Industrial And Commercial Stock Market Value
| IDCBF Stock | USD 0.51 0.00 0.00% |
| Symbol | Industrial |
Industrial '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 Industrial's 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 Industrial.
| 03/06/2024 |
| 05/05/2024 |
If you would invest 0.00 in Industrial on March 6, 2024 and sell it all today you would earn a total of 0.00 from holding Industrial and Commercial or generate 0.0% return on investment in Industrial over 60 days. Industrial is related to or competes with Bank of America, Bank of America, Bank of America, Bank of America, Wells Fargo, and Bank of America. Industrial and Commercial Bank of China Limited, together with its subsidiaries, provides banking products and services ... More
Industrial 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 Industrial's 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 Industrial and Commercial upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 4.03 | |||
| Information Ratio | 0.0018 | |||
| Maximum Drawdown | 17.41 | |||
| Value At Risk | (1.96) | |||
| Potential Upside | 2.0 |
Industrial Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Industrial's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Industrial's standard deviation. In reality, there are many statistical measures that can use Industrial historical prices to predict the future Industrial's volatility.| Risk Adjusted Performance | 0.0313 | |||
| Jensen Alpha | 0.1006 | |||
| Total Risk Alpha | (0.17) | |||
| Sortino Ratio | 0.001 | |||
| Treynor Ratio | (0.19) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Industrial'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.
Industrial and Commercial Backtested Returns
We consider Industrial extremely dangerous. Industrial and Commercial holds Efficiency (Sharpe) Ratio of 0.0393, which attests that the entity had a 0.0393% return per unit of risk over the last 3 months. We have found twenty-five technical indicators for Industrial and Commercial, which you can use to evaluate the volatility of the firm. Please check out Industrial's Downside Deviation of 4.03, risk adjusted performance of 0.0313, and Market Risk Adjusted Performance of (0.18) to validate if the risk estimate we provide is consistent with the expected return of 0.0873%. Industrial has a performance score of 3 on a scale of 0 to 100. The company retains a Market Volatility (i.e., Beta) of -0.39, which attests to possible diversification benefits within a given portfolio. As returns on the market increase, returns on owning Industrial are expected to decrease at a much lower rate. During the bear market, Industrial is likely to outperform the market. Industrial and Commercial right now retains a risk of 2.22%. Please check out Industrial total risk alpha, value at risk, and the relationship between the information ratio and treynor ratio , to decide if Industrial will be following its current trending patterns.
Auto-correlation | -0.66 |
Very good reverse predictability
Industrial and Commercial has very good reverse predictability. Overlapping area represents the amount of predictability between Industrial time series from 6th of March 2024 to 5th of April 2024 and 5th of April 2024 to 5th 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 Industrial and Commercial price movement. The serial correlation of -0.66 indicates that around 66.0% of current Industrial price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.66 | |
| Spearman Rank Test | -0.43 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Industrial and Commercial lagged returns against current returns
Autocorrelation, which is Industrial 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 Industrial's pink sheet expected returns. We can calculate the autocorrelation of Industrial returns to help us make a trade decision. For example, suppose you find that Industrial 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 |
Industrial 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 Industrial pink sheet is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Industrial pink sheet is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Industrial pink sheet over time.
Current vs Lagged Prices |
| Timeline |
Industrial Lagged Returns
When evaluating Industrial's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Industrial pink sheet have on its future price. Industrial 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, Industrial autocorrelation shows the relationship between Industrial pink sheet current value and its past values and can show if there is a momentum factor associated with investing in Industrial and Commercial.
Regressed Prices |
| Timeline |
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Try AI Portfolio ArchitectCheck out Industrial Correlation, Industrial Volatility and Industrial Alpha and Beta module to complement your research on Industrial. Note that the Industrial and Commercial information on this page should be used as a complementary analysis to other Industrial's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Technical Analysis module to check basic technical indicators and analysis based on most latest market data.
Complementary Tools for Industrial Pink Sheet analysis
When running Industrial's price analysis, check to measure Industrial'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 Industrial is operating at the current time. Most of Industrial's value examination focuses on studying past and present price action to predict the probability of Industrial's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Industrial's price. Additionally, you may evaluate how the addition of Industrial to your portfolios can decrease your overall portfolio volatility.
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Industrial 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.