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Clustering stocks with similar exposures to risk factors


I am trying to group stocks based on their exposures to common risk factors. I first identify market wide risk factors and then want to cluster stocks which move similarly w.r.t risk factors using KMeans algorithm. My code is as below:

def get_cluster(stocks, returns, riskfactors):  
    betas = smapi.OLS(returns, smapi.add_constant(riskfactors)).fit().params.T[:, 1:]  
    betas = preprocessing.scale(betas)  
    labels = KMeans(n_clusters=10).fit_predict(betas)  
    clusters = {}  
    for i, stock in enumerate(stocks):  
        label = labels[i]  
        if label not in clusters:  
            clusters[label] = []  
   return clusters  

Would someone with clustering experience comment if what I am doing makes sense?

Best regards,

5 responses

Hi @Pravin, I've been working on stock clustering for a couple months. I'll be making a post on it in the next couple weeks. I'll share the link here when I do.


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@Jonathan. Thanks, I look forward to your link and approach.

Best regards,

Hi @Pravin, As promised, my clustering post is here.

Thanks Jonathan. This is awesome.

Pravin -

Here's another example.