An empirical behavioral order‑driven model with price limit rules

We propose an empirical behavioral order-driven(EBOD)model with price limit rules,which consists of an order placement process and an order cancellation process.All the ingredients of the model are determined based on the empirical microscopic regularities in the order flows of stocks traded on the Shenzhen Stock Exchange.The model can reproduce the main stylized facts in real markets.Computational experiments unveil that asymmetric setting of price limits will cause the stock price to diverge exponentially when the up price limit is higher than the down price limit and to vanish vice versa.We also find that asymmetric price limits have little influence on the correlation structure of the return series and the volatility series,but cause remarkable changes in the average returns and the tail exponents of returns.Our EBOD model provides a suitable computational experiment platform for academics,market participants,and policy makers.

Seat inventory control methods for Chinese passenger railways

Railway seat inventory control strategies play a crucial role in the growth of profit and train load factor. The railway passenger seat inventory control problem in China was addressed. Chinese passenger railway operation features and seat inventory control practice were analyzed firstly. A dynamic demand forecasting method was introduced to forecast the coming demand in a ticket booking period. By clustering, passengers' historical ticket bookings were used to forecast the demand to come in a ticket booking period with least squares support vector machine. Three seat inventory control methods: non-nested booking limits, nested booking limits and bid-price control, were modeled under a single-fare class. Different seat inventory control methods were compared with the same demand based on ticket booking data of Train T15 from Beijing West to Guangzhou. The result shows that the dynamic non-nested booking limits control method performs the best, which gives railway operators evidence to adjust the remaining capacity in a ticket booking period.

Order Execution Probability and Order Queue in Limit Order Markets

The shaping of a limit order book illustrates the dynamics of the trading process,the changing pattern of the execution probability of limit orders therefore plays an important role.This paper presents a computable execution probability model for limit order market,as well as a numerical example that intuitively characterizes the changing pattern of the execution probability.The common effects of the lengths of both buy and sell queues on the execution probability are explored.In the limit book,the cumulative probability of limit orders is introduced as a crucial index of market depth to describe the shaping process which brings new insights into the structure of the order placement decision.

Analysis of Trading Volume Behavior Under Continuous Double Auction Mechanism in Limit Order Markets

In this paper, we develop a theoretical model to describe the dynamics of the trading volume under continuous double auction mechanism in limit order markets. We examine the formation process and statistical properties （including the mean, wriance, and realized value） of the buy side cumulative trading volume, sell side cumulative trading volume and total cumulative volume under continuous double auction mechanism by means of mathematical modeling based on Poisson process of order flows, and do some corresponding numerical simulations and comparative statics on the factors that would influence these three volumes aforementioned. The results indicate that these three volumes are all influenced by the factors including the arrival rate of orders, demands of each order, proportional structure between buy and sell orders, executed probability and time interval we examined. And our established theoretical model can well capture the dynamics of these three volumes under continuous double auction mechanism in limit order markets when all these factors interact.

Explicit Solution for Constrained Optimal Execution Problem with General Correlated Market Depth

This work studies the constrained optimal execution problem with a random market depth in the limit order market.Motivated from the real trading activities,our execution model considers the execution bounds and allows the random market depth to be statistically correlated in different periods.Usually,it is difficult to achieve the analytical solution for this class of constrained dynamic decision problem.Thanks to the special structure of this model,by applying the proposed state separation theorem and dynamic programming,we successfully obtain the analytical execution policy.The revealed policy is of feedback nature.Examples are provided to illustrate our solution methods.Simulation results demonstrate the advantages of our model comparing with the classical execution policy.