Tactical Asset Allocation Strategies Research Articles

Tactical Asset Allocation, Risk Premia, and the Business Cycle: A Macro Regime Approach

Market conditions change over the course of the business cycle. When are investors compensated to take risk? And what type of risk? We propose a practical regime-based framework for tactical asset allocation (TAA), combining leading economic indicators and global risk appetite to identify four macro regimes: recovery, expansion, slowdown, and contraction. We document distinct performance characteristics across regimes for traditional asset classes and their underlying risk factors, focusing on the term premium, credit premium, and equity premium. We provide simple and practical examples of TAA strategies for long-only multi-asset, and fixed income portfolios with the potential to generate attractive excess returns. Results are statistically significant and economically relevant after transaction costs, with information ratios between 0.70 and 0.80.

Practical Applications of Is Tactical Allocation a Winning Strategy?

In <b><i>Is Tactical Allocation a Winning Strategy?</i></b>, from the Fall 2021 issue of <b><i>The Journal of Index Investing</i></b>, authors <b>Srinidhi Kanuri</b> (of the <b>University of Southern Mississippi</b>), <b>James Malm</b> (of the <b>College of Charleston</b>), and <b>D.K. Malhotra</b> (of <b>Thomas Jefferson University</b>) analyzed the performance of actively managed mutual funds that pursue tactical asset allocation (TAA) strategies. In such a fund, the manager frequently reallocates investments among different asset classes, based on performance predictions. The goals are to improve diversification, protect against short-term losses, and achieve positive alpha. The authors measured the performance of all tactical allocation funds from January 1994 to October 2016 and compared it to the performance of benchmarks consisting of broad-market indexes and static mixed portfolios that did not reallocate. They found that tactical allocation funds underperformed all the benchmarks and showed negative alpha—meaning that fund managers failed to predict which assets would outperform the market. While TAA funds did have some short-term risk reduction benefits, the authors nevertheless concluded that investors are better off investing in passive funds that follow indexes.

Winners Repeat, Losers Repeat

I present a tactical asset allocation proof-of-concept portfolio. It is intended to harvest the non-IID statistical attributes of stocks, bonds, commodities, and currencies, both domestic and international. It has as its objective to benefit from markets’ propensity to trend from month to month and during both bull and bear market environments. The proof-of-concept portfolio relies on a simple quantitative rule that allows for rigorous evaluation over the past 102.1 years. The results presented herein suggest that Tactical Asset Allocation (TAA) is an approach worthy of consideration. Moreover, the article suggests that a necessary condition for TAA success lies in correctly specifying its rather differentiated investment objective—one that may be unrelated to comparisons with popular fixed-weight index benchmarks. Such fixed-weight benchmarks have correlations with TAA strategies that are so low as to make commonly used statistical comparisons irrelevant (i.e., not statistically significant). This article attempts to correct our industry’s mischaracterization and overpromising of all things TAA by focusing on the time required for success.

Towards a Better Fed Model

We present an alternative to the widely known and much-maligned model. The proposed alternative makes a coherent comparison between equities and bonds that eliminates the theoretical and empirical flaws of the original (as well as any need for ad hoc asset-class volatility adjustments). The output of the model is a time-series value factor, which is then used to develop a tactical asset allocation strategy. Historical simulations suggest the resulting strategy is superior not only to the original Fed model, but to tactical strategies based on other popular time-series value factors as well. Beyond its forecasting and tactical allocation performance, the proposed model also provides significant insight into equity market dynamics--insight that has been validated by recent historical events.

Market anomalies in the Korean stock market

This paper aims to replicate 148 anomalies and to examine whether the performance of the Korean market anomalies is statistically and economically significant. First, the authors observe that only 37.8% anomalies in the universe of the KOSPI and the KOSDAQ and value-weighted portfolios have t-statistics that exceed 1.96. When the authors impose a higher threshold (an absolute value of t-statistics of 2.78), only 27.7% of the 148 anomalies survive. Second, microcaps have large impacts. The results vary significantly depending on whether the sample included stocks in the KOSDAQ and whether value-weighted or equal-weighted portfolios are used. The results suggest that data mining explains large portion of abnormal returns. Any tactical asset allocation strategies based on market anomalies should be applied very cautiously.

