Developing Robust Asset Allocations1 Working Paper First Version: February 17, 2006 Current Version: April 18, 2006 Thomas M. Idzorek, CFA Director of Research Ibbotson Associates 225 North Michigan Avenue Suite 700 Chicago, Illinois 60601-7676 312-616-1620 (Main) 312-616-0404 (Fax) tidzorek@ibbotson.com Abstract Over the last 50 years, Markowitz’s mean-variance optimization framework has become the asset allocation model of choice. Unfortunately the model often leads to highly concentrated asset allocations, the primary reason that practitioners haven’t fully embraced this Nobel Prize winning idea. Two relatively new techniques that help practitioners develop robust, well-diversified asset allocations are the BlackLitterman model and …show more content…
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 © 2006 Ibbotson Associates Robust Asset Allocation Page 2 leads to extreme asset allocations. These examples highlight the sensitivity of the output (the asset allocations) to changes in the inputs (the capital market assumptions). We examine the causes and possible solutions to highly concentrated
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]
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 correlation between the market portfolio and HML and the correlation between intercept and HML is -0.335 and -0.070, which indicates a moderate negative relationship between market portfolio and HML, and weak negative relationship between intercept and HML. Also, the correlations between the market portfolio and SMB, and between the SMB and HML are 0.348 and 0.191 respectively, which means that there are some positive relationships between them.
One assumption of CPAM model is that all investors invest in the same portfolio with the highest expected excess return per unit of risk and combine leverage using risky-free assets to maximize their utility. However, there are some investors constrained in such kind of leverage due to margin requirements or any prohibitions. For these investors, they tend to overprice the risky high-beta assets instead of leverage. Therefore, the risky assets with higher betas require lower risk-adjusted returns than lower-beta assets with leverage because the tilting behavior alleviates the no-leverage constraint (Black, Jensen and Scholes 1972). Here the BAB strategy generates a funding constrained CAPM model which is based on the standard CAPM model but provides a more practical implement to investors’ portfolio construction.
This study explores which asset classes add value to a traditional portfolio of stocks, bonds and cash. Next, we determine the optimal weights of all asset classes in the optimal portfolio. This study adds to the literature by distinguishing ten different investment categories simultaneously in a mean-variance analysis as well as a market portfolio approach. We also demonstrate how to combine these two methods. Our results suggest that real estate, commodities and high yield add most value to the
Nestle is a swiss multinational food and beverages company. Its headquarters is located at vevey, Switzerland. In terms of revenue it is largest food company in world. Nestle produces the portified products such as baby food ,bottled water ,breakfast cereals ,coffee ,tea ,dairy products ,ice cream ,frozen food ,pet foods ,and snacks .Nestle provided 167 billion servings of fortified products .Among them 29 brands of Nestle are getting turnover of $US1.1 billions. Nestle is one of main shareholders of L’OREAL company, the worlds largest cosmetic company.
A well diversified investor is at an advantage when participating in the investing of securities because the more diversified he or she is, the less unsystematic risk he or she will have to deal with. The reduction of risk is a fundamental principle in risk management. There are different methods of analyzing the risk of an equity security; some highlighted in the previous questions (6-10) show that the mean return of a company called Zemin Corporation is at 24% annually. The standard deviation of this expected return is 3.46. Also, we know that its beta is 1.54. Both its standard deviation and beta are relatively small for such a high return. With this much data available, a large amount of risk management techniques and formulas can be utilized to determine if this investment is worth partaking in. The capital asset pricing model for example, shows an investor an appropriate return for the amount of systematic risk that would be undertaken by the investor for purchasing the security. This systematic risk is the beta. The Sharpe ratio is another method of analyzing the risk of an investment. It takes the historical annualized return and subtracts the risk free rate from it. This excess return is then divided by the standard deviation (which is seen in investing as a level of uncertainty or risk) to find how much excess return per
In this section, Lee Wai (2001) briefly explained characteristics of the four well-known risk based portfolio construction methods - Equally Weighted Portfolio, Global Mean-Variance Portfolio, Most Diversified Portfolio, and Risk Contribution Portfolio.
Portfolio optimisation is a method of calculating and generating the maximum profit for the investors by allocating the initial capital into various asset classes. During the procedure, investors must consider the rate of return as well as the potential financial risks that could affect the expected value and accuracy of asset allocation decisions. Markowitz’s Modern portfolio theory builds up the foundation of solving portfolio optimisation problem nowadays using standard deviations to estimate the span of risk where investments with higher returns tend to have more risks accordingly.
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.
In order to maximize a portfolio’s return, it is important to analyze risk and diversify securities, while adhering to the goals of an investor. Through analyzing the different classes of risk, one can match investments to an investor’s risk tolerance and return requirements. Even though some investments may present greater risk they are countered by a higher rate of return and vice versa, less risk corresponds to a lower return. Moreover, investment risk can be substantially reduced through diversification, which spreads a portfolio across different industries, businesses and investment options. The makeup of a diversified portfolio continually changes based on an investor’s time horizon and investment goals. In accordance with the Modern Portfolio Theory (MPT), one can maximize return while reducing risk, through assessing investments standard deviation and beta. When applied to the capital asset pricing model (CAPM) an investor can determine what the expected rate of return should be and if the risk is worth it. Therefore, by analyzing risk and diversifying investments one can maximize an investment growth, increasing a portfolios return.
They showed that under the assumption of normal portfolio returns, reward-to-VaR ratio and Sharpe ratio give the same ranking of portfolio performance. While under non-normality, the rankings are different. Agarwal (2004) reached important conclusions that some hedge fund strategies have payoffs similar to “a short position in a put option on the market index”, and a traditional mean-variance framework tends to ignore this risk. Using mean-conditional VaR framework, Agarwal examined the extent to which the mean-variance approach underestimates the left tail risk.
Every finance students have learnt diversification is to reduce total risk by investing a basket of assets in portfolios. But what contributes to the success of portfolio diversification? A large number of assets? A variety types of asset allocation? Adding international investment? Numerous of risk factors? They are all indicators of a well-diversified portfolio. In this case, we will discuss about the advantages and disadvantages of diversification in portfolio management with related indicators. On one hand, some mention dynamic and numerous assets allocation in the portfolio will reduce both risks. While some also state the benefit of introduce multi-factor portfolio pricing models. On the other hand, arguments arise demonstrating adding international investment may disappoint investors because foreign market could be correlated and moved together. Another disadvantage could be the correlated assets collected weaken the effect of diversification. At the end, a balanced conclusion will be drawn to support the useful diversification.
(Francis, Sangbae, & Ramazan, 2011) analysed using Fama–French portfolios show that as the investment horizon increases, the optimal mean allocation of investors tilts heavily away from growth stocks particularly for lower and moderate levels of risk aversion. This result implies that value stocks are less risky than growth stocks at long horizons. In the study, the authors using the Wavelet approach concluded that investors may have different investment horizons due to their different patterns of
We can see that the value for this ratio in Nestlé is roughly 0,41. In order to avoid liquidity problems, the ratio’s value must be closed to 1, but we can see that the value for this ratio in Nestlé is roughly 0,41. Since it is quite lower, it means that Nestlé has risk of bankruptcy, due to the fact that, with the resources owned in short term, the company cannot pay back its short-term liabilities. This could be related to the fact that Nestlé has a very high bargaining power that could useful for them in order to exercise their power on suppliers to negotiate their payment commitments. SOLVENCY RATIO AND LIQUIDITY RATIO By means of solvency ratio, short-term assets are compared with short-term liabilities and it shows the liquidity situation of the company’s cash. It is also known as working capital ratio or solvency ratio at short term.