Liquidity Risks, Transaction costs and Online Portfolio Selection

Abstract

The performance of online (sequential) portfolio selection (OPS), which rebalances a portfolio in every period (e.g. daily or weekly) in order to maximise the portfolio's expected terminal wealth in the long run, has been overestimated by the ideal assumption of unlimited market liquidity (i.e. no market impact costs). Therefore, a new transaction cost factor model that considers both market impact costs, estimated from limit order book data, and proportional transaction costs (e.g. brokerage commissions or transaction taxes in a fixed percentage) has been proposed in this paper to measure existing OPS strategies performance in a more practical way as well as to develop a more effective OPS method. Backtesting results from the historical limit order book (LOB) data of NASDAQ-traded stocks show both the performance deterioration of existing OPS methods by the market impact costs and the superiority of our proposed OPS method in the environment of limited market liquidity.

Online Portfolio Optimization with Risk Control

“…This additional information allows the Newton Step Online algorithm to get Regret O(log T ). Works such as [10,14,20] have focused on considering transaction costs as a way to enable brokers and investors to use online algorithms, but on the other hand, do not consider the risk of the built portfolio.…”

Algorithmic trading for online portfolio selection under limited market liquidity

“…However, the liquidity risks or the market impact costs (MICs), a common feature of financial markets, has been ignored in OPS literature. Ha and Zhang (2018) did propose a more practical OPS method which considers both the proportional TCs and MICs, but none compatible optimal intraday trading algorithm has been developed in their framework to reduce the higher MICs under a limited market liquidity.…”