Short Duration Bond Fund Market Value
| RSBTX Fund | USD 18.49 0.02 0.11% |
| Symbol | Short |
Short Duration '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 Short Duration's mutual fund 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 Short Duration.
| 06/04/2022 |
| 05/24/2024 |
If you would invest 0.00 in Short Duration on June 4, 2022 and sell it all today you would earn a total of 0.00 from holding Short Duration Bond or generate 0.0% return on investment in Short Duration over 720 days. Short Duration is related to or competes with Vanguard Short, Vanguard Short-term, Vanguard Short-term, and Vanguard Short. The fund has a non-fundamental policy to invest, under normal circumstances, at least 80 percent of the value of its net... More
Short Duration 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 Short Duration's mutual fund 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 Short Duration Bond upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.1229 | |||
| Information Ratio | (0.41) | |||
| Maximum Drawdown | 0.5437 | |||
| Value At Risk | (0.11) | |||
| Potential Upside | 0.1634 |
Short Duration Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Short Duration's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Short Duration's standard deviation. In reality, there are many statistical measures that can use Short Duration historical prices to predict the future Short Duration's volatility.| Risk Adjusted Performance | 0.023 | |||
| Jensen Alpha | (0) | |||
| Total Risk Alpha | (0.01) | |||
| Sortino Ratio | (0.36) | |||
| Treynor Ratio | 0.0311 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Short Duration'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.
Short Duration Bond Backtested Returns
We consider Short Duration out of control. Short Duration Bond owns Efficiency Ratio (i.e., Sharpe Ratio) of 0.12, which indicates the fund had a 0.12% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Short Duration Bond, which you can use to evaluate the volatility of the fund. Please validate Short Duration's Risk Adjusted Performance of 0.023, standard deviation of 0.1093, and Downside Deviation of 0.1229 to confirm if the risk estimate we provide is consistent with the expected return of 0.0136%. The entity has a beta of 0.0773, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Short Duration's returns are expected to increase less than the market. However, during the bear market, the loss of holding Short Duration is expected to be smaller as well.
Auto-correlation | 0.69 |
Good predictability
Short Duration Bond has good predictability. Overlapping area represents the amount of predictability between Short Duration time series from 4th of June 2022 to 30th of May 2023 and 30th of May 2023 to 24th of May 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 Short Duration Bond price movement. The serial correlation of 0.69 indicates that around 69.0% of current Short Duration price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.69 | |
| Spearman Rank Test | 0.58 | |
| Residual Average | 0.0 | |
| Price Variance | 0.09 |
Short Duration Bond lagged returns against current returns
Autocorrelation, which is Short Duration mutual fund'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 Short Duration's mutual fund expected returns. We can calculate the autocorrelation of Short Duration returns to help us make a trade decision. For example, suppose you find that Short Duration has exhibited high autocorrelation historically, and you observe that the mutual fund 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 |
Short Duration 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 Short Duration mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Short Duration mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Short Duration mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Short Duration Lagged Returns
When evaluating Short Duration's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Short Duration mutual fund have on its future price. Short Duration 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, Short Duration autocorrelation shows the relationship between Short Duration mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Short Duration Bond.
Regressed Prices |
| Timeline |
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Check out Short Duration Correlation, Short Duration Volatility and Short Duration Alpha and Beta module to complement your research on Short Duration. You can also try the AI Portfolio Architect module to use AI to generate optimal portfolios and find profitable investment opportunities.
Short Duration technical mutual fund 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, fund market cycles, or different charting patterns.