Tactical Asset Allocation Research Articles

Is active management of mandatory pension funds in Croatia creating value for second pillar fund members?

This paper analyses Croatian mandatory pension funds’ investment returns during the 2005-2014 period using performance attribution methodology. Results from active investment management are compared to a long-term policy return. Such analysis is essential to shed light on the contribution of active portfolio management in the second pillar pension scheme. Evidence suggests that in the period analysed portfolio managers have added value through active management decisions. In addition, we determined the sources of portfolio return by breaking down active return into policy, tactical asset allocation and security selection effect.

Tactical asset allocation for US pension investors: How tactical should the plan be?

Following the recession in the early 2000s, US corporate and public defined benefit (DB) plans faced unprecedented uncertainty with respect to their funding requirements going forward. Just as capital market performance started helping plan sponsors improve the health of their DB plans, the financial crisis of 2007–2009 delivered another serious blow. Consequently, plan sponsors turned their focus on improving their risk management practices and determining whether asset managers with proven track records should be given more broadly defined mandates, specifically designed to allow for more effective navigation in more volatile markets. Tactical asset allocation (TAA) strategies seek to add value by deviating from a plan’s policy mix based on the manager’s view on the attractiveness of various asset classes, regions and sectors within the investment opportunity set. Although TAA can add value to a portfolio, manager skill and risk taking are required to achieve reasonable risk-adjusted performance. The timing and magnitude of shifts from the policy mix can have a significant impact on the portfolio outcomes. Therefore, it is essential for investors to assess the appropriate role of TAA in their portfolio management process and evaluate the risk-return tradeoff of tactical deviations from policy. Our study uses a sample of historical returns from the global financial markets and simulation methodology to investigate the relationship of tactical band size and rebalancing practices to various measures of portfolio performance. The results show that providing investment managers with limited flexibility in making asset allocation decisions may allow DB plans to weather down markets better. For DB plan sponsors who are considering giving managers less constrained mandates, manager skill in adding value through TAA decisions should be considered.

The Global Financial Crisis and the Case for MEFAA Strategic Asset Allocation

Major institutional investment managers, such as, major hedge funds and large university endowments, have based their investment portfolios upon tactical asset allocation among multiple asset classes with low correlation with the goal of achieving superior risk-adjusted returns. However, during the current financial crisis, many of these asset classes experienced high degrees of correlation as they all decreased in value. In addition, many alternative asset classes not only decreased in value but also were illiquid in nature, impeding asset class re-allocation efforts. This paper examines a new strategic asset allocation framework called Monetary Environmental Flow Analysis™ (MEFA™) which can offer downside protection in such environments using only extremely liquid investment vehicles. The result over time is long-term returns comparable to equities but lower draw-downs in financial crisis environments. These strategies are tested over the period 1996-2014 with live signals for them from 2006 and 2007. Several of the strategies have been tested back to the 1970’s.

MEFAA Asset Allocation Strategies: Using Strategic Asset Allocation to Enhance Investment Returns and to Reduce Risk

Major institutional investment managers, such as, hedge funds and large university endowments, have based their investment portfolios upon tactical asset allocation among multiple asset classes with low correlation with the goal of achieving superior risk-adjusted returns. Until recently, this strategy has been extremely successful achieving compound annual returns over time of 10-15% with lower levels of volatility and superior risk-adjusted returns.However, during the current financial crisis, many of these asset classes experienced high degrees of correlation as they all decreased in value. It appears that in a global financial crisis, any asset classes that contain any form of market risk are quite linked. In addition, many alternative asset classes, such as, hedge funds and private equity not only decreased in value but also were illiquid in nature. This has impeded asset class re-allocation efforts.The Channel Capital Research Institute offers a new strategic asset allocation framework called Monetary Environmental Flow Analysis™ (MEFA™) which can offer downside protection in such environments using only Exchange Traded Funds (ETFs) and other extremely liquid investment vehicles. It utilizes basic tenets of asset allocation. However, it recognizes that many asset classes can be highly correlated in a downturn and offers the ability to allocate to riskless asset classes depending upon one’s goals and objectives. MEFA™ strategies offer the ability to create a customized framework for creating a portfolio based upon the specific risk-return tradeoff desired by the specific investor. The results over time are long-term returns comparable to equities but with lower drawdowns in financial crisis environments. These strategies are tested over the period 1996-2014.

