Risk Hedging Application of Quantitative Trading Risk Assessment Method in Securities Market

This study focuses on the field of quantitative trading and explores in depth the application of risk assessment methods in securities market risk hedging. Through in-depth analysis of different risk categories in quantitative trading, the transmission mechanism and core influencing factors are clarified, such as market risk, credit risk, operational risk, liquidity risk, etc. Based on capital allocation theory, a dynamic risk parity strategy is created with the goal of balancing asset risk contributions, enhancing the robustness of quantitative strategies, and achieving sustained positive returns. Variables and data sources are selected from multiple perspectives in the securities market to construct a complex quantitative trading risk evaluation model. Through subsequent regression analysis, variance decomposition, time series stability check, and Montcallo simulation methods, the model settings are strictly checked to ensure accurate theoretical analysis. The final empirical results revealed that the new risk assessment method proposed specific suggestions for strategy optimization and adjustment through strategy backtesting and sensitivity analysis. In order to provide reference for efficient execution of risk hedging strategies in practice.

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Publication Details

Journal
Highlights in Business Economics and Management
Published
2024-11-19
DOI
https://doi.org/10.54097/5y86rv58
Primary Topic
Stock Market Forecasting Methods
Type
article
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article

Risk Hedging Application of Quantitative Trading Risk Assessment Method in Securities Market

C. Gao
Highlights in Business Economics and Management
Stock Market Forecasting Methods
article

Risk Hedging Application of Quantitative Trading Risk Assessment Method in Securities Market

C. Gao
article en

Abstract

This study focuses on the field of quantitative trading and explores in depth the application of risk assessment methods in securities market risk hedging. Through in-depth analysis of different risk categories in quantitative trading, the transmission mechanism and core influencing factors are clarified, such as market risk, credit risk, operational risk, liquidity risk, etc. Based on capital allocation theory, a dynamic risk parity strategy is created with the goal of balancing asset risk contributions, enhancing the robustness of quantitative strategies, and achieving sustained positive returns. Variables and data sources are selected from multiple perspectives in the securities market to construct a complex quantitative trading risk evaluation model. Through subsequent regression analysis, variance decomposition, time series stability check, and Montcallo simulation methods, the model settings are strictly checked to ensure accurate theoretical analysis. The final empirical results revealed that the new risk assessment method proposed specific suggestions for strategy optimization and adjustment through strategy backtesting and sensitivity analysis. In order to provide reference for efficient execution of risk hedging strategies in practice.

Highlights in Business Economics and ManagementVol. 42
Openalex Percentile: Top 74%
Stock Market Forecasting Methods
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