activity
20122022
most citedNon-Arbitrage up to Random Horizon for Semimartingale Models

13 citations · 34 across the 12 of their papers we have counts for

collaborators

13 papers

q-fin.GN2022★ 6 cited

Static Replication of Impermanent Loss for Concentrated Liquidity Provision in Decentralised Markets

Jun Deng, Hua Zong, Yun Wang

This article analytically characterizes the impermanent loss of concentrated liquidity provision for automatic market makers in decentralised markets such as Uniswap. We propose tw…

q-fin.GN2021

Net Buying Pressure and the Information in Bitcoin Option Trades

Carol Alexander, Jun Deng, Jianfen Feng +1

How do supply and demand from informed traders drive market prices of bitcoin options? Deribit options tick-level data supports the limits-to-arbitrage hypothesis about the market…

q-fin.TR2021

Liquidation, Leverage and Optimal Margin in Bitcoin Futures Markets

Zhiyong Cheng, Jun Deng, Tianyi Wang +1

Using the generalized extreme value theory to characterize tail distributions, we address liquidation, leverage, and optimal margins for bitcoin long and short futures positions. T…

q-fin.RM2021★ 3 cited

Hedging with Bitcoin Futures: The Effect of Liquidation Loss Aversion and Aggressive Trading

Carol Alexander, Jun Deng, Bin Zou

We consider the hedging problem where a futures position can be automatically liquidated by the exchange without notice. We derive a semi-closed form for an optimal hedging strateg…

q-fin.MF2020

Quadratic Hedging for Sequential Claims with Random Weights in Discrete Time

Jun Deng, Bin Zou

We study a quadratic hedging problem for a sequence of contingent claims with random weights in discrete time. We obtain the optimal hedging strategy explicitly in a recursive repr…

q-fin.RM2017

An Explicit Default Contagion Model and Its Application to Credit Derivatives Pricing

Dianfa Chen, Jun Deng, Jianfen Feng +1

We propose a novel credit default model that takes into account the impact of macroeconomic information and contagion effect on the defaults of obligors. We use a set-valued Markov…