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In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...
Persistent link: https://www.econbiz.de/10014462056
The paper offers an alternative approach to analyzing stock market time series data. The purpose is to develop descriptive, more intuitive, and closer to reality analogs of the behavior of US stock market prices, as indexed by the S&P500 stock price index covering the period October 2003 to...
Persistent link: https://www.econbiz.de/10010288058
In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...
Persistent link: https://www.econbiz.de/10003794031
The paper offers an alternative approach to analyzing stock market time series data. The purpose is to develop descriptive, more intuitive, and closer to reality analogs of the behavior of US stock market prices, as indexed by the S&P500 stock price index covering the period October 2003 to...
Persistent link: https://www.econbiz.de/10003844122
In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...
Persistent link: https://www.econbiz.de/10012939999
Single-company event studies are commonly employed in applied practice, such as in analyzing market efficiency, reliance, and damages in securities litigation. However, the presence of significant company-specific events among the observations used to estimate the market model results in...
Persistent link: https://www.econbiz.de/10012941842
In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...
Persistent link: https://www.econbiz.de/10012770230
This paper will provide information on what a hypercube is and how to use them in graphing the financial markets, especially in the Poseidon software that I am developing. What types of hypercubes are there? How to describe the market in higher dimensions? What are the common variables to use in...
Persistent link: https://www.econbiz.de/10012992697
This paper will provide information on what happened in the financial crisis of 2008 and how to graph volatility outside of the option market. We will investigate the causes of the financial crisis, as well as some of the social inequalities that still exist today. We will explore household...
Persistent link: https://www.econbiz.de/10012993297
This paper will provide information on topographic finance and how it can be used in econometric and financial analysis. First we will cover what topographic finance means. Secondly, a discussion of what problems can be visualized will be but forth. Thirdly, a high level description of the...
Persistent link: https://www.econbiz.de/10012993924