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An investor can reduce portfolio risk simply by holding instruments which are not perfectly correlated. In other words, investors can reduce their exposure to individual asset risk by holding a diversified portfolio of assets. Diversification will allow for the same portfolio return with reduced risk.

About correlation table

Correlation table is a two-dimensional matrix that shows correlation coefficient between pairs of securities. The cells in the table are color-coded to highlight significantly positive and negative relationships.

About correlation cloud

Correlation cloud is a flat representation of correlation coefficients between pairs of securities. The links in the cloud are color-coded to highlight significantly positive and negative relationships.

To create correlation table or cloud specify valid comma-separated symbols and hit Build It button.

Please note, the New York Stock Exchange (NYSE) and American Stock Exchange (AMEX) have recently merged. Although Macroaxis has implemented solutions to handle this transition gracefully, you may still find some securities that may not be fully transferred from one exchange to another.
       

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Correlation Analysis

       
  View All Portfolios 
       
    
       
       
       
 Specify valid comma-separated symbols
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Select investment horizon: 
30 Days (Login to change)
Generate output as
       
       

       
NPMRF
BBW
OBSPF
ESNR
OMRI
DPBSF
MRWSF
AALQL
TKCZF
CCEGF
SHSH
SYKE
BNYTF
TTIL
FWEIF
FCRV
HIBB
WVK
LKREF
CNWT
NPMRF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
BBW
0.00.00.00.00.00.180.00.00.00.16-0.230.00.00.00.0-0.380.0-0.160.0
OBSPF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
ESNR
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
OMRI
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
DPBSF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
MRWSF
0.00.180.00.00.00.00.00.00.0-0.130.240.00.00.00.0-0.190.0-0.240.0
AALQL
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
TKCZF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
CCEGF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
SHSH
0.00.160.00.00.00.0-0.130.00.00.0-0.20.00.00.00.0-0.20.0-0.090.0
SYKE
0.0-0.230.00.00.00.00.240.00.00.0-0.20.00.00.00.00.430.0-0.020.0
BNYTF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
TTIL
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
FWEIF
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
FCRV
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
HIBB
0.0-0.380.00.00.00.0-0.190.00.00.0-0.20.430.00.00.00.00.00.040.0
WVK
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0
LKREF
0.0-0.160.00.00.00.0-0.240.00.00.0-0.09-0.020.00.00.00.00.040.00.0
CNWT
0.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.00.0

      Hover over cells for correlations between assets, or click to compare fundamentalsVolatilityBacktest

Correlation Matchups

    

High positive correlations

HIBB   + 0.43   SYKE
SYKE   + 0.24   MRWSF
MRWSF   + 0.18   BBW
SHSH   + 0.16   BBW
LKREF   + 0.04   HIBB

Insignificant Correlation

LKREF   - 0.02   SYKE
LKREF   - 0.09   SHSH
SHSH   - 0.13   MRWSF
LKREF   - 0.16   BBW
HIBB   - 0.19   MRWSF
SYKE   - 0.2   SHSH
HIBB   - 0.2   SHSH
LKREF   + 0.04   HIBB
SHSH   + 0.16   BBW
MRWSF   + 0.18   BBW
SYKE   + 0.24   MRWSF

High negative correlations

HIBB   - 0.38   BBW
LKREF   - 0.24   MRWSF
SYKE   - 0.23   BBW
HIBB   - 0.2   SHSH
SYKE   - 0.2   SHSH
HIBB   - 0.19   MRWSF
LKREF   - 0.16   BBW
SHSH   - 0.13   MRWSF
LKREF   - 0.09   SHSH
LKREF   - 0.02   SYKE
    
       

Why correlation coefficient is important?

If all the assets of a portfolio have a correlation of 1, i.e., perfect correlation, the portfolio volatility (standard deviation) will be equal to the weighted sum of the individual asset volatilities. Hence the portfolio variance will be equal to the square of the total weighted sum of the individual asset volatilities. If all the assets have a correlation of 0, i.e., perfectly uncorrelated, the portfolio variance is the sum of the individual asset weights squared times the individual asset variance (and volatility is the square root of this sum). If correlation is less than zero, i.e., the assets are inversely correlated, the portfolio variance and hence volatility will be less than if the correlation is 0. Learn more...


