Triangle Momentum

<p>This research investigates the breakout of security prices from periods of sideways drift known as Triangles. Contributions are made to the existing literature by considering returns conditionally based on Triangles in particular terms of how momentum traders time positions, and by then using alternative statistical methods to more clearly show results. Returns are constructed by scanning for Triangle events, and determining simulated trader returns from predetermined price levels. These are compared with a Naive model consisting of randomly sampled events of comparable measure. Modelling of momentum results is achieved using a marked point Poisson process based approach, used to compare arrival times and profit/losses. These results are confirmed using a set of 10 day return heuristics using bootstrapping to define confidence intervals. Using these methods applied to CRSP US equity data inclusive from years 1960 to 2017, US equities show a consistent but weak predictable return contribution after Triangle events occur; however, the effect has decreased over time, presumably as the market becomes more efficient. While these observed short term momentum changes in price have likely been compensated to a degree by risk, they do show that such patterns have contained forecastable information about US equities. This shows that prices have likely weakly been affected by past prices, but that currently the effect has reduced to the point that it is of negligible size as of 2017.</p>

Triangle Momentum

<p>This research investigates the breakout of security prices from periods of sideways drift known as Triangles. Contributions are made to the existing literature by considering returns conditionally based on Triangles in particular terms of how momentum traders time positions, and by then using alternative statistical methods to more clearly show results. Returns are constructed by scanning for Triangle events, and determining simulated trader returns from predetermined price levels. These are compared with a Naive model consisting of randomly sampled events of comparable measure. Modelling of momentum results is achieved using a marked point Poisson process based approach, used to compare arrival times and profit/losses. These results are confirmed using a set of 10 day return heuristics using bootstrapping to define confidence intervals. Using these methods applied to CRSP US equity data inclusive from years 1960 to 2017, US equities show a consistent but weak predictable return contribution after Triangle events occur; however, the effect has decreased over time, presumably as the market becomes more efficient. While these observed short term momentum changes in price have likely been compensated to a degree by risk, they do show that such patterns have contained forecastable information about US equities. This shows that prices have likely weakly been affected by past prices, but that currently the effect has reduced to the point that it is of negligible size as of 2017.</p>

Marked point processes and intensity ratios for limit order book modeling

This paper extends the analysis of Muni Toke and Yoshida (2020) to the case of marked point processes. We consider multiple marked point processes with intensities defined by three multiplicative components, namely a common baseline intensity, a state-dependent component specific to each process, and a state-dependent component specific to each mark within each process. We show that for specific mark distributions, this model is a combination of the ratio models defined in Muni Toke and Yoshida (2020). We prove convergence results for the quasi-maximum and quasi-Bayesian likelihood estimators of this model and provide numerical illustrations of the asymptotic variances. We use these ratio processes to model transactions occurring in a limit order book. Model flexibility allows us to investigate both state-dependency (emphasizing the role of imbalance and spread as significant signals) and clustering. Calibration, model selection and prediction results are reported for high-frequency trading data on multiple stocks traded on Euronext Paris. We show that the marked ratio model outperforms other intensity-based methods (such as “pure” Hawkes-based methods) in predicting the sign and aggressiveness of market orders on financial markets.

GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY

Elaboration of the method of creating a web-GIS of Polish burials at the Baikove Cemetery in Kyiv. Achieving this goal involves the following tasks: to develop the structure of the geographic information system, its framework and to fill the file database. For realization of the set tasks the technological scheme consisting of 12 stages of work is offered. The first stage involved the collection of cartographic and descriptive data on the territory of the object of study, as well as the search for possible registers of Polish burials within the object under study. In the second stage, field surveys were performed to determine the coordinates of each grave of the Polish burials at the Baikove Cemetery using a GIS tablet with an RTK antenna LT700H (accuracy up to 0.30 m). The total number of coordinated points was 565, which were concentrated in 7 sections of the cemetery. The third stage included the coordination of reference points and the binding of this support in the GIS MapInfo environment of the fragment of the topographic plan of Kyiv on a scale of 1: 2000 to the territory of the Baikove Cemetery. There were a total of 11 landmarks. The maximum binding error is 0.2 m. In the fourth stage, all point objects were displayed according to their coordinates on the basis of the map and the corresponding symbols were selected. The next step was to develop and populate a relational database for point objects. The database contained the following columns: grave number, name and surname of the buried person, grave coordinates and hyperlinks to burial information in the file database. Next, all map layers were exported to html format, and the point object layer was exported to kml format using a universal translator, which allowed to view burial data in GoogleEarth. At the eighth stage of the technological scheme the structure of layouts of each html-page of the created online GIS was developed. All map data had hyperlinks to the selected AOI objects. In the case of the Baikove Cemetery scheme, plots with Polish burials were marked. Clicking on them opened a topographic plan with marked point objects of burials. In turn, when you click on them, information about the burial appeared from the file database. At the tenth stage, 5 sheets of topographic plans with burials were generated. One sheet of scale 1: 2000 and four sheets of scale 1: 500, for better "spreading" and initialization of burials. The eleventh stage is devoted to the creation and filling of a file database on Polish burials. This database contained the following structure: photo of the burial, coordinates, surname and name, years of life, additional photographs (if available), sex of the buried person, interpreted inscription on the tombstone, as well as, if possible, detailed information and belonging of the buried person to a certain profession, its outstanding achievements and accomplishments. At the last stage, the hyperlinks of the transition between the pages were configured and the system was tested. The scientific novelty lies in the development of the concept of joint use of various applications of geoinformation and non-geoinformation purposes. The technological scheme of creation of WEB-GIS of Polish burials of the Baikove Cemetery in Kyiv is offered. Implemented geographic information system is designed for inventory of burials, analysis of the condition of tombstones and their spatial location in the cemetery. In addition, the created GIS can be used for tourism purposes and in the study of historical figures of Polish origin.

Analysis of remote sensing images by methods of convolutional neural networks and marked random point fields

The methodology of remote sensing image analysis for detection of dependences in the process of development of biological species is proposed. Classification methods based on convolutional networks are applied to a set of fragments of the input image. In order to increase the accuracy of classification by increasing the training and test samples, an original method of data augmentation is proposed. For a series of images of one part of the landscape, the fragments of images are classified by their numbers, which coincide with the numbers of the previously classified image of the training and test samples which are created manually. This approach has improved the accuracy of classification compared to known methods of data augmentation. Numerous studies of various convolutional neural networks have shown the similarity of the classification results of the remote sensing images fragments with increasing learning time with the complication of the network structure. A set of image fragment centers of a particular class is considered as random point configuration, the class labels are used as a mark for every point. Marked point field is considered as consisting of several sub-point fields in each of which all points have the same qualitative marks. We perform the analysis of the bivariate point pattern to reveal relationships between points of different types, using the characteristics of marked random point fields. Such relationships can characterize dependences and relative degrees of dominance. A series of remote sensing images are studied to identify the relationships between point configurations that describe different classes to monitor their development.

Ultrasound Image Features under Decomposition Algorithm to Analyze the Nursing Intervention on Patients with Colon Polyps Undergoing Endoscopic Resection

Based on the ultrasonic imaging and endoscopic resection of the intelligent segmentation algorithm, this study is aimed at exploring whether nursing intervention can promote the good recovery of patients with colon polyps, hoping to find a new method for clinical treatment of the colon polyps. Patients with colon polyps were divided into an experimental group (fine nursing) and a control group (general nursing). The colonoscopy polyp ultrasound image was preprocessing to select the seed points and background points. The random walk decomposition algorithm was applied to calculate the probability of each marked point, and then, the marked image was outputted. The accuracy of the intelligent segmentation algorithm was 81%. The incidence of complications in the experimental group was 4.83%, which was lower than 16.66% in the control group, and the difference was statistically obvious ( P < 0.05 ). Perioperative refined nursing intervention for colon polyp patients undergoing endoscopic electrosurgical resection can decrease postoperative adverse reactions; reduce postoperative mucosal perforation, blood in the stool, abdominal pain, and small bleeding; lower the incidence of postoperative complications; and allow patients to recover quickly, enhancing the life comfort of patient.

