Compare MTA to Staked, EigenLayer, EOSDAC, BLZ, Highstreet, Tokocrypto

Comparing MTA to Staked, EigenLayer, EOSDAC, BLZ, Highstreet, Tokocrypto 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.

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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.

	MTA	STETH	EIGEN	EOSDAC	BLZ	HIGH	TKO
MTA		-0.02	0.5	-0.03	-0.37	-0.27	-0.18	MTA
STETH	-0.02		0.34	0.49	0.01	0.6	-0.25	STETH
EIGEN	0.5	0.34		0.32	-0.49	-0.12	-0.19	EIGEN
EOSDAC	-0.03	0.49	0.32		0.13	0.37	0.15	EOSDAC
BLZ	-0.37	0.01	-0.49	0.13		0.73	0.6	BLZ
HIGH	-0.27	0.6	-0.12	0.37	0.73		0.3	HIGH
TKO	-0.18	-0.25	-0.19	0.15	0.6	0.3		TKO
	MTA	STETH	EIGEN	EOSDAC	BLZ	HIGH	TKO

Click cells to compare fundamentals

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High positive correlations

HIGH	+ 0.73	BLZ
HIGH	+ 0.6	STETH
TKO	+ 0.6	BLZ
EIGEN	+ 0.5	MTA
EOSDAC	+ 0.49	STETH
HIGH	+ 0.37	EOSDAC

High negative correlations

BLZ	- 0.49	EIGEN
BLZ	- 0.37	MTA
HIGH	- 0.27	MTA
TKO	- 0.25	STETH
TKO	- 0.19	EIGEN
TKO	- 0.18	MTA

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.

	Mean Deviation	Jensen Alpha	Sortino Ratio	Treynor Ratio	Semi Deviation	Expected Shortfall	Potential Upside	Value @Risk	Maximum Drawdown
MTA	17.86	3.85	0.13	(0.71)	16.93	(23.59)	52.76	(36.62)	108.26
STETH	2.71	0.23	0.07	0.31	3.45	(2.92)	6.34	(5.12)	16.67
EIGEN	3.81	(0.36)	0.00	(0.16)	0.00	0.00	11.42	(8.93)	33.38
EOSDAC	8.41	0.99	0.10	0.74	9.37	(9.46)	21.28	(18.71)	90.64
BLZ	4.38	(0.05)	(0.01)	0.03	5.88	(8.53)	9.09	(9.09)	29.09
HIGH	3.51	(0.03)	(0.01)	0.07	5.28	(3.46)	6.90	(6.77)	20.01
TKO	3.50	0.22	0.02	5.06	3.68	(6.32)	7.69	(6.25)	43.13

Unable to evaluate fundamental data of [MTA.CC, STETH.CC, EIGEN.CC, EOSDAC.CC, BLZ.CC, HIGH.CC, TKO.CC] at this time. Please try again later

