Dimension of Matrices

[letian-w]

In cell 7 of the notebook, the estimate function is defined as the following.

def estimate(T):

    # LINES OMMITED

    Q_counts=np.resize(np.array(no_move_counts[0:(n_imb*n_imb)]),(n_imb,n_imb))
    # loop over all spreads and add block matrices
    for i in range(1,n_spread):
        Qi=np.resize(np.array(no_move_counts[(i*n_imb*n_imb):(i+1)*(n_imb*n_imb)]),(n_imb,n_imb))
        Q_counts=block_diag(Q_counts,Qi)

    # LINES OMMITED

    return G1,B,Q,Q2,R1,R2,K

Should this be n_imb*n_spread instead of n_imb*n_imb? In the paper, matrix Q is of dimension nm by nm, where n and m are discretized grids of I and S respectively.

[sstoikov]

In the end of the loop the Q matrix is of size n_imbn_spread by n_imbn_spread

It is made up of n_spread blocks of n_imb by n_imb matrices

On Wed, Sep 15, 2021 at 12:24 AM Letian Wang @.***> wrote:

In cell 7 of the notebook https://github.com/sstoikov/microprice/blob/master/Microprice%20-%20Big%20Data%20Conference.ipynb, the estimate function is defined as the following.

def estimate(T):

# LINES OMMITED

Q_counts=np.resize(np.array(no_move_counts[0:(n_imb*n_imb)]),(n_imb,n_imb))
# loop over all spreads and add block matrices
for i in range(1,n_spread):
    Qi=np.resize(np.array(no_move_counts[(i*n_imb*n_imb):(i+1)*(n_imb*n_imb)]),(n_imb,n_imb))
    Q_counts=block_diag(Q_counts,Qi)

# LINES OMMITED

return G1,B,Q,Q2,R1,R2,K

Should this be n_imbn_spread instead of n_imbn_imb? In the paper https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2970694, matrix Q is of dimension nm by nm, where n and m are discretized grids of I and S respectively.

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[letian-w]

Got it, thank you @sstoikov. That was my oversight.