Compare Agilyx to BQE, EcoPlus, Charah, Anaergia, BacTech

Comparing Agilyx to BQE, EcoPlus, Charah, Anaergia, BacTech can provide valuable insights into potential diversification opportunities when combining these positions into a portfolio. By using this module, you can analyze the advantages of specified entities, assessing both technical and fundamental indicators across various peers. Please use the input box below to enter the symbols for specific investments you'd like to analyze. Check out your portfolio center.
Specify up to 10 symbols:

Correlation Matrix

Typically, diversification allows investors to combine positions across different asset classes to reduce overall portfolio risk. Correlation between positions in your portfolio represents the degree of relationship between the price movements of corresponding instruments. A correlation of about +1.0 implies that the prices move in tandem. A correlation of -1.0 means that prices move in opposite directions. A correlation of close to zero suggests that the price movements of assets are uncorrelated.
Click cells to compare fundamentals   Check Volatility   Backtest Portfolio
High positive correlations   
CHRA
+ 0.69
AGXXF
BCCEF
+ 0.28
CHRA
ANRGF
+ 0.27
AGXXF
ANRGF
+ 0.17
ECPL
ANRGF
+ 0.15
CHRA
BCCEF
+ 0.08
AGXXF
  
High negative correlations   
BCCEF
- 0.47
ECPL
BCCEF
- 0.4
ANRGF
BTQNF
- 0.16
AGXXF
CHRA
- 0.13
ECPL
ANRGF
- 0.13
BTQNF
ECPL
- 0.07
BTQNF

Risk-Adjusted Indicators

There is a big difference between a company's stock performing well and the company itself doing well as a business compared to the competition. There are so many exceptions to the norm that investors cannot definitively determine what's good or bad unless they analyze multiple risk-adjusted performance indicators across the competitive landscape. These indicators are quantitative in nature and help investors forecast volatility and risk-adjusted expected returns across various positions.
All Fundamental Data

