Blackrock vs Blckrck Comparison
Blackrock vs Blckrck comparative analysis provides an insight into diversification possibilities from combining Blackrock and Blckrck into the same portfolio. You can use this module to analyze the comparative aspects of Blackrock and Blckrck across most of their technical and fundamental indicators. Please use the input box below to enter a few concurrent symbols you would like to analyze. With this comparative module, you can estimate the relative strength of Blackrock against Blckrck. Check out your portfolio center.
The Macroaxis Comparable Analysis module helps investors to evaluate stocks by comparing them to other traded companies based on similar metrics to determine their enterprise value. The basic idea behind this approach is that Blackrock Equity and Blckrck Fds should bear some resemblance to each other or to other equities in a similar class. Blckrck Fds
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.
Please specify at least 3 valid symbols having historical data to build a meaningful correlation cloud. You can use symbol search above to locate your securities.
Competitive Analysis
Better Than Average | Worse Than Peers | View Performance Chart |
MKDVX | BRGKX | |
0.19 20.79 | 0.66 38.18 | Market Volatility (90 Days Market Risk) |
Market Performance (90 Days Performance) | ||
Odds of Financial Distress (Probability Of Bankruptcy) | ||
Current Valuation (Equity Enterprise Value) | ||
Buy or Sell Advice (Average Analysts Consensus) | ||
Trade Advice (90 Days Macroaxis Advice) | ||
Net Asset | ||
Price To Book | ||
Five Year Return | ||
One Year Return | ||
Last Dividend Paid | ||
Price To Earning | ||
Price To Sales | ||
Cash Position Weight | ||
Equity Positions Weight | ||
Three Year Return | ||
Annual Yield | ||
Year To Date Return | ||
Ten Year Return | ||
Day Typical Price | ||
Daily Balance Of Power | ||
Period Momentum Indicator | ||
Rate Of Daily Change | ||
Day Median Price | ||
Price Action Indicator | ||
Relative Strength Index | ||
Coefficient Of Variation | ||
Mean Deviation | ||
Jensen Alpha | ||
Total Risk Alpha | ||
Sortino Ratio | ||
Downside Variance | ||
Standard Deviation | ||
Kurtosis | ||
Potential Upside | ||
Treynor Ratio | ||
Maximum Drawdown | ||
Variance | ||
Market Risk Adjusted Performance | ||
Risk Adjusted Performance | ||
Skewness | ||
Semi Deviation | ||
Information Ratio | ||
Value At Risk | ||
Expected Short fall | ||
Downside Deviation | ||
Semi Variance |
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.
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)
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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
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