Solving modern crime in financial markets : analytics and by Marius-Cristian Frunza

By Marius-Cristian Frunza

This entire resource of data approximately monetary fraud promises a mature method of fraud detection and prevention. It brings jointly all vital element of analytics utilized in investigating glossy crime in monetary markets and makes use of R for its statistical examples. It specializes in crime in monetary markets in place of the monetary undefined, and it highlights technical facets of crime detection and prevention instead of their qualitative elements. For people with robust analytic abilities, this e-book unleashes the usefulness of robust predictive and prescriptive analytics in predicting and combating smooth crime in monetary markets.

  • Interviews and case reviews supply context and intensity to examples
  • Case experiences use R, the robust statistical freeware tool
  • Useful in school room contexts

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However, a dedicated team that does the maintenance of the software does exist. Software that I. MODERN FINANCIAL CRIME 41 1 BACKGROUND allows interface with the Bitcoin universe can be downloaded freely, and the system runs through a decentralized and fully distributed peer-topeer network. This implies that all hardware terminals are connected to each other and each terminal can leave and rejoin the network at any time, and can later accept the information supplied by other terminals. This type of functioning revolves around the concept of blocks, which incorporate information about the previous validated transactions.

Obviously, those with stronger mining tools have an advantage in price discovery. Each technological jump also creates new sources of asymmetry among miners. In theory, this heterogeneity will need to be addressed when the total Bitcoin monetary mass becomes stable, due to the fact that the mining will became more and more cost intense. If technology represents a first source of behavioral asymmetry, another source of inefficiency is the breakdown of memory and computational capacity among miners.

2. The practical aspects consist of acquiring one or a few social media (Twitter) accounts. The creation of a new account is needed to avoid an account that is already known by the social media company. This step should make the tracking of the account difficult during the investigation process. 3. The social media fraudsters then conceive a strategy based on the rogue information they want to spread. Thus, they should take positions on target stock or on correlated assets. More sophisticated strategies include spread betting and derivatives, which are more difficult for investigators to trace.

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