Correlation Between SPTSX Dividend and Nano One

Can any of the company-specific risk be diversified away by investing in both SPTSX Dividend and Nano One 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 SPTSX Dividend and Nano One into the same portfolio, which is an essential part of the fundamental portfolio management process.

By analyzing existing cross correlation between SPTSX Dividend Aristocrats and Nano One Materials, you can compare the effects of market volatilities on SPTSX Dividend and Nano One 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 SPTSX Dividend with a short position of Nano One. Check out your portfolio center. Please also check ongoing floating volatility patterns of SPTSX Dividend and Nano One.

Diversification Opportunities for SPTSX Dividend and Nano One

-0.2

Correlation Coefficient

SPTSX Dividend  Nano One

Good diversification

The 3 months correlation between SPTSX and Nano is -0.2. Overlapping area represents the amount of risk that can be diversified away by holding SPTSX Dividend Aristocrats and Nano One Materials in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Nano One Materials and SPTSX Dividend 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 SPTSX Dividend Aristocrats are associated (or correlated) with Nano One. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Nano One Materials has no effect on the direction of SPTSX Dividend i.e., SPTSX Dividend and Nano One go up and down completely randomly.

Pair Corralation between SPTSX Dividend and Nano One

Assuming the 90 days trading horizon SPTSX Dividend Aristocrats is expected to under-perform the Nano One. But the index apears to be less risky and, when comparing its historical volatility, SPTSX Dividend Aristocrats is 9.63 times less risky than Nano One. The index trades about -0.3 of its potential returns per unit of risk. The Nano One Materials is currently generating about 0.14 of returns per unit of risk over similar time horizon. If you would invest  81.00  in Nano One Materials on September 28, 2024 and sell it today you would earn a total of  11.00  from holding Nano One Materials or generate 13.58% return on investment over 90 days.

Time Period	3 Months [change]
Direction	Moves Against
Strength	Insignificant
Accuracy	100.0%
Values	Daily Returns

SPTSX Dividend Aristocrats  vs.  Nano One Materials

Pair Trading with SPTSX Dividend and Nano One

The main advantage of trading using opposite SPTSX Dividend and Nano One positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if SPTSX Dividend position performs unexpectedly, Nano One 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 Nano One will offset losses from the drop in Nano One's long position.

The idea behind SPTSX Dividend Aristocrats and Nano One Materials 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.

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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.