FT Cboe Competition
| DFEB Etf | USD 42.55 0.09 0.21% |
You can use the Comparative Equity Analysis module to analyze the advantages of investing in your portfolio's related equities across multiple sectors and thematic ideas. Please use the input box below to enter symbols for particular investments you would like to analyze. With the equity comparison module, you can estimate the relative effect of FT Cboe competition on your existing holdings.
DFEB |
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 DFEB 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.
| Click cells to compare fundamentals | Check Volatility | Backtest Portfolio |
FT Cboe Constituents Risk-Adjusted Indicators
There is a big difference between DFEB 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 | ||
|---|---|---|---|---|---|---|---|---|---|---|
| DNOV | 0.10 | 0.02 | (0.32) | 0.33 | 0.00 | 0.26 | 0.79 | |||
| FFEB | 0.28 | 0.00 | (0.12) | 0.11 | 0.36 | 0.74 | 2.17 | |||
| DAUG | 0.26 | 0.00 | (0.15) | 0.10 | 0.27 | 0.63 | 1.78 | |||
| FNOV | 0.12 | 0.02 | (0.23) | 0.21 | 0.00 | 0.38 | 1.24 | |||
| FMAY | 0.33 | 0.00 | (0.10) | 0.10 | 0.35 | 0.71 | 2.12 |
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 |
| DFEB | DNOV | FFEB | DAUG | FNOV | FMAY | |
| 0.21 42.55 DFEB | 0.14 43.05 DNOV | 0.32 49.67 FFEB | 0.13 39.75 DAUG | 0.25 48.13 FNOV | 0.23 47.57 First | 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) | ||||||
| Five Year Return | ||||||
| One Year Return | ||||||
| Equity Positions Weight | ||||||
| Three Year Return | ||||||
| Net Asset | ||||||
| Beta | ||||||
| Day Typical Price | ||||||
| Accumulation Distribution | ||||||
| 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 |
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 Small Value Funds Thematic Idea Now
Small Value Funds
Funds or Etfs that invest in the undervalued stocks of small to mid-sized companies. The Small Value Funds theme has 35 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 Small Value Funds Theme or any other thematic opportunities.
| View All Next | Launch |
Check out FT Cboe Correlation with its peers. You can also try the Alpha Finder module to use alpha and beta coefficients to find investment opportunities after accounting for the risk.
The market value of FT Cboe Vest is measured differently than its book value, which is the value of DFEB 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.