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20082020
most citedAsymptotics for rough stochastic volatility models

88 citations · 379 across the 20 of their papers we have counts for

collaborators

20 papers

q-fin.MF2020★ 8 cited

When to sell an asset amid anxiety about drawdowns

Neofytos Rodosthenous, Hongzhong Zhang

We consider risk averse investors with different levels of anxiety about asset price drawdowns. The latter is defined as the distance of the current price away from its best perfor…

q-fin.MF2017★ 11 cited

On the optimality of threshold type strategies in single and recursive optimal stopping under Lévy models

Mingsi Long, Hongzhong Zhang

In the spirit of [Surya07'], we develop an average problem approach to prove the optimality of threshold type strategies for optimal stopping of Lévy models with a continuous addit…

q-fin.MF2017★ 17 cited

Beating the Omega Clock: An Optimal Stopping Problem with Random Time-horizon under Spectrally Negative Lévy Models

Neofytos Rodosthenous, Hongzhong Zhang

We study the optimal stopping of an American call option in a random time-horizon under exponential spectrally negative Lévy models. The random time-horizon is modeled as the so-ca…

q-fin.MF2017★ 26 cited

A Unified Approach for Drawdown (Drawup) of Time-Homogeneous Markov Processes

David Landriault, Bin Li, Hongzhong Zhang

Drawdown (resp. drawup) of a stochastic process, also referred as the reflected process at its supremum (resp. infimum), has wide applications in many areas including financial ris…

q-fin.MF2017★ 7 cited

Optimal Trading with a Trailing Stop

Tim Leung, Hongzhong Zhang

Trailing stop is a popular stop-loss trading strategy by which the investor will sell the asset once its price experiences a pre-specified percentage drawdown. In this paper, we st…

q-fin.PR2016★ 88 cited

Asymptotics for rough stochastic volatility models

Martin Forde, Hongzhong Zhang

Using the large deviation principle (LDP) for a re-scaled fractional Brownian motion where the rate function is defined via the reproducing kernel Hilbert space, we compute…