Correlation Between Big Time and MNW
Specify exactly 2 symbols:
By analyzing existing cross correlation between Big Time and MNW, you can compare the effects of market volatilities on Big Time and MNW and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Big Time with a short position of MNW. Check out your portfolio center. Please also check ongoing floating volatility patterns of Big Time and MNW.
Diversification Opportunities for Big Time and MNW
Significant diversification
The 3 months correlation between Big and MNW is 0.03. Overlapping area represents the amount of risk that can be diversified away by holding Big Time and MNW in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on MNW and Big Time is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Big Time are associated (or correlated) with MNW. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of MNW has no effect on the direction of Big Time i.e., Big Time and MNW go up and down completely randomly.
Pair Corralation between Big Time and MNW
Assuming the 90 days trading horizon Big Time is expected to generate 53.2 times less return on investment than MNW. But when comparing it to its historical volatility, Big Time is 28.01 times less risky than MNW. It trades about 0.14 of its potential returns per unit of risk. MNW is currently generating about 0.27 of returns per unit of risk over similar time horizon. If you would invest 29.00 in MNW on September 4, 2024 and sell it today you would earn a total of 29.00 from holding MNW or generate 100.0% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Big Time vs. MNW
Performance |
| Timeline |
| Big Time |
| MNW |
Big Time and MNW Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Big Time and MNW
The main advantage of trading using opposite Big Time and MNW positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Big Time position performs unexpectedly, MNW 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 MNW will offset losses from the drop in MNW's long position.The idea behind Big Time and MNW pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.Check out your portfolio center.Note that this page's information should be used as a complementary analysis 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 Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.
Other Complementary Tools
| Stock Screener Find equities using a custom stock filter or screen asymmetry in trading patterns, price, volume, or investment outlook. | |
| CEOs Directory Screen CEOs from public companies around the world | |
| ETF Categories List of ETF categories grouped based on various criteria, such as the investment strategy or type of investments | |
| Top Crypto Exchanges Search and analyze digital assets across top global cryptocurrency exchanges | |
| Portfolio Backtesting Avoid under-diversification and over-optimization by backtesting your portfolios |