In most OTC markets, a small number of market makers provide liquidity to clients from the buy side . More precisely,  they set prices at which they agree to buy and sell the assets they cover . Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money out of their bid-ask spread while mitigating the risk associated with holding inventory in a volatile market. Many market making models have been proposed in the academic literature, most of them dealing with single-asset market making whereas market makers are usually in charge of a long list of assets. The rare models tackling multi-asset market making suffer however from the curse of dimensionality when it comes to the numerical approximation of the optimal quotes. The goal of this paper is to propose a dimensionality reduction technique to address multi-asset market making with grid methods . Moreover, we generalize existing market making models by the addition of an important feature for OTC markets: the variability of transaction sizes and the possibility for the market maker to answer different prices to requests with different sizes.
In most OTC markets, a small number of market makers provide liquidity to other market participants . More precisely, for a list of assets, they set prices at which they agree to buy and sell . Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while mitigating the risk associated with holding inventory in a volatile market. Many market making models have been proposed in the academic literature, most of them dealing with single-asset market making whereas market makers are usually in charge of a long list of assets. The rare models tackling multi-asset market making suffer however from the curse of dimensionality when it comes to the numerical approximation of the optimal quotes. The goal of this paper is to propose a dimensionality reduction technique to address multi-asset market making by using a factor model . Moreover, we generalize existing market making models by the addition of an important feature : the existence of different transaction sizes and the possibility for the market makers in OTC markets to answer different prices to requests with different sizes.
R
clients from the buy side
other market participants
A
for a list of assets,
D
the assets they cover
D
out of their bid-ask spread
R
with grid methods
by using a factor model
R
for OTC markets: the variability of
: the existence of different
R
maker
makers in OTC markets