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量化交易以及技术指标（14）
TS001&&& & & & THE NEW SCIENCE OF TECHNICAL ANALYSIS&&& & & &&&552
& & & & 技术分析新思维(Thomas R. DeMark) & & & &&
TS002 & & & & SMARTER TRADING:Improving Performance in Changing Markets & & & & 365
& & & & 潇洒买卖(Perry Kanfman) & & & &&
TS003 & & & & COMPUTER ANALYSIS OF THE FUTURES MARKETS & & & & 702
& & & & 期货市场电脑分析(Charies LeBeau & David Lucas) & & & &&
TS004 & & & & THE BUSINESS ONE IRWIN GUIDE TO TRADING SYSTEMS & & & & 702
& & & & IRWIN公司的买卖程式指南(Bruce Babcock, Jr.) & & & &&
TS005 & & & & THE TRADING SYSTEMS TOOLKIT & & & & 608
& & & & 买卖程式工具箱(Joe Krutsinger) & & & &&
TS006 & & & & DESIGN,TESTING,AND OPTIMIZATION OF TRADING SYSTEMS & & & & 552
& & & & 买卖程式的设计、测试和优化 (Robert Pardo) & & & &&
TS008 & & & & STOCK MARKET TRADING SYSTEMS & & & & 515
& & & & 股票市场交易系统(G.Appel & F.Hitschier) & & & &&
TS009 & & & & THE TAYLOR TRADING TECHNIQUE & & & & 364
& & & & TAYLOR交易技术(George D.Taylor) & & & &&
TS010 & & & & TRIDENT:A TRADING STRATEGY & & & & 609
& & & & 三叉戟交易策略(Charles L.Lindsay) & & & &&
TS011 & & & & THE RSL MARKET TIMING SYSTEM & & & & 609
& & & & RSL市场预测系统(Humphrey Lloyd) & & & &&
TS012 & & & & CAMPAIGN TRADING:Tactics & Strategies to Exploit the Markets & & & & 608
& & & & 冠军炒家：开拓投资市场的战术与战略(John Sweeney) & & & &&
TS013 & & & & TRADING IN CHOPPY MARKETS & & & & 554
& & & & 如何在变幻莫测的市场进行交易 (Robert M.Barnes)
TS014&&& & & & TRADING SYSTEM ANALYSIS&&& & & &&&644
& & & & 交易系统分析(Robert M.Barnes) & & & &&
TS015 & & & & TRADING SYSTEMS:Secrets of the masters & & & & 558
& & & & 交易系统：主宰市场的秘诀(Joe Krutsinger) & & & &&
TS016 & & & & THE MASTER TRADER & & & & 506
& & & & 投资交易大师(Mitchell Holland) & & & &&
TS017 & & & & USING EASYLANGUAGE & & & & 1030
& & & & 电脑分析软件简易编程语言应用(Arthur G. Putt) & & & &&
TS018 & & & & TRADING THE PLAN & & & & 506
& & & & 按既定计划进行交易(Robert DEEL) & & & &&
TS019 & & & & THE MAGIC OF MOVING AVERAGES & & & & 365
& & & & 移动平均线的魔力() & & & &&
TS020 & & & & TRADING SECRETS OF THE INNER CIRCLE & & & & 552
& & & & 内在循环的交易秘诀(Goodwin) & & & &&
TS021 & & & & BEYOND TECHNICAL ANALYSIS & & & & 842
& & & & 超越技术分析(Tushar S.Chande) & & & &&
TS022 & & & & TECHNICAL TRADING SYSTEMS FOR COMMODITIES & STOCKS & & & & 514
& & & & 商品期货与股票技术交易系统(Charles Patel) & & & &&
TS023 & & & & TRADE YOUR WAY TO FINANCIAL FREEDOM & & & & 365
& & & & 以你自己的交易方式自由进出金融市场(Van K.Tharp) & & & &&
TS024 & & & & TRADING SYSTEM AND METHODS & & & & 888
& & & & 交易系统与交易方法(Perry J.Kaufman) & & & &&
TS025 & & & & SEASONALITY SYSTEMS,STRATEGIES & SIGNALS & & & & 646
& & & & 季节性交易系统、交易策略与交易信号(Jake Bernstein)
TS026&&& & & & ASK Mr.EASYLANGUAGE&&& & & &&&552
& & & & 电脑分析软件简易编程语言指南(Samuel Knight Tennis) & & & &&
TS027 & & & & SHORT-TERM TRADING WITH PRICE PATTERNS & & & & 562
& & & & 短线交易与价格形态(MICHAEL HARRIS) & & & &&
TS028 & & & & THE ENCYCLOPEDIA OF TRADING STRATEGIES & & & & 655
& & & & 交易策略的百科全书(KATZ AND McCORMICK)
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An automated trading system (ATS) is a computer program that creates orders and automatically submits them to a market center or exchange. The program will automatically generate orders based on predefined set of rules using a
which is often based on
but can also be based on input from other electronic sources.
Automated trading systems are often used with
in automated , including , "", and automated exchanges. Automated trading systems and
can execute repetitive tasks at speeds with orders of magnitude greater than any human equivalent. Traditional risk controls and safeguards that relied on human judgment are not appropriate for automated trading and this has caused issues such as the . New controls such as
or 'circuit breakers' have been put in place in some electronic markets to deal with automated trading systems.
As of 2014, more than 75 percent of the stock shares traded on United States exchanges (including the
and ) originate from automated trading system orders. ATSs can be designed to trade stocks, ,
based on a predefined set of rules which determine when to enter an order, when to exit a position and how much money to invest in each trading product. Tradi some are designed to pick market tops and bottoms, others to follow a trend, and others involve complex strategies including randomizing orders to make them less visible in the marketplace.
