Mean Variance Analysis

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Harry W. Markowitz, the father of “Modern Portfolio theory”, developed the mean-variance analysis, which focuses on creating portfolios of assets that minimizes the variance of returns i.e. risk, given a level of desired return, or maximizes the returns given a level of risk tolerance. This theory aids the process of portfolio construction by providing a quantitative take on it. It integrates the field of quantitative analysis with portfolio management. Mean variance analysis has found wide applications both inside and outside financial economics. However it is based on certain assumptions which do not hold good in practice. Hence there have been certain revisions to it, so as to make it a more useful tool in portfolio management. Mean Variance Analysis

Within the mean variance approach of Markowitz, the basic assumption is that risk is measured by variance, and the investment decision is based on the trade-off between higher mean and lower variance of the returns. The locus of optimal mean-variance combinations is called the efficient frontier, on which all rational investors would desire to be positioned. Asset returns are assumed to be (jointly) normally distributed random variables, and correlations between assets are also assumed to be fixed and constant forever. (Mz)

Other assumptions include: (Mz)

All investors aim to maximize economic utility (in other words, to make as much money as possible, regardless of any other considerations).
All investors are rational and risk averse.
All investors have access to the same information at the same point of time. It assumes efficient market hypothesis holds good and there is no information asymmetry or insider trading.
Investors have an accurate conception of possible returns, i.e., the probability beliefs of investors match the true distribution of returns. Investor’s beliefs are unbiased.
There are no taxes or transaction costs. It assumes perfect markets.
All investors are price takers i.e....
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