Schwab Monthly Income Fund Market Value
| SWKRX Fund | USD 10.14 0.03 0.30% |
| Symbol | Schwab |
Schwab Monthly '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 Schwab Monthly'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 Schwab Monthly.
| 12/20/2024 |
| 01/19/2025 |
If you would invest 0.00 in Schwab Monthly on December 20, 2024 and sell it all today you would earn a total of 0.00 from holding Schwab Monthly Income or generate 0.0% return on investment in Schwab Monthly over 30 days. Schwab Monthly is related to or competes with Financials Ultrasector, Davis Financial, John Hancock, Vanguard Financials, and Fidelity Advisor. The fund invests primarily in a combination of Schwab Funds and Schwab ETFs in accordance with its target asset allocati... More
Schwab Monthly 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 Schwab Monthly'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 Schwab Monthly Income upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.18) | |||
| Maximum Drawdown | 2.15 | |||
| Value At Risk | (0.87) | |||
| Potential Upside | 0.582 |
Schwab Monthly Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Schwab Monthly's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Schwab Monthly's standard deviation. In reality, there are many statistical measures that can use Schwab Monthly historical prices to predict the future Schwab Monthly's volatility.| Risk Adjusted Performance | (0.10) | |||
| Jensen Alpha | (0.06) | |||
| Total Risk Alpha | (0.06) | |||
| Treynor Ratio | (0.30) |
Schwab Monthly Income Backtested Returns
Schwab Monthly Income owns Efficiency Ratio (i.e., Sharpe Ratio) of -0.0916, which indicates the fund had a -0.0916% return per unit of risk over the last 3 months. Schwab Monthly Income exposes twenty-one different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please validate Schwab Monthly's Variance of 0.1588, coefficient of variation of (918.47), and Risk Adjusted Performance of (0.10) to confirm the risk estimate we provide. The entity has a beta of 0.18, which indicates not very significant fluctuations relative to the market. As returns on the market increase, Schwab Monthly's returns are expected to increase less than the market. However, during the bear market, the loss of holding Schwab Monthly is expected to be smaller as well.
Auto-correlation | -0.09 |
Very weak reverse predictability
Schwab Monthly Income has very weak reverse predictability. Overlapping area represents the amount of predictability between Schwab Monthly time series from 20th of December 2024 to 4th of January 2025 and 4th of January 2025 to 19th of January 2025. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Schwab Monthly Income price movement. The serial correlation of -0.09 indicates that less than 9.0% of current Schwab Monthly price fluctuation can be explain by its past prices.
| Correlation Coefficient | -0.09 | |
| Spearman Rank Test | 0.13 | |
| Residual Average | 0.0 | |
| Price Variance | 0.0 |
Schwab Monthly Income lagged returns against current returns
Autocorrelation, which is Schwab Monthly 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 Schwab Monthly's mutual fund expected returns. We can calculate the autocorrelation of Schwab Monthly returns to help us make a trade decision. For example, suppose you find that Schwab Monthly 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 |
Schwab Monthly 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 Schwab Monthly mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Schwab Monthly mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Schwab Monthly mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Schwab Monthly Lagged Returns
When evaluating Schwab Monthly's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Schwab Monthly mutual fund have on its future price. Schwab Monthly 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, Schwab Monthly autocorrelation shows the relationship between Schwab Monthly mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Schwab Monthly Income.
Regressed Prices |
| Timeline |
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Other Information on Investing in Schwab Mutual Fund
Schwab Monthly financial ratios help investors to determine whether Schwab Mutual Fund is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Schwab with respect to the benefits of owning Schwab Monthly security.
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