Asset Allocation & the Global Financial Crisis: The Standard Case for the 50/50 Balanced Account and the Follow the Fedd Investment Strategies

Major institutional investment managers, such as large university endowments, have based their investment portfolios upon tactical asset allocation among multiple asset classes with low correlation with the goal of achieving superior risk-adjusted returns. Until recently, this strategy has been extremely successful achieving compound annual returns over time of 10-15% with lower levels of volatility and superior risk-adjusted returns.However, during the current financial crisis, many of these asset classes experienced high degrees of correlation as they all decreased in value. It appears that in a global financial crisis, any asset classes that contain any form of market risk are quite linked. In addition, many alternative asset classes, such as, hedge funds and private equity, not only decreased in value but also were illiquid in nature. This has impeded asset class re-allocation efforts.We examine the classic 50/50 balanced investment portfolio in comparison with fixed asset allocation portfolio in multiple asset classes. Despite the increased diversification, we find the investment performance to be quite similar. The reason is that many asset classes can be highly correlated in a downturn. Thus, riskless assets offer the only real protection in a severe downturn. The Follow the Fed® investment strategies offer the ability to enhance the performance of the classic 50/50 balanced portfolio in both positive and negative market environments. The results over time are long-term returns superior to the original 50/50 balanced portfolio. These strategies are tested over the periods 1996-2014 and in select cases 1970-2014 with live signals for them from 2006 and 2007.

How Often Should You Take Tactical Asset Allocation Decisions?

About once a quarter. We compute optimal tactical asset allocation (TAA) policies over equities and bonds when both asset returns are predictable. By varying how often the weights are reset, we estimate the benefits and costs of different frequencies of TAA decisions. Tactical tilts taking advantage of predictable stock returns generate approximately twice as much value as those market-timing bond returns.

What’s in the News? Using News Sentiment Momentum for Tactical Asset Allocation

News and news sentiment often influence financial markets and asset prices. Investors commonly recognize this, but only a few studies have used news sentiment in news to predict future financial market developments and to formulate alpha-generating strategies, let alone create a best-practice approach for tactical asset allocation. In order to fill this gap, the authors combine company- and macro-specific news sentiment from around 100,000 news pieces per week and use the CUSUM (cumulative sum) filter method to calculate momentum in news sentiment. With this approach, they obtain a strategy that delivers solid outperformance with an information ratio of 0.8, while switching as few as eight times per year (on average), making it practicable for both tactical asset allocators and investors in general. <b>TOPICS:</b>Financial crises and financial market history, exchanges/markets/clearinghouses, in markets

The role of South African property in balanced portfolios

The overriding objective of this paper is to establish the features that South African property brings to a balanced portfolio – and importantly to give insight into a strategic investment weight for this asset class. We acknowledge that listed and unlisted property are potentially two different asset classes and we conduct analysis on both listed and unlisted property. Using a mean-variance approach we find that listed property elevates the efficient frontier across the entire spectrum of risks having allocation weights in excess of 20% across typical risk mandates. Our non-parametric optimisation approach yields an optimal allocation to listed property of 23%, significantly higher than found in local pension funds. Using a non-parametric approach for tactical allocation considerations in differing economic regimes, we find there is indeed scope for tactical asset allocation to the listed property asset class. Considering the role of unlisted property separately in a balanced portfolio setting we find that unlisted property plays a diversification role in low-risk portfolios. However we find its role in optimal portfolios is less clear as it tends to be substituted by listed property.

Tactical Asset Allocation for U.S. Pension Investors: How Tactical Should the Plan Be?

Tactical Asset Allocation for U.S. Pension Investors: How Tactical Should the Plan Be?

Practical Applications of Risk-versus Trend-Driven Global Tactical Asset Allocation

Institutional investors who seek protection during bearish market environments should balance risk-based with trend-driven GTAA strategies, advises Benoit Guilleminot in this report. Guilleminot, Director of Research and Innovation at Riskelia, co-wrote Risk- Versus Trend-Driven Global Tactical Asset Allocation for The Journal of Portfolio Management. His co-authors are Jean-Jacques Ohana, President and Co-Founder of Riskelia, and Steve Ohana, Professor of Finance at ESCP Europe in Paris. They compared the performance of risk- and trend-driven investment strategies on equities, commodities and bonds between 1993 and 2012. “The relative weight of a trend-driven strategy should be increased during a major crisis, but when there is no real crisis investors should keep more diversification with a risk-driven strategy,” says Guilleminot.

