Continuous-Time Risk Contribution of the Terminal Variance and its Related Risk Budgeting Problem

TL;DR

This paper extends risk contribution and risk budgeting concepts from static covariance matrices to continuous-time models using stochastic calculus, providing new methods for portfolio risk management and allocation.

Contribution

It introduces a continuous-time framework for risk contributions and risk budgeting, utilizing Gateaux differentials and Doleans measures, with applications to volatility-managed portfolios.

Findings

Risk contributions are characterized as predictable processes.

Total risk can be decomposed into asset-specific contributions.

Continuous-time risk budgeting policies relate to single-period policies.

Abstract

To achieve robustness of risk across different assets, risk parity investing rules, a particular state of risk contributions, have grown in popularity over the previous few decades. To generalize the concept of risk contribution from the simple covariance matrix case to the continuous-time case in which the terminal variance of wealth is used as the risk measure, we characterize risk contributions and marginal risk contributions on various assets as predictable processes using the Gateaux differential and Doleans measure. Meanwhile, the risk contributions we extend here have the aggregation property, namely that total risk can be represented as the aggregation of those among different assets and $(t,\omega)$. Subsequently, as an inverse target -- allocating risk, the risk budgeting problem of how to obtain policies whose risk contributions coincide with pre-given risk budgets in the continuous-time case is also explored in this paper. These policies are solutions to stochastic convex optimizations parametrized by the pre-given risk budgets. Moreover, single-period risk budgeting policies are explained as the projection of risk budgeting policies in continuous-time cases. On the application side, volatility-managed portfolios in [Moreira and Muir,2017] can be obtained by risk budgeting optimization; similarly to previous findings, continuous-time mean-variance allocation in [Zhou and Li, 2000] appears to be concentrated in terms of risk contribution.