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Author : Jose Joy Thoppan
Publisher : Emerald Group Publishing
Page : 120 pages
File Size : 32,55 MB
Release : 2021-05-05
Category : Business & Economics
ISBN : 1801173966
Developing an Effective Model for Detecting Trade-Based Market Manipulation determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.
Author : Jose Joy Thoppan
Publisher : Emerald Group Publishing
Page : 86 pages
File Size : 11,25 MB
Release : 2021-05-05
Category : Business & Economics
ISBN : 1801173982
Developing an Effective Model for Detecting Trade-Based Market Manipulation determines an appropriate model to help identify stocks witnessing activities that are indicative of potential manipulation through three separate but related studies.
Author : Sarah Youssef
Publisher :
Page : 0 pages
File Size : 40,87 MB
Release : 2021
Category : Machine learning
ISBN :
Abstract: Stock market manipulation detection is important for both investors and regulators. Being able to detect stock manipulation and preventing it gives investors the confidence in the market fairness and integrity. It also helps maintaining liquidity of the stocks and market efficiency. Implementing data mining algorithms in manipulation detection is a relatively recent technique but in the past few years there has been an increasing interest in it's applications in this domain. The benefit of monitoring manipulative trade behavior is that it can be implemented on live feed of stock data, which saves a lot of time in detecting stock price manipulation. This research implements machine learning algorithms in detecting trade manipulations where trade behaviors artificially impact the National Best Bid and Offer (NBBO) of traded stocks. Research methodology implemented is based on feature extraction using signal analysis, taking advantage of the similarity between physical signals measured by machines and raw financial data. Accordingly, Continuous Wavelet Transform (CWT) is applied on actual manipulation data for feature extraction, Principal Component Analysis (PCA) and factor analysis are used for dimensionality reduction and then Machine Learning Classifiers are trained and tested. Tick Bid/Ask Price and volume data of actual 15 manipulation cases published by the Security Exchange Center (SEC) was extracted from an online interface and labeled accordingly. This data was then used to train, and test 3 different classification models (XGBoost, KNN & SVM) and the outcome was compared accordingly. Results showed that introducing continuous wavelet transform enhances model accuracy, it increased precision results tremendously, while reducing recall values slightly. Adding PCA, reduced run time greatly, yet reduced the quality of some models prediction. Out of the three classifiers XGboost & KNN are showing the highest performance.
Author : Gregory J Durston
Publisher : Waterside Press
Page : 152 pages
File Size : 33,14 MB
Release : 2020-01-29
Category : Law
ISBN : 1909976733
Market manipulation comes in many forms. For a wrong that some say started life with groups of men dressed in Bourbon uniforms spreading false information in cod French accents, the speed of change has accelerated dramatically in the modern era, via the Internet, novel forms of electronic communication, ultra-fast computer-generated trading, new types of financial instruments, and increased globalisation. This means that opportunities for carrying-out new forms of manipulation now exist on an exponential scale. Looks at the mechanisms, criminal and civil, to confront market manipulation, its enforcement regimes, legal and evidential rules and potential loopholes. Shows how every individual involved in market transactions can fall foul of the law if they do not ensure integrity in their dealings. The ‘tricks’ used by those seeking to benefit from this special category of fraud and the relationship of dedicated provisions to the general law is outlined, with key statutory provisions set out in an appendix. A valuable accompaniment to The Little Book of Insider Dealing (Waterside Press, 2018). An invaluable pocket guide and law primer. An essential guide for investors. With practical examples and decided cases. An up-to-date treatment of a fast-moving topic. Describes both criminal and regulatory regimes. Contents include Forms of Market Manipulation; Suspicion, Identification, Detection and Investigation; Obligations and Enforcement; Criminal Offences, Defences and Punishment; Regulatory Provisions and Penalties; Evidence; Acronyms; Select Bibliography; Key Statutory Provisions and Index.