References

Modern Portfolio Theory From Wikipedia, the free encyclopedia Learn About Modern Portfolio Theory (MPT)
Markowitz, Harry M. (1952). Portfolio Selection, Journal of Finance, 7 (1)
Sharpe, William F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk, Journal of Finance, 19(3)
Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets, The Review of Economics and Statistics, 47 (1), 13-39
Burmeister E and Wall KD., The arbitrage pricing theory and macroeconomic factor measures, The Financial Review, 21:1-20, 1986
Chen, N.F, and Ingersoll, E., Exact pricing in linear factor models with finitely many assets: A note, Journal of Finance June 1983
Fama, E. and French, K. (1992). The Cross-Section of Expected Stock Returns, Journal of Finance, June 1992, 427-466
Black, F., Jensen, M., and Scholes, M. The Capital Asset Pricing Model: Some Empirical Tests, in M. Jensen ed., Studies in the Theory of Capital Markets. (1972)
French, C. W. (2003). "The Treynor Capital Asset Pricing Model", Journal of Investment Management, 1 (2), 60-72
Lintner, J. (1965). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets, Review of Economics and Statistics, 47 (1), 13-37
Markowitz, Harry M. (1999). The early history of portfolio theory: 1600-1960, Financial Analysts Journal, 55 (4)
Tobin, James (1958). Liquidity preference as behavior towards risk, The Review of Economic Studies, 25 Treynor, J. L. (1961). "Market Value, Time, and Risk." Unpublished manuscript.
Treynor, J. L. (1962). "Toward a Theory of Market Value of Risky Assets." Unpublished manuscript.

Other Resources

Robust Portfolio Optimization and Management by Frank J. Fabozzi, Petter N. Kolm, Dessislava Pachamanova, Sergio M. Focardi
Portfolio Optimization and Performance Analysis by Jean-Luc Prigent
Option Pricing and Portfolio Optimization by Ralf Korn, Elke Korn
Portfolio optimizations in incomplete financial markets by Walter Schachermayer
Bond Portfolio Optimization by Michael Puhle
An MCDM approach to portfolio optimization by M. Ehrgott, K. Klamroth, C. Schwehm
    
Efficient Frontier
Efficient Frontier
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Sharpe Ratios 

   
 Macroaxis: United States NEPTUNE 0.00 Price Moved None
   
 Macroaxis: United States Build-A-Bear 0.18 Price Moved Up
   
 Macroaxis: United States ORBUS 0.00 Price Moved None
   
 Macroaxis: United States Electronic 0.00 Price Moved None
   
 Macroaxis: United States Omrix 0.00 Price Moved None
   
 Macroaxis: United States DAMPSKIBSSEL 0.00 Price Moved None
   
 Macroaxis: United States MORRISON 0.05 Price Moved Down
   
 Macroaxis: United States ALL AMER 0.00 Price Moved None
   
 Macroaxis: United States TURKCELL 0.00 Price Moved None
   
 Macroaxis: United States CARCLO 0.00 Price Moved None
   
 Macroaxis: United States Shoshone 0.21 Price Moved Down
   
 Macroaxis: United States Sykes 0.10 Price Moved Up
   
 Macroaxis: United States BRAINYTOYS 0.00 Price Moved None
   
 Macroaxis: United States TTI Team 0.00 Price Moved None
   
 Macroaxis: United States FAR WEST 0.00 Price Moved None
   
 Macroaxis: United States FIRST 0.00 Price Moved None
   
 Macroaxis: United States Hibbett 0.21 Price Moved Up
   
 Macroaxis: United States MORGAN 0.00 Price Moved None
   
 Macroaxis: United States LINK 0.06 Price Moved Up
   
 Macroaxis: United States Cistera 0.00 Price Moved None
    
    

Sectors 

Cars Correlation  Cars
Banks Correlation  Banks
Drugs Correlation  Drugs
    
       

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