Unifosa (Taiwan) Market Value
| 8277 Stock | TWD 11.85 0.05 0.42% |
| Symbol | Unifosa |
Unifosa '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 Unifosa'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 Unifosa.
| 04/01/2024 |
| 05/01/2024 |
If you would invest 0.00 in Unifosa on April 1, 2024 and sell it all today you would earn a total of 0.00 from holding Unifosa or generate 0.0% return on investment in Unifosa over 30 days. Unifosa is related to or competes with Taiwan Semiconductor, MediaTek, United Microelectronics, Novatek Microelectronics, GlobalWafers, Realtek Semiconductor, and Global Unichip. Unifosa Corp. operates as a memory modules ODMOEM company in Taiwan More
Unifosa 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 Unifosa'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 Unifosa upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.07) | |||
| Maximum Drawdown | 6.66 | |||
| Value At Risk | (1.68) | |||
| Potential Upside | 1.72 |
Unifosa Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Unifosa's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Unifosa's standard deviation. In reality, there are many statistical measures that can use Unifosa historical prices to predict the future Unifosa's volatility.| Risk Adjusted Performance | (0.01) | |||
| Jensen Alpha | (0.04) | |||
| Total Risk Alpha | (0.12) | |||
| Treynor Ratio | (0.39) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Unifosa'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.
Unifosa Backtested Returns
We consider Unifosa very steady. Unifosa owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0124, which indicates the firm had a 0.0124% return per unit of risk over the last 3 months. We have found twenty-three technical indicators for Unifosa, which you can use to evaluate the volatility of the company. Please validate Unifosa's Risk Adjusted Performance of (0.01), variance of 1.29, and Coefficient Of Variation of (4,458) to confirm if the risk estimate we provide is consistent with the expected return of 0.0146%. The entity has a beta of 0.0916, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Unifosa's returns are expected to increase less than the market. However, during the bear market, the loss of holding Unifosa is expected to be smaller as well. Unifosa right now has a risk of 1.18%. Please validate Unifosa mean deviation, standard deviation, total risk alpha, as well as the relationship between the coefficient of variation and jensen alpha , to decide if Unifosa will be following its existing price patterns.
Auto-correlation | -0.08 |
Very weak reverse predictability
Unifosa has very weak reverse predictability. Overlapping area represents the amount of predictability between Unifosa time series from 1st of April 2024 to 16th of April 2024 and 16th of April 2024 to 1st 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 Unifosa price movement. The serial correlation of -0.08 indicates that barely 8.0% of current Unifosa price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.08 | |
| Spearman Rank Test | -0.13 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Unifosa lagged returns against current returns
Autocorrelation, which is Unifosa 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 Unifosa's stock expected returns. We can calculate the autocorrelation of Unifosa returns to help us make a trade decision. For example, suppose you find that Unifosa 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 |
Unifosa 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 Unifosa stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Unifosa stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Unifosa stock over time.
Current vs Lagged Prices |
| Timeline |
Unifosa Lagged Returns
When evaluating Unifosa's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Unifosa stock have on its future price. Unifosa 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, Unifosa autocorrelation shows the relationship between Unifosa stock current value and its past values and can show if there is a momentum factor associated with investing in Unifosa.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Unifosa in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Unifosa's short interest history, or implied volatility extrapolated from Unifosa options trading.
Thematic Opportunities
Explore Investment Opportunities
Check out Unifosa Correlation, Unifosa Volatility and Unifosa Alpha and Beta module to complement your research on Unifosa. You can also try the Instant Ratings module to determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance.
Complementary Tools for Unifosa Stock analysis
When running Unifosa's price analysis, check to measure Unifosa'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 Unifosa is operating at the current time. Most of Unifosa's value examination focuses on studying past and present price action to predict the probability of Unifosa's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Unifosa's price. Additionally, you may evaluate how the addition of Unifosa to your portfolios can decrease your overall portfolio volatility.
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Unifosa 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.