Evolution of Electronic Trading

Standard

Historical Background and Electronification of Securities Trading The electronification of securities trading commenced 40 years ago, when the National Association of Securities Dealers (NASD) started its computer-assisted market making system for automated quotation (AQ) in the U.S., forming what is nowadays known as NASDAQ (Black 1971a; Black 1971b). In Europe, the first computer-assisted equities exchanges launched their trading services in the 1980s, but not until the 1990s securities trading was organized in fully automated exchanges. The majority of market models of those fully automated equities exchanges are implemented as electronic central limit order books (CLOB), which store market participants‘ trading interests visible to and executable for all other connected traders. According to Pagano and Roell (1996) and Jain (2005), the transparency induced by the introduction of CLOBs reduces information asymmetry, enhances liquidity and supports efficient price determination. While prices were determined manually in floor trading, orders are matched automatically according to price-time priority in electronic trading systems.4 By applying uniform rules to all market participants, operational fairness and fair access to the respective trading venue shall be ensured (Harris 2003). Thereby, the electronification of securities markets and the electronic connectivity of market participants went hand in hand, leading to decentralized market access. Physical trading floors were not required any longer and have mostly been replaced by electronic trading systems. Investors can submit their orders electronically to a market‘s backend from remote locations. On the investors‘ side, human trading processes have been substituted by electronic systems, too. While systems generating automated quotes and stop-loss orders were the first technological artifacts that conquered the trading process, in recent years information technology (IT) has successively established and can nowadays be found on every stage of trading and post-trading processes. State-of-the-art technology has developed as a crucial competitive factor for market operators in recent decades and market participants themselves continued to further automate and optimize their trading processes along the entire value chain. 4 Although slight modifications exist, price-time priority has established as a de-facto standard in securities trading globally.

