Portfolio Optimization, Quantitative Finance, Python Programming, Convex Optimization, Data Science.
portfolio belongs to class 5. Backtesting result (initial capital is $100) notional = 100 cumprod_mat = (ret_vec + 1).iloc[::-1].cumprod().iloc[::-1] # for agggressively weighted (advice from MPFA :) fingercrossed my friend) w_agg = np.array([0.8, 0, 0, 0, 0, 0, 0, 0.2, 0, 0, 0]) agg_cumprod =