Backtesting of a
involves programmers running the program using historical
in order to determine whether the underlying
guiding the system may produce the expected results. Developers can create backtesting software to enable a trading system designer to develop and test their trading systems using historical market data to optimize the results obtained with the historical data. Although backtesting of automated trading systems cannot accurately determine future results, an automated trading system can be backtested using historical prices to see how the system theoretically would have performed if it had been active in a past market environment.
Forward testing of an algorithm can also be achieved using simulated trading with real-time market data to help confirm the effectiveness of the trading strategy in the current market and may be used to reveal issues inherent in the computer code.
Automated trading or high frequency trading causes regulatory concerns as a contributor to market fragility.
United States regulators have published releases discussing several types of risk controls that could be used to limit the extent of such disruptions, including financial and regulatory controls to prevent the entry of erroneous orders as a result of computer malfunction or human error, the breaching of various regulatory requirements, and exceeding a credit or capital limit.
The use of
(HFT) strategies has grown substantially over the past several years and drives a significant portion of activity on U.S. markets. Although many HFT strategies are legitimate, some are not and may be used for manipulative trading. Given the scale of the potential impact that these practices may have, the surveillance of abusive algorithms remains a high priority for regulators. FINRA has reminded firms using HFT strategies and other trading algorithms of their obligation to be vigilant when testing these strategies pre- and post-launch to ensure that the strategies do not result in abusive trading.
FINRA continues to be concerned about the use of so-called "momentum ignition strategies" where a market participant attempts to induce others to trade at artificially high or low prices. Examples of this activity include layering and spoofing strategies where a market participant places a nonbona fide order on one side of the market (typically, but not always, above the offer or below the bid) in an attempt to bait other market participants to react to the non-bona fide order and trade with another order on the other side of the market.
Other examples of problematic HFT or algorithmic activity include order entry strategies related to placing orders near the open or close of regular trading hours that involve distorting disseminated market imbalance indicators through the entry of non-bona fide orders and/or aggressive trading activity near the open or close.
FINRA also continues to focus concern on the entry of problematic HFT and algorithmic activity through sponsored participants who initiate their activity from outside of the United States. In this regard, FINRA reminds firms of their surveillance and control obligations under the SEC's Market Access Rule and Notice to Members 04-66, as well as potential issues related to treating such accounts as customer accounts, anti-money laundering and margin levels, as highlighted in Regulatory Notice 10-18
and the SEC's Office of Compliance Inspections and Examination's National Exam Risk Alert dated September 29, 2011.
FINRA conducts surveillance to identify cross-market, cross-product manipulation of the price of underlying equity securities, typically through abusive trading algorithms, and strategies used to close out pre-existing option positions at favorable prices or establish new option positions at advantageous prices.
In recent years, there have been a number of algorithmic trading malfunctions that caused substantial market disruptions. These raise concern about firms' ability to develop, implement and effectively supervise their automated systems. The
(FINRA) has stated that it will assess whether firms' testing and controls related to algorithmic trading and other automated trading strategies and trading systems are adequate in light of the
and firms' supervisory obligations. This assessment may take the form of examinations and targeted investigations. Firms will be required to address whether they conduct separate, independent and robust pre-implementation testing of algorithms and trading systems and whether the firm's legal, compliance and operations staff are reviewing the design and development of the algorithms and trading systems for compliance with legal requirements. FINRA will review whether a firm actively monitors and reviews algorithms and trading systems once they are placed into production systems and after they have been modified, including procedures and controls used to detect potential trading abuses such as wash sales, marking, layering and momentum ignition strategies. Finally, firms will need to describe their approach to firm-wide disconnect or “kill” switches, as well as procedures for responding to catastrophic system malfunctions.
Examples of recent substantial market disruptions include the following:
On May 6, 2010, the
declined about 1,000 points (about 9 percent) and recovered those losses within minutes. It was the second-largest point swing (1,010.14 points) and the largest one-day point decline (998.5 points) on an intraday basis in the Average's history. This market disruption became known as the
and resulted in U.S. regulators issuing new regulations to control market access achieved through automated trading.
On August 1, 2012, between 9:30 a.m. and 10:00 a.m. EDT,
lost four times its 2011 net income. Knight's CEO Thomas Joyce stated, on the day after the market disruption, that the firm had "all hands on deck" to fix a bug in one of Knight's trading algorithms that submitted erroneous orders to exchanges for nearly 150 different stocks. Trading volumes soared in so many issues, that the
(SYMBOL: SPY), which is generally the most heavily traded U.S. security, became the 52nd-most traded stock on that day, according to Eric Hunsader, CEO of market data service . Knight shares closed down 62 percent as a result of the trading error and Knight Capital nearly collapsed. Knight ultimately reached an agreement to merge with , a Chicago-based high-speed trading firm.
Lemke, T Lins, Gerald. "2:25-2:29". Soft Dollars and Other Trading Activities ( ed.). Thomson West.  .
(PDF). Commodity Futures Trading Commission. September 9, .
. 29 May 2013.
Giovanni Cespa, Xavier Vives (February 2017).
(PDF). Working Papers Series.
(2020). This supports regulatory concerns about the potential drawbacks of automated trading due to operational and transmission risks and implies that fragility can arise in the absence of order flow toxicity.
. Archived from
. Archived from
matthewaphilips, Matthew Philips. .
Dealbook. .
matthewaphilips, Matthew Philips. .
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Mean Reversion Trading Systems Perfect Paperback – January 15, 2013
by Dr Howard B Bandy&&(Author)
Practical and fully disclosed methods for swing trading: Trading frequently and holding a few days. Identifying overbought and oversold conditions. Trading major ETFs and liquid equities.
载入中......
偷着乐，瞎忙。
thanks, only sample chapters.
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