2.2 Drivers for Widespread Usage of Algorithmic/High-Frequency Trading The emergence of AT and HFT in the past went hand in hand with other market structural developments in European securities trading. In the following, multiple drivers for the rise of AT and HFT are identified, i.e. new market access models and fee structures, a significant reduction of latency and an increase in competition for and fragmentation of order flow5. In most markets, only registered members are granted direct access.6 Hence, those members are the only ones allowed to conduct trading directly, leading to their primary role as market access intermediaries for other investors. Market members performing that function are referred to as brokers7. In the past, those access intermediaries transformed their clients‘ general investment decisions into orders that were allocated to appropriate market venues. As the cost awareness of the buy side has increased over the years, brokers have begun to provide different market access models, i.e. direct market access (DMA) and sponsored access (SA). When an investor makes use of DMA, his orders are no longer touched by the broker, but rather forwarded directly to the markets through the broker‘s infrastructure. One key characteristic of DMA presents the fact that the respective broker can conduct pre-trade risk checks. Sponsored access (SA) represents a slightly different possibility for the buy side to access a marketplace. Here, an investment firm (that is not a member of the respective market) is enabled to route its orders to the market directly using a registered broker‘s member ID without using the latter‘s infrastructure (in contrast to DMA). Resulting from this setup, the sponsor can conduct pre-trade risk checks only if the option to conduct those checks is provided by the trading venue (filtered SA). In case of unfiltered (also referred to as naked) SA, the sponsor only receives a drop copy of each order to control his own risk exposure. A reduction in latency represents the main advantage of SA over DMA from a non-member firm‘s perspective and therefore is highly attractive for AT or HFT based trading strategies. Another driver for the success of AT and HFT is the new trading fee structures found in Europe. Market operators try to attract order flow that is generated automatically (i) by applying special discounts for algorithmic orders within their fee schedules. MTFs 5 Obviously, this list of drivers is not exhaustive. Other drivers that could be listed additionally include, e.g., the growing number of proprietary trading firms founded by former investment bank staffers and other mathematically/technically oriented traders. 6 Access is restricted to registered market members mainly due to post-trading issues, i.e. clearing and settlement. A pre-requisite for trading directly in a market is an approved relationship with the respective clearing house(s). 7 As brokers basically offer their services to other market participants they are also referred to as the sell side. Respective clients purchasing those services are referred to as the buy side (Harris 2003). implemented (ii) fee schedules with very aggressive levels to compete with incumbent exchanges. Furthermore, some MTFs like e.g. Chi-X, BATS or Turquoise started offering pricing schemes that are a novelty to European exchange fee schedules: (iii) asymmetric pricing (Jeffs 2009; Mehta 2008). With asymmetric pricing, market participants removing liquidity from the market (taker) are charged a higher fee while traders that submit liquidity to the market (maker) are charged a lower fee or are even provided with a rebate. Such an asymmetric fee structure is supposed to incentivize liquidity provision. Faced with the MTFs‘ aggressive pricing strategies, many European exchanges were urged to lower their fee levels as well, while others even adopted the asymmetric pricing regime. As will be further explained in section 4, market participants have specialized in making profits from those fee structures by applying trading algorithms. Although latency has always been of importance in securities trading, its role is more intensely stressed by market participants with AT/HFT on the rise. In traditional trading involving human interaction on trading floors, a trader could also profit from trading faster than others. Traders often benefited from their physical abilities, e.g. when they could run faster across the trading floor or shout louder than their counterparts and thus drew a market maker‘s or specialist‘s attention to their trading intentions. With algorithms negotiating on prices nowadays, those physical advantages are no longer needed. Nevertheless, in markets trading at high speed, the capability to receive data and submit orders at lowest latency is essential. When the market situation at the arrival of an order differs significantly from the market situation, which led to that particular trading decision, there is a risk that the order is no longer appropriate in terms of size and/or limit (Harris 2003; Brown and Holden 2005; Liu 2009). Hence, an order bears the risk of being executed at an improper price or not being executed at all. To minimize that risk, reducing the delay of data communication with the market‘s backend is of utmost importance to AT/HFT based strategies concerning market data receipt, order submissions and execution confirmations. In order to reduce latency8, automated traders make use of co-location or proximity services that are provided by a multitude of market operators.9 By co-locating their servers, market participants can place their trading machines directly adjacent to the market operator‘s infrastructure. Regulation in European securities trading has promoted the market penetration of AT/HFT as well: with the advent of MiFID (European Commission 2004), the European equity trading landscape became more complex. As intended by the regulator, competition among market venues has increased, and the available liquidity in a security is scattered among different market venues (Gomber et al. 2011b). This fragmentation of markets is a direct consequence of the harmonized level playing field for different types of trading venues intended by MiFID. In order to attract market share, new venues challenged the incumbent exchanges by lower trading fees and forced them to adapt their pricing schemes as well. These recently emerged MTFs steadily increased their market penetration. The lowered costs of trading (both explicit and implicit10) are beneficial for all market participants including issuers, as lower trading costs increase liquidity and thereby lower the cost of capital. However, Over the Counter (OTC)-trading11 represents a high and stable market share around 40% (see Figure 112). 0%20%40%60%80%100%OTCRMMTF Figure 1: Distribution of trading among regulated markets, MTFs and OTC, based on Thomson Reuters (2008, 2009, 2010) Market participants are urged to compare potential prices offered as well as different fee regimes across a multitude of market venues, which imposes increased search costs for the best available price. In addition, dark pools and OTC trading, which are exempted from pre-trade transparency, distort the clear picture of available prices. Against this background, algorithms support market participants to benefit from competition between markets and help to overcome negative effects from fragmentation of order flow

This is Jill, manager of Zhejiang Kaixin Industrial & Trade Co.,ltd
, we have manufacturing and trading high quality since 2008

If you are interested in me our our company ,please feel free to contact me.