Competitive Analysis

    
 Better Than Average     
    
 Worse Than Peers    View Performance Chart
AGXXF BTQNF ECPL CHRA ANRGF BCCEF
 6.67 
 3.20 
Agilyx
 0.00 
 41.70 
BQE
 3.85 
 0.01 
EcoPlus
 0.18 
 5.67 
Charah
 18.75 
 0.65 
Anaergia
 4.85 
 0.02 
BacTech
Market Volatility
(90 Days Market Risk)
Unstable
Not too volatile
Out of control
Very steady
Out of control
Out of control
Market Performance
(90 Days Performance)
OK
Weak
OK
Very Weak
OK
Very Weak
Odds of Financial Distress
(Probability Of Bankruptcy)
Above Average
Low
Average
Dangerous
Below Average
Very High
Current Valuation
(Equity Enterprise Value)
Over Valued
Over Valued
Fairly Valued
Over Valued
Fairly Valued
Over Valued
Buy or Sell Advice
(Average Analysts Consensus)
Not Available
Not Available
Not Available
Not Available
Not Available
Not Available
Trade Advice
(90 Days Macroaxis Advice)
Strong Sell
Strong Sell
Strong Sell
Not Rated
Cautious Hold
Strong Sell
Current Ratio
1.50 X
3.16 X
0.02 X
1.07 X
1.63 X
1.50 X
Net Asset
28.61 M
13.8 M
205.34 K
344.11 M
703.91 M
234.97 K
Profit Margin
(1.66) %
0.20 %
N/A
(0.11) %
(0.21) %
N/A
EBITDA
(16.8 M)
2.96 M
(2.36 M)
34.69 M
(6.14 M)
(1.36 M)
Operating Margin
(1.55) %
0.02 %
N/A
(0.15) %
(0.10) %
N/A
Current Valuation
250.97 M
23.54 M
994.68 K
258.3 M
366.53 M
9.57 M
Price To Book
46.51 X
3.00 X
N/A
15.98 X
1.52 X
1.26 X
Five Year Return
2.37 %
N/A
N/A
N/A
N/A
N/A
Retained Earnings
N/A
N/A
N/A
(33.87 M)
(99.18 M)
N/A
Current Asset
N/A
N/A
N/A
83.92 M
9.33 M
N/A
Beta
1.01
0.95
-55.77
0.63
N/A
1.14
Number Of Employees
81
15
3
693
345
4
Shares Outstanding
85.14 M
1.25 M
4.04 B
3.37 M
32.19 M
174.21 M
Cash Flow From Operations
(15.98 M)
(249.82 K)
(159.01 K)
(10.17 M)
(38.95 M)
(2.18 M)
Total Debt
N/A
268.12 K
N/A
133.66 M
196.12 M
1.08 M
Return On Equity
-1.11
0.19
N/A
-0.86
-0.13
N/A
Z Score
N/A
65.4
-36.3
N/A
0.6
-11.7
Return On Asset
-0.39
0.0086
-1.47
-0.0837
-0.0137
-1.56
Book Value Per Share
0.07 X
10.14 X
(0.18) X
(5.30) X
3.07 X
(0.01) X
Number Of Shares Shorted
N/A
N/A
N/A
53.63 K
N/A
N/A
Current Liabilities
N/A
N/A
N/A
72.88 M
4.04 M
N/A
Total Asset
28.61 M
13.8 M
205.34 K
344.11 M
703.91 M
234.97 K
Debt To Equity
0.23 %
0.04 %
N/A
4.88 %
0.76 %
0.34 %
Short Ratio
N/A
N/A
N/A
3.48 X
N/A
N/A
Target Price
N/A
N/A
N/A
12.5
N/A
N/A
Shares Owned By Institutions
23.88 %
N/A
N/A
73.20 %
46.00 %
N/A
Market Capitalization
248.6 M
29.35 M
84.93 M
19.12 M
245.56 M
9.71 M
Price To Earning
(47.05) X
25.94 X
N/A
52.63 X
27.00 X
30.00 X
Price To Earnings To Growth
N/A
N/A
N/A
(0.02) X
N/A
N/A
Price To Sales
22.31 X
2.46 X
N/A
0.07 X
1.04 X
N/A
Net Income
(16.24 M)
2.63 M
(2.64 M)
(5.8 M)
(11.21 M)
(1.6 M)
Earnings Per Share
(0.21) X
1.31 X
(0.14) X
(16.03) X
(0.25) X
(0.01) X
Shares Owned By Insiders
44.44 %
53.87 %
N/A
3.17 %
4.23 %
14.03 %
Revenue
4.89 M
7.51 M
21 K
293.22 M
153.58 M
N/A
Working Capital
N/A
N/A
N/A
11.05 M
5.29 M
N/A
Cash And Equivalents
13.42 M
2.9 M
1.51 K
7.07 M
63.77 M
1.7 M
Cash Per Share
0.17 X
2.32 X
N/A
0.21 X
0.99 X
0.01 X
Gross Profit
63.41 K
3.56 M
21 K
25.9 M
23.4 M
(4.08 K)
Day Typical Price
3.2
41.7
0.0127
5.67
0.65
0.0216
Accumulation Distribution
N/A
N/A
0.0385
0.0018
N/A
N/A
Market Facilitation Index
N/A
N/A
5.0E-4
0.01
N/A
N/A
Daily Balance Of Power
9.2 T
0.0
(1.00)
1.0
(9,223,372,036,855)
9.2 T
Period Momentum Indicator
0.2
N/A
(0.0005)
0.01
(0.15)
0.001
Rate Of Daily Change
1.07
1.0
0.96
1.0
0.81
1.05
Day Median Price
3.2
41.7
0.0128
5.67
0.65
0.0216
Price Action Indicator
0.1
N/A
(0.0005)
0.01
(0.07)
5.0E-4
Relative Strength Index
49.29
45.48
64.47
64.76
46.36
52.36
Coefficient Of Variation
4059.94
80587.63
811.92
2316.22
726.9
(10,497)
Mean Deviation
1.45
1.25
15.96
5.53
10.45
5.02
Jensen Alpha
0.3001
0.0234
5.15
0.7604
2.62
0.3197
Total Risk Alpha
(0.49)
(0.78)
(2.50)
(1.66)
(1.05)
(1.70)
Sortino Ratio
(0.01)
(0.01)
0.1229
0.0537
0.1352
N/A
Downside Variance
42.56
90.82
1507.75
46.21
438.06
N/A
Standard Deviation
2.96
4.16
39.82
11.56
21.54
8.67
Kurtosis
5.07
17.06
15.51
8.0
19.61
2.85
Potential Upside
5.63
1.87
18.18
30.7
28.57
17.13
Treynor Ratio
(0.03)
0.0213
(2.40)
(0.22)
1.11
0.0279
Maximum Drawdown
16.96
39.99
249.12
50.46
185.79
48.2
Variance
8.77
17.27
1586.01
133.61
463.93
75.11
Market Risk Adjusted Performance
(0.02)
0.0313
(2.39)
(0.21)
1.12
0.0379
Risk Adjusted Performance
0.0242
0.0092
0.0921
0.0383
0.1016
0.0029
Skewness
(1.17)
(0.03)
3.69
2.28
3.34
0.8971
Semi Deviation
2.6
3.01
12.96
6.11
9.91
N/A
Information Ratio
(0.02)
(0.03)
0.1198
0.0316
0.1313
(0.03)
Value At Risk
(4.62)
(2.91)
(28.75)
(11.16)
(18.75)
(13.75)
Expected Short fall
(3.27)
(8.28)
(136.55)
(9.56)
(27.56)
N/A
Downside Deviation
6.52
9.53
38.83
6.8
20.93
N/A
Semi Variance
6.74
9.08
168.03
37.39
98.18
N/A