A Non-Parametric Method for Estimating Rates of Intracellular Ice Formation Due to Independent Competing Mechanisms

The probability of intracellular ice formation (IIF) has conventionally been analyzed by counting the cumulative number of IIF events observed in a cell population, and normalizing to the total cell count to estimate the cumulative IIF probability. However, this method is invalid when attempting to distinguish among multiple, independent IIF mechanisms, because of confounding effects due to competition for a finite pool of unfrozen cells. Therefore, an alternative approach for analyzing IIF data is proposed, based on treating IIF as a marked point process, in which the points represent IIF events and the marks represent different mechanisms of IIF. Using the new method, it is possible to quantify the kinetics associated with any IIF mechanism for which corresponding events can be marked (experimentally distinguished from competing IIF mechanisms). The proposed approach is non-parametric, making possible characterization of IIF mechanisms that have not yet been fully elucidated. The new analytical approach was compared to the conventional method of IIF analysis using data from a simulated experiment, demonstrating that the new method yielded superior estimates of the cumulative distribution function of IIF times when two competing mechanisms of IIF were active. The proposed algorithm was also applied to cryomicroscopic IIF observations in adherent endothelial cells, yielding rate estimates for two concurrent IIF processes. Furthermore, a proof is presented to demonstrate that when the proposed data analysis algorithm is applied to IIF data from a single mechanism of IIF, the results are equivalent to those obtained by the conventional method of analysis.

Design as a Marked Point Process

Although AI systems which support composition using predictive text are well established there are no analogous technologies for mechanical design. Motivated by the vision of a predictive system that interactively suggests features to designer, this paper describes the theory, implementation and assessment of an intelligent system that learns from a family of previous designs and generates inferences using a form of spatial statistics. The formalism presented, models 3D design activity as a ‘Marked Point Process’ that enables the probability of specific features being added at a particular locations to be calculated. Because the resulting probabilities are updated every time a new feature is added the predictions will become more accurate as a design develops. This approach allows the cursor position on a CAD model to implicitly define a spatial focus for every query made to the statistical model. The authors describe the mathematics underlying a statistical model that amalgamates the frequency of occurrence of the features in the existing designs of a product family. Having established the theoretical foundations of the work, a generic six step implementation process is described. This process is then illustrated for circular hole features using a statistical model generated from a dataset of hydraulic valves. The paper describes how the positions of each design's extracted hole features can be homogenized through rotation and scaling. Results suggest that within generic part families (i.e. designs with common structure) a marked point process can be effective at predicting incremental steps in the development of new designs.

ABELIAN CYCLES IN THE HOMOLOGY OF THE TORELLI GROUP

In the early 1980s, Johnson defined a homomorphism $\mathcal {I}_{g}^1\to \bigwedge ^3 H_1\left (S_{g},\mathbb {Z}\right )$ , where $\mathcal {I}_{g}^1$ is the Torelli group of a closed, connected, and oriented surface of genus g with a boundary component and $S_g$ is the corresponding surface without a boundary component. This is known as the Johnson homomorphism. We study the map induced by the Johnson homomorphism on rational homology groups and apply it to abelian cycles determined by disjoint bounding-pair maps, in order to compute a large quotient of $H_n\left (\mathcal {I}_{g}^1,\mathbb {Q}\right )$ in the stable range. This also implies an analogous result for the stable rational homology of the Torelli group $\mathcal {I}_{g,1}$ of a surface with a marked point instead of a boundary component. Further, we investigate how much of the image of this map is generated by images of such cycles and use this to prove that in the pointed case, they generate a proper subrepresentation of $H_n\left (\mathcal {I}_{g,1}\right )$ for $n\ge 2$ and g large enough.