Active margin system for margin loans and its application in Chinese market: using cash and randomly selected stock as collateral

TL;DR

This paper proposes an active margin system for Chinese margin loans using cash and stock as collateral, employing a risk measure based on CPNR and a recursive algorithm under a Markov chain model, demonstrating reduced margin calls and costs.

Contribution

It introduces a novel active margin system that dynamically adjusts to market changes using a Markov chain-based risk measure, improving over traditional static systems.

Findings

Fewer margin calls compared to standard systems.

Lower average costs of margin loans.

Effective risk management demonstrated on real market data.

Abstract

An active margin system for margin loans is proposed for Chinese margin lending market, which uses cash and randomly selected stock as collateral. The conditional probability of negative return(CPNR) after a forced sale of securities from under-margined account in a falling market is used to measure the risk faced by the brokers, and the margin system is chosen under the constraint of the risk measure. In order to calculate CPNR, a recursive algorithm is proposed under a Markov chain model, which is constructed by sample learning method. The resulted margin system is an active system, which is able to adjust actively with respect to the changes of stock prices and the changes of different collateral. The resulted margin system is applied to 30,000 margin loans of 150 stocks listed on Shanghai Stock Exchange. The empirical results show the number of margin calls and the average costs of the loans under the proposed margin system are less than their counterparts under the system required by SSE and SZSE.