Silicon Power (Taiwan) Market Value
| 4973 Stock | TWD 24.40 0.25 1.01% |
| Symbol | Silicon |
Silicon Power '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 Silicon Power'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 Silicon Power.
| 04/21/2025 |
| 07/20/2025 |
If you would invest 0.00 in Silicon Power on April 21, 2025 and sell it all today you would earn a total of 0.00 from holding Silicon Power Computer or generate 0.0% return on investment in Silicon Power over 90 days. Silicon Power is related to or competes with Avalue Technology, GMI Technology, Excellence Optoelectronic, Song Shang, Kinsus Interconnect, STL Technology, and Sitronix Technology. More
Silicon Power 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 Silicon Power'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 Silicon Power Computer upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 2.79 | |||
| Information Ratio | (0.01) | |||
| Maximum Drawdown | 16.54 | |||
| Value At Risk | (5.19) | |||
| Potential Upside | 8.3 |
Silicon Power Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Silicon Power's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Silicon Power's standard deviation. In reality, there are many statistical measures that can use Silicon Power historical prices to predict the future Silicon Power's volatility.| Risk Adjusted Performance | 0.0373 | |||
| Jensen Alpha | 0.0753 | |||
| Total Risk Alpha | (0.38) | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.5318 |
Silicon Power Computer Backtested Returns
Silicon Power Computer owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.0377, which indicates the firm had a -0.0377 % return per unit of risk over the last 3 months. Silicon Power Computer exposes thirty different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Silicon Power's Risk Adjusted Performance of 0.0373, coefficient of variation of 3107.1, and Semi Deviation of 2.51 to confirm the risk estimate we provide. The entity has a beta of 0.19, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Silicon Power's returns are expected to increase less than the market. However, during the bear market, the loss of holding Silicon Power is expected to be smaller as well. At this point, Silicon Power Computer has a negative expected return of -0.12%. Please make sure to validate Silicon Power's semi deviation, coefficient of variation, jensen alpha, as well as the relationship between the downside deviation and standard deviation , to decide if Silicon Power Computer performance from the past will be repeated at some point in the near future.
Auto-correlation | -0.09 |
Very weak reverse predictability
Silicon Power Computer has very weak reverse predictability. Overlapping area represents the amount of predictability between Silicon Power time series from 21st of April 2025 to 5th of June 2025 and 5th of June 2025 to 20th of July 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Silicon Power Computer price movement. The serial correlation of -0.09 indicates that less than 9.0% of current Silicon Power price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.09 | |
| Spearman Rank Test | 0.15 | |
| Residual Average | 0.0 | |
| Price Variance | 1.04 |
Silicon Power Computer lagged returns against current returns
Autocorrelation, which is Silicon Power 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 Silicon Power's stock expected returns. We can calculate the autocorrelation of Silicon Power returns to help us make a trade decision. For example, suppose you find that Silicon Power 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 |
Silicon Power 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 Silicon Power stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Silicon Power stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Silicon Power stock over time.
Current vs Lagged Prices |
| Timeline |
Silicon Power Lagged Returns
When evaluating Silicon Power's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Silicon Power stock have on its future price. Silicon Power 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, Silicon Power autocorrelation shows the relationship between Silicon Power stock current value and its past values and can show if there is a momentum factor associated with investing in Silicon Power Computer.
Regressed Prices |
| Timeline |
Pair Trading with Silicon Power
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 Silicon Power 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 Silicon Power will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Silicon Power could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Silicon Power 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 Silicon Power - 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 Silicon Power Computer to buy it.
The correlation of Silicon Power 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 Silicon Power moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Silicon Power Computer 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 Silicon Power 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 Silicon Stock Analysis
When running Silicon Power's price analysis, check to measure Silicon Power'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 Silicon Power is operating at the current time. Most of Silicon Power's value examination focuses on studying past and present price action to predict the probability of Silicon Power's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Silicon Power's price. Additionally, you may evaluate how the addition of Silicon Power to your portfolios can decrease your overall portfolio volatility.