Have a nice day!

our company website is :

www.gardenfurniture-china.com

 

China garden furniture China garden furniture

Drivers for Widespread Usage of Algorithmic/High-Frequency Trading

Standard

The emergence of AT and HFT in the past went hand in hand with other market structural developments in European securities trading. In the following, multiple drivers for the rise of AT and HFT are identified, i.e. new market access models and fee structures, a significant reduction of latency and an increase in competition for and fragmentation of order flow5. In most markets, only registered members are granted direct access.6 Hence, those members are the only ones allowed to conduct trading directly, leading to their primary role as market access intermediaries for other investors. Market members performing that function are referred to as brokers7. In the past, those access intermediaries transformed their clients‘ general investment decisions into orders that were allocated to appropriate market venues. As the cost awareness of the buy side has increased over the years, brokers have begun to provide different market access models, i.e. direct market access (DMA) and sponsored access (SA). When an investor makes use of DMA, his orders are no longer touched by the broker, but rather forwarded directly to the markets through the broker‘s infrastructure. One key characteristic of DMA presents the fact that the respective broker can conduct pre-trade risk checks. Sponsored access (SA) represents a slightly different possibility for the buy side to access a marketplace. Here, an investment firm (that is not a member of the respective market) is enabled to route its orders to the market directly using a registered broker‘s member ID without using the latter‘s infrastructure (in contrast to DMA). Resulting from this setup, the sponsor can conduct pre-trade risk checks only if the option to conduct those checks is provided by the trading venue (filtered SA). In case of unfiltered (also referred to as naked) SA, the sponsor only receives a drop copy of each order to control his own risk exposure. A reduction in latency represents the main advantage of SA over DMA from a non-member firm‘s perspective and therefore is highly attractive for AT or HFT based trading strategies. Another driver for the success of AT and HFT is the new trading fee structures found in Europe. Market operators try to attract order flow that is generated automatically (i) by applying special discounts for algorithmic orders within their fee schedules. MTFs 5 Obviously, this list of drivers is not exhaustive. Other drivers that could be listed additionally include, e.g., the growing number of proprietary trading firms founded by former investment bank staffers and other mathematically/technically oriented traders. 6 Access is restricted to registered market members mainly due to post-trading issues, i.e. clearing and settlement. A pre-requisite for trading directly in a market is an approved relationship with the respective clearing house(s). 7 As brokers basically offer their services to other market participants they are also referred to as the sell side. Respective clients purchasing those services are referred to as the buy side (Harris 2003).

implemented (ii) fee schedules with very aggressive levels to compete with incumbent exchanges. Furthermore, some MTFs like e.g. Chi-X, BATS or Turquoise started offering pricing schemes that are a novelty to European exchange fee schedules: (iii) asymmetric pricing (Jeffs 2009; Mehta 2008). With asymmetric pricing, market participants removing liquidity from the market (taker) are charged a higher fee while traders that submit liquidity to the market (maker) are charged a lower fee or are even provided with a rebate. Such an asymmetric fee structure is supposed to incentivize liquidity provision. Faced with the MTFs‘ aggressive pricing strategies, many European exchanges were urged to lower their fee levels as well, while others even adopted the asymmetric pricing regime. As will be further explained in section 4, market participants have specialized in making profits from those fee structures by applying trading algorithms. Although latency has always been of importance in securities trading, its role is more intensely stressed by market participants with AT/HFT on the rise. In traditional trading involving human interaction on trading floors, a trader could also profit from trading faster than others. Traders often benefited from their physical abilities, e.g. when they could run faster across the trading floor or shout louder than their counterparts and thus drew a market maker‘s or specialist‘s attention to their trading intentions. With algorithms negotiating on prices nowadays, those physical advantages are no longer needed. Nevertheless, in markets trading at high speed, the capability to receive data and submit orders at lowest latency is essential. When the market situation at the arrival of an order differs significantly from the market situation, which led to that particular trading decision, there is a risk that the order is no longer appropriate in terms of size and/or limit (Harris 2003; Brown and Holden 2005; Liu 2009). Hence, an order bears the risk of being executed at an improper price or not being executed at all. To minimize that risk, reducing the delay of data communication with the market‘s backend is of utmost importance to AT/HFT based strategies concerning market data receipt, order submissions and execution confirmations. In order to reduce latency8, automated traders make use of co-location or proximity services that are provided by a multitude of market operators.9 By co-locating their servers, market participants can place their trading machines directly adjacent to the market operator‘s infrastructure. 8 Actually, quantifying the economic value of low latency is hardly possible as measuring latency is difficult and the methodologies applied are inconsistent (Ende et al. 2011). 9 Proximity services refer to facility space that is made available by specialized network providers to market participants for the purpose of locating their network and computing hardware closer to the matching engines specifically in order to optimize the location with respect to multiple venues and to maximize flexibility. Co-location services are provided by a market operator and refer to a setup where a market participant‗s hardware is located directly next to a market‘s matching engine.
Regulation in European securities trading has promoted the market penetration of AT/HFT as well: with the advent of MiFID (European Commission 2004), the European equity trading landscape became more complex. As intended by the regulator, competition among market venues has increased, and the available liquidity in a security is scattered among different market venues (Gomber et al. 2011b). This fragmentation of markets is a direct consequence of the harmonized level playing field for different types of trading venues intended by MiFID. In order to attract market share, new venues challenged the incumbent exchanges by lower trading fees and forced them to adapt their pricing schemes as well. These recently emerged MTFs steadily increased their market penetration. The lowered costs of trading (both explicit and implicit10) are beneficial for all market participants including issuers, as lower trading costs increase liquidity and thereby lower the cost of capital. However, Over the Counter (OTC)-trading11 represents a high and stable market share around 40% (see Figure 112). 0%20%40%60%80%100%OTCRMMTF Figure 1: Distribution of trading among regulated markets, MTFs and OTC, based on Thomson Reuters (2008, 2009, 2010)
Market participants are urged to compare potential prices offered as well as different fee regimes across a multitude of market venues, which imposes increased search costs for the best available price. In addition, dark pools and OTC trading, which are exempted from pre-trade transparency, distort the clear picture of available prices. Against this background, algorithms support market participants to benefit from competition between markets and help to overcome negative effects from fragmentation of order flow.

