Essays in Quantitative Investments



Yang, Y
(2018) Essays in Quantitative Investments. PhD thesis, University of Liverpool.

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Abstract

This thesis studies the characteristics of Chinese futures markets and the quantitative investment strategies. The main objective of this thesis is to provide a comprehensive analysis on the performance of quantitative investment strategies in the Chinese market. Furthermore, with an econometric analysis, the stylised facts of the Chinese futures markets are documented. Extensive backtesting results on the performance of momentum, reversal and pairs trading type strategies are provided. In the case of pairs trading type strategies, risk and return relationship is characterised by the length of the maximum holding periods, and thus re ected in the maximum drawdown risk. In line with the increasing holding periods, the pro tability of pairs trading increases over longer holding periods. Therefore, the abnormal returns from pairs trading in the Chinese futures market do not necessarily re ect market ine ciency. Momentum and reversal strategies are compared by employing both high- and low-frequency time series with precise estimation of transaction costs. The comparison of momentum and reversal investment strategies at the intra- and inter-day scales displays that the portfolio rebalancing frequency signi cantly impacts the pro tability of such strategies. Complementarily, the excess returns of inter-day momentum trading with the inclusion of precise estimates of transaction costs re ect that quantitative investment strategies consistently produce abnormal pro ts in the Chinese commodity futures markets. However, from a risk-adjusted view, the returns are obtained only by bearing additional drawdown risks. Finally, this thesis suggests that investor should choose quantitative trading strategies according to the investment horizon, tolerance for maximum drawdown and portfolio rebalancing costs.

Item Type: Thesis (PhD)
Divisions: Faculty of Science and Engineering > School of Physical Sciences
Depositing User: Symplectic Admin
Date Deposited: 23 Aug 2018 08:26
Last Modified: 17 Dec 2022 03:18
DOI: 10.17638/03021457
Supervisors:
  • Goncu, A
URI: https://livrepository.liverpool.ac.uk/id/eprint/3021457