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Wee-Ling Tan

4 papers hereh-index 00 citations0 works total

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

author position
  • first author3
  • middle author1

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

fields
  • q-fin.PM3
  • cs.LG1
same name
  • Wee-Ling Tan — 1 paper, h 1

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

activity
20222026
most citedADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data

76 citations · 85 across the 3 of their papers we have counts for

collaborators

4 papers

q-fin.PM2026

Taming the Greeks: Option Portfolios with Inductive Biases

Wee Ling Tan, Stephen Roberts, Stefan Zohren

We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures. Wh…

q-fin.PM2024★ 2 cited

Deep Learning for Options Trading: An End-To-End Approach

Wee Ling Tan, Stephen Roberts, Stefan Zohren

We introduce a novel approach to options trading strategies using a highly scalable and data-driven machine learning algorithm. In contrast to traditional approaches that often req…

q-fin.PM2023★ 7 cited

Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies

Wee Ling Tan, Stephen Roberts, Stefan Zohren

We introduce Spatio-Temporal Momentum strategies, a class of models that unify both time-series and cross-sectional momentum strategies by trading assets based on their cross-secti…

cs.LG2022★ 76 cited

ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data

Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan +5

Unsupervised domain adaptation methods aim to generalize well on unlabeled test data that may have a different (shifted) distribution from the training data. Such methods are typic…

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