1 / 19

Quadratic Portfolio Management Variance - Covariance Analysis

Quadratic Portfolio Management Variance - Covariance Analysis. EMIS 8381 Prepared by Carlos V Caceres SID: 27957167 . Agenda. Objectives Portfolio Management Investment I n Action The Return The Volume Weighted Average Price (VWAP) The Risk Variance and Covariance

gasha
Download Presentation

Quadratic Portfolio Management Variance - Covariance Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Quadratic Portfolio ManagementVariance - Covariance Analysis EMIS 8381 Prepared by Carlos V Caceres SID: 27957167

  2. Agenda • Objectives • Portfolio Management • Investment In Action • The Return • The Volume Weighted Average Price (VWAP) • The Risk • Variance and Covariance • Optimization Of The Portfolio: Quadratic Programming

  3. Objectives • To buy and invest in stocks efficiently by maximizing the return • To maximize the expected return of a stock portfolio • To minimize the risk with investing in different stocks • To use Excel Solver and the variance-covariance procedure to resolve Markowitz quadratic model

  4. Portfolio Management • Portfolio management optimization is often called mean-variance (MV) optimization. • The mathematical problem can be formulated in many ways. The principal problems can be summarized as follows: • Minimize risk for a specified expected return • Maximize the expected return for a specified risk • Minimize the risk and maximize the expected return using a specified risk aversion factor • Minimize the risk regardless of the expected return • Maximize the expected return regardless of the risk • Minimize the expected return regardless of the risk

  5. Investment in Action – The Return The return is calculated by the following components: Where: Pt – Pt-1 is the price variance of the stock in the P t-1market Pt = Price at time t Pt-1 = Price at t-1 Dt= Dividends for each stock Ct = Premium The Return: Rt = Pt - Pt- 1 + Dt + Ct Pt - 1

  6. Investment in Action – VWAP The Volume Weighted Average Price

  7. The portfolio

  8. Expected Return VARVWAP for Portfolio We first calculate the variances of the prices Where: • VWAPt is price of current week • VWAPt-1 price of prior week Expected Return = VARPRICEAverage

  9. The Risk of A Stock To determine the risk of a stock we apply the variance/covariance method • * Wherei is the number of observations STDDEV =

  10. Probability Of Losing A Stock The Z-Value =

  11. The Portfolio Expected Return is the weighted sum of the expected returns for all the stocks Rp = ΣRj * Aj where Rp: Expected return of portfolio Rj: Expected return of stock j Aj : Percent of investment in stock j The Risk of the portfolio is equal to Risk =

  12. Optimization of the Portfolio Maximize Return = Σ Ai * VARVWAPi subject to: Where: - Ai is the percent of investment in stock I - VARVWAP is the volume weighted average price of the stock - COVARij is the covariance between each pair of stock - B is the desired risk level

  13. Covariance It shows how two stock prices behave between one another with respect to the expected return of each stock Covariance (A1,A2) = (1/(n-1))*Σ(A1i-U1)(A2i-U2) Where: - A1i = Variance in price of Stock 1 - A2i = Variance in price of Stock 2 - A1 = Stock 1 - A2 = Stock 2 - U1 = Expected Return of Stock 1 - U2 = Expected Return of Stock 2

  14. Correlation Coefficient ( r ) Where: r = -1 the correlation is perfect and inverse r = 1 the correlation is perfect and direct r = 0 means that the two stocks are not correlated

  15. Covariance and Correlation

  16. The Model. Portfolio Optimization

  17. The Model. Minimum Risk

  18. The Efficient Frontier How to balance maximum return and minimum risk?

  19. Questions?

More Related