Strategic Asset Allocation Research Articles

Practical Applications of The New Neutral: The Long-Term Case for Currency Hedging

<h3>Practical Applications Summary</h3> In <b>The New Neutral: <i>The Long-Term Case for Currency Hedging</i></b>, from the Summer 2018 issues of the <b><i>Journal of Investing</i></b>, authors <b>Robert Bush</b> and <b>Abby Woodham</b> (both of <b>DWS</b> in New York, NY) examine the role of currency risk in long-term asset allocation for international equities. They address the impact of currency exposure on overall portfolio risk and return, and recommend using a portfolio approach as a framework to understand the role of foreign currencies in strategic asset allocation. The authors argue that fully hedging currency risk should be the new neutral for making long-term asset allocation decisions. <b>TOPICS:</b>Real assets/alternative investments/private equity, portfolio management/multi-asset allocation, emerging

Robust Dynamic Portfolio Choice Based on Out-Of-Sample Performance

We introduce a novel dynamic portfolio choice method, focusing on robust out-of-sample performance rather than on optimal in-sample performance. We therefore devise a strategy that rigorously tackles the problem of estimation error. The method involves defining a discrete set of single-period portfolio allocation policies (candidate portfolio strategies) that accommodate time-varying predictability of individual assets and choosing between them at portfolio revision dates based on bootstrapped out-of-sample portfolio returns. Our approach can handle an extensive menu of important features, in particular, arbitrarily complex types of conditional predictability, a large asset universe, parameter uncertainty, model uncertainty and downside risk aversion. We demonstrate the method's feasibility and usefulness in dynamic investment problems in futures trading, strategic asset allocation and a cross-sectional momentum strategy in equity markets.

A Wavelet Coherence Analysis: Contagion in Emerging Countries Stock Markets

This study aims to investigate the financial contagion during and after Greek Crisis to observe the impact on global economy. Financial contagion may affect the portfolio risk management, the formulation of monetary, fiscal policy, strategic asset allocation and pricing. To analyse the contagion after Greek Crisis, the co-movements of six stock exchange markets have been studied for an 8-year term. For this study between countries’ time series, bivariate wavelet technique called wavelet coherence is employed, and Matlab 2016a wavelet tool is used for the analysis. Daily closing prices of stock market indices of six countries, Greece (ASE), UK (FTSE100), Germany (DAX), Hungary (BUX), Poland (WIG) and Turkey (BIST100) are used in this analysis between 06 March 2009 and 28 February 2017.This paper targets to show if there is a certain sign for a co-movement between markets during and after Greek Debt Crisis. Therefore, it eventually sets out the benefits or harm of integration in the financial markets by using Wavelet Method. This study contributes the literature by analyzing the effects of contagion among stock markets by using wavelet method. This analysis has been filling the gap in the literature by employing a new technique to explain leverage effect with financial time series data. As wavelet tool displays the leverage effect by comparing crisis and non-crisis periods, the study supports the idea that convergence is adversely affecting the connected markets. According to the results of the study, the contagion is high especially during crisis within European financial markets. whereas positive improvements have less impact on markets.

Strategic Asset Allocation for Life Insurers with Stochastic Liability

The problem of strategic asset allocation and product mix choice of a life insurancecompany is considered where account is taken of the stochastic risk associated with both assets and liabilities. Using the methods of stochastic dynamic programming we derive equations for optimal weights of both risky and riskless assets under continuous time. The resulting equations can be solved exactly for some parameter values and utility functions. When this is not possible a general perturbation expansion method is set up for which explicit solutions are derived for the first terms but the method can be generalized to any order in the expansion parameter.

Factor Investing in Currency Markets: Does it Make Sense?

The concept of factor investing emerged at the end of the 2000s and has completely changed the landscape of equity investing. Today, institutional investors structure their strategic asset allocation around five risk factors: size, value, low beta, momentum and quality. This approach has been extended to multi-asset portfolios and is known as the alternative risk premia model. This framework recognizes that the construction of diversified portfolios cannot only be reduced to the allocation policy between asset classes, such as stocks and bonds. Indeed, diversification is multifaceted and must also consider alternative risk factors. More recently, factor investing has gained popularity in the fixed income universe, even though the use of risk factors is an old topic for modeling the yield curve and pricing interest rate contingent claims. Factor investing is now implemented for managing portfolios of corporate bonds or emerging bonds. In this paper, we focus on currency markets. The dynamics of foreign exchange rates are generally explained by several theoretical economic models that are commonly presented as competing approaches. In our opinion, they are more complementary and they can be the backbone of a Fama-French-Carhart risk factor model for currencies. In particular, we show that these risk factors may explain a significant part of time-series and cross-section returns in foreign exchange markets. Therefore, this result helps us to better understand the management of forex portfolios. To illustrate this point, we provide some applications concerning basket hedging, overlay management and the construction of alpha strategies.

