Precious Selling And Marketing Expenses vs Total Revenue Analysis

MMP-UN Stock  CAD 1.80  0.01  0.55%   
Precious Metals financial indicator trend analysis is much more than just breaking down Precious Metals And prevalent accounting drivers to predict future trends. We encourage investors to analyze account correlations over time for multiple indicators to determine whether Precious Metals And is a good investment. Please check the relationship between Precious Metals Selling And Marketing Expenses and its Total Revenue accounts. Check out Correlation Analysis to better understand how to build diversified portfolios, which includes a position in Precious Metals And. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in employment.

Selling And Marketing Expenses vs Total Revenue

Selling And Marketing Expenses vs Total Revenue Correlation Analysis

The overlapping area represents the amount of trend that can be explained by analyzing historical patterns of Precious Metals And Selling And Marketing Expenses account and Total Revenue. At this time, the significance of the direction appears to have significant contrarian relationship.
The correlation between Precious Metals' Selling And Marketing Expenses and Total Revenue is -0.24. Overlapping area represents the amount of variation of Selling And Marketing Expenses that can explain the historical movement of Total Revenue in the same time period over historical financial statements of Precious Metals And, assuming nothing else is changed. The correlation between historical values of Precious Metals' Selling And Marketing Expenses and Total Revenue is a relative statistical measure of the degree to which these accounts tend to move together. The correlation coefficient measures the extent to which Selling And Marketing Expenses of Precious Metals And are associated (or correlated) with its Total Revenue. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when Total Revenue has no effect on the direction of Selling And Marketing Expenses i.e., Precious Metals' Selling And Marketing Expenses and Total Revenue go up and down completely randomly.

Correlation Coefficient

-0.24
Relationship DirectionNegative 
Relationship StrengthInsignificant

Selling And Marketing Expenses

Total Revenue

Total revenue comprises all receipts Precious Metals And generated from the sale of its products or services. The total amount of income generated by the sale of goods or services related to the company's primary operations.
Most indicators from Precious Metals' fundamental ratios are interrelated and interconnected. However, analyzing fundamental ratios indicators one by one will only give a small insight into Precious Metals And current financial condition. On the other hand, looking into the entire matrix of fundamental ratios indicators, and analyzing their relationships over time can provide a more complete picture of the company financial strength now and in the future. Check out Correlation Analysis to better understand how to build diversified portfolios, which includes a position in Precious Metals And. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in employment.
As of November 30, 2024, Selling General Administrative is expected to decline to about 248.9 K. In addition to that, Sales General And Administrative To Revenue is expected to decline to 1.07
 2021 2022 2023 2024 (projected)
Total Operating Expenses425K321K8K7.6K
Cost Of Revenue662K512K488K873.2K

