“The Impact of Skewness and Fat Tails on the Asset Allocation Decision”: Author Response

2012 ◽  
Vol 68 (3) ◽  
pp. 10-12 ◽  
Author(s):  
Thomas M. Idzorek ◽  
James X. Xiong
2011 ◽  
Vol 67 (2) ◽  
pp. 23-35 ◽  
Author(s):  
James X. Xiong ◽  
Thomas M. Idzorek

2010 ◽  
Vol 66 (4) ◽  
pp. 17-18 ◽  
Author(s):  
James X. Xiong ◽  
Roger G. Ibbotson ◽  
Thomas M. Idzorek ◽  
Peng Chen

2019 ◽  
Vol 24 (2) ◽  
Author(s):  
Yamin S Ahmad ◽  
Ivan Paya

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.


2011 ◽  
Vol 01 (02) ◽  
pp. 265-292 ◽  
Author(s):  
Ernst Maug ◽  
Narayan Naik

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.


2018 ◽  
Vol 11 (2) ◽  
pp. 169-186 ◽  
Author(s):  
Omokolade Akinsomi ◽  
Yener Coskun ◽  
Rangan Gupta ◽  
Chi Keung Marco Lau

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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