“The Impact of Skewness and Fat Tails on the Asset                     Allocation Decision”: A Comment

AbstractThis paper examines the impact of time averaging and interval sampling data assuming that the data generating process for a given series follows a random walk with iid errors. We provide exact expressions for the corresponding variances, and covariances, for both levels and higher order differences of the aggregated series, as well as that for the variance ratio, demonstrating exactly how the degree of temporal aggregation impacts these properties. We empirically investigate this issue on exchange rates and find that the values of the variance ratios and autocorrelation coefficients at different frequencies are consistent with our theoretical results. We also conduct a simulation exercise that illustrates the potential effect that conditional heteroskedasticity and fat tails may have on the temporal aggregation of a random walk and of a highly persistent autoregressive process.

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Herding and Delegated Portfolio Management: The Impact of Relative Performance Evaluation on Asset Allocation

Quarterly Journal of Finance ◽

10.1142/s2010139211000092 ◽

2011 ◽

Vol 01 (02) ◽

pp. 265-292 ◽

Cited By ~ 28

Author(s):

Ernst Maug ◽

Narayan Naik

Keyword(s):

Performance Evaluation ◽

Portfolio Management ◽

Asset Allocation ◽

Relative Performance ◽

Optimal Contracts ◽

Fund Managers ◽

Portfolio Managers ◽

Delegated Portfolio Management ◽

The Impact ◽

Allocation Decisions

This paper investigates the effect of fund managers' performance evaluation on their asset allocation decisions. We derive optimal contracts for delegated portfolio management and show that they always contain relative performance elements. We then show that this biases fund managers to deviate from return-maximizing portfolio allocations and follow those of their benchmark (herding). In many cases, the trustees of the fund who employ the fund manager prefer such a policy. We also show that fund managers in some situations ignore their own superior information and "go with the flow" in order to reduce deviations from their benchmark. We conclude that incentive provisions for portfolio managers are an important factor in their asset allocation decisions.

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Impact of volatility and equity market uncertainty on herd behaviour: evidence from UK REITs

Journal of European Real Estate Research ◽

10.1108/jerer-06-2017-0021 ◽

2018 ◽

Vol 11 (2) ◽

pp. 169-186 ◽

Cited By ~ 5

Author(s):

Omokolade Akinsomi ◽

Yener Coskun ◽

Rangan Gupta ◽

Chi Keung Marco Lau

Keyword(s):

Asset Allocation ◽

Regime Switching ◽

Stock Exchange ◽

Equity Market ◽

Market Uncertainty ◽

Content Type ◽

Regime Switching Model ◽

Switching Model ◽

Market Sentiment ◽

The Impact

PurposeThis paper aims to examine herding behaviour among investors and traders in UK-listed Real Estate Investment Trusts (REITs) within three market regimes (low, high and extreme volatility periods) from the period June 2004 to April 2016.Design/methodology/approachObservations of investors in 36 REITs that trade on the London Stock Exchange as at April 2016 were used to analyse herding behaviour among investors and traders of shares of UK REITs, using a Markov regime-switching model.FindingsAlthough a static herding model rejects the existence of herding in REITs markets, estimates from the regime-switching model reveal substantial evidence of herding behaviour within the low volatility regime. Most interestingly, the authors observed a shift from anti-herding behaviour within the high volatility regime to herding behaviour within the low volatility regime, with this having been caused by the FTSE 100 Volatility Index (UK VIX).Originality/valueThe results have various implications for decisions regarding asset allocation, diversification and value management within UK REITs. Market participants and analysts may consider that collective movements and market sentiment/psychology are determinative factors of risk-return in UK REITs. In addition, general uncertainty in the equity market, proxied by the impact of the UK VIX, may also provide a signal for increasing herding-related risks among UK REITs.

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Building and maintaining investment portfolios

From Main Street to Wall Street ◽

10.1093/oso/9780198866404.003.0020 ◽

2021 ◽

pp. 315-324

Author(s):

Jesper Rangvid

Keyword(s):

Asset Allocation ◽

Portfolio Diversification ◽

Economic Environment ◽

Allocation Decision ◽

Practical Advice ◽

Investment Portfolios

This last chapter in the book provides research-based perspectives on a number of challenges investors face when building and maintaining investment portfolios. The paper discusses portfolio diversification, the active vs. passive debate, the asset allocation decision, i.e. what determines the fraction of a portfolio that should be invested in stocks, practical advice on how the economic environment should affect your asset allocation, and other topics.

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Ambiguity aversion and experiential learning: implications for long-term savings decisions

Review of Behavioral Finance ◽

10.1108/rbf-03-2019-0045 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Bryan Foltice ◽

Rachel Rogers

Keyword(s):

Decision Making ◽

Experiential Learning ◽

Asset Allocation ◽

Ambiguity Aversion ◽

Sample Population ◽

Allocation Decision ◽

Content Type ◽

Learning Modules ◽

Return Data

PurposeThis paper evaluates potential methods for reducing ambiguity surrounding returns on equity to improve long-term savings decisions.Design/methodology/approachWe evaluate 221 undergraduate students in the US and first assess the degree of ambiguity aversion exhibited by individuals in the sample population as they decide between a risky (known probability) option and ambiguous (unknown probability) option pertaining to their chances of winning $0 or $1 in a hypothetical lottery. Similarly, we test whether sampling historical return data through learning modules influences long-term decision making regarding asset allocation within a retirement portfolio.FindingsAllowing participants to experience the underlying probability through sampling significantly influences behavior, as participants were more likely to select the ambiguous option after sampling. Here, we also find that participants who receive interactive learning modules – which require users to manually alter the asset allocation to produce a sample of historical return data based on the specific allocation entered in the model – increase their post-learning equity allocations by 10.1% more than individuals receiving static modules. Interestingly, we find no significant evidence of ambiguity aversion playing a role in the asset allocation decision.Originality/valueWe find that decision-making related to ambiguous and risky options can be substantially influenced by experiential learning. Our study supplements previous literature, providing a link between research on the effect of ambiguity on stock market participation and implementation of educational programs to improve the asset allocation decision for young adults.

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The missing link: economic exposure and pension plan risk

Annals of Actuarial Science ◽

10.1017/s1748499515000020 ◽

2015 ◽

Vol 9 (2) ◽

pp. 290-303

Author(s):

Paul Sweeting ◽

Alexandre Christie ◽

Edward Gladwyn

Keyword(s):

Asset Allocation ◽

Pension Plan ◽

Asset Returns ◽

Oil Price ◽

Defined Benefit ◽

Financial Health ◽

Defined Benefit Pension Plan ◽

Asset Class ◽

Normal Shape ◽

The Impact

AbstractThe funding position of a defined benefit pension plan is often closely linked to the performance of the sponsoring company’s business. For example, a plan sponsor whose financial health is dependent on high oil prices may struggle during periods of oil price weakness. If the pension plan’s assets perform poorly at this time, the ability of the sponsor to address any funding requirement could be restricted precisely when the need for funding is heightened. In this paper, we propose an approach to dealing with joint plan and sponsor risk that can provide protection against extreme adverse events for the sponsor. In particular, adopt a strategy of minimising a portfolio’s expected losses in the event of an assumed drop of x% in the oil price. Our methodology relies on an asset allocation framework that takes into account the impact of serial correlation in asset returns, as well as the negative skewness and leptokurtosis resulting from the non-normal shape of marginal distributions of historical asset returns. We also make use of copulas to measure the dependence between asset class returns.

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