Fixed Income and Passive Asset Allocation Outperformance in Brazil

The fixed income asset class has outperformed stocks for more than two decades in Brazil. Passive equally weighted strategic asset allocation portfolios outperformed actively managed balanced funds in the same period. These vehicles are accessible to individual or less sophisticated investors. However, is this evidence persistent so that it should be considered in future asset allocation decisions? This investigation employs Bayesian bootstrapping simulations because lengthy time series that are still economically relevant are not available, which is likely the case in other emerging markets. The results indicate that the previous evidence is quite likely persistent. Investors should hold a significant proportion of their assets in the fixed income class in Brazil, and it could pay off to carry out an equally weighted strategic asset allocation strategy by means of indexed funds, thus saving in management and incentive fees charged by actively managed balanced funds. This article also presents economic scenarios and discussions of asset manager characteristics to support these conclusions. These conclusions may apply to investors in other emerging markets as well, particularly in those with high interest rates and a reduced choice of investment vehicles. TOPICS:Fixed income and structured finance, mutual funds/passive investing/indexing, simulations, emerging markets

Analysis on the Risk Return Profile of Alternative Assets Under Reference Portfolio Concept

This paper provides the methodology of estimating the risk-return relationship of alternative asset investments within the mean-variance framework. While conducting strategic asset allocation, most of the institutional investors do not take into account the risk-return relationship of alternative assets, or use arbitrary policy numbers that do not properly reflect the characteristics of alternative assets. This paper borrows the concept of reference portfolio in developing the methodology of estimating the risk-return relationship of alternative investments. The reference portfolio is the benchmark portfolio used in strategic asset allocation by pension funds. This can serve as the opportunity costs of alternative investments. We use the realized IRR’s from actual investments, and estimate the risk-return characteristics of alternative investments. We find that by properly estimating the mapping relationship between the reference portfolio and alternative asset classes, we can incorporate the risk-return profile of these non-market assets within the mean-variance framework together with the other traditional asset classes.

Private and Public Real Estate - What's the Link? (May 2010)

In this paper, we study the relationship between private and public real estate in the US and UK markets. We demonstrate a strong link between public and private real estate returns in each of these markets. To uncover these relationships, we correct for appraisal smoothing and properly account for the lead-lag relationship between public and private returns. We find that public returns lead private returns, even after removing appraisal smoothing in private returns. We also discuss how real estate risk changes over longer horizons. In particular, our results suggest that private and public returns become more correlated at longer investment horizons. This carries important implications for risk management and strategic asset allocation.

Practical Applications of Rebalancing-Diversification Return: The Opportunity Cost of Illiquid Investments

Practical Applications Summary In Rebalancing-Diversification Return: The Opportunity Cost of Illiquid Investments, published in the Summer 2018 issue of The Journal of Investing, John Linder of Ryan Labs Asset Management examines how portfolio managers can employ illiquid investments to increase returns, and quantifies the trade-offs they present in terms of illiquidity. Led by private markets (especially private equity), asset managers pursuing greater returns amid the ongoing low rate-of-return environment have increasingly turned to illiquid investments. These alternative investments are especially attractive if the investor’s time horizon is substantially longer. In contrast with a liquid portfolio, investments in illiquid assets give up three main attributes: the ability to spontaneously rebalance the holdings, reallocating back to the strategic asset allocation to maintain the intended risk posture over time, and purchasing distressed assets in times when liquidity is dear and thus prices are depressed. Linder discusses how alternative illiquid investments introduce an opportunity cost for which investors should demand an illiquidity premium, and proposes a framework to quantify it. He also suggests strategies to increase the available returns from liquid investment through diversification and leverage. TOPICS:Real assets/alternative investments/private equity, analysis of individual factors/risk premia, performance measurement