Dynamic Asset Allocation Based on Valuation and Momentum Applied to a Global All-Equity Portfolio

There has been considerable research into dynamic global tactical asset allocation (GTAA) strategies driven by simple measures of Valuation and Momentum applied to a baseline balanced portfolio of equities and fixed income (see Blitz and van Vliet 2008, Wang and Kochard 2011, Gnedenko and Yelnik 2014, and Dewey and Haghani 2016). In sum, this research has found that historically, these Valuation-and-Momentum-driven investment approaches have produced higher returns and more attractive risk-adjusted returns than a static-weight approach. However, the above-cited research has been mostly silent on the question of how such an approach could be implemented and would have performed in the context of an All-Equity portfolio, where the Valuation and Momentum signals would drive a dynamic allocation between different regional equity markets. This note explores this question. It finds that such a dynamic approach would have produced higher absolute returns, and higher risk-adjusted returns, than a static approach would have produced. However, the improvement in simulated historical returns is less than the improvement that Valuation and Momentum deliver when applied to a balanced baseline portfolio of equities and fixed income. For example, simulated historical returns for the All-Equity strategy described below over the past roughly 40 years had about 50% more variability but only 20% higher returns than did a similar dynamic Global Balanced strategy. We examine a form of the strategy that can be followed by any investor with a simple brokerage account, using low-cost, liquid and widely available ETFs or index funds, and without use of leverage or shorting. The implementation we explore in this note trades monthly, with turnover averaging about 50% per annum. It is be based on data that is freely available in the public domain.

Dynamic Hedging of Currency Risk in Investment Strategies

Often, investors fully hedge their portfolios for currency risk. This can lead to significant drag in performance for currencies with negative carry. However, not hedging the foreign currency exposure can lead to significant drawdowns, especially for conservative investments. In this paper, we consider a conservative, global tactical asset allocation strategy implemented in US dollar denominated securities for a hypothetical, European investor and highlight the benefits of dynamic currency hedging over static hedging. Using a parsimonious model for hedge ratio based on multiple features of merit and an explicit check for maximum allowed under-hedging, we show that a cost aware, dynamic hedging strategy can reduce the hedging costs substantially while keeping the portfolio risk within mandate specifications.

Developing an Effective Dynamic Beta Overlay

Many institutions – both multi-asset managers and asset owners – have developed Global Tactical Asset Allocation (GTAA) strategies. These strategies could be either long-only or long-short, but are typically fully funded. In an environment where the future expectations of asset and portfolio returns are low, and cash is valuable for pension funds that are often paying more in benefits than they receive in contributions, asset owners need to be creative and re-purpose certain strategies. Many of these GTAA strategies trade assets that are not in the client’s Strategic Asset Allocation (SAA) and GTAA strategies could potentially be adding to total fund risk to the extent they take bets similar to those embedded in the SAA. This paper is an adapted case study to demonstrate how an innovative asset owner that had crowdsourced best ideas from strategic partners to create their own unique GTAA, was able to adapt the GTAA model into a futures-based Dynamic Beta/SMART Rebalancing overlay to not only improve the Sharpe ratio, but also greatly enhance the risk management properties of the overall fund. More importantly, cash utilization was improved because futures overlays need only be financed with limited cash if designed appropriately.

