Risk Based Portfolio Construction Methods

Advisors and investors would do well to pay as much attention to the expected volatility of any portfolio or investment as they do to anticipated returns. Moreover, all things being equal, a new investment should only be added to a portfolio when it either reduces the expected risk for a targeted level of returns, or when it boosts expected portfolio returns without adding additional risk, as measured by the expected standard deviation of those returns. Lesson 2: Don’t assume bonds or international stocks offer adequate portfolio diversification. As the world’s financial markets become more closely correlated, bonds and foreign stocks may not provide adequate portfolio diversification. Instead, advisors may want to recommend that suitable investors add modest exposure to nontraditional investments such as hedge funds, private equity and real assets. Such exposure may bolster portfolio returns, while reducing overall risk, depending on how it is structured. Lesson 3: Be disciplined in adhering to asset allocation targets. The long-term benefits of portfolio diversification will only be realized if investors are disciplined in adhering to asset allocation guidelines. For this reason, it is recommended that advisors regularly revisit portfolio allocations and rebalance

“The Benefits of diversification are clear. Portfolio theory has played a crucial role in explaining the relationship between risk and return where more than one investment is held. It also enables us to identify optimal and efficient portfolios.”

Diversification is a basic principle in investing the idea being that since you cannot possibly know beforehand which stocks will perform better or worse than the average, you cannot afford to put all of your money into one company, or even in companies within a single industry. One resorts to diversification to spread the risk -- and opportunity. The average returns are obtained by diversifying.

(b) To determine Policy Portfolio by using mean-variance analysis. Given a variable number of expected portfolio return, we would choose our strategy from a set of minimum-variance portfolio basing on our tolerance for risk.

Harry Markowitz 1991, developed a theory of “Portfolio choice”, that allows the investors to examine the risk as per the expected returns. In modern World, this theory is known as Modern portfolio theory (MPT). It attempts to attain the best portfolio expected return for a predefined portfolio risk, or to minimise the risk for the predefined expected returns, by a careful choice of assets. Though it’s a widely used theory, still has been challenged widely. The critics question the feasibility of theory as a strategy for

increasing w by a small amount. Therefore, Marginal VAR (value at risk) allows risk managers to study the effects of adding or subtracting positions from an investment portfolio. Since value at risk is affected by the correlation of investment positions, it is not enough to consider an individual investment's VAR level in isolation. Rather, it must be compared with the total portfolio to determine what

(b) The mean excess return, standard deviation, and portfolio weights for the optimum (maximum Sharpe ratio) portfolio.

The idea behind diversification is to invest in a large number of assets so that a loss in any particular investment is minimized by gains

In order to find the optimal portfolio allocation, the group needs to find the portfolio structured with lowest risk under a given return. This can be achieved by applying Mean-Variance Theory and Markowitz model find the efficient frontier, which yields the most optimal portfolio under given returns. It can be expressed in mathematical terms and solved by quadratic programming. [Appendix A]

UNIVERSITY OF ILLINOIS AT CHICAGO Liautaud Graduate School of Business Department of Finance Professor Hsiu-lang Chen 1 Practice Problem I

To reduce a firm’s specific risk or residual risk a portfolio should have negative covariance or rather it should have no variance at all, for large portfolios however calculating variance requires greater and sophisticated computing power. As such, Index models greatly decrease the computations needed to calculate the optimum portfolio. The use of such Index models also eliminates illogical or rather absurd results. The Single Index model (SIM) and the Capital Asset Pricing Model (CAPM) are such models used to calculate the optimum portfolio.

Diversification is a method of investing that been shown to increase portfolio return while reducing portfolio risk as measured by standard deviation. This method specifically increases the efficient frontier for investors. The challenge to an investing firm is an appetite by its customers for an ever increasing efficient frontier. One area to explore to obtain this increase is through further diversifying through international diversification.

As a result, many different factors have been tested across different markets. Historically, most studies have relied on general economic theories or empirical observations in selecting Factors. Benaković and Posedel (2010) emphasize Interest rates, oil prices, and industrial production. Chen, Roll and Ross (1986) use industrial production growth, inflation, bonds spread, NYSE stock market returns, oil prices, interest term structure, and consumption to decompose returns of a portfolio with general securities. Bodurtha, Cho and Senbet (1989) even uses international factors. Most of literatures have focused on applying different factors with a portfolio of many securities, as it is widely known that idiosyncratic risks diversifies away as the number of

If the assets exist to help meet a liability, the liability should be considered in the process; 3. Basing one’s decision solely on an asset allocation’s mean and variance is insufficient to base one’s decisions, in a world in which asset class returns are not normally distributed; and, 4. Most investors have multi-period objectives and the mean-variance framework is a single period model. These potential shortcomings are the likely reasons that practitioners have not fully embraced meanvariance optimization. For a number of practitioners, mean-variance optimization creates the illusion of quantitative sophistication; yet, in practice, asset allocations are developed using judgmental, ad hoc approaches. Recent advances significantly improve the quality of typical mean-variance optimizationbased asset allocations that should allow a far wider audience to realize the benefits of the Markowitz paradigm, or at least the intent of the paradigm. In this article, we focus on the first issue: the lack of diversification that can result from traditional meanvariance optimization. We begin with two examples in which traditional mean-variance optimization

This scope of study   is limited to 6 firms /companies of selected industries. Pharmaceutical, Information Technologies, Automobile, & 12 companies / banks from Banking Industry.