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Lingfei Li

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • q-fin.PR2
  • math.PR1
  • q-fin.ST1
ORCID 0000-0002-1761-3458
same name
  • Lingfei Li — 2 papers
  • Lingfei Li — 1 paper, h 14

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSimulation of Multidimensional Diffusions with Sticky Boundaries via Markov Chain Approximation

3 citations · 7 across the 4 of their papers we have counts for

collaborators

4 papers

q-fin.ST2021★ 2 cited

Data-driven Hedging of Stock Index Options via Deep Learning

Jie Chen, Lingfei Li

We develop deep learning models to learn the hedge ratio for S&P500 index options directly from options data. We compare different combinations of features and show that a feedforw…

math.PR2021★ 3 cited

Simulation of Multidimensional Diffusions with Sticky Boundaries via Markov Chain Approximation

Christian Meier, Lingfei Li, Gongqiu Zhang

We develop a new simulation method for multidimensional diffusions with sticky boundaries. The challenge comes from simulating the sticky boundary behavior, for which standard meth…

q-fin.PR2012★ 1 cited

Evaluating Callable and Putable Bonds: An Eigenfunction Expansion Approach

Dongjae Lim, Lingfei Li, Vadim Linetsky

We propose an efficient method to evaluate callable and putable bonds under a wide class of interest rate models, including the popular short rate diffusion models, as well as thei…

q-fin.PR2012★ 1 cited

Time-Changed Ornstein-Uhlenbeck Processes And Their Applications In Commodity Derivative Models

Lingfei Li, Vadim Linetsky

This paper studies subordinate Ornstein-Uhlenbeck (OU) processes, i.e., OU diffusions time changed by Lévy subordinators. We construct their sample path decomposition, show that th…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.