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Web Note 7.1: Mean Reversion
Web Note 7.1: Mean Reversion

... exceed its mean value for a prolonged period of time, or similarly fall short of it, it eventually and repeatedly returns to its mean value.1 In the finance literature, this concept is most typically applied to equity rate of return series. When authors speak of mean reversion in stock prices, it is ...
The impact of stock recommendations given on Dutch television
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... performs approximately 3% better than the market. While the average sell recommendation performs 4.5% worse than the market. The biggest initial reaction is reported for the stocks with the smallest market capitalization. The small cap stocks show the biggest outperformance in the first few days. Se ...
V 1 +n($m)
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... price (if the option is eventually exercised) will be paid later. The time difference involved in the two payment amounts implies that one of the two should be adjusted by an interest rate factor. Second, there may be brokerage or other expenses associated with the purchase of an option, and there m ...
Trends in Institutional Investor Use of Fixed Income ETFs
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... Source: Greenwich Associates 2015 U.S. Fixed Income ETF Study Fund assets and trading volume compiled from Bloomberg. Trading volumes based on cumulative monthly ADV from the period 12/31/2007– 12/31/2014. “Five largest credit ETFs” determined by ranking the total net asset value of the funds as of ...
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... Limited, a new generation supplier of real-time market data and trading systems. In July 2004 the London Stock Exchange moved from Thread needle Street to Paternoster Square (EC4) close to St Paul's Cathedral, still within the "Square Mile" (the City of London). It was officially opened by Queen Eli ...
Geometric Average Capitalization
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... When a fund owns stocks from only one of the seven style zones (US, Canada, Latin America, Europe, Japan, Australia/NZ, and Asia ex-Japan), the geometric average capitalization of the fund can be compared to the large-, mid-, and small-cap divisions of the Morningstar Style BoxTM. In these cases, th ...
Prescription pricing
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when hedge funds betray a creditor committee`s fiduciary role
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... last two years. Strong net issuance and surging gold and silver prices were the primary drivers behind the increase in assets during this time. By construction, a passively managed commodity ...
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Equity Quantitative Study - International Swaps and Derivatives

... to eliminate data-entry errors and certain trade-reporting idiosyncrasies. For example, when reporting conversion trades (buy a put and sell a call with the same strike) or “reverse conversions”, which have two legs, counterparties often tend to report a premium of 1 for each leg rather than the act ...
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... previous day’s closing price is set for most securities. Volatility auctions occur within the day if a stock moves static +/-10% from last close and dynamic +/-2% from previous trade. They last approximately 5 minutes. Closing Auction As of January 30th, 2017: If a stock indicates more than +/- 3% f ...
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... • The hurdle rate should be higher for riskier projects and reflect the financing mix used - owners’ funds (equity) or borrowed money (debt) • Returns on projects should be measured based on cash flows generated and the timing of these cash flows; they should also consider both positive and negative ...
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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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