The Hartford Checks Fund Market Value
HCKFX Fund | USD 9.63 0.10 1.05% |
Symbol | Hartford |
Hartford Checks '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 Hartford Checks' 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 Hartford Checks.
04/01/2024 |
| 05/01/2024 |
If you would invest 0.00 in Hartford Checks on April 1, 2024 and sell it all today you would earn a total of 0.00 from holding The Hartford Checks or generate 0.0% return on investment in Hartford Checks over 30 days. Hartford Checks is related to or competes with Hartford Growth, Hartford Growth, Hartford Growth, Hartford Growth, Hartford Growth, Hartford Growth, and Hartford Growth. The fund invests in a combination of Hartford Funds the Hartford Capital Appreciation Fund, which normally invests at least 65 percent of its net assets in common stocks the Hartford Dividend and Growth Fund, which invests primarily in a portfolio of equity securities that typically have above average dividend yields and the Hartford Total Return Bond ETF, which under normal circumstances invests at least 80 percent of its net assets in bonds. More
Hartford Checks 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 Hartford Checks' 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 The Hartford Checks upside and downside potential and time the market with a certain degree of confidence.
Downside Deviation | 0.647 | |||
Information Ratio | (0.05) | |||
Maximum Drawdown | 2.29 | |||
Value At Risk | (0.83) | |||
Potential Upside | 0.7338 |
Hartford Checks Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Hartford Checks' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Hartford Checks' standard deviation. In reality, there are many statistical measures that can use Hartford Checks historical prices to predict the future Hartford Checks' volatility.Risk Adjusted Performance | 0.0421 | |||
Jensen Alpha | 0.0247 | |||
Total Risk Alpha | (0.01) | |||
Sortino Ratio | (0.04) | |||
Treynor Ratio | (11.71) |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Hartford Checks' 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.
Hartford Checks Backtested Returns
We consider Hartford Checks very steady. Hartford Checks holds Efficiency (Sharpe) Ratio of 0.0552, which attests that the entity had a 0.0552% return per unit of risk over the last 3 months. We have found twenty-eight technical indicators for Hartford Checks, which you can use to evaluate the volatility of the entity. Please check out Hartford Checks' Risk Adjusted Performance of 0.0421, market risk adjusted performance of (11.70), and Downside Deviation of 0.647 to validate if the risk estimate we provide is consistent with the expected return of 0.0278%. The fund retains a Market Volatility (i.e., Beta) of -0.0021, which attests to not very significant fluctuations relative to the market. As returns on the market increase, returns on owning Hartford Checks are expected to decrease at a much lower rate. During the bear market, Hartford Checks is likely to outperform the market.
Auto-correlation | -0.47 |
Modest reverse predictability
The Hartford Checks has modest reverse predictability. Overlapping area represents the amount of predictability between Hartford Checks time series from 1st of April 2024 to 16th of April 2024 and 16th of April 2024 to 1st 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 Hartford Checks price movement. The serial correlation of -0.47 indicates that about 47.0% of current Hartford Checks price fluctuation can be explain by its past prices.
Correlation Coefficient | -0.47 | |
Spearman Rank Test | -0.62 | |
Residual Average | 0.0 | |
Price Variance | 0.0 |
Hartford Checks lagged returns against current returns
Autocorrelation, which is Hartford Checks 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 Hartford Checks' mutual fund expected returns. We can calculate the autocorrelation of Hartford Checks returns to help us make a trade decision. For example, suppose you find that Hartford Checks 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 |
Hartford Checks 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 Hartford Checks mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Hartford Checks mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Hartford Checks mutual fund over time.
Current vs Lagged Prices |
Timeline |
Hartford Checks Lagged Returns
When evaluating Hartford Checks' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Hartford Checks mutual fund have on its future price. Hartford Checks 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, Hartford Checks autocorrelation shows the relationship between Hartford Checks mutual fund current value and its past values and can show if there is a momentum factor associated with investing in The Hartford Checks.
Regressed Prices |
Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Hartford Checks in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Hartford Checks' short interest history, or implied volatility extrapolated from Hartford Checks options trading.
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Try AI Portfolio ArchitectCheck out Hartford Checks Correlation, Hartford Checks Volatility and Hartford Checks Alpha and Beta module to complement your research on Hartford Checks. Note that the Hartford Checks information on this page should be used as a complementary analysis to other Hartford Checks' statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Stock Screener module to find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook..
Hartford Checks 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.