This is Jill, manager of Zhejiang Kaixin Industrial & Trade Co.,Ltd
, we have manufacturing and trading high quality since 2008

If you are interested in me our our company ,please feel free to contact me.

Have a nice day!

our company website is :

www.gardenfurniture-china.com

China garden furniture China garden furniture

Historical Background and Electronification of Securities Trading

Standard

The electronification of securities trading commenced 40 years ago, when the National Association of Securities Dealers (NASD) started its computer-assisted market making system for automated quotation (AQ) in the U.S., forming what is nowadays known as NASDAQ (Black 1971a; Black 1971b). In Europe, the first computer-assisted equities exchanges launched their trading services in the 1980s, but not until the 1990s securities trading was organized in fully automated exchanges. The majority of market models of those fully automated equities exchanges are implemented as electronic central limit order books (CLOB), which store market participants‘ trading interests visible to and executable for all other connected traders. According to Pagano and Roell (1996) and Jain (2005), the transparency induced by the introduction of CLOBs reduces information asymmetry, enhances liquidity and supports efficient price determination. While prices were determined manually in floor trading, orders are matched automatically according to price-time priority in electronic trading systems.4 By applying uniform rules to all market participants, operational fairness and fair access to the respective trading venue shall be ensured (Harris 2003). Thereby, the electronification of securities markets and the electronic connectivity of market participants went hand in hand, leading to decentralized market access. Physical trading floors were not required any longer and have mostly been replaced by electronic trading systems. Investors can submit their orders electronically to a market‘s backend from remote locations. On the investors‘ side, human trading processes have been substituted by electronic systems, too. While systems generating automated quotes and stop-loss orders were the first technological artifacts that conquered the trading process, in recent years information technology (IT) has successively established and can nowadays be found on every stage of trading and post-trading processes. State-of-the-art technology has developed as a crucial competitive factor for market operators in recent decades and market participants themselves continued to further automate and optimize their trading processes along the entire value chain.

This is Jill, manager of Zhejiang Kaixin Industrial & Trade Co.,Ltd
, we have manufacturing and trading high quality since 2008

If you are interested in me our our company ,please feel free to contact me.

