Optimum Small Mid Cap Fund Market Value

OCSVX Fund  USD 12.93  0.03  0.23%   
Optimum Small-mid's market value is the price at which a share of Optimum Small-mid trades on a public exchange. It measures the collective expectations of Optimum Small Mid Cap investors about its performance. Optimum Small-mid is trading at 12.93 as of the 28th of November 2024; that is 0.23 percent decrease since the beginning of the trading day. The fund's open price was 12.96.
With this module, you can estimate the performance of a buy and hold strategy of Optimum Small Mid Cap and determine expected loss or profit from investing in Optimum Small-mid over a given investment horizon. Check out Optimum Small-mid Correlation, Optimum Small-mid Volatility and Optimum Small-mid Alpha and Beta module to complement your research on Optimum Small-mid.
Symbol

Please note, there is a significant difference between Optimum Small-mid's value and its price as these two are different measures arrived at by different means. Investors typically determine if Optimum Small-mid is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Optimum Small-mid'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.

Optimum Small-mid '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 Optimum Small-mid'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 Optimum Small-mid.
0.00
06/01/2024
No Change 0.00  0.0 
In 5 months and 30 days
11/28/2024
0.00
If you would invest  0.00  in Optimum Small-mid on June 1, 2024 and sell it all today you would earn a total of 0.00 from holding Optimum Small Mid Cap or generate 0.0% return on investment in Optimum Small-mid over 180 days. Optimum Small-mid is related to or competes with The Hartford, Rbc Ultra-short, Locorr Dynamic, Doubleline Core, Balanced Fund, and Ms Global. Under normal circumstances, the fund will invest at least 80 percent of its net assets, plus the amount of any borrowing... More

Optimum Small-mid 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 Optimum Small-mid'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 Optimum Small Mid Cap upside and downside potential and time the market with a certain degree of confidence.

Optimum Small-mid Market Risk Indicators

Today, many novice investors tend to focus exclusively on investment returns with little concern for Optimum Small-mid's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Optimum Small-mid's standard deviation. In reality, there are many statistical measures that can use Optimum Small-mid historical prices to predict the future Optimum Small-mid's volatility.
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Optimum Small-mid'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.
Hype
Prediction
LowEstimatedHigh
11.8212.9314.04
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Intrinsic
Valuation
LowRealHigh
11.6212.7313.84
Details

Optimum Small Mid Backtested Returns

At this stage we consider Optimum Mutual Fund to be very steady. Optimum Small Mid maintains Sharpe Ratio (i.e., Efficiency) of 0.13, which implies the entity had a 0.13% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Optimum Small Mid, which you can use to evaluate the volatility of the fund. Please check Optimum Small-mid's Risk Adjusted Performance of 0.1128, coefficient of variation of 698.32, and Semi Deviation of 0.6922 to confirm if the risk estimate we provide is consistent with the expected return of 0.15%. The fund holds a Beta of 1.27, which implies a somewhat significant risk relative to the market. As the market goes up, the company is expected to outperform it. However, if the market returns are negative, Optimum Small-mid will likely underperform.

Auto-correlation

    
  0.48  

Average predictability

Optimum Small Mid Cap has average predictability. Overlapping area represents the amount of predictability between Optimum Small-mid time series from 1st of June 2024 to 30th of August 2024 and 30th of August 2024 to 28th 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 Optimum Small Mid price movement. The serial correlation of 0.48 indicates that about 48.0% of current Optimum Small-mid price fluctuation can be explain by its past prices.
Correlation Coefficient0.48
Spearman Rank Test0.37
Residual Average0.0
Price Variance0.19

Optimum Small Mid lagged returns against current returns

Autocorrelation, which is Optimum Small-mid 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 Optimum Small-mid's mutual fund expected returns. We can calculate the autocorrelation of Optimum Small-mid returns to help us make a trade decision. For example, suppose you find that Optimum Small-mid 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  

Optimum Small-mid 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 Optimum Small-mid mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Optimum Small-mid mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Optimum Small-mid mutual fund over time.
   Current vs Lagged Prices   
       Timeline  

Optimum Small-mid Lagged Returns

When evaluating Optimum Small-mid's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Optimum Small-mid mutual fund have on its future price. Optimum Small-mid 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, Optimum Small-mid autocorrelation shows the relationship between Optimum Small-mid mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Optimum Small Mid Cap.
   Regressed Prices   
       Timeline  

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Other Information on Investing in Optimum Mutual Fund

Optimum Small-mid financial ratios help investors to determine whether Optimum 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 Optimum with respect to the benefits of owning Optimum Small-mid security.
Alpha Finder
Use alpha and beta coefficients to find investment opportunities after accounting for the risk
Portfolio Volatility
Check portfolio volatility and analyze historical return density to properly model market risk