Liontown Resources Limited Stock Market Value
| LINRF Stock | USD 0.88 0.03 3.53% |
| Symbol | Liontown |
Liontown Resources '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 Liontown Resources' pink sheet 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 Liontown Resources.
| 03/04/2024 |
| 06/02/2024 |
If you would invest 0.00 in Liontown Resources on March 4, 2024 and sell it all today you would earn a total of 0.00 from holding Liontown Resources Limited or generate 0.0% return on investment in Liontown Resources over 90 days. Liontown Resources is related to or competes with HUMANA, Barloworld, Morningstar Unconstrained, Thrivent High, High-yield Municipal, and Via Renewables. Liontown Resources Limited engages in the exploration, evaluation, and development of mineral properties in Australia More
Liontown Resources 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 Liontown Resources' pink sheet 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 Liontown Resources Limited upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 4.6 | |||
| Information Ratio | 0.0314 | |||
| Maximum Drawdown | 20.88 | |||
| Value At Risk | (6.59) | |||
| Potential Upside | 7.5 |
Liontown Resources Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Liontown Resources' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Liontown Resources' standard deviation. In reality, there are many statistical measures that can use Liontown Resources historical prices to predict the future Liontown Resources' volatility.| Risk Adjusted Performance | 0.0346 | |||
| Jensen Alpha | 0.1185 | |||
| Total Risk Alpha | (0.07) | |||
| Sortino Ratio | 0.0301 | |||
| Treynor Ratio | 0.1111 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Liontown Resources' 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.
Liontown Resources Backtested Returns
We consider Liontown Resources abnormally volatile. Liontown Resources has Sharpe Ratio of 0.0252, which conveys that the firm had a 0.0252% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Liontown Resources, which you can use to evaluate the volatility of the firm. Please verify Liontown Resources' Mean Deviation of 3.24, downside deviation of 4.6, and Risk Adjusted Performance of 0.0346 to check out if the risk estimate we provide is consistent with the expected return of 0.11%. Liontown Resources has a performance score of 1 on a scale of 0 to 100. The company secures a Beta (Market Risk) of 1.56, which conveys a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Liontown Resources will likely underperform. Liontown Resources right now secures a risk of 4.29%. Please verify Liontown Resources Limited treynor ratio and the relationship between the downside variance and day typical price , to decide if Liontown Resources Limited will be following its current price movements.
Auto-correlation | -0.61 |
Very good reverse predictability
Liontown Resources Limited has very good reverse predictability. Overlapping area represents the amount of predictability between Liontown Resources time series from 4th of March 2024 to 18th of April 2024 and 18th of April 2024 to 2nd of June 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 Liontown Resources price movement. The serial correlation of -0.61 indicates that roughly 61.0% of current Liontown Resources price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.61 | |
| Spearman Rank Test | -0.32 | |
| Residual Average | 0.0 | |
| Price Variance | 0.01 |
Liontown Resources lagged returns against current returns
Autocorrelation, which is Liontown Resources pink sheet'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 Liontown Resources' pink sheet expected returns. We can calculate the autocorrelation of Liontown Resources returns to help us make a trade decision. For example, suppose you find that Liontown Resources has exhibited high autocorrelation historically, and you observe that the pink sheet 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 |
Liontown Resources 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 Liontown Resources pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Liontown Resources pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Liontown Resources pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Liontown Resources Lagged Returns
When evaluating Liontown Resources' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Liontown Resources pink sheet have on its future price. Liontown Resources 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, Liontown Resources autocorrelation shows the relationship between Liontown Resources pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Liontown Resources Limited.
Regressed Prices |
| Timeline |
Currently Active Assets on Macroaxis
Check out Liontown Resources Correlation, Liontown Resources Volatility and Liontown Resources Alpha and Beta module to complement your research on Liontown Resources. You can also try the Analyst Advice module to analyst recommendations and target price estimates broken down by several categories.
Complementary Tools for Liontown Pink Sheet analysis
When running Liontown Resources' price analysis, check to measure Liontown Resources' 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 Liontown Resources is operating at the current time. Most of Liontown Resources' value examination focuses on studying past and present price action to predict the probability of Liontown Resources' future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Liontown Resources' price. Additionally, you may evaluate how the addition of Liontown Resources to your portfolios can decrease your overall portfolio volatility.
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Liontown Resources technical pink sheet 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, pink sheet market cycles, or different charting patterns.