Have a nice day!

our company website is :

www.gardenfurniture-china.com

China garden furniture China garden furniture

THE SCIENTIFIC APPROACH TO SYSTEM DEVELOPMEN

Standard

This book is intended to accomplish a systematic and detailed analysis of theindividual components that make up a complete trading system. We are propos-ing nothing less than a scientific study of entries, exits, and other trading systemelements. The basic substance of the scientific approach as applied herein isas f0110ws:1. The object of study, in this case a trading system (or one or more of itselements), must be either directly or indirectly observable, preferablywithout dependence on subjective judgment, something easily achieved with proper testing and simulation software when working with com-plete mechanical trading systems.2. An orderly means for assessing the behavior of the object of study mustbe available, which, in the case of trading systems, is back-testing overlong periods of historical data, together with, if appropriate, the applica-tion of various models of statistical inference, the aim of the latter beingto provide a fix or reckoning of how likely a system is to hold up in thefuture and on different samples of data.3. A method for making the investigative task tractable by holding mostparameters and system components fixed while focusing upon the effectsof manipulating only one or two critical elements at a time.The structure of this book reflects the scientific approach in many ways.Trading systems are dissected into entry and exit models. Standardized methods forexploring these components independently are discussed and implemented, leadingto separate sections on entries and exits. Objective tests and simulations are run,and statistical analyses are performed. Results are presented in a consistent mannerthat permits direct comparison. This is “old hat” to any practicing scientist.Many traders might be surprised to discover that they, like practicing scien-tists, have a working knowledge of the scientific method, albeit in different guise!Books for traders often discuss “paper trading” or historical back-testing, or pre-sent results based on these techniques. However, this book is going to be moreconsistent and rigorous in its application of the scientific approach to the prob-lem of how to successfully trade the markets. For instance, few books in whichhistorical tests of trading systems appear offer statistical analyses to assess valid-ity and to estimate the likelihood of future profits. In contrast, this book includesa detailed tutorial on the application of inferential statistics to the evaluationof trading system performance.Similarly, few pundits test their entries and exits independently of oneanother. There are some neat tricks that allow specific system components to betested in isolation. One such trick is to have a set of standard entry and exit strate-gies that remain fixed as the particular entry, exit, or other element under study isvaried. For example, when studying entry models, a standardized exit strategy willbe repeatedly employed, without change, as a variety of entry models are testedand tweaked. Likewise, for the study of exits, a standardized entry technique willbe employed. The rather shocking entry technique involves the use of a randomnumber generator to generate random long and short entries into various markets!Most traders would panic at the idea of trading a system with entries based on thefall of the die; nevertheless, such entries are excellent in making a harsh test foran exit strategy. An exit strategy that can pull profits out of randomly enteredtrades is worth knowing about and can, amazingly, be readily achieved, at least for the S&P 500 (Katz and McCormick, March 1998, April 1998). The tests will bedone in a way that allows meaningful comparisons to be made between differententry and exit methods.To summarize, the core elements of the scientific approach are:1. The isolation of system elements2. The use of standardized tests that allow valid comparisons3. The statistical assessment of resultsTOOLS AND MATERIALS NEEDED FOR THE SCIENTIFICAPPROACHBefore applying the scientific approach to the study of the markets, a number ofthings must be considered. First, a universe of reliable market data on which toperform back-testing and statistical analyses must be available. Since this book isfocused on commodities trading, the market data used as the basis for our universeon an end-of-day time frame will be a subset of the diverse set of markets suppliedby Pinnacle Data Corporation: these include the agriculturals, metals, energyresources, bonds, currencies, and market indices. Intraday time-frame trading isnot addressed in this book, although it is one of our primary areas of interest thatmay be pursued in a subsequent volume. In addition to standard pricing data,explorations into the effects of various exogenous factors on the markets some-times require unusual data. For example, data on sunspot activity (solar radiationmay influence a number of markets, especially agricultural ones) was obtainedfrom the Royal Observatory of Belgium.Not only is a universe of data needed, but it is necessary to simulate one ormore trading accounts to perform back-testing. Such a task requires the use of atrading simulator, a software package that allows simulated trading accounts to becreated and manipulated on a computer. The C+ + Trading Simulator fromScientific Consultant Services is the one used most extensively in this bookbecause it was designed to handle portfolio simulations and is familiar to theauthors. Other programs, like Omega Research’s TradeStation or SystemWriterPlus, also offer basic trading simulation and system testing, as well as assortedcharting capabilities. To satisfy the broadest range of readership, we occasionallyemploy these products, and even Microsoft’s Excel spreadsheet, in our analyses.Another important consideration is the optimization of model parameters.When running tests, it is often necessary to adjust the parameters of some compo-nent (e.g., an entry model, an exit model, or some piece thereof) to discover thebest set of parameters and/or to see how the behavior of the model changes as itsparameters change. Several kinds of model parameter optimizations may be conducted. In manual optimization, the user of the simulator specifies a parameter thatis to be manipulated and the range through which that parameter is to be stepped;the user may wish to simultaneously manipulate two or more parameters in thismanner, generating output in the form of a table that shows how the parametersinteract to affect the outcome. Another method is brute force optimization, whichcomes in several varieties: The most common form is stepping every parameterthrough every possible value. If there are many parameters, each having many pos-sible values, running this kind of optimization may take years. Brute force opti-mization can, however, be a workable approach if the number of parameters, andvalues through which they must be stepped, is small. Other forms of brute forceoptimization are not as complete, or as likely to find the global optimum, but canbe run much more quickly. Finally, for heavy-duty optimization (and, if naivelyapplied, truly impressive curve-fitting) there are genetic algorithms. An appropri-ate genetic algorithm (GA) can quickly tind a good solution, if not a global opti-mum, even when large numbers of parameters are involved, each having largenumbers of values through which it must be stepped. A genetic optimizer is animportant tool in the arsenal of any trading system developer, but it must be usedcautiously, with an ever-present eye to the danger of curve-fitting. In the inves-tigations presented in this book, the statistical assessment techniques, out-of-sample tests, and such other aspects of the analyses as the focus on entire portfoliosprovide protection against the curve-fitting demon, regardless of the optimizationmethod employed

