Lithium Power International Stock Current Liabilities
LTHHFDelisted Stock | USD 0.22 0.00 0.00% |
Lithium Power International fundamentals help investors to digest information that contributes to Lithium Power's financial success or failures. It also enables traders to predict the movement of Lithium Pink Sheet. The fundamental analysis module provides a way to measure Lithium Power's intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Lithium Power pink sheet.
Lithium |
Lithium Power International Company Current Liabilities Analysis
Lithium Power's Current Liabilities is the company's short term debt. This usually includes obligations that are due within the next 12 months or within one fiscal year. Current liabilities are very important in analyzing a company's financial health as it requires the company to convert some of its current assets into cash.
Current liabilities appear on the company's balance sheet and include all short term debt accounts, accounts and notes payable, accrued liabilities as well as current payments due on the long-term loans. One of the most useful applications of Current Liabilities is the current ratio which is defined as current assets divided by its current liabilities. High current ratios mean that current assets are more than sufficient to pay off current liabilities.
CompetitionIn accordance with the recently published financial statements, Lithium Power International has a Current Liabilities of 0.0. This is 100.0% lower than that of the Basic Materials sector and about the same as Other Industrial Metals & Mining (which currently averages 0.0) industry. The current liabilities for all United States stocks is 100.0% higher than that of the company.
Lithium Current Liabilities Peer Comparison
Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Lithium Power's direct or indirect competition against its Current Liabilities to detect undervalued stocks with similar characteristics or determine the pink sheets which would be a good addition to a portfolio. Peer analysis of Lithium Power could also be used in its relative valuation, which is a method of valuing Lithium Power by comparing valuation metrics of similar companies.Lithium Power is currently under evaluation in current liabilities category among its peers.
Lithium Fundamentals
Return On Equity | -0.31 | |||
Return On Asset | -0.0459 | |||
Current Valuation | 125.54 M | |||
Shares Outstanding | 629.1 M | |||
Shares Owned By Insiders | 35.31 % | |||
Shares Owned By Institutions | 9.86 % | |||
Price To Book | 4.48 X | |||
Price To Sales | 385,514 X | |||
Revenue | 349 | |||
Gross Profit | 349 | |||
EBITDA | (12.64 M) | |||
Net Income | (12.89 M) | |||
Cash And Equivalents | 6.43 M | |||
Cash Per Share | 0.02 X | |||
Debt To Equity | 15.10 % | |||
Current Ratio | 15.40 X | |||
Book Value Per Share | 0.12 X | |||
Cash Flow From Operations | (3.59 M) | |||
Earnings Per Share | (0.03) X | |||
Beta | 1.0 | |||
Market Capitalization | 181.65 M | |||
Total Asset | 42.66 M | |||
Net Asset | 42.66 M |
About Lithium Power Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Lithium Power International's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Lithium Power using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Lithium Power International based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
Please read more on our fundamental analysis page.
Currently Active Assets on Macroaxis
Check out Correlation Analysis to better understand how to build diversified portfolios. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in rate. You can also try the Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
Other Consideration for investing in Lithium Pink Sheet
If you are still planning to invest in Lithium Power Intern check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Lithium Power's history and understand the potential risks before investing.
Watchlist Optimization Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm | |
Performance Analysis Check effects of mean-variance optimization against your current asset allocation | |
Content Syndication Quickly integrate customizable finance content to your own investment portal | |
Earnings Calls Check upcoming earnings announcements updated hourly across public exchanges | |
Top Crypto Exchanges Search and analyze digital assets across top global cryptocurrency exchanges | |
Competition Analyzer Analyze and compare many basic indicators for a group of related or unrelated entities | |
AI Portfolio Architect Use AI to generate optimal portfolios and find profitable investment opportunities | |
Equity Forecasting Use basic forecasting models to generate price predictions and determine price momentum | |
Volatility Analysis Get historical volatility and risk analysis based on latest market data |