Stone Ridge 2063 Etf Market Value
| LFBB Etf | 18.63 0.05 0.27% |
| Symbol | Stone |
The market value of Stone Ridge 2063 is measured differently than its book value, which is the value of Stone that is recorded on the company's balance sheet. Investors also form their own opinion of Stone Ridge's value that differs from its market value or its book value, called intrinsic value, which is Stone Ridge'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 Stone Ridge's market value can be influenced by many factors that don't directly affect Stone Ridge'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 Stone Ridge's value and its price as these two are different measures arrived at by different means. Investors typically determine if Stone Ridge is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Stone Ridge'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.
Stone Ridge '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 Stone Ridge's 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 Stone Ridge.
| 09/28/2024 |
| 11/27/2024 |
If you would invest 0.00 in Stone Ridge on September 28, 2024 and sell it all today you would earn a total of 0.00 from holding Stone Ridge 2063 or generate 0.0% return on investment in Stone Ridge over 60 days. Stone Ridge is related to or competes with US Treasury, Tidal Trust, Franklin Liberty, SPDR Bloomberg, US Treasury, Vanguard Extended, and Bondbloxx ETF. Stone Ridge is entity of United States. It is traded as Etf on BATS exchange. More
Stone Ridge 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 Stone Ridge's 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 Stone Ridge 2063 upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.38) | |||
| Maximum Drawdown | 3.24 | |||
| Value At Risk | (1.35) | |||
| Potential Upside | 1.12 |
Stone Ridge Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Stone Ridge's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Stone Ridge's standard deviation. In reality, there are many statistical measures that can use Stone Ridge historical prices to predict the future Stone Ridge's volatility.| Risk Adjusted Performance | (0.15) | |||
| Jensen Alpha | (0.13) | |||
| Total Risk Alpha | (0.25) | |||
| Treynor Ratio | 1.13 |
Stone Ridge 2063 Backtested Returns
Stone Ridge 2063 owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.19, which indicates the etf had a -0.19% return per unit of risk over the last 3 months. Stone Ridge 2063 exposes twenty-two different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Stone Ridge's Coefficient Of Variation of (519.98), variance of 0.472, and Risk Adjusted Performance of (0.15) to confirm the risk estimate we provide. The entity has a beta of -0.13, which indicates not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Stone Ridge are expected to decrease at a much lower rate. During the bear market, Stone Ridge is likely to outperform the market.
Auto-correlation | 0.31 |
Below average predictability
Stone Ridge 2063 has below average predictability. Overlapping area represents the amount of predictability between Stone Ridge time series from 28th of September 2024 to 28th of October 2024 and 28th of October 2024 to 27th of November 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 Stone Ridge 2063 price movement. The serial correlation of 0.31 indicates that nearly 31.0% of current Stone Ridge price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.31 | |
| Spearman Rank Test | 0.23 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
Stone Ridge 2063 lagged returns against current returns
Autocorrelation, which is Stone Ridge 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 Stone Ridge's etf expected returns. We can calculate the autocorrelation of Stone Ridge returns to help us make a trade decision. For example, suppose you find that Stone Ridge 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 |
Stone Ridge 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 Stone Ridge etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Stone Ridge etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Stone Ridge etf over time.
Current vs Lagged Prices |
| Timeline |
Stone Ridge Lagged Returns
When evaluating Stone Ridge's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Stone Ridge etf have on its future price. Stone Ridge 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, Stone Ridge autocorrelation shows the relationship between Stone Ridge etf current value and its past values and can show if there is a momentum factor associated with investing in Stone Ridge 2063.
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 Stone Ridge 2063 offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Stone Ridge's financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Stone Ridge 2063 Etf. Outlined below are crucial reports that will aid in making a well-informed decision on Stone Ridge 2063 Etf:Check out Stone Ridge Correlation, Stone Ridge Volatility and Stone Ridge Alpha and Beta module to complement your research on Stone Ridge. You can also try the Headlines Timeline module to stay connected to all market stories and filter out noise. Drill down to analyze hype elasticity.
Stone Ridge 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.