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Competitive Analysis

Better Than Average

Worse Than Peers

View Performance Chart

	MTA	STETH	EIGEN	EOSDAC	BLZ	HIGH	TKO
	40.42 0.02 MTA	1.94 3,396 Staked	6.92 2.78 EigenLayer	5.28 0.0003 EOSDAC	7.69 0.14 BLZ	6.90 1.55 Highstreet	6.25 0.34 Tokocrypto
Market Volatility (90 Days Market Risk)	Abnormally risky	Very volatile	Abnormally risky	Abnormally risky	Unusually volatile	Very risky	Unusually risky
Market Performance (90 Days Performance)	OK	Good	OK	OK	Insignificant	Modest	Insignificant
Odds of Financial Distress (Probability Of Bankruptcy)	Low	Below Average	Very High	Low	Above Average	Very High	Very High
Current Valuation (Equity Enterprise Value)	Fairly Valued	Over Valued	Over Valued	Over Valued	Over Valued	Over Valued	Over Valued
Buy or Sell Advice (Average Analysts Consensus)	Not Available	Not Available	Not Available	Not Available	Not Available	Not Available	Not Available
Trade Advice (90 Days Macroaxis Advice)	Strong Sell	Strong Sell	Strong Sell	Strong Sell	Strong Sell	Strong Sell	Strong Sell
Day Typical Price	0.0199	3395.84	2.72	3.0E-4	0.14	1.52	0.33
Accumulation Distribution	N/A	7.0E-4	0.12	0.0611	0.0714	0.0892	0.0882
Market Facilitation Index	N/A	2.38	0.34	0.0	0.01	0.14	0.03
Daily Balance Of Power	(9,223,372,036,855)	27.197479	0.5294	(0.86)	1.0	0.7143	0.6667
Period Momentum Indicator	(0.01)	64.73	0.18	(0.000019)	0.01	0.1	0.02
Rate Of Daily Change	0.6	1.02	1.07	0.95	1.08	1.07	1.06
Day Median Price	0.0199	3395.78	2.69	3.0E-4	0.14	1.5	0.33
Price Action Indicator	(0.01)	32.53	0.18	(0.000018)	0.01	0.1	0.025
Relative Strength Index	41.86	35.8	33.86	9.46	9.38	16.49	15.21
Coefficient Of Variation	811.0	987.73	(3,150)	1194.53	25248.92	10027.71	2356.26
Mean Deviation	17.86	2.71	3.81	8.41	4.38	3.51	3.5
Jensen Alpha	3.85	0.227	(0.36)	0.9865	(0.05)	(0.03)	0.2206
Total Risk Alpha	(0.93)	(0.22)	(1.18)	(1.06)	(1.04)	(0.71)	(0.65)
Sortino Ratio	0.1321	0.068	N/A	0.0984	(0.01)	(0.01)	0.0196
Downside Variance	578.22	13.57	N/A	115.65	103.81	32.12	28.9
Standard Deviation	26.81	3.77	6.2	14.21	6.69	4.73	5.56
Kurtosis	0.1684	2.05	2.26	7.07	0.8937	2.52	9.35
Potential Upside	52.76	6.34	11.42	21.28	9.09	6.9	7.69
Treynor Ratio	(0.71)	0.3108	(0.16)	0.7392	0.0295	0.0664	5.06
Maximum Drawdown	108.26	16.67	33.38	90.64	29.09	20.01	43.13
Variance	719.04	14.19	38.49	201.79	44.75	22.4	30.92
Market Risk Adjusted Performance	(0.70)	0.3208	(0.15)	0.7492	0.0395	0.0764	5.07
Risk Adjusted Performance	0.1043	0.0856	(0.02)	0.0737	0.0119	0.016	0.0412
Skewness	0.6592	0.0752	0.7779	1.92	(0.69)	(0.96)	1.83
Semi Deviation	16.93	3.45	N/A	9.37	5.88	5.28	3.68
Information Ratio	0.1184	0.0665	(0.05)	0.0745	(0.02)	(0.02)	0.0189
Value At Risk	(36.62)	(5.12)	(8.93)	(18.71)	(9.09)	(6.77)	(6.25)
Expected Short fall	(23.59)	(2.92)	N/A	(9.46)	(8.53)	(3.46)	(6.32)
Downside Deviation	24.05	3.68	N/A	10.75	10.19	5.67	5.38
Semi Variance	286.72	11.9	N/A	87.81	34.58	27.93	13.58

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.

Trending Themes

If you are a self-driven investor, you will appreciate our idea-generating investing themes. Our themes help you align your investments inspirations with your core values and are essential building blocks of your portfolios. A typical investing theme is an unweighted collection of up to 20 funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of equities with common characteristics such as industry and growth potential, volatility, or market segment.

	Entertainment Invested over 90 shares	Go
	Macroaxis Index Invested few shares	Go
	Warren Buffett Holdings Invested over 60 shares	Go
	Business Services Invested over 100 shares	Go
	Banking Invested over 20 shares	Go
	FinTech Invested over 40 shares	Go
	Cash Cows Invested few shares	Go
	Adviser Favorites Invested few shares	Go
	Automobiles and Trucks Invested over 50 shares	Go
	Macroaxis Picks Invested over 30 shares	Go
	Manufacturing Invested over 30 shares	Go
	Hedge Favorites Invested over 60 shares	Go
	Artificial Intelligence Invested few shares	Go

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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 Portfolio File Import module to quickly import all of your third-party portfolios from your local drive in csv format.

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