Your code doesn't appear to work.

[stockpsyop]

Not certain, but the predicted values are way out of line with expectations.

I also note some code that is appending the data set:
def formatData(dataSet, initialFactors):
print("Styvio Console: formatting data...")
differences = []
for i in range(0, (len(dataSet)-1)):
differences.append(initialFactors[i]-dataSet[i])
differences.append(-999)
orderedDifferences, orderedDataSet = zip(*sorted(zip(differences, dataSet)))
return(orderedDifferences, orderedDataSet)

This value in particular, what is the meaning [differences.append(-999)] ?

Here is the data set and results:
Original Dataset: [3906.75, 3896.25, 3885.5, 3928.75, 3973.25, 3943.75, 3992.5, 4021.5, 4024.25, 4035.25, 4033.5, 3948.75, 3990.5, 4056.75, 4047.5, 4040.5, 4077, 4109.25, 4086, 4091.25, 4163.25, 4208.5, 4194, 4143, 4188.25, 4179.25, 4170.25, 4104.25, 4150.75, 4186.5, 4161.75, 4168.5, 4096, 4089.25, 4025, 4034.25, 4023.25, 4024.75, 4003.75, 3991, 3995.25, 4053, 4082.5, 4064.5, 4003.25, 4019.75, 3941.75, 3938.75, 3938, 3931, 3966.5, 3974, 3989.5, 4043.25, 4073.75, 4039.5, 4010.75, 4034.25, 4023.75, 4061.25, 4087.75, 4142.5, 4157.75, 4171.75, 4135.5, 4135.25, 4143, 4151.75, 4177.75, 4177, 4189, 4180.5, 4198.25, 4187.5, 4173.5, 4161, 4164.25, 4158.5, 4116.25, 4166.5, 4193.75, 4206.25, 4191.5, 4167, 4118, 4163.25, 4161, 4153, 4173.25, 4168.5, 4164.5, 4156.25, 4151.5, 4179, 4215.75, 4227.25, 4221.75, 4222.75, 4166.25, 4175.5, 4221.25, 4243.25, 4217.75, 4239.75, 4297.75, 4305.75, 4294.75, 4304.75, 4302.5, 4325.5, 4346.5, 4377.75, 4394.75, 4441, 4453.35, 4462, 4438.5, 4427, 4426.25, 4403, 4424.75, 4430.25, 4438, 4498, 4494, 4493.75, 4483.5, 4476, 4448.25, 4478.5, 4523.75, 4551.5, 4560.5, 4565.75, 4594.5, 4609.25, 4594.25, 4590, 4592.5, 4608.75, 4610.75, 4634.5, 4616.5, 4619.25, 4621.75, 4593.5, 4547.5, 4560.75, 4541.75, 4541, 4536.25, 4544.75, 4496.25, 4507.75, 4517.75, 4467.25, 4436.75, 4396, 4421, 4440, 4476.25, 4485.5, 4429, 4449.5, 4509.5, 4530.75, 4541.25, 4547.75, 4531.25, 4503.75, 4471.75, 4477.5, 4493.5, 4491, 4481, 4513, 4517.75, 4514.5, 4509.5, 4508, 4447, 4399, 4383.5, 4382, 4336.5, 4355.75, 4371.25, 4355.5, 4335.75, 4304, 4302, 4358.5, 4375.75, 4419, 4419.75, 4430.5, 4407.75, 4414.25, 4423.25, 4399.25, 4366.5, 4304.25, 4280.75, 4290.5, 4273.5, 4205, 4185, 4197.5, 4215, 4264.75, 4339.75, 4391.75, 4389.5, 4403.25, 4407.75, 4413, 4435.5, 4436.75, 4524.25, 4541.25, 4529.5, 4539.5, 4571, 4567, 4580.5, 4572.75, 4574, 4570, 4577.25, 4597, 4579.5, 4607.75, 4604.5, 4585.5, 4598.5, 4596, 4613.75, 4627.25, 4649.75, 4711.75, 4739.25, 4736.5, 4802.25, 4821.5, 4830.75, 4798.25, 4821.75, 4834.5, 4836.5, 4841.5, 4841, 4828, 4790.75, 4766.5, 4760.25, 4803.25, 4804]

Next Value Prediction: 47618.481712062254

... the next value in the series should have been in the neighborhood of 4828.

Is this project still being supported?