On Tackling Real-Life Optimization Problems

Most real-world applications are concerned with minimizing or maximizing some quantity so as to enhance some result. This emphasizes the importance of optimization and subsequently the significance of the optimization methods that are able to tackle these real-life optimization problems. There are a number of practical reasons for which traditional optimization and exhaustive algorithms cannot deal with a variety of these real-life optimization applications although there are numerous optimization problems that can benefit from applying these traditional optimization algorithms to handle them. Therefore, their is a need for propsong new optimization algorithms (such as nature inspired optimization methods) and optimize the capabilities of the existing ones (such as hybridization and parallelization) as well. This paper investigates the most recent optimization directions for dealing with the real-life optimization problems with an application to one of the most common and important optimization problems in a variety of financial fields and other fields which is the portfolio optimization problem since it is considered one of the most crucial problems in the modern financial management and has a variety of applications such as asset management and building strategic asset allocation. The computational results were got utilizing benchmark data from the OR library with the use of modern optimization algorithms. In addition, the article highlights the differences and similarities among the utilized optimization methods. In addition, recent advancements to the utilized optimization methods are highlighted.

KiwiSaver fund performance and asset allocation policy

PurposeThis paper aims to examine the performance and benchmark asset allocation policy of 70 KiwiSaver funds catergorised as growth, balanced or conservative over the period October 2007-June 2016. The study focuses on the sources for returns variability across time and returns variation among funds.Design/methodology/approachEach fund is benchmarked against a portfolio of eight indices representing eight invested asset classes. Three measures were used to examine the after-fee benchmark-adjusted performance of each fund: excess return, cumulative abnormal return and holding period returns difference. Tracking error and active share were used to capture manager’s benchmark deviation.FindingsOn average, funds underperform their respective benchmarks, with the mean quarterly excess return (after management fees) of −0.15 per cent (growth), −0.63 per cent (balanced) and −0.83 per cent (conservative). Benchmark returns variability, on average, explains 43-78 per cent of fund’s across-time returns variability, and this is primarily driven by fund’s exposures to global capital markets. Differences in benchmark policies, on average, account for 18.8-39.3 per cent of among-fund returns variation, while differences in fees and security selection may explain the rest. About 61 per cent of balanced and 47 per cent of Growth funds’ managers make selection bets against their benchmarks. There is no consistent evidence that more actively managed funds deliver higher after-fee risk-adjusted performance. Superior performance is often due to randomness.Originality/valueThis study makes use of a unique data set gathered directly from KiwiSaver managers and captures the long-term strategic asset allocation target which underlines the investment management process in reality. The study represents the first attempt to examine the impact of benchmark asset allocation policy on KiwiSaver fund’s returns variability across time and returns variation among funds.

Practical Applications of What Investment Risk Means to You, Illustrated: Strategic Asset Allocation, the Budget Constraint, and the Volatility of Spending During Retirement

Practical Applications Summary In What Investment Risk Means to You, Illustrated: Strategic Asset Allocation, the Budget Constraint, and the Volatility of Spending During Retirement , from the Fall 2018 issue of The Journal of Retirement , Barton Waring , retired chief investment officer of Barclays Global Investors , and Laurence Siegel , director of research of the CFA Institute Research Foundation , present and explain two key points. First, individual investors often do not correctly understand the real meaning of risk. The problem is that the concept is often articulated in vague or confusing terms. An individual investor can easily miss the point that although a risky investment strategy may offer a higher “expected return, ” it may also entail significant risk of seriously adverse outcomes or even financial ruin. Individual investors may not readily grasp the important difference between the statistical concept of expected return as just the middle of what might be a very broad range of possible outcomes, and the everyday notion of expectation as something that is likely to happen. Second, static retirement spending plans are a major source of risk for retirees. A safer spending plan—one that ameliorates risk—responds to periods of weak investment performance with lower spending levels. Such a plan can nearly eliminate the risk of exhausting a retiree’s assets. The authors demonstrate a mechanism for periodically adjusting spending in response to actual investment performance.

Private Equity Program Breadth and Strategic Asset Allocation

It is quite often the case that investors form views on private equity program return and cash flow profiles by analyzing broad-based swaths of the private equity industry, while side-stepping idiosyncratic risks associated with narrower, realistic baskets of private equity pools. This article remedies this by performing an empirical analysis of private equity historical performance while accounting for program diversification. Comparing a private equity program to peer group averages is somewhat unfair, as such methodology favors larger programs, arguably without merit. The authors explain a way to correct for this bias. Finally, the authors present a probabilistic strategic asset allocation framework for private equity programs that help make informed trade-offs between breadth, strategy mix, and associated costs.

