Correlation Between LSI Industries and Dow Jones
Can any of the company-specific risk be diversified away by investing in both LSI Industries and Dow Jones at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining LSI Industries and Dow Jones into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between LSI Industries and Dow Jones Industrial, you can compare the effects of market volatilities on LSI Industries and Dow Jones 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 LSI Industries with a short position of Dow Jones. Check out your portfolio center. Please also check ongoing floating volatility patterns of LSI Industries and Dow Jones.
Diversification Opportunities for LSI Industries and Dow Jones
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between LSI and Dow is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding LSI Industries and Dow Jones Industrial in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Dow Jones Industrial and LSI Industries 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 LSI Industries are associated (or correlated) with Dow Jones. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Dow Jones Industrial has no effect on the direction of LSI Industries i.e., LSI Industries and Dow Jones go up and down completely randomly.
Pair Corralation between LSI Industries and Dow Jones
Given the investment horizon of 90 days LSI Industries is expected to generate 2.53 times more return on investment than Dow Jones. However, LSI Industries is 2.53 times more volatile than Dow Jones Industrial. It trades about 0.23 of its potential returns per unit of risk. Dow Jones Industrial is currently generating about 0.2 per unit of risk. If you would invest 1,566 in LSI Industries on August 31, 2024 and sell it today you would earn a total of 462.00 from holding LSI Industries or generate 29.5% return on investment over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 98.44% |
Values | Daily Returns |
LSI Industries vs. Dow Jones Industrial
Performance |
Timeline |
LSI Industries and Dow Jones Volatility Contrast
Predicted Return Density |
Returns |
LSI Industries
Pair trading matchups for LSI Industries
Dow Jones Industrial
Pair trading matchups for Dow Jones
Pair Trading with LSI Industries and Dow Jones
The main advantage of trading using opposite LSI Industries and Dow Jones positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if LSI Industries position performs unexpectedly, Dow Jones 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 Dow Jones will offset losses from the drop in Dow Jones' long position.LSI Industries vs. Plexus Corp | LSI Industries vs. OSI Systems | LSI Industries vs. CTS Corporation | LSI Industries vs. Benchmark Electronics |
Dow Jones vs. Aerofoam Metals | Dow Jones vs. ACG Metals Limited | Dow Jones vs. China Clean Energy | Dow Jones vs. Fast Retailing Co |
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 Portfolio Volatility module to check portfolio volatility and analyze historical return density to properly model market risk.
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