The document discusses research analyzing high frequency trading data from 29 Russian stocks over 6 months in 2010. 369 shock events were identified, where the price changed significantly within a short time period, on average about 13 events per stock. The research uses different filtering techniques at the tick, minute, and hour timescales to identify these shocks. The goal is to better understand market microstructure and dynamics around periods of large price changes.
Extent 2013 Obninsk Test Tools for Trading Systems: Evolution Theoryextentconf Tsoy
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Anastasia Matveeva, QA Manager, Exactpro Systems
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Extent 2013 Obninsk Test Tools for Trading Systems: Evolution Theoryextentconf Tsoy
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Anastasia Matveeva, QA Manager, Exactpro Systems
Extent 2013 Obninsk Trading Systems: Testing at the Confluence of FT & NFTextentconf Tsoy
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Ivan Bobrov, HFT Analyst, Exactpro Systems
Millennium Surveillance™ – Achieving Excellence
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Accelerated life testing (ALT) is widely used to expedite failures of a product in a short time period for predicting the product’s reliability under normal operating conditions. The resulting ALT data are often characterized by a probability distribution, such as Weibull, Lognormal, Gamma distribution, along with a life-stress relationship. However, if the selected failure time distribution is not adequate in describing the ALT data, the resulting reliability prediction would be misleading. In this talk, we provide a generic method for modeling ALT data which will assist engineers in dealing with a variety of failure time distributions. The method uses Erlang-Coxian (EC) distributions, which belong to a particular subset of phase-type (PH) distributions, to approximate the underlying failure time distributions arbitrarily closely. To estimate the parameters of such an EC-based ALT model, two statistical inference approaches are proposed. First, a mathematical programming approach is formulated to simultaneously match the moments of the EC-based ALT model to the ALT data collected at all test stress levels. This approach resolves the feasibility issue of the method of moments. In addition, the maximum likelihood estimation (MLE) approach is proposed to handle ALT data with type-I censoring. Numerical examples are provided to illustrate the capability of the generic method in modeling ALT data.
This document is the distribution material on "Code-Saturne beginner seminar". (November 1 2014 "OpenCAE Study Meeting @ Kansai")
http://ofbkansai.sakura.ne.jp/
Optimising Autonomous Robot Swarm Parameters for Stable Formation DesignDaniel H. Stolfi
Autonomous robot swarm systems allow to address many inherent limitations of single robot systems, such as scalability and reliability. As a consequence, these have found their way into numerous applications including in the space and aerospace domains like swarm-based asteroid observation or counter-drone systems. However, achieving stable formations around a point of interest using different number of robots and diverse initial conditions can be challenging. In this article we propose a novel method for autonomous robots swarms self-organisation solely relying on their relative position (angle and distance). This work focuses on an evolutionary optimisation approach to calculate the parameters of the swarm, e.g. inter-robot distance, to achieve a reliable formation under different initial conditions. Experiments are conducted using realistic simulations and considering four case studies. The results observed after testing the optimal configurations on 72 unseen scenarios per case study showed the high robustness of our proposal since the desired formation was always achieved. The ability of self-organise around a point of interest maintaining a predefined fixed distance was also validated using real robots.
https://doi.org/10.1145/3512290.3528709
Introduction to behavior based recommendation systemKimikazu Kato
Material presented at Tokyo Web Mining Meetup, March 26, 2016.
The source code is here:
https://github.com/hamukazu/tokyo.webmining.2016-03-26
東京ウェブマイニング(2016年3月27)の発表資料です。すべて英語です。
Millennium Surveillance™ – Achieving Excellence
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11 November 2015
Trading Technology Trends & Quality Assurance Conference in St. Petersburg
Tradecope - Low-Latency Solution for Algorithmic and High Frequency Trading
Milan Dvorak, Netcope Technologies
11 November 2015
Trading Technology Trends & Quality Assurance Conference in St. Petersburg
EXTENT-2015: A Test Harness for Algo Trading Systems Iosif Itkin
A Test Harness for Algo Trading Systems
Victoria Leonchik, Exactpro
11 November 2015
Trading Technology Trends & Quality Assurance Conference in St. Petersburg
Reconciliation Testing Aspects
Elena Moiseeva, QA, Exactpro
11 November 2015
Trading Technology Trends & Quality Assurance Conference in St. Petersburg
Accelerated life testing (ALT) is widely used to expedite failures of a product in a short time period for predicting the product’s reliability under normal operating conditions. The resulting ALT data are often characterized by a probability distribution, such as Weibull, Lognormal, Gamma distribution, along with a life-stress relationship. However, if the selected failure time distribution is not adequate in describing the ALT data, the resulting reliability prediction would be misleading. In this talk, we provide a generic method for modeling ALT data which will assist engineers in dealing with a variety of failure time distributions. The method uses Erlang-Coxian (EC) distributions, which belong to a particular subset of phase-type (PH) distributions, to approximate the underlying failure time distributions arbitrarily closely. To estimate the parameters of such an EC-based ALT model, two statistical inference approaches are proposed. First, a mathematical programming approach is formulated to simultaneously match the moments of the EC-based ALT model to the ALT data collected at all test stress levels. This approach resolves the feasibility issue of the method of moments. In addition, the maximum likelihood estimation (MLE) approach is proposed to handle ALT data with type-I censoring. Numerical examples are provided to illustrate the capability of the generic method in modeling ALT data.