This is Jill, manager of Zhejiang Kaixin industrial & Trade Co.,Ltd
, we have manufacturing and trading high quality since 2008

If you are interested in me our our company ,please feel free to contact me.

Have a nice day!

our company website is :

www.gardenfurniture-china.com

China garden furniture China garden furniture

WHAT ARE GOOD ENTRIES AND EXIT

Standard

Given a mechanical trading system that contains an entry model to generate entryorders and an exit model to generate exit orders (including those required formoney management), how are the entries and exits evaluated to determine whetherthey are good? In other words, what constitutes a good entry or exit?Notice we used the terms entry orders and exit orders, not entry or exit sig-nals. Why? Because “signals” are too ambiguous. Does a buy “signal” mean thatone should buy at the open of the next bar, or buy using a stop or limit order? Andif so, at what price? In response to a “signal” to exit a long position, does the exitoccur at the close, on a profit target, or perhaps on a money management stop?Each of these orders will have different consequences in terms of the resultsachieved. To determine whether an entry or exit method works, it must producemore than mere signals; it must, at smne point, issue highly specific entry and exitorders. A fully specified entry or exit order may easily be tested to determine itsquality or effectiveness.In a broad sense, a good entry order is one that causes the trader to enter themarket at a point where there is relatively low risk and a fairly high degree ofpotential reward. A trader’s Nirvana would be a system that generated entry ordersto buy or sell on a limit at the most extreme price of every turning point. Even if the exits were only merely acceptable, none of the trades would have more thanone or two ticks of adverse excursion (the largest unrealized loss to occur withina trade), and in every case, the market would be entered at the best obtainableprice. In an imperfect world, however, entries will never be that good, but they canbe such that, when accompanied by reasonable effective exits, adverse excursionis kept to acceptable levels and satisfying risk-reward ratios are obtained.What constitutes an elective exit? An effective exit must quickly extricate thetrader from the market when a trade has gone wrong. It is essential to preserve cap-ital from excessive erosion by losing trades; an exit must achieve this, however,without cutting too many potentially profitable trades short by converting them intosmall losses. A superior exit should be able to hold a trade for as long as it takes tocapture a significant chunk of any large move; i.e., it should be capable of riding asizable move to its conclusion. However, riding a sizable move to conclusion is nota critical issue if the exit strategy is combined with an entry formula that allows forreentry into sustained trends and other substantial market movements.In reality, it is almost impossible, and certainly unwise, to discuss entriesand exits independently. To back-test a trading system, both entries and exitsmust be present so that complete round-turns will occur. If the market is entered,but never exited, how can any completed trades to evaluate be obtained? An entrymethod and an exit method are required before a testable system can exist.However, it would be very useful to study a variety of entry strategies and makesome assessment regarding how each performs independent of the exits.Likewise, it would be advantageous to examine exits, testing different tech-niques, without having to deal with entries as well. In general, it is best to manip-ulate a minimum number of entities at a time, and measure the effects of thosemanipulations, while either ignoring or holding everything else constant. Is thisnot the very essence of the scientific, experimental method that has achieved somuch in other fields? But how can such isolation and control be achieved, allow-ing entries and exits to be separately, and scientifically, studied

