Impact Of Globalization On Non Institutional Investors

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Impact on Non HFT institutional investors There is a severe variation of capital at risk of high frequency trading when compared to capita at risk for institutional investors as noted by KF&Y. Capital at risk is the total amount of capital that an organization deploys in all of its market positions at any specific point of time, as defined by IRRC institute. A high frequency trader generally keeps its capital at risk negligible. Although, HFT companies contributes for nearly 65% by volume in equities, their capital risk is small. On the other hand, the institutional investors or non- high frequency traders amount to a larger market ownership, more than 64% at the end of 2009. The hypothesis is that a small percentage of minority ownership…show more content…
There is no definite scientific proof for the same but there are some anecdotal evidences. It is evident that the Flash Crash of May 6, 2010 was provoked by HFT resulting in the decline in markets in a very short amount of time. However, it was a singular event, and thus, the assessment cannot be verified that HFT caused a systemic disruption. Different HFT Strategies There are primarily 3 high frequency trading strategies: Liquidity providing, trading the tape and Statistical Trading. And each of these three strategies are classified further into two sub categories. 1. LIQUIDITY PROVIDING Rebate Trading: This type of trading provides liquidity in stocks by posting bids and offers in order to collect ECN rebates without requiring capital gains. It is most prevalent in higher volume, lower volatility stocks and is capable of tolerating small trading losses (Borchgrevink, 2015). Example: Post bid to buy shares, upon execution immediately post offer on the inside market to sell position thus capturing rebate from ECN with or without capital gain (Borchgrevink, 2015). Market Making: It attempts to reduce spreads by creating a more liquid market and earns profit from the spread as well as ECN rebates for providing liquidity (Borchgrevink, 2015). Examples: •
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