FT Cboe Competition
DJUN Etf | USD 43.46 0.10 0.23% |
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DJUN |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of FT Cboe's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
FT Cboe Competition Correlation Matrix
Typically, diversification allows investors to combine positions across different asset classes to reduce overall portfolio risk. Correlation between FT Cboe and its competitors represents the degree of relationship between the price movements of corresponding etfs. A correlation of about +1.0 implies that the price of DJUN and its corresponding peer 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; in other words, the historical price movement of FT Cboe Vest does not affect the price movement of the other competitor.
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FT Cboe Competition Risk-Adjusted Indicators
There is a big difference between DJUN Etf performing well and FT Cboe ETF 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 FT Cboe's 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 | ||
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META | 1.05 | 0.01 | (0.01) | 0.12 | 1.40 | 2.62 | 8.02 | |||
MSFT | 0.90 | (0.11) | 0.00 | (0.05) | 0.00 | 2.09 | 8.19 | |||
UBER | 1.56 | (0.16) | 0.00 | (0.06) | 0.00 | 2.53 | 20.10 | |||
F | 1.39 | (0.12) | (0.03) | 0.02 | 2.20 | 2.53 | 11.72 | |||
T | 0.92 | 0.26 | 0.15 | 57.17 | 0.86 | 2.56 | 6.47 | |||
A | 1.12 | (0.13) | 0.00 | (0.16) | 0.00 | 2.29 | 9.02 | |||
CRM | 1.28 | 0.27 | 0.23 | 0.33 | 0.92 | 3.18 | 9.09 | |||
JPM | 1.11 | 0.03 | 0.07 | 0.12 | 1.44 | 2.05 | 15.87 | |||
MRK | 0.85 | (0.24) | 0.00 | (1.03) | 0.00 | 1.73 | 4.89 | |||
XOM | 1.04 | 0.06 | 0.01 | 0.20 | 1.20 | 2.14 | 5.78 |
FT Cboe Competitive Analysis
The better you understand FT Cboe competitors, the better chance you have of utilizing it as a position in your portfolios. From an individual investor's perspective, FT Cboe's competitive analysis can cover a whole range of metrics. Some of these will be more critical depending on who you are as an investor and how you react to market volatility. However, if you are locking your investment sandscape to a long-term horizon, comparing the fundamental indicator across FT Cboe's competition over several years is one of the best ways to analyze its investment potential.Better Than Average | Worse Than Peers | View Performance Chart |
DJUN | DMAY | DNOV | FNOV | DFEB | DJUL | |
0.23 43.46 DJUN | 0.20 40.86 First | 0.14 43.05 DNOV | 0.25 48.13 FNOV | 0.21 42.55 DFEB | 0.24 42.17 DJUL | Market Volatility (90 Days Market Risk) |
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Total Risk Alpha | ||||||
Sortino Ratio | ||||||
Downside Variance | ||||||
Standard Deviation | ||||||
Kurtosis | ||||||
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Semi Variance |
FT Cboe Competition Performance Charts
Five steps to successful analysis of FT Cboe Competition
FT Cboe's competitive analysis is the process of researching and evaluating its competitive landscape. It provides an understanding of the strengths, weaknesses, opportunities, and threats (SWOT) faced by FT Cboe Vest in relation to its competition. FT Cboe's competition analysis typically involves several steps, including:- Identifying the key players in the market: This involves identifying the major competitors of FT Cboe in the market, 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 FT Cboe's competitive landscape.
- Identifying opportunities and threats: This involves using the information gathered during the analysis to identify opportunities and threats to FT Cboe Vest, 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.
Complement your FT Cboe position
In addition to having FT Cboe in your portfolios, you can quickly add positions using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your investment opportunity, you can then find an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility.Did You Try This Idea?
Run Long Short Funds Thematic Idea Now
Long Short Funds
Funds or Etfs that are designed to hedge away market risk by investing in combination of bonds, stocks, derivative instruments as well as short positions to maximize returns irrespective of market conditions. The Long Short Funds theme has 40 constituents at this time.
You can either use a buy-and-hold strategy to lock in the entire theme or actively trade it to take advantage of the short-term price volatility of individual constituents. Macroaxis can help you discover thousands of investment opportunities in different asset classes. In addition, you can partner with us for reliable portfolio optimization as you plan to utilize Long Short Funds Theme or any other thematic opportunities.
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Check out FT Cboe Correlation with its peers. You can also try the Cryptocurrency Center module to build and monitor diversified portfolio of extremely risky digital assets and cryptocurrency.
The market value of FT Cboe Vest is measured differently than its book value, which is the value of DJUN that is recorded on the company's balance sheet. Investors also form their own opinion of FT Cboe's value that differs from its market value or its book value, called intrinsic value, which is FT Cboe's true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because FT Cboe's market value can be influenced by many factors that don't directly affect FT Cboe's underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between FT Cboe's value and its price as these two are different measures arrived at by different means. Investors typically determine if FT Cboe is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, FT Cboe's price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.