Download or read book Detecting and Forecasting High Frequency Price Jumps in the Stock Market written by Thibaut Moyaert and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we investigate some predictable patterns in high frequency price jumps using trades, orders and quotes data on the Euronext 100 Index. A fixed volume chart allows us to control for trading volume effects and avoid non trading issues at high frequency aggregation. We detect jumps through four different methods that encompass constant volatility, time-varying volatility and periodicity. Our forecasting model is a logistic model adjusted to rare events. At an average 2-minute trading volume frequency, we find that price jumps are mainly driven by liquidity gaps in the order book. The origin of those gaps is still an open question. They may be due to order cancellations or to a low resiliency of the stock market. Our results suggest that market participants could take advantage of some predictable patterns in price jumps in order to enhance their hedging or investment strategies.
Download or read book The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility written by Rodrigo Hizmeri and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Financial Market Volatility and Jumps written by Xin Huang and published by . This book was released on 2007 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: JEL classification. C1, C2, C5, C51, C52, F3, F4, G1, G14.
Download or read book How can I get started Investing in the Stock Market written by Lokesh Badolia and published by Educreation Publishing. This book was released on 2016-10-27 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is well-researched by the author, in which he has shared the experience and knowledge of some very much experienced and renowned entities from stock market. We want that everybody should have the knowledge regarding the different aspects of stock market, which would encourage people to invest and earn without any fear. This book is just a step forward toward the knowledge of market.
Download or read book Forecasting the Monthly Movements of Stock Prices written by William Dunnigan and published by . This book was released on 1930 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Price Jump Indicators written by Jan Novotny and published by . This book was released on 2013 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the behavior and performance of multiple price jump indicators across markets and over time. By using high-frequency stock market data we identify clusters of price jump indicators that share similar properties in terms of their performance in that they minimize Type I and Type II errors. We show that clusters of price jump indicators formed over the observations do not exhibit equal size. Clusters are stable across stock market indices and accuracy across price jump indicators are both stable over time. There was no significant change in the composition of clusters associated with market activity and the detected numbers of price jumps are stable over time. The recent financial crisis does not seem to affect the overall jumpiness of mature or emerging stock markets. Our results support the stress testing approach of the Basel III Accords in that the jump component of the volatility process does not need to be treated separately for the purpose of stress testing.
Download or read book High Frequency Financial Econometrics written by Yacine Aït-Sahalia and published by Princeton University Press. This book was released on 2014-07-21 with total page 683 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.
Download or read book Modelling and Forecasting High Frequency Financial Data written by Stavros Degiannakis and published by Springer. This book was released on 2016-04-29 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets. This book provides a comprehensive guide to the quantitative analysis of high frequency financial data in the light of current events and contemporary issues, using the latest empirical research and theory. It highlights and explains the shortcomings of theoretical frameworks and provides an explanation of high-frequency theory, emphasising ways in which to critically apply this knowledge within a financial context. Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.
Download or read book Exploiting High Frequency Data for Volatility Forecasting and Portfolio Selection written by Yujia Hu and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: An instant may matter for the course of an entire life. It is with this idea that the present research had its inception. High frequency financial data are becoming increasingly available and this has triggered research in financial econometrics where information at high frequency can be exploited for different purposes. The most prominent example of this is the estimation and forecast of financial volatility. The research, chapter by chapter is summarized below. Chapter 1 provides empirical evidence on univariate realized volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. It examines leverage and volatility feedback effects among continuous and jump components of the S & P500 price and volatility dynamics, using recently developed methodologies to detect jumps and to disentangle their size from the continuous return and the continuous volatility. The research finds that jumps in return can improve forecasts of volatility, while jumps in volatility improve volatility forecasts to a lesser extent. Moreover, disentangling jump and continuous variations into signed semivariances further improves the out-of-sample performance of volatility forecasting models, with negative jump semivariance being highly more informative than positive jump semivariance. A simple autoregressive model is proposed and this is able to capture many empirical stylized facts while still remaining parsimonious in terms of number of parameters to be estimated. Chapter 2 investigates the out-of-sample performance and the economic value of multivariate forecasting models for volatility of exchange rate returns. It finds that, when the realized covariance matrix approximates the true latent covariance, a model that uses high frequency information for the correlation is more appropriate compared to alternative models that uses only low-frequency data. However multivariate FX returns standardized by the.
Download or read book Allowing for Jump Measurements in Volatility written by Vassilios G. Papavassiliou and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous jump part of the quadratic variation process for individual stocks and incorporate it into heterogeneous autoregressive volatility models. We analyze the distributional properties of the jump measures vis-à-vis the corresponding realized volatility ones, and compare them to those of aggregate US market index series. We also demonstrate important gains in the forecasting accuracy of high-frequency volatility models.
Download or read book The Dynamics of Price Jumps in the Stock Market written by Fabrizio Ferriani and published by . This book was released on 2017 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study the bivariate jump process involving the S&P 500 and the Euro Stoxx 50 with jumps extracted from high frequency data using non-parametric methods. Our analysis, based on a generalized Hawkes process, reveals the presence of self-excitation in the jump activity which is responsible for jump clustering but has a very small persistence in time. Concerning cross-market effects, we find statistically significant co-jumps occurring when both markets are simultaneously operating but no evidence of contagion in the jump activity, suggesting that the role of jumps in volatility transmission is negligible. Moreover, we find a negative relationship between the jump activity and the continuous volatility indicating that jumps are mostly detected during tranquil market conditions rather than in periods of stress. Importantly, our empirical results are robust under different jump detection methods.
