I'm trying to convert a Python HMM code into Matlab (warning - I'm just learning about HMM models and probably missing something easy).
The Python code seeds itself uses HMMlearn as its model:
os.environ['PYTHONHASHSEED'] = str(seed)
#Tweaking the fonts, etc.
import matplotlib.pyplot as plt
from matplotlib import rcParams
I'm getting tripped up as the Python code simply uses a single column array of stock returns as its input:
model = hmm.GaussianHMM(n_components=2, covariance_type="diag")
X_train = df_train['returns'].to_numpy().reshape(-1, 1)
How can I do this in Matlab? The transition matrix is simply a 2x2.
Below is my sample attempt in Matlab:
stock_returns = [0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01];
mu = mean(stock_returns);
sigma = std(stock_returns);
transMatGuess = [0.95, 0.05; 0.05, 0.95];
emissionGuess = struct('mu', mu, 'Sigma', sigma);
hmmModel = struct('StartProb', [0.5, 0.5], 'TransProb', transMatGuess, 'Emissions', emissionGuess);
[trained_hmm, logL] = hmmtrain(hmmModel, stock_returns);
I am having absolutely no luck getting this to run. Would someone please help me get my model on the right path? Thanks in advance!
