Correlation Between Sinar Mas and Wahana Ottomitra

Specify exactly 2 symbols:
Can any of the company-specific risk be diversified away by investing in both Sinar Mas and Wahana Ottomitra 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 Sinar Mas and Wahana Ottomitra into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Sinar Mas Multiartha and Wahana Ottomitra Multiartha, you can compare the effects of market volatilities on Sinar Mas and Wahana Ottomitra 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 Sinar Mas with a short position of Wahana Ottomitra. Check out your portfolio center. Please also check ongoing floating volatility patterns of Sinar Mas and Wahana Ottomitra.

Diversification Opportunities for Sinar Mas and Wahana Ottomitra

SinarWahanaDiversified AwaySinarWahanaDiversified Away100%
0.19
  Correlation Coefficient

Average diversification

The 3 months correlation between Sinar and Wahana is 0.19. Overlapping area represents the amount of risk that can be diversified away by holding Sinar Mas Multiartha and Wahana Ottomitra Multiartha in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Wahana Ottomitra Mul and Sinar Mas 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 Sinar Mas Multiartha are associated (or correlated) with Wahana Ottomitra. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Wahana Ottomitra Mul has no effect on the direction of Sinar Mas i.e., Sinar Mas and Wahana Ottomitra go up and down completely randomly.

Pair Corralation between Sinar Mas and Wahana Ottomitra

Assuming the 90 days trading horizon Sinar Mas is expected to generate 1.43 times less return on investment than Wahana Ottomitra. In addition to that, Sinar Mas is 1.24 times more volatile than Wahana Ottomitra Multiartha. It trades about 0.03 of its total potential returns per unit of risk. Wahana Ottomitra Multiartha is currently generating about 0.05 per unit of volatility. If you would invest  26,181  in Wahana Ottomitra Multiartha on December 11, 2024 and sell it today you would earn a total of  10,419  from holding Wahana Ottomitra Multiartha or generate 39.8% return on investment over 90 days.
Time Period3 Months [change]
DirectionMoves Together 
StrengthInsignificant
Accuracy99.79%
ValuesDaily Returns

Sinar Mas Multiartha  vs.  Wahana Ottomitra Multiartha

 Performance 
JavaScript chart by amCharts 3.21.15Dec2025Feb -505
JavaScript chart by amCharts 3.21.15SMMA WOMF
       Timeline  
Sinar Mas Multiartha 

Risk-Adjusted Performance

OK

 
Weak
 
Strong
Compared to the overall equity markets, risk-adjusted returns on investments in Sinar Mas Multiartha are ranked lower than 9 (%) of all global equities and portfolios over the last 90 days. Despite quite conflicting forward-looking signals, Sinar Mas may actually be approaching a critical reversion point that can send shares even higher in April 2025.
JavaScript chart by amCharts 3.21.15JanFebMarFebMar14,00014,50015,00015,50016,00016,50017,00017,50018,000
Wahana Ottomitra Mul 

Risk-Adjusted Performance

Insignificant

 
Weak
 
Strong
Compared to the overall equity markets, risk-adjusted returns on investments in Wahana Ottomitra Multiartha are ranked lower than 3 (%) of all global equities and portfolios over the last 90 days. Despite quite persistent forward-looking signals, Wahana Ottomitra is not utilizing all of its potentials. The latest stock price mess, may contribute to short-term losses for the institutional investors.
JavaScript chart by amCharts 3.21.15JanFebMarFebMar340360380400420440

Sinar Mas and Wahana Ottomitra Volatility Contrast

   Predicted Return Density   
JavaScript chart by amCharts 3.21.15-3.29-2.47-1.64-0.810.00.811.672.523.384.23 0.050.100.150.200.250.300.35
JavaScript chart by amCharts 3.21.15SMMA WOMF
       Returns  

Pair Trading with Sinar Mas and Wahana Ottomitra

The main advantage of trading using opposite Sinar Mas and Wahana Ottomitra positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Sinar Mas position performs unexpectedly, Wahana Ottomitra 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 Wahana Ottomitra will offset losses from the drop in Wahana Ottomitra's long position.
The idea behind Sinar Mas Multiartha and Wahana Ottomitra Multiartha 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 ETF Categories module to list of ETF categories grouped based on various criteria, such as the investment strategy or type of investments.

Other Complementary Tools

Portfolio Holdings
Check your current holdings and cash postion to detemine if your portfolio needs rebalancing
Pattern Recognition
Use different Pattern Recognition models to time the market across multiple global exchanges
Price Exposure Probability
Analyze equity upside and downside potential for a given time horizon across multiple markets
Watchlist Optimization
Optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm
Equity Valuation
Check real value of public entities based on technical and fundamental data