OSOTSPA PCL (Thailand) Market Value
| OSP-R Stock | 20.83 0.29 1.37% |
| Symbol | OSOTSPA |
OSOTSPA PCL '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 OSOTSPA PCL'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 OSOTSPA PCL.
| 10/24/2024 |
| 11/23/2024 |
If you would invest 0.00 in OSOTSPA PCL on October 24, 2024 and sell it all today you would earn a total of 0.00 from holding OSOTSPA PCL NVDR or generate 0.0% return on investment in OSOTSPA PCL over 30 days.
OSOTSPA PCL 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 OSOTSPA PCL'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 OSOTSPA PCL NVDR upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.17) | |||
| Maximum Drawdown | 26.15 |
OSOTSPA PCL Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for OSOTSPA PCL's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as OSOTSPA PCL's standard deviation. In reality, there are many statistical measures that can use OSOTSPA PCL historical prices to predict the future OSOTSPA PCL's volatility.| Risk Adjusted Performance | (0.09) | |||
| Jensen Alpha | (0.44) | |||
| Total Risk Alpha | (0.90) | |||
| Treynor Ratio | (1.55) |
OSOTSPA PCL NVDR Backtested Returns
OSOTSPA PCL NVDR maintains Sharpe Ratio (i.e., Efficiency) of -0.12, which implies the firm had a -0.12% return per unit of volatility over the last 3 months. OSOTSPA PCL NVDR exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check OSOTSPA PCL's coefficient of variation of (800.12), and Risk Adjusted Performance of (0.09) to confirm the risk estimate we provide. The company holds a Beta of 0.26, which implies not very significant fluctuations relative to the market. As returns on the market increase, OSOTSPA PCL's returns are expected to increase less than the market. However, during the bear market, the loss of holding OSOTSPA PCL is expected to be smaller as well. At this point, OSOTSPA PCL NVDR has a negative expected return of -0.4%. Please make sure to check OSOTSPA PCL's accumulation distribution, as well as the relationship between the day typical price and relative strength index , to decide if OSOTSPA PCL NVDR performance from the past will be repeated at some future point.
Auto-correlation | 0.00 |
No correlation between past and present
OSOTSPA PCL NVDR has no correlation between past and present. Overlapping area represents the amount of predictability between OSOTSPA PCL time series from 24th of October 2024 to 8th of November 2024 and 8th of November 2024 to 23rd 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 OSOTSPA PCL NVDR price movement. The serial correlation of 0.0 indicates that just 0.0% of current OSOTSPA PCL price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.0 | |
| Spearman Rank Test | -0.47 | |
| Residual Average | 0.0 | |
| Price Variance | 11.97 |
OSOTSPA PCL NVDR lagged returns against current returns
Autocorrelation, which is OSOTSPA PCL 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 OSOTSPA PCL's stock expected returns. We can calculate the autocorrelation of OSOTSPA PCL returns to help us make a trade decision. For example, suppose you find that OSOTSPA PCL 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 |
OSOTSPA PCL 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 OSOTSPA PCL stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if OSOTSPA PCL stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in OSOTSPA PCL stock over time.
Current vs Lagged Prices |
| Timeline |
OSOTSPA PCL Lagged Returns
When evaluating OSOTSPA PCL's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of OSOTSPA PCL stock have on its future price. OSOTSPA PCL 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, OSOTSPA PCL autocorrelation shows the relationship between OSOTSPA PCL stock current value and its past values and can show if there is a momentum factor associated with investing in OSOTSPA PCL NVDR.
Regressed Prices |
| Timeline |
Building efficient market-beating portfolios requires time, education, and a lot of computing power!
The Portfolio Architect is an AI-driven system that provides multiple benefits to our users by leveraging cutting-edge machine learning algorithms, statistical analysis, and predictive modeling to automate the process of asset selection and portfolio construction, saving time and reducing human error for individual and institutional investors.
Try AI Portfolio Architect