This is Jill, manager of Shanghai Chiyang leisure product Co.,ltd
, we have manufacturing and trading high quality since 2008
If you are interested in me our our company ,please feel free to contact me.
Have a nice day!

our company website is :

www.shanghai-cyf.com

our alibaba website is : www.jiachi-furniture.cn

China garden furniture China garden furniture

WHAT IS A COMPLETE, MECHANICAL TRADING SYSTEM

Standard

One of the problems witb Katz’s early trading was that his “system” only providedentry signals, leaving the determination of exits to subjective judgment; it was not,therefore, a complete, mechanical trading system. A complete, mechanical tradingsystem, one that can be tested and deployed in a totally objective fashion, withoutrequiring human judgment, must provide both entries and exits. To be truly com-plete, a mechanical system must explicitly provide the following information:1. When and how, and possibly at what price, to enter the market2. When and how, and possibly at what price, to exit the market with a loss3. When and how, and possibly at what price, to exit the market witha profitThe entry signals of a mechanical trading system can be as simple as explic-it orders to buy or sell at the next day’s open. The orders might be slightly moreelaborate, e.g., to enter tomorrow (or on the next bar) using either a limit or stop.Then again, very complex contingent orders, which are executed during certainperiods only if specified conditions are met, may be required-for example, ordersto buy or sell the market on a stop if the market gaps up or down more than somany points at the open.A trading system’s exits may also be implemented using any of a range oforders, from the simple to the complex. Exiting a bad trade at a loss is frequentlyachieved using a money management stop, which tertninates the trade that hasgone wrong before the loss becomes seriously damaging. A money managementstop, which is simply a stop order employed to prevent runaway losses, performsone of the functions that must be achieved in some manner by a system’s exit strat-egy; the function is that of risk control. Exiting on a profit may be accomplishedin any of several different ways, including by the use of pm@ targets, which aresimply limit orders placed in such a way that they end the trade once the marketmoves a certain amount in the trader’s favor; trailing stops, which are stop ordersused to exit with a profit when the market begins to reverse direction; and a widevariety of other orders or combinations of orders.
In Katz’s early trading attempts, the only signals available were of probabledirection or turning points. These signals were responded to by placing buy-at-market or sell-at-market orders, orders that are often associated with poor fills andlots of slippage. Although the signals were often accurate, not every turning pointwas caught. Therefore, Katz could not simply reverse his position at each signal.Separate exits were necessary. The software Katz was using only served as a par-tially mechanical entry model; i.e., it did not provide exit signals. As such, it wasnot a complete mechanical trading system that provided both entries and exits.Since there were no mechanically generated exit signals, all exits had to be deter-mined subjectively, which was one of the factors responsible for his trading prob-lems at that time. Another factor that contributed to his lack of success was theinability to properly assess, in a rigorous and objective manner, the behavior of thetrading regime over a sufficiently long period of historical data. He had been fly-ing blind! Without having a complete system, that is, exits as well as entries, notto mention good system-testing software, how could such things as net profitabil-ity, maximum drawdown, or the Sharpe Ratio be estimated, the historical equitycurve be studied, and other important characteristics of the system (such as thelikelihood of its being profitable in the future) be investigated? To do these things,it became clear-a system was needed that completed the full circle, providingcomplete “round-turns,” each consisting of an entry followed by an exit.

