PT Sarimelati (Indonesia) Market Value
| PZZA Stock | IDR 260.00 16.00 5.80% |
| Symbol | PZZA |
PT Sarimelati '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 PT Sarimelati'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 PT Sarimelati.
| 04/04/2024 |
| 05/04/2024 |
If you would invest 0.00 in PT Sarimelati on April 4, 2024 and sell it all today you would earn a total of 0.00 from holding PT Sarimelati Kencana or generate 0.0% return on investment in PT Sarimelati over 30 days. PT Sarimelati is related to or competes with Telkom Indonesia, Bank Mandiri, Bank Central, Indofood Sukses, and Unilever Indonesia. More
PT Sarimelati 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 PT Sarimelati'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 PT Sarimelati Kencana upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.37) | |||
| Maximum Drawdown | 8.51 | |||
| Value At Risk | (3.01) | |||
| Potential Upside | 1.45 |
PT Sarimelati Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for PT Sarimelati's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as PT Sarimelati's standard deviation. In reality, there are many statistical measures that can use PT Sarimelati historical prices to predict the future PT Sarimelati's volatility.| Risk Adjusted Performance | (0.19) | |||
| Jensen Alpha | (0.53) | |||
| Total Risk Alpha | (0.72) | |||
| Treynor Ratio | 4.01 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of PT Sarimelati'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.
PT Sarimelati Kencana Backtested Returns
PT Sarimelati Kencana retains Efficiency (Sharpe Ratio) of -0.3, which implies the firm had a -0.3% return per unit of price deviation over the last 3 months. PT Sarimelati exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please check PT Sarimelati's market risk adjusted performance of 4.02, and Information Ratio of (0.37) to confirm the risk estimate we provide. The company owns a Beta (Systematic Risk) of -0.13, which implies not very significant fluctuations relative to the market. As returns on the market increase, returns on owning PT Sarimelati are expected to decrease at a much lower rate. During the bear market, PT Sarimelati is likely to outperform the market. PT Sarimelati Kencana has an expected return of -0.51%. Please make sure to check PT Sarimelati Kencana coefficient of variation, jensen alpha, and the relationship between the mean deviation and standard deviation , to decide if PT Sarimelati Kencana performance from the past will be repeated at some future date.
Auto-correlation | -0.55 |
Good reverse predictability
PT Sarimelati Kencana has good reverse predictability. Overlapping area represents the amount of predictability between PT Sarimelati time series from 4th of April 2024 to 19th of April 2024 and 19th of April 2024 to 4th 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 PT Sarimelati Kencana price movement. The serial correlation of -0.55 indicates that about 55.0% of current PT Sarimelati price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.55 | |
| Spearman Rank Test | 0.37 | |
| Residual Average | 0.0 | |
| Price Variance | 12.56 |
PT Sarimelati Kencana lagged returns against current returns
Autocorrelation, which is PT Sarimelati 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 PT Sarimelati's stock expected returns. We can calculate the autocorrelation of PT Sarimelati returns to help us make a trade decision. For example, suppose you find that PT Sarimelati 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 |
PT Sarimelati 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 PT Sarimelati stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if PT Sarimelati stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in PT Sarimelati stock over time.
Current vs Lagged Prices |
| Timeline |
PT Sarimelati Lagged Returns
When evaluating PT Sarimelati's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of PT Sarimelati stock have on its future price. PT Sarimelati 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, PT Sarimelati autocorrelation shows the relationship between PT Sarimelati stock current value and its past values and can show if there is a momentum factor associated with investing in PT Sarimelati Kencana.
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 PT Sarimelati 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, PT Sarimelati's short interest history, or implied volatility extrapolated from PT Sarimelati options trading.
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Check out PT Sarimelati Correlation, PT Sarimelati Volatility and PT Sarimelati Alpha and Beta module to complement your research on PT Sarimelati. You can also try the Commodity Channel module to use Commodity Channel Index to analyze current equity momentum.
Complementary Tools for PZZA Stock analysis
When running PT Sarimelati's price analysis, check to measure PT Sarimelati'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 PT Sarimelati is operating at the current time. Most of PT Sarimelati's value examination focuses on studying past and present price action to predict the probability of PT Sarimelati's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move PT Sarimelati's price. Additionally, you may evaluate how the addition of PT Sarimelati to your portfolios can decrease your overall portfolio volatility.
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PT Sarimelati 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.