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Regression techniques for Portfolio Optimisation using MOSEK


  • Thomas Schmelzer
  • Raphael Hauser
  • Erling Andersen
  • Joachim Dahl


Regression is widely used by practioners across many disciplines. We reformulate the underlying optimisation problem as a second-order conic program providing the flexibility often needed in applications. Using examples from portfolio management and quantitative trading we solve regression problems with and without constraints. Several Python code fragments are given. The code and data are available online at

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  • Thomas Schmelzer & Raphael Hauser & Erling Andersen & Joachim Dahl, 2013. "Regression techniques for Portfolio Optimisation using MOSEK," Papers 1310.3397,
  • Handle: RePEc:arx:papers:1310.3397

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    1. Yinyu Ye & Michael J. Todd & Shinji Mizuno, 1994. "An O(√nL)-Iteration Homogeneous and Self-Dual Linear Programming Algorithm," Mathematics of Operations Research, INFORMS, vol. 19(1), pages 53-67, February.
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