This is Jill, manager of Shanghai Chiyang leisure product Co.,ltd
, we have manufacturing and trading high quality since 2008
If you are interested in me our our company ,please feel free to contact me.
Have a nice day!

our company website is :

www.shanghai-cyf.com

our alibaba website is : www.jiachi-furniture.cn

China garden furniture China garden furniture

What do we believe to be life’s most important necessities

Standard

What do we believe to be life’s most important necessities? Not long ago, most people would answer, “housing, food, transportation and clothing,” which have always been seen as the four basic needs of the Chinese. These days however, we need to add another item to this traditional list. Education has not only grown by leaps and bounds in importance, but also developed with the same speed in expense, especially higher education. According to a recent survey, only 7.5 per cent of the sample group could easily afford university fees which exceed 5,000 yuan (US$602) every year. More than 51 per cent, both from suburban and urban areas, consider the current fee system above their means. People frequently raise the question, “On what grounds are such high university fees based?” Before answering this, let’s first read some statistics. Usually, education fees are proportional to the economic situation of the country. For example, in the United States in 2003, the average annual college fee was US$5,132, which is about 15 per cent of per capita GDP. In China, while per capita GDP is a little above US$1,000, the average university fee was 4,172 yuan (US$502) last year, which means the proportion nearly surpasses 50 per cent.

The initiative in industrializing education is a way of seeking new growth for China’s economy. The term “Education Industrialization,” first used by Stanford University, was aimed at transferring knowledge and techniques from universities directly into socially productive forces. It brought about Silicon Valley, which has given great impetus to the American economy. However, in China, this term equals skyrocketing college fees and the expansion of college sizes. Instead of stimulating consumption, parents begin to save money for their child’s future education even before its birth. In a larger sense, it withered people’s consumption capabilities. Another result is that it laid a heavier burden on students from rural areas. Going to college was considered the only way these youngsters could change their lives and the underprivileged conditions of their families. With the striking increase in college fees, it is now harder for them to realize this collegiate dream. Thus, the demographics of student bodies changed dramatically. The proportion of students from rural areas once accounted for 60 per cent of all college students. Now, it is less than 30 per cent. It’s worrying that the majority of college students are now from “well-off” families who barely understand the real situations faced by those in poor and remote areas. In the coming years, high fees will further exacerbate the uneven development between rich and poor. The increase of college fees doesn’t reflect an increase in teaching quality at these institutions. With the growth of recruitment numbers every year, some colleges are short of qualified professors and equipment. Accordingly, there have been more and more big classes, which often have more than 80 students. The teachers have almost no time to communicate with their students as they are also busy rushing from one class to another. In the labs, two or three students often share a single piece of equipment. The cycle doesn’t end with students’ graduation. With the large sums spent on tertiary education, students and their parents are often extremely disappointed if the student fails to find a job which can pay back the investment. The relationship between colleges and students should not merely be seen as providers and consumers, since a good tertiary education benefits both the individual student and society as a whole. Similarly, if education veers from its appointed role, the aftermath will be shouldered by China as a whole.

This is Jill, manager of Shanghai Chiyang leisure product Co.,ltd
, we have manufacturing and trading high quality since 2008

If you are interested in me our our company ,please feel free to contact me.

Have a nice day!

our company website is :

www.gardenfurniture-

china.com

our alibaba website is : www.gardenfurniture-china.com

China garden furniture China

garden furniture