Apex Science (Taiwan) Market Value
| 3052 Stock | TWD 13.70 0.40 3.01% |
| Symbol | Apex |
Apex Science '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 Apex Science'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 Apex Science.
| 04/21/2024 |
| 05/21/2024 |
If you would invest 0.00 in Apex Science on April 21, 2024 and sell it all today you would earn a total of 0.00 from holding Apex Science Engineering or generate 0.0% return on investment in Apex Science over 30 days. Apex Science is related to or competes with Yang Ming, Wan Hai, and China Airlines. Apex Science Engineering Corp. operates as an engineering and construction manufacturing and service company worldwide More
Apex Science 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 Apex Science'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 Apex Science Engineering upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.08 | |||
| Information Ratio | 0.0501 | |||
| Maximum Drawdown | 8.55 | |||
| Value At Risk | (2.93) | |||
| Potential Upside | 3.09 |
Apex Science Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Apex Science's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Apex Science's standard deviation. In reality, there are many statistical measures that can use Apex Science historical prices to predict the future Apex Science's volatility.| Risk Adjusted Performance | 0.0608 | |||
| Jensen Alpha | 0.189 | |||
| Total Risk Alpha | (0.05) | |||
| Sortino Ratio | 0.0427 | |||
| Treynor Ratio | (0.33) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Apex Science'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.
Apex Science Engineering Backtested Returns
We consider Apex Science not too volatile. Apex Science Engineering secures Sharpe Ratio (or Efficiency) of 0.0853, which signifies that the company had a 0.0853% return per unit of standard deviation over the last 3 months. We have found thirty technical indicators for Apex Science Engineering, which you can use to evaluate the volatility of the firm. Please confirm Apex Science's mean deviation of 1.23, and Risk Adjusted Performance of 0.0608 to double-check if the risk estimate we provide is consistent with the expected return of 0.16%. Apex Science has a performance score of 6 on a scale of 0 to 100. The firm shows a Beta (market volatility) of -0.48, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning Apex Science are expected to decrease at a much lower rate. During the bear market, Apex Science is likely to outperform the market. Apex Science Engineering right now shows a risk of 1.83%. Please confirm Apex Science Engineering market risk adjusted performance, semi deviation, coefficient of variation, as well as the relationship between the mean deviation and downside deviation , to decide if Apex Science Engineering will be following its price patterns.
Auto-correlation | -0.44 |
Modest reverse predictability
Apex Science Engineering has modest reverse predictability. Overlapping area represents the amount of predictability between Apex Science time series from 21st of April 2024 to 6th of May 2024 and 6th of May 2024 to 21st 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 Apex Science Engineering price movement. The serial correlation of -0.44 indicates that just about 44.0% of current Apex Science price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.44 | |
| Spearman Rank Test | -0.09 | |
| Residual Average | 0.0 | |
| Price Variance | 0.05 |
Apex Science Engineering lagged returns against current returns
Autocorrelation, which is Apex Science 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 Apex Science's stock expected returns. We can calculate the autocorrelation of Apex Science returns to help us make a trade decision. For example, suppose you find that Apex Science 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 |
Apex Science 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 Apex Science stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Apex Science stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Apex Science stock over time.
Current vs Lagged Prices |
| Timeline |
Apex Science Lagged Returns
When evaluating Apex Science's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Apex Science stock have on its future price. Apex Science 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, Apex Science autocorrelation shows the relationship between Apex Science stock current value and its past values and can show if there is a momentum factor associated with investing in Apex Science Engineering.
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.Check out Apex Science Correlation, Apex Science Volatility and Apex Science Alpha and Beta module to complement your research on Apex Science. You can also try the Portfolio Optimization module to compute new portfolio that will generate highest expected return given your specified tolerance for risk.
Complementary Tools for Apex Stock analysis
When running Apex Science's price analysis, check to measure Apex Science's 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 Apex Science is operating at the current time. Most of Apex Science's value examination focuses on studying past and present price action to predict the probability of Apex Science's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Apex Science's price. Additionally, you may evaluate how the addition of Apex Science to your portfolios can decrease your overall portfolio volatility.
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Apex Science technical stock 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, stock market cycles, or different charting patterns.