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Using Candlestick Charts to Trade Forex copy
Using Candlestick Charts to Trade Forex copy

... bottom, and the closing price of a white candle is on top. This is reversed for black candles. The “shadows” or “wicks” of the candle consist of a line protruding up from the top that visually indicates the high point of the time period, as well as a line protruding down from the bottom of the body ...
Printed Documentation - futuresource.com | futuresource.com
Printed Documentation - futuresource.com | futuresource.com

... Add a Study to a Chart ........................................................................................................... 40 Overlay a Study ...................................................................................................................... 40 Change Study Color ......... ...
Generating South African Volatility Surface
Generating South African Volatility Surface

... details of the optimisations are given in some Appendixes. ...
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Predicting Returns and Volatilities with Ultra

... Two indistinguishable classes of traders - informed and uninformed When there is good news, informed traders will buy while the rest will be buyers and sellers. When there are more buyers than sellers, there is some probability that this is due to information traders – hence prices are increased by ...
Stock Return Serial Dependence and Out-of
Stock Return Serial Dependence and Out-of

... find lead-lag relations between: big-stock portfolios and small-stock portfolios, growth-stock portfolios and value-stock portfolios, the HiTec industry portfolio and other industry portfolios, and big individual stocks and small individual stocks. Our second contribution is to characterize, both an ...
Stock Return Serial Dependence and Out-of
Stock Return Serial Dependence and Out-of

... has been documented in the literature to select portfolios of risky assets that perform well outof-sample. We tackle this task in three steps. First, we propose a vector-autoregressive (VAR) model to capture stock return serial dependence, and test its statistical significance. Second, we characteri ...
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Investor Sentiment and the Mean

... perturbing prices away from levels that would otherwise reflect a positive mean–variance tradeoff. Despite some debate with respect to the overall importance of sentiment traders, one can reasonably make the following two cases. First, sentiment traders exert greater influence during high-sentiment pe ...
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An Examination of Primary and Secondary Market Returns in Equity

... findings are consistent with the theories based on compensation to primary market participants for information production and risk taking during the roadshow.5 Third, we compare the primary and secondary market returns of equity REIT IPOs with traditional non-REIT IPOs in an effort to focus on the p ...
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Stock market liquidity and firm value

... to disguise private information and profit from it. The higher information flow that results from higher liquidity increases the signal-to-noise ratio in stock prices which increases the gain from using stock-based compensation. We do not find support for other agency-based operating performance theori ...
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Understanding Trading and Investment Warrants

... In the case of cash settled warrants, the difference between the exercise price (sometimes referred to as the exercise level) and the value of the underlying instrument at expiry is paid on settlement. ...
Night Trading: Lower Risk But Higher Returns? by Marie
Night Trading: Lower Risk But Higher Returns? by Marie

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The performance of estimators of the bid-ask

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... the floor of an Exchange by just one Member who is both buyer and seller. If a Member has matching buy and sell orders from two different customer accounts for the same contract and at the same price, he is allowed to cross the transaction (execute the deal) by matching both his client accounts. How ...
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Does Financial Development Volatility Affect Industrial Growth

... controls, Larrain (2006) finds a significantly negative coefficient on the interaction term, arguing that lower volatility output occurs in sectors with higher external dependence and in countries with better financial development. Raddatz (2006) uses the same framework to investigate whether financ ...
Causes and Consequences of Margin Levels in Futures Markets
Causes and Consequences of Margin Levels in Futures Markets

... the lack of readily available data on historical margins. Gay et al. (1986) and Fishe et al. (1990), who consider commodity futures, and Goldberg and Hachey (1992), who consider foreign exchange futures, find that margin levels are primarily determined by price volatility. Fenn and Kupiec (1993) find ...
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Common Factors in Return Seasonalities

... We show that return seasonalities exist almost everywhere, are remarkably persistent over time, and are often so large that they completely overwhelm the unconditional differences in expected asset returns. Although seasonality strategies are immensely risky because of their exposures to common fact ...
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Asset Liquidity and Stock Liquidity

... different time periods. Using the Fama-MacBeth (1973) approach, we also find a strong, positive relation between asset liquidity and stock liquidity in the cross section. Thus, our empirical analysis shows that, on average, the balance sheet relation between asset liquidity and stock liquidity does ...
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Takeovers, Freezeouts, and Risk Arbitrage

... of shares, provides a threat that forces the bidder to o¤er a high preemptive bid, even though there may be no de facto trading during the tender o¤er (see also Fishman (1988)). A concentrated ownership structure allows target shareholders to leverage their rights and increase their bargaining power ...
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... increments. In other words, the accuracy of the fair variance is more prone to truncation errors. Safex publishes volatility skews for a strike range of 70% to of 130%. The strike range used will thus be from 70% moneyness to 130% moneyness. For a small number of symmetrical options (< 20) we have t ...
Speculation and Risk Sharing with New Financial Assets
Speculation and Risk Sharing with New Financial Assets

... diversi…cation and the sharing of risks.1 However, this view does not take into account that new assets are often associated with much uncertainty, especially because they do not have a long track record. Belief disagreements come as a natural by-product of this uncertainty and change the implicatio ...
Risk and Long-Run IPO Returns - Berkeley-Haas
Risk and Long-Run IPO Returns - Berkeley-Haas

... due to the extremely low returns earned by companies that went public during the period 1970{ 1972. The equal-weighted BHAR for size-matched rms is 68.7%, resulting in a relative IPO underperformance of BHAAR = ;28:8%, which compares to the BHAAR of ;50:7% reported for the IPO sample in Loughran an ...
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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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