This document is the distribution material on "Code-Saturne beginner seminar". (November 1 2014 "OpenCAE Study Meeting @ Kansai")
http://ofbkansai.sakura.ne.jp/
Optimising Autonomous Robot Swarm Parameters for Stable Formation DesignDaniel H. Stolfi
Autonomous robot swarm systems allow to address many inherent limitations of single robot systems, such as scalability and reliability. As a consequence, these have found their way into numerous applications including in the space and aerospace domains like swarm-based asteroid observation or counter-drone systems. However, achieving stable formations around a point of interest using different number of robots and diverse initial conditions can be challenging. In this article we propose a novel method for autonomous robots swarms self-organisation solely relying on their relative position (angle and distance). This work focuses on an evolutionary optimisation approach to calculate the parameters of the swarm, e.g. inter-robot distance, to achieve a reliable formation under different initial conditions. Experiments are conducted using realistic simulations and considering four case studies. The results observed after testing the optimal configurations on 72 unseen scenarios per case study showed the high robustness of our proposal since the desired formation was always achieved. The ability of self-organise around a point of interest maintaining a predefined fixed distance was also validated using real robots.
https://doi.org/10.1145/3512290.3528709
Introduction to behavior based recommendation systemKimikazu Kato
Material presented at Tokyo Web Mining Meetup, March 26, 2016.
The source code is here:
https://github.com/hamukazu/tokyo.webmining.2016-03-26
東京ウェブマイニング(2016年3月27)の発表資料です。すべて英語です。
The window functions used for digital filter design are used to eliminate oscillations in
the FIR (Finite Impulse Response) filter design. In this work, the use of Particle Swarm Optimization
(PSO) algorithm is proposed in the design of cosh window function, in which has widely used in the
literature and has useful spectral parameters. The cosh window is a window function derived from the
Kaiser window. It is more advantageous than the Kaiser window because there is no power series
expansion in the time domain representation. The designed window function shows better ripple ratio
characteristics than other window functions commonly used in the literature. The results obtained
were presented in tables and figures and successful results were obtained
The Comprehensive Product Platform Planning (CP3) framework presents a flexible mathematical model of the platform planning process, which allows (i) the formation of sub-families of products, and (ii) the simultaneous identification and quantification of plat- form/scaling design variables. The CP3 model is founded on a generalized commonality matrix that represents the product platform plan, and yields a mixed binary-integer non- linear programming problem. In this paper, we develop a methodology to reduce the high dimensional binary integer problem to a more tractable integer problem, where the com- monality matrix is represented by a set of integer variables. Subsequently, we determine the feasible set of values for the integer variables in the case of families with 3 − 7 kinds of products. The cardinality of the feasible set is found to be orders of magnitude smaller than the total number of unique combinations of the commonality variables. In addition, we also present the development of a generalized approach to Mixed-Discrete Non-Linear Optimization (MDNLO) that can be implemented through standard non-gradient based op- timization algorithms. This MDNLO technique is expected to provide a robust and compu- tationally inexpensive optimization framework for the reduced CP3 model. The generalized approach to MDNLO uses continuous optimization as the primary search strategy, how- ever, evaluates the system model only at the feasible locations in the discrete variable space.
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Talk given at the ZK Study Club by Jonathan Bootle and Katerina Sotiraki about the universality of sumcheck arguments and their importance in zero-knowledge cryptography.
