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Causative Factors of Downturn in Growth and Performance of Stock
Causative Factors of Downturn in Growth and Performance of Stock

... The March 2005 stock market Crash* is another example of internal crisis caused by the stock brokers itself. That crash at Karachi Stock Exchange and Lahore Stock Exchange took away around $ 13 Billions. A Stock Market crash is sudden dramatic decline of the share prices in the stock market. Such cr ...
Option Trading: Information or Differences of
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... questionable if this type of demand would explain the large volume of trading. Besides, Lakonsihok, Lee, Pearson and Poteshman (2006) found that the most popular option-trading strategy is covered call writing, followed by purchasing calls and writing puts, none of which appears to be a logical hedg ...
An Empirical Analysis of the Profitability of Technical Analysis
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... many studies that find technical rules to outperform a market benchmark are criticized for cherry picking results and over regressing trading strategies to find significant results. In an interview with Xetra.com (2015), professional trader and technical analysist advisor Dan Gramza, gave his view o ...
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... (Scharfstein & Stein, 1990; Banerjee, 1992; Devenow & Welch, 1996), a large stream of scholars consider herding as irrational behavior. Indeed under uncertainly and fear to commit wrong decision, individuals emerge into a collective trading (buying or selling) willful blindness ignoring their inform ...
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... Given the majority of hedge fund activity and academic research focuses on the US, what are the returns from following such strategies in the UK? Is there a difference in performance and if so, can it be explained by the different characteristics of the two markets? In this paper we attempt to addr ...
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The effects of short-selling public disclosure regimes on equity markets

... decrease in trading volumes, while both the US and UK control groups experienced increases in trading volumes. Importantly, this indicates that when short-selling liquidity comes out of equity markets it does not return as liquidity on the long side. –– Bid-ask spreads for the UK test group widened ...
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... absence of analysts’ forecasts. We test for PEAD effects not only in general, but also across industries on the stocks listed on the Saudi stock exchange. Third, the Saudi Stock Market (hereafter, SSM) is dominated by retail investors, which provides a perfect setting for studying investor behaviour ...
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Tick Size and Institutional Trading Costs: Evidence from Mutual Funds

... order into smaller pieces, each of which may be routed to different markets and brokers. As each component of the order is executed, prices may move against the portfolio manager. One way to capture the resulting price impact is to analyze the order as far upstream as possible. Some studies of the ...
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Algorithmic trading

Algorithmic trading, also called algo trading and blackbox trading, encompasses trading systems that are heavily reliant on complex mathematical formulas and high-speed, computer programs to determine trading strategies. These strategies use electronic platforms to enter trading orders with an algorithm which executes pre-programmed trading instructions accounting for a variety of variables such as timing, price, and volume. Algorithmic trading is widely used by investment banks, pension funds, mutual funds, and other buy-side (investor-driven) institutional traders, to divide large trades into several smaller trades to manage market impact and risk.Algorithmic trading may be used in any investment strategy or trading strategy, including market making, inter-market spreading, arbitrage, or pure speculation (including trend following). The investment decision and implementation may be augmented at any stage with algorithmic support or may operate completely automatically.Many types of algorithmic or automated trading activities can be described as high-frequency trading (HFT), which is a specialized form of algorithmic trading characterized by high turnover and high order-to-trade ratios. As a result, in February 2012, the Commodity Futures Trading Commission (CFTC) formed a special working group that included academics and industry experts to advise the CFTC on how best to define HFT. HFT strategies utilize computers that make elaborate decisions to initiate orders based on information that is received electronically, before human traders are capable of processing the information they observe. Algorithmic trading and HFT have resulted in a dramatic change of the market microstructure, particularly in the way liquidity is provided.Profitability projections by the TABB Group, a financial services industry research firm, for the US equities HFT industry were US$1.3 billion before expenses for 2014, significantly down on the maximum of US$21 billion that the 300 securities firms and hedge funds that then specialized in this type of trading took in profits in 2008, which the authors had then called ""relatively small"" and ""surprisingly modest"" when compared to the market's overall trading volume. In March 2014, Virtu Financial, a high-frequency trading firm, reported that during five years the firm as a whole was profitable on 1,277 out of 1,278 trading days, losing money just one day, empirically demonstrating the law of large numbers benefit of trading thousands to millions of tiny, low-risk and low-edge trades every trading day.A third of all European Union and United States stock trades in 2006 were driven by automatic programs, or algorithms. As of 2009, studies suggested HFT firms accounted for 60-73% of all US equity trading volume, with that number falling to approximately 50% in 2012. In 2006, at the London Stock Exchange, over 40% of all orders were entered by algorithmic traders, with 60% predicted for 2007. American markets and European markets generally have a higher proportion of algorithmic trades than other markets, and estimates for 2008 range as high as an 80% proportion in some markets. Foreign exchange markets also have active algorithmic trading (about 25% of orders in 2006). Futures markets are considered fairly easy to integrate into algorithmic trading, with about 20% of options volume expected to be computer-generated by 2010. Bond markets are moving toward more access to algorithmic traders.Algorithmic trading and HFT have been the subject of much public debate since the U.S. Securities and Exchange Commission and the Commodity Futures Trading Commission said in reports that an algorithmic trade entered by a mutual fund company triggered a wave of selling that led to the 2010 Flash Crash. The same reports found HFT strategies may have contributed to subsequent volatility by rapidly pulling liquidity from the market. As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered. (See List of largest daily changes in the Dow Jones Industrial Average.) A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while ""algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010."" However, other researchers have reached a different conclusion. One 2010 study found that HFT did not significantly alter trading inventory during the Flash Crash. Some algorithmic trading ahead of index fund rebalancing transfers profits from investors.
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