The Role of Risk Forecast and Risk Tolerance in Portfolio
Management: A Case Study of the Chinese Financial Sector

Jianxu Liu 1,2 , Yangnan Cheng 2,* , Xiaoqing Li 1 and Songsak Sriboonchitta 2
1 Faculty of Economics, Shandong University of Finance and Economics, Jinan 250000, China;
liujianxu1984@163.com (J.L.); lxq35008@163.com (X.L.)
2 Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand; songsakecon@gmail.com
* Correspondence: cheng_yangnan@163.com

Abstract: Portfolio decisions are affected by the volatility of financial markets and investors’ risk tolerance levels. To better allocate portfolios; we introduce risk tolerance into the portfolio management
problem by considering the risk contribution of portfolio components. In this paper, portfolio weights
are allocated to two stages. In the first stage, the portfolio risks and the risk contribution of each
share are forecasted. In the second stage, we put forward three weighting techniques—“aggressive”,
“moderate” and “conservative”, according to three standard levels of risk tolerance. In addition, a
new risk measure called “joint extreme risk probability” (JERP), with risk tolerance taken into account,
is proposed. A case study of the Chinese financial industry is conducted to verify the performance
of our methods. The empirical results demonstrate that weighting techniques constrained by risk
tolerance lead to higher gains in a normal market and less loss when a market is risky. Compared
with risk-tolerance-adjusted strategies, the relationship between the performance of the traditional
conditional value at risk (CVaR) minimization method and the market risk level is less obviously
demonstrated. Viewed from the results, JERP functions as an effective signal that helps investors to
deal with potential market risks.
Keywords: risk contribution; one-factor copula with Durante generators; component expected
shortfall; conditional value at risk; joint extreme risk probability