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As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
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The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. About Prognoz
Leading Russian developers of Business Intelligence
and Performance Management systems
• international company that has
been working in the IT market
since 1991
• joint team of over 1 200 skilled
economists, programmers,
analysts
• 50% market of BI in Russia
• Prognoz Platform, 1-st Russian
platform in Magic Quadrant of
Gartner
3. CONTENTS
Technical architecture Practical approach
Evolution of bubble and risk management
About MMP cluster Monitoring of financial bubbles
MMP cluster architecture The system of bubble recognition
Financial bubbles Science and experiment
Historical bubbles Financial bubble experiment
Definition of financial bubbles Market microstructure approach
Theory of crashes
LPPL model
Fitting of the model
Models selection
3
5. Technical info:
Installation Site: Perm state university
Supercomputer type: Cluster
Number of nodes: 3
Number of Cores per node: 12
CPU type: Intel Xeon 5650 (2.66 GHz)
RAM per node: 64 Gb
OS: Windows Server 2003
5
7. R is statistical and graphical
programming environment
Appeared in 1993 and designed by There is more than 4300
Ross Ihaka and Robert Gentleman packages that allow to use
specialized statistical
R is a GNU project techniques, graphical
devices, import/export
R – a free implementation of the S capabilities, reporting tools,
etc.
language
It runs on a variety of platforms
including Windows, Unix and MacOS
It contains advanced statistical
routines not yet available in other
packages
7
8. Commands
Database
Batch file R file
Task R file
Batch file
Runner
Batch file R file
8
13. Mr. Greenspan
Thefreedictionary.com
Charles Kindleberger, MIT
Professor J.Barley Rosser, James Madison University
13
14. Authors
A.Johansen, O.Ledoit, D.Sornette (JLS)
First publication
Large financial crashes (1997)
Famous book
Didier Sornette
Why Stock Markets Crash (2004)
𝑡 𝑐 - critical time when bubble crash or
change to another regime
14
21. For each log periodic curve we fixed:
𝑡0 - start time of the bubble
First model 𝑡 𝑐 - critical time when bubble crash or
change to another regime
Second model
Sample of 𝑡 𝑐
𝑡 𝑐1 𝑡 𝑐2
21
27. Timeframe LPPL
• Bubble • Long • Large
• Anti - bubble • Short • Small • Parameters
Type Size
27
28. The Financial Crisis Observatory (FCO) is a scientific platform aimed at testing and
quantifying rigorously, in a systematic way and on a large scale the hypothesis that
financial markets exhibit a degree of inefficiency and a potential for predictability,
especially during regimes when bubbles develop. (http://www.er.ethz.ch/fco/index)
Testing two hypotheses:
• Hypothesis H1: financial (and other) bubbles can be diagnosed in real-time
before they end..
• Hypothesis H2: The termination of financial (and other) bubbles can be
bracketed using probabilistic forecasts, with a reliability better than chance
(which remains to be quantied).
D. Sornette, R. Woodard,
M. Fedorovsky,S. Reimann, H. Woodard, W.-X. Zhou
The Financial Bubble Experiment. First Results (2 November 2009 - 1 May 2010)
28
29. 2 November 2009 – 1 May 2010 [http://www.er.ethz.ch/fco/FBE_report_May_2010]
2 of 4 bubbles detected by model were real bubbles
All of them changed their regimes
12 May 2010 – 1 November 2010 [http://www.er.ethz.ch/fco/fbe_Report_1Nov10_2]
5 of 7 bubbles detected by model were real bubbles
4 of 5 changed their regimes
12 November 2011 – 2 May 2011 [http://www.er.ethz.ch/fco/fbe_20110502_assets_3.pdf]
24 of 27 bubbles detected by model were real bubbles
17 of 24 changed there regime
29
33. Statistics: IDENT UP DOWN ALL
PMTL 15 36 51
MAGN 31 6 37
Stocks analyzed 29 blue chips NOTK
OGKC
18
13
18
23
36
36
01.04.2010-30.06.2010; AFLT 9 25 34
RTKM 14 19 33
Period 1.09.2010-12.10.2010 MGNT 4 16 20
NLMK 8 12 20
Trading days 82 URKA 7 11 18
Sample analyzed 20.2 mln. ticks SIBN
RASP
6
7
10
8
16
15
Trading time 11.30-18.40 MRKH 3 9 12
MSNG 5 7 12
CHMF 3 4 7
Shocks found 369 RU14TATN3006
HYDR
3
3
3
2
6
5
TRNFP 3 0 3
IUES 0 2 2
We use a tick dynamics of prices for MTSI 1 1 2
SNGSP 2 0 2
filtering (source: MICEX) ROSN 1 0 1
SNGS 1 0 1
FEES 0 0 0
GAZP 0 0 0
GMKN 0 0 0
Total 369 events (13 per stock) LKOH 0 0 0
On average 1 shock/7 days per stock SBER03 0 0 0
SBERP03 0 0 0
VTBR 0 0 0
Average 5 7 33
13
34. Science
Laboratory of financial modeling and risk
management - Prognoz Risk Lab
Мagistracy in finance and IT (Master in
Finance & IT) in Perm State National Research
University
mifit.ru
Perm Winter School is an annual conference
on modeling of financial markets and risk
management
permwinterschool.ru