Tactical asset allocation on technical trading rules and data snooping

In this paper, we investigate the performance of tactical asset allocation on technical trading rules controlling for data snooping bias. By using reality check (RC), superior predictive ability (SPA) test and their extensions, and false discovery rate (FDR), we find that none of 15376 technical trading rules at monthly frequency outperforms buy-and-hold (B&H) strategy in terms of 1/N portfolio. In addition, we also investigate the performance of tactical asset allocation in terms of other usual portfolio strategies: minimum variance portfolio (MVP), tangency portfolio (TP), equally weighted risk contribution portfolio (ERCP), most diversified portfolio (MDP), Volatility timing portfolio (VTP) and Reward-to-risk timing portfolio (RRTP). Our empirical study shows that no tactical asset allocation strategies on technical trading rules outperform B&H benchmark. Our findings call into question the value of tactical asset allocation on technical trading rules.

Practical Applications of A Quantitative Approach to Tactical Asset Allocation Revisited 10 Years Later

<h3>Practical Applications Summary</h3> In <b>A Quantitative Approach to Tactical Asset Allocation Revisited 10 Years Later</b>, published in the in the 2018 Multi-Asset Special Issue of <b><i>The Journal of Portfolio Management</i></b>, <b>Meb Faber</b> of <b>Cambria Investment Management </b>in El Segundo, California, reviews the performance of his tactical asset allocation strategy over the past decade. He concludes that the model served its primary goal of minimizing volatility over an extended period. As for returns, although the model did underperform in each of the past eight years in a strong bull market, it outperformed during the 2008–2009 downturn, allowing it to modestly outperform for the decade. Faber then applies the strategy to a global asset allocation portfolio, invested in U.S. stocks, foreign stocks, bonds, real estate, and commodities. He finds that his approach would have reduced volatility dramatically for such a portfolio over the past decade, and he maintains that his strategy can be applied to a broad range of asset allocations strategies. The key is a consistent buy-and-sell strategy. <b>TOPICS:</b>Portfolio construction, statistical methods

Want Smart Beta? Follow the Smart Money: Market and Factor Timing Using Relative Sentiment

We present a real-time, cross-asset, positions-based relative sentiment indicator to predict the U.S. equity market. Derived from the Commitments of Traders report, the indicator measures — in a novel way — the aggregate positioning in equities of institutional investors relative to individual investors. Applying a wide range of statistical tests and controlling for data snooping, we find this indicator to be highly significant, exceptionally robust, and substantially more powerful than both value and momentum in predicting equity returns. Beyond the broad market, the indicator also facilitates the timing of several “smart beta” equity factors — many of which were thought difficult or impossible to time. We propose a tactical asset allocation strategy based on the indicator and compare it to several value- and/or momentum-based alternatives — finding the proposed strategy produces higher returns (both absolute and risk-adjusted), while having considerably less time-averaged exposure to equities.

Market Timing: Opportunities and Risks

Asset allocation decisions, particularly those involving market timing, create both opportunities and pitfalls for investors. In the aftermath of the crash of October 1987, many investors sought protection of capital through market timing or tactical asset allocation strategies. Since then, the popularity of tactical asset allocation has increased both for professional investment managers and individual investors alike. In this paper, I explore opportunities for enhancing returns using tactical asset allocation and market timing, as well as the challenges posed by market timing, including higher costs and the risk of missing the best-performing days of the market. I examine whether investors can succeed using tactical asset allocation and market timing strategies and look to behavioral finance concepts to explain why investors continue to embrace market timing in their investment process. I find that strategic asset allocation was the most important driver of long-term investment success. This is because most market timers typically fail to accurately predict important equity market swings. The long-term odds are not in favor of market timing strategies.

The EVA Style Approach to Tactical Asset Allocation

We refine tactical asset allocation (TAA) by arguing that the equity style component of a TAA strategy should distinguish between—and rotate among—predefined value creators and value destroyers in the marketplace. We assess equity style in the context of an economic profit approach to securities analysis and active portfolio management. We illustrate TAA in the context of an economic value added style analysis, and we demonstrate both the macroeconomic aspects and cyclicality of economic profit and its equity rotational implications for TAA. We conclude with a look at some well-known value creators and value destroyers, as well as known market anomalies that can also drive an economic profit approach to TAA and active portfolio management.

