Matahari Department (Indonesia) Market Value
| LPPF Stock | IDR 1,555 15.00 0.96% |
| Symbol | Matahari |
Matahari Department '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 Matahari Department'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 Matahari Department.
| 02/04/2024 |
| 05/04/2024 |
If you would invest 0.00 in Matahari Department on February 4, 2024 and sell it all today you would earn a total of 0.00 from holding Matahari Department Store or generate 0.0% return on investment in Matahari Department over 90 days. Matahari Department is related to or competes with Telkom Indonesia, Bank Mandiri, Bank Central, Indofood Sukses, and Unilever Indonesia. More
Matahari Department 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 Matahari Department'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 Matahari Department Store upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.18) | |||
| Maximum Drawdown | 11.24 | |||
| Value At Risk | (3.42) | |||
| Potential Upside | 3.11 |
Matahari Department Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Matahari Department's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Matahari Department's standard deviation. In reality, there are many statistical measures that can use Matahari Department historical prices to predict the future Matahari Department's volatility.| Risk Adjusted Performance | (0.09) | |||
| Jensen Alpha | (0.28) | |||
| Total Risk Alpha | (0.46) | |||
| Treynor Ratio | 0.3548 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Matahari Department'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.
Matahari Department Store Backtested Returns
Matahari Department Store has Sharpe Ratio of -0.15, which conveys that the firm had a -0.15% return per unit of risk over the last 3 months. Matahari Department exposes twenty-three different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please verify Matahari Department's Mean Deviation of 1.53, risk adjusted performance of (0.09), and Standard Deviation of 2.06 to check out the risk estimate we provide. The company secures a Beta (Market Risk) of -0.9, which conveys possible diversification benefits within a given portfolio. As the market becomes more bullish, returns on owning Matahari Department are expected to decrease slowly. On the other hand, during market turmoil, Matahari Department is expected to outperform it slightly. Matahari Department Store has an expected return of -0.31%. Please make sure to verify Matahari Department Store skewness, accumulation distribution, and the relationship between the potential upside and kurtosis , to decide if Matahari Department Store performance from the past will be repeated at some point in the near future.
Auto-correlation | 0.41 |
Average predictability
Matahari Department Store has average predictability. Overlapping area represents the amount of predictability between Matahari Department time series from 4th of February 2024 to 20th of March 2024 and 20th of March 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 Matahari Department Store price movement. The serial correlation of 0.41 indicates that just about 41.0% of current Matahari Department price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.41 | |
| Spearman Rank Test | 0.3 | |
| Residual Average | 0.0 | |
| Price Variance | 2417.72 |
Matahari Department Store lagged returns against current returns
Autocorrelation, which is Matahari Department 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 Matahari Department's stock expected returns. We can calculate the autocorrelation of Matahari Department returns to help us make a trade decision. For example, suppose you find that Matahari Department 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 |
Matahari Department 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 Matahari Department stock is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Matahari Department stock is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Matahari Department stock over time.
Current vs Lagged Prices |
| Timeline |
Matahari Department Lagged Returns
When evaluating Matahari Department's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Matahari Department stock have on its future price. Matahari Department 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, Matahari Department autocorrelation shows the relationship between Matahari Department stock current value and its past values and can show if there is a momentum factor associated with investing in Matahari Department Store.
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 Matahari Department 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, Matahari Department's short interest history, or implied volatility extrapolated from Matahari Department options trading.
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Complementary Tools for Matahari Stock analysis
When running Matahari Department's price analysis, check to measure Matahari Department'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 Matahari Department is operating at the current time. Most of Matahari Department's value examination focuses on studying past and present price action to predict the probability of Matahari Department's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Matahari Department's price. Additionally, you may evaluate how the addition of Matahari Department to your portfolios can decrease your overall portfolio volatility.
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Matahari Department 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.