Sun, Yuemeng. 2011. Price Manipulation with Dark Pools And Multi-Product Separation In
Inventory Hedging. Doctoral Dissertation, Cornell University.
This dissertation addresses
two different problems within mathematical finance: an optimal execution
problem with dark pools using a market impact model, and multi-product
separation with financial hedging for inventory management. In the first part
of the dissertation we consider an optimal liquidation problem in which a large
investor can sell on a traditional exchange or in a so-called dark pool. Dark
pools differ from traditional exchanges in that the orders placed in it
generate little to no price impact on the market price of the asset. Within the
framework of the Almgren-Chriss market impact model, we study an extended model
which includes the cross-impact between the two venues. By analyzing the
optimal execution strategy, we identify those model specifications for which
the corresponding order execution problem is stable in the sense that are no
price manipulation strategies which can be beneficial. In the second part of
the dissertation, we propose financial hedging tools for inventory management.
Based on a framework for hedging against the correlation of operational returns
with financial market returns, we consider the general problem of optimizing
simultaneously over both the operational policy and the hedging policy of the
corporation. Our main goal is to achieve a separation result such that for a
corporation with multiple products and inventory departments, the inventory
decisions of each department can be made independently of the other
departments' decisions. We focus initially on a single-period, multi-product
hedging problem for inventory management, and model an economy experiencing
monetary inflation. We use the Heath-Jarrow- Morton model to represent the
financial market. We then extend the model to consider multiple periods and
more general market models. In both cases, we prove a separation result for
inventory management that allows each inventory department to make decisions
independently. In particular, the separation result for the multi-period
problem is a global separation in the sense that no interaction needs to be
considered among products in intermediate time periods. In addition, we propose
a dynamic programming simplification of the multi-period single-item inventory
problem which further simplifies the computation by reducing the dimension of
the state space.
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