A tactical asset allocation strategy that exploits variations in VIX

Buy and hold strategies make staying disciplined difficult for investors, especially given the variability of returns for different asset classes/strategies during divergent market conditions. Market timing strategies, on the other hand, present significant theoretical benefits, but in reality these benefits are difficult to obtain. Tactical asset allocation, where limited deviations from the strategic allocation are allowed permits the portfolio manager to take advantage of market conditions fits between these two extremes. The authors correlate daily returns for each of eighteen separate asset classes typically used in diversified institutional portfolios and daily closing values of the VIX (the ticker symbol for the Chicago Board Options Exchange Volatility Index). This information is used to select those classes whose returns are most responsive to the level of the VIX. Portfolio allocations for eight selected asset classes are revised depending on the level of the VIX at the daily close of the market. The portfolio is rebalanced on the business day following the day the VIX hits the trigger value. The VIX tactical allocation overlay yields an increase in return over the buy and hold portfolio of approximately 38 basis points. The authors conclude that the tactical asset allocation strategy based on the level of VIX provides a higher return than the neutral buy and hold allocation with a higher Sharpe ratio and lower volatility.

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.

Equity Sector Rotation via Credit Relative Value

NAAIM 2013 Wagner Award-winning paper. Describes a straightforward sector rotation + tactical asset allocation strategy that uses a high yield credit index to judge equity relative value.

Global Tactical Asset Allocation for Institutional Investment Management

The Alberta Investment Management Corporation (AIMCo) was established in 2008 to manage approximately C$70 billion on behalf of 26 pension, endowment, and government reserve funds in the Province of Alberta. The fund’s over-arching goal is to earn incremental return on risk over what our clients could achieve by passively implementing their policy asset mix with equity and fixed income index funds. One way to add return in excess of passive portfolios is through our Global Tactical Asset Allocation (GTAA) strategy. In this brief note, we provide a description of the ways in which AIMCo has developed and executed its GTAA process over the past few years. In so doing, we hope to offer some insights to other institutional investors that might be considering or preparing to launch a similar GTAA or tilting policy. We conclude that executing a successful GTAA requires developing world-class talent, systems, process and governance.

Tactical Asset Allocation Using Relative Strength

This paper presents the results of several relative strength (momentum) tactical asset allocation strategies tested in a real world portfolio management setting. Monte Carlo simulations are used to determine the possible range of outcomes if a portfolio manager selects a subset of high relative strength (momentum) asset classes over time. A testing protocol that rebalances the portfolio on a continuous basis is also used to simulate real world portfolio management practices.

Determining the Current Optimal Allocation to Property: A Survey of Australian Fund Managers

This research paper examines the property asset allocation strategies for the A$1.7 trillion Australian managed funds industry and identifies the important steps and considerations that influence their optimal property allocation view and decision making process. It investigates the use and relevance of strategic and tactical asset allocation strategies for property asset allocation decisions. The results indicate that the allocation of resources to property assets is a complex system of interdependent decisions given its distinctive investment characteristics when compared to alternative asset classes. Apart from definitive/quantitative inputs in property asset allocation models, Australian fund managers are influenced by many other non-financial considerations. In addition, there are notable differences in techniques for direct property, unlisted property and securitised property asset allocation. The results also demonstrate that there has been a shift in Australian fund manager’s property asset allocation views and strategies driven mainly by the fund’s need to adapt to the continued uncertain global financial market conditions.

Credit-Informed Tactical Asset Allocation

This paper outlines a tactical asset allocation (TAA) strategy that takes signals from the credit markets and applies them to the stock market. A power model is built using the Russell 2000 equity index and the Bank of America/Merrill Lynch High Yield B index. This model is then used in a tactical asset allocation strategy to judge whether equities are expensive or cheap relative to high yield bonds. Based on back-test results from 1997 to the present, the approach provides equity-like returns while lowering portfolio volatility.