Precious Metals fundamental ratios Correlations

0.40.61.0-0.830.940.830.040.690.50.690.960.60.040.91-0.710.680.760.64-0.330.520.550.580.540.58
0.40.970.35-0.520.140.520.720.83-0.280.750.390.970.720.74-0.480.530.520.5-0.210.360.330.370.310.36
0.60.970.56-0.610.360.610.620.87-0.130.810.61.00.630.88-0.580.640.630.59-0.250.420.40.450.390.44
1.00.350.56-0.820.950.820.00.660.530.670.960.560.00.89-0.70.660.750.63-0.330.510.540.570.530.57
-0.83-0.52-0.61-0.82-0.76-1.0-0.28-0.84-0.3-0.66-0.79-0.62-0.29-0.810.64-0.52-0.67-0.570.29-0.5-0.46-0.5-0.45-0.49
0.940.140.360.95-0.760.76-0.110.550.50.420.950.37-0.110.75-0.490.550.540.49-0.230.360.360.390.350.39
0.830.520.610.82-1.00.760.280.840.30.660.790.620.290.81-0.640.520.670.57-0.290.50.460.50.450.49
0.040.720.620.0-0.28-0.110.280.53-0.320.370.070.621.00.34-0.170.070.17-0.04-0.380.350.160.30.20.26
0.690.830.870.66-0.840.550.840.53-0.10.710.70.870.530.86-0.50.620.550.54-0.150.280.320.340.340.34
0.5-0.28-0.130.53-0.30.50.3-0.32-0.10.340.34-0.13-0.320.23-0.630.310.590.29-0.370.650.580.650.630.64
0.690.750.810.67-0.660.420.660.370.710.340.540.810.370.85-0.890.690.940.66-0.480.690.790.80.790.81
0.960.390.60.96-0.790.950.790.070.70.340.540.60.080.88-0.530.60.580.55-0.210.370.370.40.360.4
0.60.971.00.56-0.620.370.620.620.87-0.130.810.60.620.88-0.580.640.630.59-0.250.420.410.450.390.44
0.040.720.630.0-0.29-0.110.291.00.53-0.320.370.080.620.34-0.170.080.18-0.04-0.380.350.160.30.20.27
0.910.740.880.89-0.810.750.810.340.860.230.850.880.880.34-0.730.740.790.69-0.330.530.560.590.550.59
-0.71-0.48-0.58-0.70.64-0.49-0.64-0.17-0.5-0.63-0.89-0.53-0.58-0.17-0.73-0.61-0.93-0.620.52-0.8-0.84-0.87-0.82-0.88
0.680.530.640.66-0.520.550.520.070.620.310.690.60.640.080.74-0.610.660.71-0.220.360.480.490.450.49
0.760.520.630.75-0.670.540.670.170.550.590.940.580.630.180.79-0.930.660.68-0.570.750.820.850.840.85
0.640.50.590.63-0.570.490.57-0.040.540.290.660.550.59-0.040.69-0.620.710.68-0.140.380.270.360.230.34
-0.33-0.21-0.25-0.330.29-0.23-0.29-0.38-0.15-0.37-0.48-0.21-0.25-0.38-0.330.52-0.22-0.57-0.14-0.59-0.66-0.76-0.6-0.73
0.520.360.420.51-0.50.360.50.350.280.650.690.370.420.350.53-0.80.360.750.38-0.590.740.90.730.87
0.550.330.40.54-0.460.360.460.160.320.580.790.370.410.160.56-0.840.480.820.27-0.660.740.930.950.95
0.580.370.450.57-0.50.390.50.30.340.650.80.40.450.30.59-0.870.490.850.36-0.760.90.930.910.99
0.540.310.390.53-0.450.350.450.20.340.630.790.360.390.20.55-0.820.450.840.23-0.60.730.950.910.92
0.580.360.440.57-0.490.390.490.260.340.640.810.40.440.270.59-0.880.490.850.34-0.730.870.950.990.92
Click cells to compare fundamentals

Precious Metals Account Relationship Matchups

Precious Metals fundamental ratios Accounts

201920202021202220232024 (projected)
Total Assets29.0M35.7M30.9M23.2M19.7M18.7M
Other Current Liab118K(140K)(13K)(3K)284K269.8K
Total Current Liabilities289K140K141K119K391K371.5K
Total Stockholder Equity28.8M35.4M30.6M22.9M19.4M18.5M
Net Debt(164K)(1.3M)(585K)(575K)(282K)(296.1K)
Accounts Payable171K140K13K3K107K101.7K
Cash164K1.3M585K575K282K267.9K
Cash And Short Term Investments28.9M1.3M585K575K19.7M34.2M
Net Receivables1K110K32K81K8K11.4K
Common Stock Shares Outstanding18.1M16.3M13.7M12.5M11.4M14.4M
Short Term Investments28.8M34.3M30.2M22.6M19.4M18.5M
Liabilities And Stockholders Equity29.0M35.7M30.9M23.2M19.7M18.7M
Total Liab289K140K141K119K284K269.8K
Total Current Assets29.0M1.4M666K586K19.7M34.4M
Non Current Assets Total28.8M34.3M30.2M22.6M19.4M18.5M
Other Current Assets63.0(27.9M)0.03K1K950.0
Common Stock28.8M35.4M30.6M22.9M19.4M29.0M
Non Currrent Assets Other(28.8M)(34.3M)(30.2M)(22.6M)(19.4M)(20.4M)
Non Current Liabilities Total289K266K263K328K284K313.2K
Net Tangible Assets27.3M28.8M35.4M30.6M27.6M25.7M
Long Term Investments28.8M34.3M30.2M22.6M19.4M22.7M

Pair Trading with Precious Metals

One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if Precious Metals position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Precious Metals will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Precious Metals could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Precious Metals when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back Precious Metals - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling Precious Metals And to buy it.
The correlation of Precious Metals is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as Precious Metals moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Precious Metals And moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for Precious Metals can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.
Pair CorrelationCorrelation Matching

Other Information on Investing in Precious Stock

Balance Sheet is a snapshot of the financial position of Precious Metals And at a specified time, usually calculated after every quarter, six months, or one year. Precious Metals Balance Sheet has two main parts: assets and liabilities. Liabilities are the debts or obligations of Precious Metals and are divided into current liabilities and long term liabilities. An asset, on the other hand, is anything of value that can be converted into cash and which Precious currently owns. An asset can also be divided into two categories, current and non-current.