Dalal Street turned out to be a “Bear’s treat” on Friday as the domestic Index NIFTY 50 plunged down by 162 points hitting the low of 9951 for the session, before closing for the week at 9998.05, just below the psychological mark of 10000, and also losing 197 points on weekly basis.
In continuation of our previous report, levels of 9970 were achieved, sooner asthe benchmark closed below 200-DEMA and going forward, we expect 9900 is next major zone at which all eyes should keep a close watch, because a firm close below this on a weekly basis, could trigger fresh rounds of selling, which could retest 9800 followed by 9600 on the lower side.
After a sharp fall, limited possibility of some consolidation is likely and if it does so we might also see few points on the higher side which are near 10090, if at any point of time NIFTY manages to cross 10135, we suggest to be on long side for next few trading sessions to gain 10280-10380 on the NIFTY.
|In the latest issue (Issue 13 – August 2017), it covers the stories of:|
|Financial Crime Risk : Anti-Money Laundering Practices in Banking
To understand anti-money laundering, we have to understand what money laundering is. Money Laundering is the process of converting illegal funds into seemingly legitimate assets with the purpose of concealing the ownership or original source of these funds. This makes it difficult for the authorities to trace the origins of the funds. To counter this, the banking sector has established a set of internal regulations and system known as anti-money laundering. These are legal controls taken by financial institutions to investigate suspicious transactions to help prevent money laundering activities within the banking sector.
|The Rise of Text Mining in Financial Markets
The world is awash in data. Financial markets are awash in data. We are generating around 2.5 quintillion (2.5×1018) bytes of information every day, and there is an average of 4,000 brokerage reports a day comprising around 36,000 pages in 53 languages. As market participants try to maximize their competitive edge from the growing mountain of information, the nancial world increasingly feels there is a need to harness the power of big data and it has been shaping the way they acquire, analyze and utilize data. The recent development is the rapid expansion of text mining. Hence, this article will focus on the development of Text Mining technology as well as Text Mining technique.