Creating Global ETF Portfolio with Considering US Market

I have created a global portfolio considering ETFs that will outperform S&amp;P 500 over the next six months. Firstly, I present the economic conditions of the US and other important developed countries along with emerging countries. Secondly, I consider the present markets of the globe and comments on the situations that what can be happened next six months. Finally, the decision is taken based on the analysis of global growth, GDP across the countries, inflation, interest rates, and unemployment rates to determine the strategic asset allocation for different asset classes.

Carry-Based Expected Returns for Strategic Asset Allocation

In this article, the author investigates expected return forecasting methodologies and their application in an asset allocation context. Although present value model–related methods are popular in practice, little is known about their performance when used for asset allocation. An intuitive and traceable carry-based method is developed by the author and tested and benchmarked against competing alternatives. The results are evaluated from different perspectives, and the obtained returns are regressed on well-known risk factors. The proposed methodology outperformed other return forecasting variants on various metrics and generated significant alphas regardless of the weight determination approach used. The methodology can be extended to further asset classes and geographic regions and provides a framework for allocating assets strategically.

Impact of Portfolio Strategies on Portfolio Performance and Risk

The Portfolio strategies are the effective investment tools pertaining to active and passive investment approaches. This signifies the investor’s inclination of buying and selling the risky and risk-free assets. The research includes four strategies namely buy and hold strategy, dynamic asset allocation, strategic asset allocation and tactical asset allocation along with their dimensions. Strategies based hypothetical portfolios are generated on the basis of 14 years’ stock prices (2005-2017). The annually and monthly risk-adjusted return ratios; Sharpe ratio, Treynor’s measure, CAPM and Jenson Alpha are calculated individually. Simulated annualized portfolios generate significant result with Sharpe and treynor measure. Alpha return is generated with buy and hold if based on growth in stock prices. For empirical result, One-way analysis of variance (ANOVA) is used for studying the relationship between the strategies. Post hoc Tukey’s test is applied to find the difference between the strategies. The ANOVA and Tukey’s post hoc test for monthly portfolios gives significant results with three measure Sharpe ratio, CAPM and Jenson Alpha. No empirical significant result is measured on the basis of treynor measure.

Independent Accountant’s Review Report

Independent Accountant’s Review Report

Inflation-Linked Bonds as a Separate Asset Class: Evidence from Emerging and Developed Markets

One of the key goals of strategic asset allocation is protection against inflation. High inflation eats up real returns, causing a damaging effect on a portfolio of bonds and equities. Inflation-linked bonds (ILBs) were introduced to shield the purchasing power of a portfolio from inflationary conditions by linking portfolio returns to inflation, over a bond’s life term. The current research evaluates the acceptability of ILBs as a separate asset class and as an inflation hedge. It uses data from four emerging and four developed markets for a period of five years, that is, 2011–2016. The study employs multiple regression, cross-correlations and mean-variance spanning techniques to demonstrate the abovementioned benefits of ILBs. The findings of the study establish an advantage of excess returns provided by ILBs over nominal bonds under varying inflationary conditions. An improvement in mean-variance efficiency is found when ILBs are added to a portfolio. Overall, the study contributes to the body of knowledge by suggesting that ILBs can be included in a portfolio to hedge, as well as to improve its strategic asset allocation.

Strategic asset allocation for insurers under Solvency II

An important question in asset management is how solvency requirements impact the investment strategies of institutional investors. In this paper, we derive the optimal asset allocation of an insurer that minimizes its capital requirement for market risk determined with the Solvency II standard formula, subject to a target return on own funds. Solvency II is the risk-based framework for setting capital requirements of European insurance companies, in force since 2016. The solvency capital requirement is set such that the insurer’s own funds can absorb losses over a 1-year horizon with a probability of at least 99.5%. Within this framework, we analyze the properties of an optimal asset allocation for a representative European life insurance company.

Does country background risk matter to the strategic asset allocation of sovereign wealth funds?

On the basis of background risk theory (Gollier 2001), this paper discusses the country background assets of sovereign wealth funds (SWFs), establishes the optimal strategic asset allocation model with consideration for background risk, and proves that the rebalanced weight of each asset is negatively correlated with the covariance of background assets and financial assets. Considering both the national foreign currency reserve assets and future payment obligations of international import goods as background risk, this paper uses China's SWF as a sample, partitions global equity markets according to MSCI country and industry indices, utilizes market implied expected return and market models to estimate the expected return of those investable assets, and finally determines the optimal strategic asset allocation of SWFs. The theoretical modeling methods in this paper can be extended to solve SWFs' asset allocation problems with non-tradable assets and to help optimize the portfolio allocation decisions of individual investors with heterogeneous background risks.