Tag: portfolio analysis

Portfolio analysis statistical considerations

Portfolio analysis statistical considerations

Portfolio analysis is essentially a statistical technique. However, because the ‘‘true’’ population parameters for the input data (expected returns, variances, and covariances) are unobservable, sample statistics must be estimated. Thus, the efficient portfolios generated by portfolio analysis are no better than the statistical input data on which they are based.

Time-varying betas in Risk Management

Time-varying betas in Risk Management

Estimation of betas with regression is adequate for asset managers, but it is not appropriate in risk management of portfolios because monitoring is done on a frequent basis – daily and even intra-daily. Indeed, parameters estimated by OLS at these frequencies will not reflect the actual market conditions because they just represent an average value over time on the sample.

The Covariance Matrix and White Noise

The Covariance Matrix and White Noise

The two fundamental ingredients of Markowitz (1952) mean-variance optimization are the expected (excess) return for each asset (the portfolio manager’s ability to forecast), and the covariance matrix of asset returns (the risk control).

The single index factor model

The single index factor model

The single-index factor model assumes that the co-movement between stocks is due to a single common influence or index. Casual observation of stock prices reveals that when the market goes up (as measured by any of the widely available stock market indexes), most stocks tend to increase in price, and when the market goes down, most stocks tend to decrease in price.

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