Simple One ETF a Month Quantitative Asset Allocation System

We developed a simple easy to use “One ETF a Month” quantitative tactical asset allocation system that beats the SP500 Benchmark consistently. Our initial results show that a part time investor can beat the SP500 benchmark index by 900 basis points (9%) – effective doubling the SP500 benchmark return – annually. The proposed method uses the relative strength strategies combined with a momentum filter. The delayed signals from the system will be tracked on the econoscience.blogspot.com website.

Strategies Based on Momentum and Term Structure in Financialized Commodity Markets

The aim of this paper is to investigate the impact of the financialization of commodity markets on the profitability of strategies based on momentum and term structure. The performance of an array of portfolios from double-sorts on non-commercial traders’ participation, historical returns and term spreads are tested against a risk model. The analysis covers the listing of 26 commodities in the period 1986–2013. First and foremost, the paper provides a fresh evidence for the validity of strategies based on momentum and term structure investing in commodity markets. Secondly, it proves that term structure strategies generate significantly higher performance results in non-financialized markets. Moreover, it supports the thesis that market financialization adversely affects momentum profits. The results are important in terms of tactical and strategic asset allocation in commodity markets. They imply that investors who implement momentum or term structure based strategies should also consider the composition of market participants.

Quantitative Tactical Asset Allocation Using Ensemble Machine Learning Methods

Beating the SP500 Index benchmark is a do-or-die among active portfolio managers. We propose a new method to add a 2-layer augmentation to relative strength and momentum based active portfolio management methods; first layer is to add a filtering mechanism to add a momentum filter in the recommendation engine and second is to include a multi level- multi layer machine learning method to integrate an ensemble model to decision making process. The ensemble model consists of gradient boosted decision trees and neural network models. Our initial results show that it is possible to beat the SP500 benchmark index by 600 basis points (in the calculations industry standard trading costs are included) as it is demonstrated by comparing the overall performance of the proposed method.

Simple and Effective Market Timing with Tactical Asset Allocation

A simple market timing algorithm is examined that switches from an exchange traded fund representing U. S. equities to one holding treasury long bonds every month on the last day, the switch being made to whichever ETF has the greatest ratio of current adjusted closing price to adjusted closing price μ months earlier. The parameter μ is determined so as to maximize total return and minimize the total number of trades, however the results are relatively insensitive to μ over a fairly wide range. The performance of this scheme is compared to that of an Ivy 5 portfolio consisting initially of equal dollar amounts of ETFs in U. S. equities, foreign large blend, 7-10 year treasuries, real estate, and commodities. As with the paired switching approach, each ETF is purchased only once a month, on the last day, in this case only if its adjusted closing price exceeds the 10-month simple moving average (SMA). Otherwise that portion of the portfolio is invested in a cash surrogate. Comparison is made over the 10-year period ending on 12/31/13. It is shown that the average annual return of the paired switching algorithm exceeds 30% in this period, which is 3 times greater than that of the Ivy 5. Moreover, only 45 trades were required for the paired switching approach, whereas the Ivy 5 required 70 in the same period. The maximum draw down was 14.6% for the Ivy 5 and 18.8% for paired switching.

Tactical Asset Allocation with Macroeconomic Factors

Tactical asset allocation is explored using an economic-based factor pricing model. Using a filtering method based on asset responses to the economy and current economic data, alternative optimization methods are considered including equally-weighted, low-volatility, and mean-variance (maximum Sharpe ratio) allocations. Using exchange-traded funds as proxies for asset classes, portfolios were constructed and rebalanced every half year from 2006 through 2013. We find that the economic response filtering with the maximum Sharpe ratio optimization provided the best overall performance in terms of returns while the low- (economic) volatility portfolio had the least volatility. <b>TOPICS:</b>Exchange-traded funds and applications, portfolio construction, performance measurement

