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Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets. / Haerdle, Wolfgang; Lee Kuo Chuen, David; Nasekin, Sergey et al.
In: Journal of Asset Management, Vol. 19, No. 1, 01.01.2018, p. 49-63.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Haerdle, W, Lee Kuo Chuen, D, Nasekin, S & Petukhina, A 2018, 'Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets', Journal of Asset Management, vol. 19, no. 1, pp. 49-63. https://doi.org/10.1057/s41260-017-0060-9

APA

Haerdle, W., Lee Kuo Chuen, D., Nasekin, S., & Petukhina, A. (2018). Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets. Journal of Asset Management, 19(1), 49-63. https://doi.org/10.1057/s41260-017-0060-9

Vancouver

Haerdle W, Lee Kuo Chuen D, Nasekin S, Petukhina A. Tail Event Driven ASset allocation: evidence from equity and mutual funds’ markets. Journal of Asset Management. 2018 Jan 1;19(1):49-63. Epub 2017 Sept 25. doi: 10.1057/s41260-017-0060-9

Author

Haerdle, Wolfgang ; Lee Kuo Chuen, David ; Nasekin, Sergey et al. / Tail Event Driven ASset allocation : evidence from equity and mutual funds’ markets. In: Journal of Asset Management. 2018 ; Vol. 19, No. 1. pp. 49-63.

Bibtex

@article{f1955287c79b47439536c913612f626a,
title = "Tail Event Driven ASset allocation: evidence from equity and mutual funds{\textquoteright} markets",
abstract = "The correlation structure across assets and opposite tail movements are essential to the asset allocation problem, since they determine the level of risk in a position. Correlation alone is not informative on the distributional details of the assets. Recently introduced TEDAS—Tail Event Driven ASset allocation approach determines the dependence between assets at different tail measures. TEDAS uses adaptive Lasso-based quantile regression in order to determine an active set of negative coefficients. Based on these active risk factors, an adjustment for intertemporal correlation is made. In this research, authors aim to develop TEDAS, by introducing three TEDAS modifications differing in allocation weights{\textquoteright} determination: a Cornish–Fisher Value-at-Risk minimization, Markowitz diversification rule or na{\"i}ve equal weighting. TEDAS strategies significantly outperform other widely used allocation approaches on two asset markets: German equity and Global mutual funds.",
keywords = "Adaptive lasso , Portfolio optimization, Quantile regression , Value-at-Risk, Tail events ",
author = "Wolfgang Haerdle and {Lee Kuo Chuen}, David and Sergey Nasekin and Alla Petukhina",
year = "2018",
month = jan,
day = "1",
doi = "10.1057/s41260-017-0060-9",
language = "English",
volume = "19",
pages = "49--63",
journal = "Journal of Asset Management",
issn = "1470-8272",
publisher = "Palgrave Macmillan Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Tail Event Driven ASset allocation

T2 - evidence from equity and mutual funds’ markets

AU - Haerdle, Wolfgang

AU - Lee Kuo Chuen, David

AU - Nasekin, Sergey

AU - Petukhina, Alla

PY - 2018/1/1

Y1 - 2018/1/1

N2 - The correlation structure across assets and opposite tail movements are essential to the asset allocation problem, since they determine the level of risk in a position. Correlation alone is not informative on the distributional details of the assets. Recently introduced TEDAS—Tail Event Driven ASset allocation approach determines the dependence between assets at different tail measures. TEDAS uses adaptive Lasso-based quantile regression in order to determine an active set of negative coefficients. Based on these active risk factors, an adjustment for intertemporal correlation is made. In this research, authors aim to develop TEDAS, by introducing three TEDAS modifications differing in allocation weights’ determination: a Cornish–Fisher Value-at-Risk minimization, Markowitz diversification rule or naïve equal weighting. TEDAS strategies significantly outperform other widely used allocation approaches on two asset markets: German equity and Global mutual funds.

AB - The correlation structure across assets and opposite tail movements are essential to the asset allocation problem, since they determine the level of risk in a position. Correlation alone is not informative on the distributional details of the assets. Recently introduced TEDAS—Tail Event Driven ASset allocation approach determines the dependence between assets at different tail measures. TEDAS uses adaptive Lasso-based quantile regression in order to determine an active set of negative coefficients. Based on these active risk factors, an adjustment for intertemporal correlation is made. In this research, authors aim to develop TEDAS, by introducing three TEDAS modifications differing in allocation weights’ determination: a Cornish–Fisher Value-at-Risk minimization, Markowitz diversification rule or naïve equal weighting. TEDAS strategies significantly outperform other widely used allocation approaches on two asset markets: German equity and Global mutual funds.

KW - Adaptive lasso

KW - Portfolio optimization

KW - Quantile regression

KW - Value-at-Risk

KW - Tail events

U2 - 10.1057/s41260-017-0060-9

DO - 10.1057/s41260-017-0060-9

M3 - Journal article

VL - 19

SP - 49

EP - 63

JO - Journal of Asset Management

JF - Journal of Asset Management

SN - 1470-8272

IS - 1

ER -