Download or read book High Frequency Trading and Limit Order Book Dynamics written by Ingmar Nolte and published by Routledge. This book was released on 2016-04-14 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the latest research in the areas of market microstructure and high-frequency finance along with new econometric methods to address critical practical issues in these areas of research. Thirteen chapters, each of which makes a valuable and significant contribution to the existing literature have been brought together, spanning a wide range of topics including information asymmetry and the information content in limit order books, high-frequency return distribution models, multivariate volatility forecasting, analysis of individual trading behaviour, the analysis of liquidity, price discovery across markets, market microstructure models and the information content of order flow. These issues are central both to the rapidly expanding practice of high frequency trading in financial markets and to the further development of the academic literature in this area. The volume will therefore be of immediate interest to practitioners and academics. This book was originally published as a special issue of European Journal of Finance.
Download or read book Exploiting high frequency data for volatility forecasting and portfolio selection kumulative Dissertation written by Yujia Hu and published by . This book was released on 2012 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: An instant may matter for the course of an entire life. It is with this idea that the present research had its inception. High frequency financial data are becoming increasingly available and this has triggered research in financial econometrics where information at high frequency can be exploited for different purposes. The most prominent example of this is the estimation and forecast of financial volatility. The research, chapter by chapter is summarized below. Chapter 1 provides empirical evidence on univariate realized volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. It examines leverage and volatility feedback effects among continuous and jump components of the S&P500 price and volatility dynamics, using recently developed methodologies to detect jumps and to disentangle their size from the continuous return and the continuous volatility. The research finds that jumps in return can improve forecasts of volatility, while jumps in volatility improve volatility forecasts to a lesser extent. Moreover, disentangling jump and continuous variations into signed semivariances further improves the out-of-sample performance of volatility forecasting models, with negative jump semivariance being highly more informative than positive jump semivariance. A simple autoregressive model is proposed and this is able to capture many empirical stylized facts while still remaining parsimonious in terms of number of parameters to be estimated. Chapter 2 investigates the out-of-sample performance and the economic value of multivariate forecasting models for volatility of exchange rate returns. It finds that, when the realized covariance matrix approximates the true latent covariance, a model that uses high frequency information for the correlation is more appropriate compared to alternative models that uses only low-frequency data. However multivariate FX returns standardized by the.
Download or read book Integrated Uncertainty in Knowledge Modelling and Decision Making written by Van-Nam Huynh and published by Springer. This book was released on 2018-03-09 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2018, held in Hanoi, Vietnam, in March 2018.The 39 revised full papers presented in this book were carefully reviewed and selected from 76 initial submissions. The papers are organized in topical sections on uncertainty management and decision support; clustering and classification; machine learning applications; statistical methods; and econometric applications.
Download or read book High Frequency Trading and Price Jumps in the Stock Market written by Thibaut Moyaert and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we investigate liquidity supply and demand around price jumps in a pure order driven stock market using a detailed tick frequency data set on the Euronext 100 index. The advantage of this database is to allow us to disentangle two major evolutions in European financial markets: the emergence of high frequency trading and the implementation of multilateral trading facilities. We generate average 2-minute trading volume interval and assess liquidity dynamics through an extensive set of order book-based measures (liquidity supply) and trade-based measures (liquidity demand). Furthermore, we also consider order submission dynamics and investor types activity around price jumps. We find the origin of market disruptions lies in a low liquidity supply while at the opposite liquidity demand slows down. All our results suggest a higher involvement of high frequency trading activity in the market around price jumps. To emphasize our findings, we conduct bidirectional Granger causality tests that support our results.
Download or read book Using High Frequency Stock Market Index Data to Calculate Model Forecast Realized Return Variance written by Roel C. A. Oomen and published by . This book was released on 2001 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Price Forecasting Models for Image Sensing Systems Inc ISNS Stock written by Ton Viet Ta and published by Independently Published. This book was released on 2020-08-25 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you want to earn up to a 24670% annual return on your money by two trades per day on Image Sensing Systems, Inc. ISNS Stock? Reading this book is the only way to have a specific strategy. This book offers you a chance to trade ISNS Stock at predicted prices. Eight methods for buying and selling ISNS Stock at predicted low/high prices are introduced. These prices are very close to the lowest and highest prices of the stock in a day. All methods are explained in a very easy-to-understand way by using many examples, formulas, figures, and tables. The BIG DATA of the 6371 consecutive trading days (from May 5, 1995 to August 24, 2020) are utilized. The methods do not require any background on mathematics from readers. Furthermore, they are easy to use. Each takes you no more than 30 seconds for calculation to obtain a specific predicted price. The methods are not transient. They cannot be beaten by Mr. Market in several years, even until the stock doubles its current age. They are traits of Mr. Market. The reason is that the author uses the law of large numbers in the probability theory to construct them. In other words, you can use the methods in a long time without worrying about their change. The efficiency of the methods can be checked easily. Just compare the predicted prices with the actual price of the stock while referring to the probabilities of success which are shown clearly in the book (click the LOOK INSIDE button to read more information before buying this book). Depending on the number of investors who are interested in this book, the performance of the methods from the publication date will be added to the book after one year, and will be stated here in the description of the book too. You will then see that the methods in this book are outstanding or not. The book is very useful for Investors who have decided to buy the stock and keep it for a long time (as the strategy of Warren Buffett), or to sell the stock and pay attention to other stocks. The methods will help them to maximize profits for their decision. Day traders who buy and sell the stock many times in a day. Although each method is valid one time per day, the information from the methods will help the traders buy/sell the stock in the second time, third time or more in a day. Beginners to ISNS Stock. The book gives an insight about the behavior of the stock. They will surely gain their knowledge of ISNS Stock after reading the book. Everyone who wants to know about the U.S. stock market.
