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Trading Rules and Practices
Trading Rules and Practices

... dividend received, the ex-day price drop will be rounded down to the nearest tick, so that the change in stock price on the ex-dividend day is always less than the amount of the dividend. Similarly, when a dividend received is between ticks, there will be positive abnormal returns. Frank and Jaganna ...
Testing for imperfect competition at the Fulton fish market - U
Testing for imperfect competition at the Fulton fish market - U

... Almost all tests for competition have been performed in oligopolistic industries with high entry barriers, in which an initial case study would suggest anticompetitive behavior.1 These studies use data that have been gathered from public sources such as trade journals, regulatory bodies, or court ca ...
Trading Strategies in the Current Commodity Market Environment
Trading Strategies in the Current Commodity Market Environment

... noted that history does provide some rare examples of trend-shifts upwards in spot commodity prices, and that perhaps the current era will be another such rare example for agricultural prices. In future issues of Commodity Risk, we will cover the flip side of these return opportunities, namely how t ...
The effect of short interest on the subsequent stock
The effect of short interest on the subsequent stock

... 1990), this number had been doubled by 2005 (Asquith et al., 2005). Similarly, Boehmer et al. (2008) reported that more than 20% of total trading volume was sold short. In 2009, this number had even increased to 32% of NASDAQ volume according to Diether et al. (2009). Hence one can see the increasin ...
Volume-Synchronized Probability of Informed Trading (VPIN
Volume-Synchronized Probability of Informed Trading (VPIN

... measures that are more suitable to examine their association with VPIN. In the first part of the thesis, we aim to choose a best VPIN calculation algorithm that has the most accurate risk-warning effect. This part serves as the basis for the thesis by choosing a VPIN metric that has the most accura ...
MiFID II Implementation
MiFID II Implementation

... otherwise, to take measures to facilitate the earliest possible execution of that order by making it public…Member States may decide that investment firms comply with that obligation by transmitting that client limit order to a trading venue…”  This reflects the current arrangement and the intentio ...
Chapter 2 Securities Markets and Transactions
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The impact of market liquidity in times of stress on corporate bond
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... If large bonds are indeed more liquid then this liquidity should be priced by the market. One standard, and relatively clean, way to test this is to put bond spreads at issuance as the dependent variable of a regression and determine if the liquidity factor affects bond spreads in the predicted dire ...
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... The role of hedging in demand-based derivative pricing The classic hedging argument should remain an important consideration in risk premium and demand analysis on derivatives. When one takes on a derivative position, one does not directly forecast its risk and ask for a compensation for the foreca ...
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Should Tender Offer Arbitrage Be Regulated

... HARV. J.LEGIS. 431, 432-33 (1968). This increase in tender offers gave rise to passage of the Williams Act, but that Act in no way dampened the incidence of tender offers. On the contrary, such offers have occurred with increasing frequency in the 1970s. See, e.g., Ehrbar, supra note 14, at 83 (refe ...
How to Model a Financial Bubble Mathematically Lecture 1 April 12, 2013
How to Model a Financial Bubble Mathematically Lecture 1 April 12, 2013

... has No Arbitrage if and only if there exists another probability measure Q ∼ P such that S is a martingale • Second Version: David Kreps, circa 1981 realized that No Arbitrage was not a strong enough condition to guarantee such a result in a more general case. He created a new condition and called i ...
Catching falling knives: speculating on market overreaction
Catching falling knives: speculating on market overreaction

... composition of orders and show how their impact on the market differs from the one exerted by traditional informed traders. Non-fundamental information is particularly relevant in periods of financial turbulence: some agents have to sell large amounts due to liquidity constraints, and other investor ...
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... After B. Mandelbrot identified the fractal structure of price fluctuations in asset markets in 1963 [1], statistical physicists have studied the economic mechanism that produces a fractal structure. Power law is an important characteristic in the fractal structure. Some research found that the size di ...
Would a Stock By Any Other Ticker Smell as Sweet? Alex Head
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... The null hypothesis is that the expected value of the daily difference is zero: H0: m = 0. The tstatistic is t= ...
What Market Believes
What Market Believes

... and produces forecasts that can capture observed deviations from standard learning behavior, such as backward induction, over-reaction and time inconsistency. In economies populated by finitely many traders in which there is more than one most accurate trader, depending on risk attitudes, the next p ...
decentralized trade mitigates the lemons problem
decentralized trade mitigates the lemons problem

... Wolinsky (1985, 1990). Except for introducing adverse selection, our model of decentralized trade is standard—in Rubinstein and Wolinsky (1985) traders engage in an alternating offer bargaining game, while in Gale (1987) one agent in a match is randomly selected to make a take-it-or-leave-it price o ...
Does high-frequency trading improve market quality?
Does high-frequency trading improve market quality?

... information. Cartea and Penalva (2013) show that HF trading raises volatility and volume. Pagnotta and Philippon (2011) show that the speed competition generally increases welfare, but decreases it when speed becomes inefficiently high. Rosu (2014) theoretically shows that volume, volatility, and li ...
“Sell in May and Go Away” Just Won`t Go Away
“Sell in May and Go Away” Just Won`t Go Away

... market-timing strategy. On average, stock returns are about 10 percentage points higher for November– April half-year periods than for May–October half-year periods. The authors also found that the sell-in-May effect is pervasive in financial markets. ...
Emergence of Networks and Market Institutions in a Large Virtual Economy ∗
Emergence of Networks and Market Institutions in a Large Virtual Economy ∗

... Economics Department, University of California Santa Cruz, CA 95064, [email protected] ...
Stock Splits, Liquidity and Limit Orders
Stock Splits, Liquidity and Limit Orders

... We find that daily share volume decreases by about 9% following a stock split. This result is consistent with Copeland (1979), Lamoureux and Poon (1987) though it differs from Desai, Nimalendran and Venkataraman (1998), who find no significant change. We find no evidence, however, of a change in to ...
week 5
week 5

... S(t) is the stock price, dS(t) is the instantaneous change in the stock price,  is the continuously compounded expected return on the stock,  is the continuously compounded standard deviation ...
the valuation of equity derivatives
the valuation of equity derivatives

... Standard contracts that are regularly traded are often referred to as “vanilla” and the more complex as “exotic”. The evolution of derivatives’ markets means there is no concise rule to classify a product as either vanilla or exotic, so what is now considered vanilla may well historically have been ...
Is it Overreaction? The Long-Horizon Performance of Value and
Is it Overreaction? The Long-Horizon Performance of Value and

... assuming that they already achieved ‘old economy’ profit margins – Zero percent cost of capital for ten years ...
Treynor Measure
Treynor Measure

... The Treynor measure is more complete because it adjusts for risk ...
The Payments System and the Market for Interbank Funds
The Payments System and the Market for Interbank Funds

... of rumors that this type of behavior was initially feared on September 11, 2001, with the communications disruptions that day affecting the Bank of New York, a large clearing bank.5 Any such gridlock was in the end averted by energetic liquidity provision by the Federal Reserve. Without significant ...
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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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