Risk- versus Trend-Driven Global TacticalAsset Allocation

The 2008 financial crisis has severely challenged passive forms of investment. In this article, the authors compare two systematic investment processes that a global asset allocator may employ to preserve its capital in a turbulent financial environment. The risk-driven allocation, derived from the popular risk-parity approach, has garnered a strong interest from both scholars and practitioners in recent years. It aims at enforcing a constant risk target and maintaining a balanced risk profile over time. This article introduces a novel trend-driven approach that enhances the risk-driven strategy by cutting exposure to downward-drifting assets. The authors compare the risk-adjusted performances of risk- and trend-driven approaches on different investment universes (composed of equity, commodity, currency, and bond futures contracts) from 1993 to 2012. They find that a trend-driven approach yields increased Sharpe ratios and lower drawdowns on average, relative to a risk-driven strategy. However, the trend-driven process’s outperformance is not stable over time: periods with exploitable trends alternate with long-lasting trendless periods. Overall, the trending strategy’s key advantage over the risk-driven one is its greater smoothness. This is due to a better resilience to financial meltdowns like those seen from 2000 to 2002 and in 2008, which are well predicted by trending signals and undermine the diversification objective the risk-parity approach pursues. These results demonstrate the value of coupling risk and trajectorial signals in tactical asset allocation. <b>TOPICS:</b>Financial crises and financial market history, portfolio construction, volatility measures

Macroeconomic Determinants of Commodity Returns in Financialized Markets

Financialization of commodity markets has been a broadly discussed topic in recent years. However, its implications for commodity investors have not yet been fully explored. This paper concentrates on the macroeconomic determinants of commodity returns in financialized and non-financialized markets and on their role for tactical asset allocation. The study aims to contribute to the academic literature in four ways. First, it provides fresh evidence on the interdependences between commodity returns, inflation and the business activity. Second, it documents increased correlation of the commodity returns with the business activity in the financialized markets. Third, it explores changes in the lead/lag relationship of commodity prices and the business cycle. Fourth, it proves that the commodities retained their inflation hedging abilities in the financialized markets. The computations are based on listings of various commodity indices, which are calculated by S&P-GSCI, JP Morgan, and Dow Jones-UBS, between 1970 and 2013.

An Analysis of the Growth in the Fixed Income ETF Market

Since the financial crisis, demand for fixed income ETFs has increased dramatically. An analysis of this market shows that most of the growth has occurred in ETFs covering U.S. Corporate Bonds, Global Bonds and Emerging Market Bonds. This rapid growth suggests that institutional investors have begun to use fixed income ETFs to achieve both strategic and tactical asset allocation goals. Changes in fixed income ETF volume are positively related to changes in the VIX, which suggests that investors are using fixed income ETFs to tactically shift into fixed income when the stock market becomes more volatile.

Do (Some) University Endowments Earn Alpha?

The authors analyzed the returns earned by U.S. educational endowments using style attribution models. For the average endowment, models with only public stock and bond benchmarks explain virtually all the time-series variation in returns, yield no alpha, and generate sensible factor loadings. Elite institutions perform better than public stock and bond benchmarks because of large allocations to alternative investments. The authors found no evidence that manager selection, market timing, and tactical asset allocation generate alpha.

International Real Estate Review

The main contribution of this study is to examine the extreme dependence between the real estate securities and stock markets in Australia, China, Hong Kong, Japan, Malaysia, the Philippines, Singapore and Taiwan between January 1995 and March 2011. For each market, we derive time series tail dependence coefficients (TDC) which measure how likely financial returns move in extreme market conditions by using the dynamic conditional correlation (DCC) methodology provided by Engle (2002). Overall, our results indicate that Singapore, the Philippines and Hong Kong have the highest extreme real estate–stock market co-movement of at least 50%. In addition, during the global financial crisis (GFC) period, the securitized real estate and common stock markets in China, Hong Kong, Japan, the Philippines and Singapore displayed the highest extreme dependence to react together to financial turmoil. The results in this paper also show that the extreme dependence patterns of real estate stock markets are similar for many of the Asia-Pacific economies. Finally, correlation coefficients are not adequate for explaining extreme co-movements between the securitized real estate and common stock markets in the longer period, as well as in the two-year GFC periods. Our TDC modeling with Asia-Pacific securitized real estate and stock markets provide useful information and advice to international investors and risk management personnel in tactical asset allocation so as to manage the extreme dependence between securitized real estate and common stock market.