Author : Jan Schröder
Publisher : KIT Scientific Publishing
Page : 180 pages
File Size : 46,14 MB
Release : 2009
Category : Business
ISBN : 3866443447
Fraud and manipulation in prediction markets are systematic results of incentive incompatibility, which, if present, have to be detected and balanced. ""Manipulations in Prediction Markets"" gives a critical insight into manipulations that are most likely to occur in prediction markets. In a general approach the book discusses the issue of incentives in markets and the breakdown of the incentive system. On this basis a new way of detecting irregular trading behaviour is introduced.
Author : Marcello Minenna
Publisher :
Page : 53 pages
File Size : 20,85 MB
Release : 2012
Category :
ISBN :
In every country with legislation on market abuse, i.e. on market manipulation and insider trading, the repression of these offences is entrusted to supervisory and judicial authorities with powers that vary with the legislation in question. A procedure permitting cases of market abuse to be detected in real time is a need that is strongly felt by financial market supervisory authorities. Such a procedure consists basically in the analysis of the transactions carried out on the market by traders in order to detect anomalies that could be symptomatic of market abuse. The aim of this paper is to develop, through recourse to probability theory, a method for identifying cases of market abuse more effectively.
Author : S. Craig Pirrong
Publisher : Springer Science & Business Media
Page : 269 pages
File Size : 39,93 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 1461562597
Deterrence of market manipulation is central to the entire regulatory and legal framework governing the operation of American commodity futures markets. However, despite all of the regulatory, scholarly, and legal scrutiny of market manipulation, the subject is widely misunderstood. Federal commodity and securities laws prohibit manipulation, but do not define it. Scholarly research has failed to analyze adequately the causes or effects of manipulation, and the relevant judicial decisions are confused, confusing, and contradictory. The aim of this book is to illuminate the process of market manipulation by presenting a rigorous economic analysis of this phenomenon, including the conditions that facilitate it and its effects on market users and others. The conclusions of this analysis are used to examine critically some legal and regulatory anti-manipulation policies. The Economics, Law and Public Policy of Market Power Manipulation concludes with a set of robust and realistic tests that regulators and jurists can apply to detect and deter manipulation.
Author : Hanning Yuan
Publisher : Springer
Page : 644 pages
File Size : 28,62 MB
Release : 2017-03-02
Category : Computers
ISBN : 9811039666
The two volume proceedings of CCIS 698 and 699 constitutes revised selected papers from the 4th International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2016, held in Hong Kong, China, in November 2016. The total of 118 papers presented in these proceedings were carefully reviewed and selected from 311 submissions. The contributions were organized in topical sections named: smart city in resource management and sustainable ecosystem; spatial data acquisition through RS and GIS in resource management and sustainable ecosystem; ecological and environmental data processing and management; advanced geospatial model and analysis for understanding ecological and environmental processes; applications of geo-informatics in resource management and sustainable ecosystem.
Author : Stefan Jansen
Publisher : Packt Publishing Ltd
Page : 822 pages
File Size : 29,70 MB
Release : 2020-07-31
Category : Business & Economics
ISBN : 1839216786
Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
Author : David C. Donald
Publisher :
Page : 27 pages
File Size : 38,8 MB
Release : 2015
Category :
ISBN :
Current rules on market manipulation ignore the existing and rapidly growing body of scholarship on how securities prices are formed in markets. These rules are primarily reactive, and depend on vague and difficult measures such as the “artificiality” of a resulting market price or the trader's intention. Some trades, like matched and wash sales, have indeed been singled out since the 1930's for special scrutiny, but this list has never been updated. Through even a cursory review of existing literature in financial economics and market microstructure, lawmakers and regulators would be able to know the times, the market conditions, and the types of securities that facilitate and give greatest incentive for trade-based market manipulation, as well as the manipulative techniques best adapted to each, specific situation. Rapid advance in the technological prowess of some institutional traders has lent urgency to the task of updating rules on market manipulation. The playing field between high-powered and retail traders has become so uneven that soon our original understanding of securities markets will be eclipsed. Lawmakers and regulators should take market manipulation seriously and develop presumptions triggered by behavior that is shown to display a very high probability of manipulative intent. This paper presents the parameters along which such presumptions can be formulated.