Measuring the Efficiency of the Intraday Forex Market with a Universal Data Compression Algorithm

Universal compression algorithms can detect recurring patterns in any type of temporal data—including financial data—for the purpose of compression. The universal algorithms actually find a model of the data that can be used for either compression or prediction. We present a universal Variable Order Markov (VOM) model and use it to test the weak form of the Efficient Market Hypothesis (EMH). The EMH is tested for 12 pairs of international intra-day currency exchange rates for one year series of 1, 5, 10, 15, 20, 25 and 30 min. Statistically significant compression is detected in all the time-series and the high frequency series are also predictable above random. However, the predictability of the model is not sufficient to generate a profitable trading strategy, thus, Forex market turns out to be efficient, at least most of the time.      

虚拟股市的建模与仿真

该文概述了复杂系统的研究状况,以股票市场为研究对象,用Multi-Agent的方法构建了一个虚拟股票市场,进行股市的仿真,以期对复杂系统的运动机理以及系统内部的个体和子系统之间的相互影响,策动进行深入研究,并取得了一些有意义的结果。     

Using Decision Trees to Construct a Practical Parser

This paper describes a novel and practical Japanese parser that uses decision trees. First, we construct a single decision tree to estimate modification probabilities; how one phrase tends to modify another. Next, we introduce a boosting algorithm in which several decision trees are constructed and then combined for probability estimation. The constructed parsers are evaluated using the EDR Japanese annotated corpus. The single-tree method significantly outperforms the conventional Japanese stochastic methods. Moreover, the boosted version of the parser is shown to have great advantages; (1) a better parsing accuracy than its single-tree counterpart for any amount of training data and (2) no over-fitting to data for various iterations. The presented parser, the first non-English stochastic parser with practical performance, should tighten the coupling between natural language processing and machine learning.     

一种利用Hausdorff距离的高效目标搜索算法

为了快速高效地进行目标搜索，提出了一种在仿射变换条件下，利用Hausdroff距离进行目标搜索的高效算法。此算法是在一种新的距离变换形式——“最小正方盒距离变换”的基础上进行的。实验结果表明，与现有算法相比，该算法在不影响搜索成功率和目标定位精度的情况下，还可以显著地缩短搜索时间。为验证该算法的有效性，将该算法与Rucklidge算法进行了对比实验，结果表明，该算法明显优于Rucklidge提出的快速目标搜索算法。     

Using hash tables to manage the time-storage complexity in a point location problem: Application to explicit model predictive control

The online computational burden of linear model predictive control (MPC) can be moved offline by using multi-parametric programming, so-called explicit MPC. The solution to the explicit MPC problem is a piecewise affine (PWA) state feedback function defined over a polyhedral subdivision of the set of feasible states. The online evaluation of such a control law needs to determine the polyhedral region in which the current state lies. This procedure is called point location; its computational complexity is challenging, and determines the minimum possible sampling time of the system. A new flexible algorithm is proposed which enables the designer to trade off between time and storage complexities. Utilizing the concept of hash tables and the associated hash functions, the proposed method solves an aggregated point location problem that overcomes prohibitive complexity growth with the number of polyhedral regions, while the storage–processing trade-off can be optimized via scaling parameters. The flexibility and power of this approach is supported by several numerical examples.     

运用Chi2算法的一种变形简化决策树归纳的实例表示空间

决策树归纳的两个重要阶段是数据表示空间的简化和决策树的生成。在将训练集的不一致率控制在某一阈值的前提下,减少实例的属性个数和各个属性的取值个数保证了决策树方法的可行性和有效性。本文在Chi2算法的基础上运用它的一种变形进行属性取值离散化和属性筛选,然后运用算术运算符合并取值个数为2或3的相邻属性。在此基础上生
成的决策树具有良好的准确性。实验数据采用的是一个保险公司捐献的数据集。     

Existence of the l-th moment of a solution to a stochastic functional-differential equation with the entire prehistory

The definition of a strong solution to a stochastic differential-functional equation with the entire prehistory is given, and basic inequalities required for obtaining existence and uniqueness theorems are proved. Global existence and uniqueness theorems are proved. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 142–151, July–August 2008.     

图像定尺在钢铁板坯二次切割中的应用

简单介绍利用摄像头进行图像采集后，通过对图像信号进行处理．实现非接触式板坯长度测量，并依据测量结果，驱动切割设备自动定住，实现连铸钢坯的高精度自动定尺切割。     

Using a Two‐Level Structure to Manage the Point Location Problem in Explicit Model Predictive Control

The problem of determining the state region in which the current state point lies is referred to as the point location problem in the explicit model predictive control. In this paper, a two‐level structure to store the state regions is proposed and two efficient methods for solving the point‐location problem are developed; these are the two‐level grid (TLG) method and the grid‐BST method. The TLG method uses a tow‐level hash table. Before building the two‐level structure, the synonymy partitions are merged to reduce the memory storage demand. By setting each parameter in a triplet, the two‐level hash table can reach its optimal state and balance the complexity among the memory storage, reprocessing (offline computation) and the online computation. The grid‐BST method uses hash table as the first‐level structure and builds the binary search tree in the hash grid in which there are many partitions. This two‐level structure reduces reprocessing time significantly especially when the state partitions and the piecewise affine control laws (PWA control laws) are in a large number. Using the hyperplane (HP) as the node (not leaf node) of the tree, the method only stores all the different PWA control laws instead of the state partitions. The two proposed methods overcome the quick complexity growth when the number of polyhedral partitions increases and 2 numerical examples show the advantages of the proposed two methods.