Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and Their Effect on Portfolio Execution

Over the past decade, there has been a significant rise in assets managed under passive and systematic strategies. Such strategies hold and trade portfolios in a coordinated manner, often concentrating trading around the end of the trading session. Simultaneously, there has been a rise in activity from market participants that act as liquidity providers, themselves trading along portfolio directions. In “Cross-Sectional Variation of Intraday Liquidity, cross-impact, and Their Effect on Portfolio Execution,” Min, Maglaras, and Moallemi investigate the implications of these two observations, specifically exploring how the phenomenon of portfolio liquidity provision leads to cross-security impact and influences the optimal execution schedules of risk-neutral traders that seek to minimize their expected execution costs. They show that the optimized schedules deviate from the naïve approach that trades each security separately and instead, couple the trading intensity across stocks so as to benefit from the liquidity provided along attractive portfolio trading directions. Empirical analysis demonstrates that coupled optimized schedules could lower costs by as much as 15% relative to the naïve approach.

Drill bit deterioration estimation with the Random Forest Regressor

Blastholes drilling performance is crucial for ensuring good performance of the whole excavation process, the correctness of which demands ‘healthy’ drill bit and appropriate behavior of an operator. Given the large volume of non-linear parameters describing the process, it appears reasonable to employ supervised learning methods to obtain drilling performance insights. Random Forest Regressor model has been trained on the dataset corresponding to correct performance of blastholes drilling and its hyperparameters have been tuned to obtain the highest possible accuracy. It has been later tested on three datasets corresponding to a good performance of drilling, and two cases of its non-optimal execution. Estimation errors are proposed to be used as bit technical state condition indicators (or more generally - process performance indicators). Root Mean Squared Error has been proven to differ significantly when compared estimation based on datasets corresponding to execution of drilling with ‘healthy’ drill bit, and its execution with worn-off one, however, it has been not sufficient to distinguish non-optimal drilling when additional feed pressure has been exerted by an operator to compensate the reduced pace of drilling. It has been, however, possible when the mean of absolute estimation errors has been used.

DISCRETE-TIME OPTIMAL EXECUTION UNDER A GENERALIZED PRICE IMPACT MODEL WITH MARKOVIAN EXOGENOUS ORDERS

This paper examines a discrete-time optimal execution problem with generalized price impact. Our main objective is to investigate the effect of price impact caused by aggregate random trade orders posed by small traders on the optimal execution strategy when orders of the small traders have a Markovian dependence. Our problem is formulated as a Markov decision process with state variables which include the last small traders’ aggregate orders. Over a finite horizon, a large trader with Constant Absolute Risk Aversion (CARA) von Neumann–Morgenstern (vN-M) utility function maximizes the expected utility from the final wealth. By applying the backward induction method of dynamic programming, we characterize the optimal execution strategy and optimal value function and conclude that the optimal execution strategy is a time-dependent affine function of three state variables. Moreover, numerical analysis prevails that the optimal execution strategy admits a “statistical arbitrage” via a round-trip trading, although our model considers a linear permanent price impact. The result differs from the previous prevailing one that a linear permanent price impact model precludes any price manipulation or arbitrage. Thus, considering a price impact caused by small traders’ orders with a Markovian dependence is significant.

Modelling Crop Insurance Based on Weather Index Using The Homotopy Analysis for American Put Option

The crop insurance in Indonesia (AUTP) is much focused on the area impacted by flood, drought, and pest attack. The complication of the procedure to claim the loss must follow several conditions. The different approaches in the insurance sector, using weather index can be taken into consideration to produce a variety of insurance products. This insurance product used the American put option with the primary asset is the rainfall and the cumulative rainfall to exercise the claim, considering the optimal execution limit. The homotopic analysis is used to determine the valuation of the American put option, which also becomes the insurance premium. The case study is focused on areas experiencing a drought so that insurance claims can be exercise when the rainfall index value is below a predetermined limit. Considering the normality of the rainfall data, the calculation of insurance premium was done for the first growing season. The insurance premium is varies based on the optimal execution limit, while the calculation of profit is based on the optimum limit exercise and the minimum rainfall for the growing season, and its different depended on insurance claim acceptance limits.

Optimal Execution considering Trading Signal and Execution Risk Simultaneously

In this paper, we study the optimal execution problem by considering the trading signal and the transaction risk simultaneously. We propose an optimal execution problem by taking into account the trading signal and the execution risk with the associated decay kernel function and the transient price impact function being of generalized forms. In particular, we solve the stochastic optimal control problems under the assumptions that the decay kernel function is the Dirac function and the transient price function is a linear function. We give the optimal executing strategies in state-feedback form and the Hamilton‐Jacobi‐Bellman equations that the corresponding value functions satisfy in the cases of a constant execution risk and a linear execution risk. We also demonstrate that our results can recover previous results when the process of the trading signal degenerates.