Megashort Semiconductors Daily Etf Market Value
| SOXD Etf | 11.53 0.01 0.09% |
| Symbol | MegaShort |
MegaShort Semiconductors '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 MegaShort Semiconductors' 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 MegaShort Semiconductors.
| 04/20/2025 |
| 07/19/2025 |
If you would invest 0.00 in MegaShort Semiconductors on April 20, 2025 and sell it all today you would earn a total of 0.00 from holding MegaShort Semiconductors Daily or generate 0.0% return on investment in MegaShort Semiconductors over 90 days.
MegaShort Semiconductors 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 MegaShort Semiconductors' 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 MegaShort Semiconductors Daily upside and downside potential and time the market with a certain degree of confidence.
| Information Ratio | (0.36) | |||
| Maximum Drawdown | 19.59 | |||
| Value At Risk | (9.92) | |||
| Potential Upside | 4.52 |
MegaShort Semiconductors Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for MegaShort Semiconductors' investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as MegaShort Semiconductors' standard deviation. In reality, there are many statistical measures that can use MegaShort Semiconductors historical prices to predict the future MegaShort Semiconductors' volatility.| Risk Adjusted Performance | (0.30) | |||
| Jensen Alpha | (1.50) | |||
| Total Risk Alpha | (2.08) | |||
| Treynor Ratio | (5.62) |
MegaShort Semiconductors Backtested Returns
MegaShort Semiconductors has Sharpe Ratio of -0.33, which conveys that the entity had a -0.33 % return per unit of risk over the last 3 months. MegaShort Semiconductors exposes twenty-one different technical indicators, which can help you to evaluate volatility embedded in its price movement. Please verify MegaShort Semiconductors' Mean Deviation of 3.22, standard deviation of 4.41, and Risk Adjusted Performance of (0.30) to check out the risk estimate we provide. The etf secures a Beta (Market Risk) of 0.26, which conveys not very significant fluctuations relative to the market. As returns on the market increase, MegaShort Semiconductors' returns are expected to increase less than the market. However, during the bear market, the loss of holding MegaShort Semiconductors is expected to be smaller as well.
Auto-correlation | 0.93 |
Excellent predictability
MegaShort Semiconductors Daily has excellent predictability. Overlapping area represents the amount of predictability between MegaShort Semiconductors time series from 20th of April 2025 to 4th of June 2025 and 4th of June 2025 to 19th of July 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 MegaShort Semiconductors price movement. The serial correlation of 0.93 indicates that approximately 93.0% of current MegaShort Semiconductors price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.93 | |
| Spearman Rank Test | 0.37 | |
| Residual Average | 0.0 | |
| Price Variance | 3.45 |
MegaShort Semiconductors lagged returns against current returns
Autocorrelation, which is MegaShort Semiconductors 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 MegaShort Semiconductors' etf expected returns. We can calculate the autocorrelation of MegaShort Semiconductors returns to help us make a trade decision. For example, suppose you find that MegaShort Semiconductors 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 |
MegaShort Semiconductors 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 MegaShort Semiconductors etf is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if MegaShort Semiconductors etf is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in MegaShort Semiconductors etf over time.
Current vs Lagged Prices |
| Timeline |
MegaShort Semiconductors Lagged Returns
When evaluating MegaShort Semiconductors' market value, investors can use the concept of autocorrelation to see how much of an impact past prices of MegaShort Semiconductors etf have on its future price. MegaShort Semiconductors 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, MegaShort Semiconductors autocorrelation shows the relationship between MegaShort Semiconductors etf current value and its past values and can show if there is a momentum factor associated with investing in MegaShort Semiconductors Daily.
Regressed Prices |
| Timeline |
Pair Trading with MegaShort Semiconductors
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if MegaShort Semiconductors position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in MegaShort Semiconductors will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to MegaShort Semiconductors could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace MegaShort Semiconductors when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back MegaShort Semiconductors - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling MegaShort Semiconductors Daily to buy it.
The correlation of MegaShort Semiconductors is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as MegaShort Semiconductors moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if MegaShort Semiconductors moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for MegaShort Semiconductors can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.