in the long position's value.Moving together with Warehouses Stock
Moving against Warehouses Stock
The ability to find closely correlated positions to Warehouses could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Warehouses 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 Warehouses - 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 Warehouses de Pauw to buy it.
The correlation of Warehouses 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 Warehouses moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Warehouses de Pauw 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 Warehouses 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.Additional Tools for Warehouses Stock Analysis
When running Warehouses' price analysis, check to measure Warehouses' 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 Warehouses is operating at the current time. Most of Warehouses' value examination focuses on studying past and present price action to predict the probability of Warehouses' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Warehouses' price. Additionally, you may evaluate how the addition of Warehouses to your portfolios can decrease your overall portfolio volatility.