Argosy Research (Taiwan) Market Value
| 3217 Stock | TWD 152.00 1.00 0.66% |
| Symbol | Argosy |
Argosy Research '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 Argosy Research'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 Argosy Research.
| 09/05/2024 |
| 12/04/2024 |
If you would invest 0.00 in Argosy Research on September 5, 2024 and sell it all today you would earn a total of 0.00 from holding Argosy Research or generate 0.0% return on investment in Argosy Research over 90 days. Argosy Research is related to or competes with TWOWAY Communications, Onyx Healthcare, Chi Hua, FarGlory Hotel, Mobiletron Electronics, Shanghai Commercial, and WinMate Communication. Argosy Research Inc. produces and sells electronic connectors and system products More
Argosy Research 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 Argosy Research'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 Argosy Research upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.21 | |||
| Information Ratio | (0.04) | |||
| Maximum Drawdown | 11.36 | |||
| Value At Risk | (2.60) | |||
| Potential Upside | 3.78 |
Argosy Research Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Argosy Research's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Argosy Research's standard deviation. In reality, there are many statistical measures that can use Argosy Research historical prices to predict the future Argosy Research's volatility.| Risk Adjusted Performance | 0.0197 | |||
| Jensen Alpha | 0.0238 | |||
| Total Risk Alpha | (0.26) | |||
| Sortino Ratio | (0.03) | |||
| Treynor Ratio | 0.9946 |
Argosy Research Backtested Returns
At this stage we consider Argosy Stock to be very steady. Argosy Research secures Sharpe Ratio (or Efficiency) of 0.0363, which signifies that the company had a 0.0363% return per unit of standard deviation over the last 3 months. We have found thirty technical indicators for Argosy Research, which you can use to evaluate the volatility of the firm. Please confirm Argosy Research's mean deviation of 1.58, and Risk Adjusted Performance of 0.0197 to double-check if the risk estimate we provide is consistent with the expected return of 0.0729%. Argosy Research has a performance score of 2 on a scale of 0 to 100. The firm shows a Beta (market volatility) of 0.0267, which signifies not very significant fluctuations relative to the market. As returns on the market increase, Argosy Research's returns are expected to increase less than the market. However, during the bear market, the loss of holding Argosy Research is expected to be smaller as well. Argosy Research right now shows a risk of 2.01%. Please confirm Argosy Research market risk adjusted performance, semi deviation, coefficient of variation, as well as the relationship between the mean deviation and downside deviation , to decide if Argosy Research will be following its price patterns.
Auto-correlation | 0.11 |
Insignificant predictability
Argosy Research has insignificant predictability. Overlapping area represents the amount of predictability between Argosy Research time series from 5th of September 2024 to 20th of October 2024 and 20th of October 2024 to 4th of December 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 Argosy Research price movement. The serial correlation of 0.11 indicates that less than 11.0% of current Argosy Research price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.11 | |
| Spearman Rank Test | -0.4 | |
| Residual Average | 0.0 | |
| Price Variance | 19.55 |
Argosy Research lagged returns against current returns
Autocorrelation, which is Argosy Research 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 Argosy Research's stock expected returns. We can calculate the autocorrelation of Argosy Research returns to help us make a trade decision. For example, suppose you find that Argosy Research 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 |
Argosy Research 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 Argosy Research stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Argosy Research stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Argosy Research stock over time.
Current vs Lagged Prices |
| Timeline |
Argosy Research Lagged Returns
When evaluating Argosy Research's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Argosy Research stock have on its future price. Argosy Research 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, Argosy Research autocorrelation shows the relationship between Argosy Research stock current value and its past values and can show if there is a momentum factor associated with investing in Argosy Research.
Regressed Prices |
| Timeline |
Pair Trading with Argosy Research
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 Argosy Research 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 Argosy Research will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Argosy Research could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Argosy Research 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 Argosy Research - 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 Argosy Research to buy it.
The correlation of Argosy Research 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 Argosy Research moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Argosy Research 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 Argosy Research 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 Argosy Stock Analysis
When running Argosy Research's price analysis, check to measure Argosy Research'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 Argosy Research is operating at the current time. Most of Argosy Research's value examination focuses on studying past and present price action to predict the probability of Argosy Research's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Argosy Research's price. Additionally, you may evaluate how the addition of Argosy Research to your portfolios can decrease your overall portfolio volatility.