Two Roads Shared Etf Market Value
| DYLD Etf | USD 22.78 0.01 0.04% |
| Symbol | Two |
The market value of Two Roads Shared is measured differently than its book value, which is the value of Two that is recorded on the company's balance sheet. Investors also form their own opinion of Two Roads' value that differs from its market value or its book value, called intrinsic value, which is Two Roads' 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 Two Roads' market value can be influenced by many factors that don't directly affect Two Roads' 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 Two Roads' value and its price as these two are different measures arrived at by different means. Investors typically determine if Two Roads is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Two Roads' 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.
Two Roads 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Two Roads' etf what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Two Roads.
| 11/11/2024 |
| 12/11/2024 |
If you would invest 0.00 in Two Roads on November 11, 2024 and sell it all today you would earn a total of 0.00 from holding Two Roads Shared or generate 0.0% return on investment in Two Roads over 30 days. Two Roads is related to or competes with Two Roads, LeaderSharesTM AlphaFactor, Two Roads, Redwood Managed, and Redwood Systematic. The fund will be an actively managed ETF that normally invests, directly or indirectly, at least 80 percent of its net a... More
Two Roads Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Two Roads' etf current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Two Roads Shared upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1521 | |||
| Information Ratio | (0.77) | |||
| Maximum Drawdown | 0.7047 | |||
| Value At Risk | (0.22) | |||
| Potential Upside | 0.2216 |
Two Roads Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Two Roads' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Two Roads' standard deviation. In reality, there are many statistical measures that can use Two Roads historical prices to predict the future Two Roads' volatility.| Risk Adjusted Performance | (0) | |||
| Jensen Alpha | (0.01) | |||
| Total Risk Alpha | (0.03) | |||
| Sortino Ratio | (0.77) | |||
| Treynor Ratio | (0.06) |
Two Roads Shared Backtested Returns
At this point, Two Roads is very steady. Two Roads Shared owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.0324, which indicates the etf had a 0.0324% return per unit of risk over the last 3 months. We have found twenty-nine technical indicators for Two Roads Shared, which you can use to evaluate the volatility of the etf. Please validate Two Roads' Semi Deviation of 0.1017, insignificant risk adjusted performance, and Coefficient Of Variation of 2029.11 to confirm if the risk estimate we provide is consistent with the expected return of 0.0049%. The entity has a beta of 0.0457, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Two Roads' returns are expected to increase less than the market. However, during the bear market, the loss of holding Two Roads is expected to be smaller as well.
Auto-correlation | -0.47 |
Modest reverse predictability
Two Roads Shared has modest reverse predictability. Overlapping area represents the amount of predictability between Two Roads time series from 11th of November 2024 to 26th of November 2024 and 26th of November 2024 to 11th of December 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Two Roads Shared price movement. The serial correlation of -0.47 indicates that about 47.0% of current Two Roads price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.47 | |
| Spearman Rank Test | 0.06 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Two Roads Shared lagged returns against current returns
Autocorrelation, which is Two Roads etf's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Two Roads' etf expected returns. We can calculate the autocorrelation of Two Roads returns to help us make a trade decision. For example, suppose you find that Two Roads has exhibited high autocorrelation historically, and you observe that the etf is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Two Roads regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Two Roads etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Two Roads etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Two Roads etf over time.
Current vs Lagged Prices |
| Timeline |
Two Roads Lagged Returns
When evaluating Two Roads' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Two Roads etf have on its future price. Two Roads autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Two Roads autocorrelation shows the relationship between Two Roads etf current value and its past values and can show if there is a momentum factor associated with investing in Two Roads Shared.
Regressed Prices |
| Timeline |
Also Currently Popular
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.When determining whether Two Roads Shared is a strong investment it is important to analyze Two Roads' competitive position within its industry, examining market share, product or service uniqueness, and competitive advantages. Beyond financials and market position, potential investors should also consider broader economic conditions, industry trends, and any regulatory or geopolitical factors that may impact Two Roads' future performance. For an informed investment choice regarding Two Etf, refer to the following important reports:Check out Two Roads Correlation, Two Roads Volatility and Two Roads Alpha and Beta module to complement your research on Two Roads. You can also try the Portfolio Diagnostics module to use generated alerts and portfolio events aggregator to diagnose current holdings.
Two Roads technical etf analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, etf market cycles, or different charting patterns.