USA Change Macroaxis User Registration

Home Portfolios Solutions About Us

More ROI Blog

Marketplace Community ScreenersEfficient Frontier Correlations Risk/Return

US Market Closed: Feb 10, 08:21 AM 2012

NYSE 8081.25 NASDAQ 2927.23

and more..

sponsered by

Processing
Collecting necessary data for LG1-R98688...

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.

Help

Correlation Analysis

View All Portfolios

More Actions
- Select Assests
- Optimize Portfolio
- Suggest Portfolio
- Backtest Watchlist
- Analyze Correlations
- View Transactions
- Check Volatilities
- Import Equities
- Search Equities
- Filter Tops

Specify valid comma-separated symbols

Build It

Select investment horizon:

30 Days (Login to change)

Generate output as Table Cloud

	LG1-R98688	RN3-I95200	EODS	DX1-I9620	TF3-U9920	CA1-S92700	MLQUD-OTC	MI1-R91650	SM1-T9720	EX2-I93200	GL1-R94700	4629C	AF1-G9900	MSE-R92150	CR1-U9800	ITBSR	EX1-I91900	2975C	3396C	DF1-U94200
LG1-R98688		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
RN3-I95200	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
EODS	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
DX1-I9620	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
TF3-U9920	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
CA1-S92700	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
MLQUD-OTC	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
MI1-R91650	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
SM1-T9720	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
EX2-I93200	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
GL1-R94700	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
4629C	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.06	0.0	0.31	0.48	0.0
AF1-G9900	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0	0.0
MSE-R92150	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0	0.0
CR1-U9800	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0	0.0	0.0
ITBSR	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.06	0.0	0.0	0.0		0.0	-0.24	0.42	0.0
EX1-I91900	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0		0.0	0.0	0.0
2975C	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.31	0.0	0.0	0.0	-0.24	0.0		0.05	0.0
3396C	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.48	0.0	0.0	0.0	0.42	0.0	0.05		0.0
DF1-U94200	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0

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

Volatility

Backtest

Correlation Matchups

High positive correlations

3396C	+ 0.48	4629C
3396C	+ 0.42	ITBSR
2975C	+ 0.31	4629C
ITBSR	+ 0.06	4629C
3396C	+ 0.05	2975C

Insignificant Correlation

2975C

- 0.24

ITBSR

3396C	+ 0.05	2975C
ITBSR	+ 0.06	4629C

High negative correlations

2975C

- 0.24

ITBSR

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

31055 global portfolios

Add positions and diversify yours portfolios

Sharpe Ratios

				LG1-R98688PA		0.00
				RN3-I95200PA		0.00
				FAURECIA		0.00
				DX1-I9620PA		0.00
				TF3-U9920PA		0.00
				CA1-S92700PA		0.00
				NOVAMEX		0.00
				MI1-R91650PA		0.00
				SM1-T9720PA		0.00
				EX2-I93200PA		0.00
				GL1-R94700PA		0.00
				4629CPA		0.29
				AF1-G9900PA		0.00
				MSE-R92150PA		0.00
				CR1-U9800PA		0.00
				ITS GROUP		0.19
				EX1-I91900PA		0.00
				2975CPA		0.03
				3396CPA		0.14
				DF1-U94200PA		0.00

Sectors

Software

Cars

Banks

Drugs

Alcohol

Broadcasting

Education

Energy

Telecom

Tobacco

Airlines

Entertainment

Top Advisors

1	Shepherd Kaplan	6
2	Hilltop Advisor	5
3	Babson Capital	3
4	Eldridge Financ	3
5	Vest Assured I	3

Top Owned Stocks

1	AAPL	464
2	GOOG	373
3	GE	335
4	MSFT	278
5	C	263

Top Owned ETFs

1	SPY	314
2	GLD	307
3	VWO	242
4	EEM	236
5	VNQ	200

Top Owned Funds

1	FCNTX	121
2	VFINX	107
3	PRPFX	105
4	DODFX	102
5	VGSIX	94