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bellkoralgorithm's Introduction

Hello! I'm Dan. 👋

  • 🔭 I’m currently working as a Senior Backend Engineer at Sigma Financial
  • 🌱 I’m currently learning about Market Making and SIMD.
  • 🤔 I’m looking for help with Market Making and Linear Programming / Optimisation.
  • 📫 How to reach me: LinkedIn or Emails

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bellkoralgorithm's Issues

wrong gradient

hello @dandxy89
I think
b_u = 2 * error * (-1 + 2 * self.REGULARISATION.b_u * rs.b_u)
is wrong
and
b_u = -2 * error + 2 * self.REGULARISATION.b_u * rs.b_u
is correct

calculation of gradients maybe wrong

In Algorithm.py, get_gradients function, your code is shown as follow:

gradients = Gradients(b_u=-2 * error + 2 * self.REGULARISATION.b_u * rs.b_u,
alpha_u=2 * error * (-rs.Dev + 2 * self.REGULARISATION.alpha_u * rs.alpha_u),
b_ut=2 * error * (-1 + self.REGULARISATION.b_ut * rs.b_ut),
b_i=2 * error * (-rs.c_u - rs.c_ut + 2 * self.REGULARISATION.b_i * rs.b_i),
b_ibin=2 * error * (-rs.c_u - rs.c_ut + 2 * self.REGULARISATION.b_ibin * rs.b_ibin),
c_u=2 * error * (-rs.b_i - rs.b_ibin + 2 * self.REGULARISATION.c_u * (rs.c_u - 1)),
c_ut=2 * error * (-rs.b_i - rs.b_ibin + 2 * self.REGULARISATION.c_ut * rs.c_ut),
p=2 * error * (rs.q + 2 * self.REGULARISATION.p * rs.p),
q=2 * error * (rs.p + rs.alpha_p * rs.Dev + 2 * self.REGULARISATION.q * rs.q),
alpha_p=2 * error * (rs.q * rs.Dev + self.REGULARISATION.alpha_p * rs.alpha_p))
——————————————————————————————————————

here's my version, which I think is correct.
+++++++++++++++++++++++++++++++++++++
gradients = Gradients(b_u=-2 * error + 2 * self.REGULARISATION.b_u * rs.b_u,
alpha_u=2 * error * (-rs.Dev) + 2 * self.REGULARISATION.alpha_u * rs.alpha_u,
b_ut=2 * error * (-1) + self.REGULARISATION.b_ut * rs.b_ut,
b_i=2 * error * (-rs.c_u - rs.c_ut) + 2 * self.REGULARISATION.b_i * rs.b_i,
b_ibin=2 * error * (-rs.c_u - rs.c_ut) + 2 * self.REGULARISATION.b_ibin * rs.b_ibin,
c_u=2 * error * (-rs.b_i - rs.b_ibin) + 2 * self.REGULARISATION.c_u * (rs.c_u - 1),
c_ut=2 * error * (-rs.b_i - rs.b_ibin) + 2 * self.REGULARISATION.c_ut * rs.c_ut,
p=2 * error * (-rs.q) + 2 * self.REGULARISATION.p * rs.p,
q=2 * error * (-rs.p - rs.alpha_p * rs.Dev) + 2 * self.REGULARISATION.q * rs.q,
alpha_p=2 * error * (-rs.q * rs.Dev) + self.REGULARISATION.alpha_p * rs.alpha_p)

Please check it. btw, this project is really impressive, thank you very much:)

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