Market Neutrality

One of the main advantages of trading using market-neutral strategies is that every trade hedges away some risk. Because there are two separate transactions required, even if one position performs unexpectedly, the other equity can make up some of the losses.
Please note, the success of pairs trading depends heavily on the modeling and forecasting of the spread time series. However, in general, pair trading minimizes risk from directional movements in the market unless the strategy's equities are perfectly correlated. For example, if an entire industry or sector drops because of unexpected headlines, the first equity's short position will appreciate offsetting losses from the drop in the long position's value.

Five steps to successful analysis of competition

Competitive analysis is the process of researching and evaluating the competitive landscape of a business entity. It provides an understanding of the company's strengths, weaknesses, opportunities, and threats (SWOT) in relation to its competition. The competition analysis typically involves several steps, including:
  • Identifying the key players in the market: This involves identifying the major competitors across the sector or industry, both direct and indirect, as well as new entrants and disruptive technologies.
  • Assessing the strengths and weaknesses of each competitor: This involves evaluating each competitor's strengths and weaknesses in areas such as product offerings, market share, brand recognition, financial performance, and distribution channels.
  • Understanding the competitive environment: This involves evaluating the regulatory environment, economic conditions, and other factors that may impact the competitive landscape.
  • Identifying opportunities and threats: This involves using the information gathered during the analysis to identify opportunities and threats and developing a strategy to address them.
  • Evaluating the competitive landscape: This involves understanding the competitive dynamics of the market, such as pricing, marketing, and distribution strategies, as well as analyzing the competitive advantage of each competitor.
Competitive analysis is an essential tool for businesses to stay ahead of the competition and can be used to inform decision-making and strategy development. By understanding the competitive landscape and staying informed about the activities of competitors, a company can make more informed decisions and improve its overall performance.

Generate Optimal Portfolios

The classical approach to portfolio optimization is known as Modern Portfolio Theory (MPT). It involves categorizing the investment universe based on risk (standard deviation) and return, and then choosing the mix of investments that achieves the desired risk-versus-return tradeoff. Portfolio optimization can also be thought of as a risk-management strategy as every type of equity has a distinct return and risk characteristics as well as different systemic risks, which describes how they respond to the market at large. Macroaxis enables investors to optimize portfolios that have a mix of equities (such as stocks, funds, or ETFs) and cryptocurrencies (such as Bitcoin, Ethereum or Monero)
By capturing your risk tolerance and investment horizon Macroaxis technology of instant portfolio optimization will compute exactly how much risk is acceptable for your desired return expectations
Check out your portfolio center.
Note that this page's information should be used as a complementary analysis 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 My Watchlist Analysis module to analyze my current watchlist and to refresh optimization strategy. Macroaxis watchlist is based on self-learning algorithm to remember stocks you like.

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