Optimal Liquidation Strategy of Multi-assets Based on Minimum Loss Probability
- PDF / 1,452,700 Bytes
- 17 Pages / 521.575 x 737.008 pts Page_size
- 101 Downloads / 146 Views
ISSN: 1004-3756 (paper), 1861-9576 (online) CN 11-2983/N
Optimal Liquidation Strategy of Multi-assets Based on Minimum Loss Probability Qixuan Luo,a Can Jia,a Shaobo Zhao,b Handong Lia a School
of Systems Science, Beijing Normal University, Beijing 100875, China [email protected], [email protected], [email protected] () b School of Government, Beijing Normal University, Beijing 100875, China [email protected]
Abstract. Based on the minimum loss probability criterion, this paper discusses the optimal strategy in
multi-asset liquidation. First, we give the framework of the multi-asset liquidation problem and obtain the boundary conditions of the optimal liquidation strategy under the assumption of linear price impact functions and transform the multi-asset liquidation problem into the portfolio liquidation problem. On this basis, the asymptotic solution and numerical solution of the optimal liquidation strategy are obtained. Then, we simulate the trajectories of the optimal liquidation strategy and analyze the effects of parameters changes. Keywords: Minimum loss probability, multi-asset liquidation, permanent impact, temporary impact, opti-
mal liquidation strategy
1. Introduction
this point, which causes the stock price to fluc-
With the rapid development of computer and Internet technology, great changes have taken
tuate greatly in a short period. Therefore, the in-depth study of algorithm trading is particularly essential.
place in the transaction modes in the modern financial market. Algorithmic trading characterized by high-frequency data processing and automatic computer ordering emerges. Algorithmic trading refers to the general term of making trading decisions, submitting orders and managing orders by computer. Brunnermeier and Pedersen (2008) and Scholtus et al. (2014) believe that algorithmic trading has significant effects on improving market efficiency, increasing liquidity and reducing transaction costs of large positions. However, improper use of algorithmic trading may lead to large consumption of market liquidity and a substantial increase in market volatility in a short period, bringing certain risks to the market and even triggering a huge crisis. The Flash Crash in the US stock market in 2010 and the fat finger accident of Everbright Securities in China in 2013 have proved
One of the core concerns of algorithmic trading is the short-term execution of the large positions of investors in financial markets. Due to the limited market liquidity, the immediate trading of large positions will inevitably impact the prices of risky assets, thus increasing transaction costs. Therefore, investors need to split their positions into small orders that can be executed in batches. However, such the split order transaction will prolong the transaction time and thus increase the risk due to uncertain volatility. Therefore, a good liquidation strategy must balance the transaction costs and risks. Many models have been developed in the studies of market price impact and optimal execution strategies. The first-class mode
Data Loading...
