The Handbook of Trading: Strategies for Navigating and Profiting from Currency, Bond, and Stock Markets (McGraw-Hill Financial Education Series) - Hardcover

GREGORIOU

Hardcover

ISBN 10: 0071743537 ISBN 13: 9780071743532

Publisher: McGraw Hill, 2010

Synopsis

Make the post-meltdown markets work for you,using the unparalleled insight of today’stop global investing experts!

“This book provides a collection of papers that examine tradingexecution, technical trading, and trading strategies, as well as algorithmsin different markets (equities, forex, fixed income, exchange traded funds,derivatives, and commodities) around the world. This is particularly relevantgiven the recent explosion in trading volumes.”
Tarun Chordia, R. Howard Dobbs Chair in Finance,Goizueta Business School, Emory University

“This book uses a number of well-respected authors in the area of asset trading.It provides a comprehensive analysis of trading-related issues coveringmomentum trading, algorithmic trading, the use of technical trading rules,strategies for ETFs, and the role of trading volume.”
Professor John Cotter, Director of the Centre for Financial Markets,University College Dublin School of Business, University College Dublin

“The Handbook of Trading is a good reference tool for both practitionersand academics. The contents cover a wide range of topical issues.”
Professor Robert McGee, Director of the Center for Accounting, Auditing, and Tax Studies,College of Business Administration, Florida International University

About the Book:

Given today’s market volatility, eventhe most advanced investors can beunsure of their next move. Ratherthan rely on one or two individuals who claimgeneral knowledge on any given investingtopic, you need the advice of professionalswho have spent their entire careers developingreal expertise on more focused sectors ofthe market.

The Handbook of Trading is the only bookavailable that provides just that.Greg N. Gregoriou has amassed forty of theworld’s top academics, researchers, and practitionerswho explain how to make today’smarkets work for you. With this highly technicalbut ultimately practical guide, you haveaccess to a broad array of trading strategiesthat will put you light years ahead of thecompetition―regardless of the state of themarket.

From technical analysis and momentumtrading to algorithmic and FOREX trading,The Handbook of Trading introduces you totechniques and insights never before published,each of which has been rigorouslyback-tested and analyzed. Chapters include:

• Performance Leakage and ValueDiscounts on the Toronto StockExchange
  Lawrence Kryzanowskiand Skander Lazrak
• Trading in Turbulent Markets: DoesMomentum Work?
  Tim A. Herbergerand Daniel M. Kohlert
• Profitability of Technical Trading Rulesin an Emerging Market
  DimitrisKenourgios and Spyros Papathanasiou
• Leveraged Exchange-Traded Fundsand Their Trading Strategies
  NaratCharupat
• The Impact of Algorithmic TradingModels on the Stock Market
  OhannesG. Paskelian

Applying critical lessons learned from the financialcrisis of 2008–2009, the contributorsexplain how to approach turbulent marketenvironments and adjust your trading methodologiesaccordingly.

The Handbook of Trading is the go-to guidefor financial professionals seeking profits intoday’s currency, bond, and stock markets.

Correlating PowerPoint slides and readingquestions created by the contributors appear onhttp://www.mhprofessional.com/handbookoftrading.

About this title

About the Author

Greg N. Gregoriou is a professor of financein the School of Business and Economics atthe State University of New York (Plattsburgh).He is co-editor of the Journal of Derivativesand Hedge Funds and an editorialboard member of the Journal of Wealth Managementand the Journal of Risk Managementin Financial Institutions. His books withMcGraw-Hill include The Credit DerivativesHandbook, The VaR Modeling Handbook,and The Risk Modeling Evaluation Handbook.He lives in Plattsburgh, NY.

Excerpt. © Reprinted by permission. All rights reserved.

The Handbook of Trading

STRATEGIES FOR NAVIGATING AND PROFITING FROM CURRENCY, BOND, AND STOCK MARKETS

By GREG N. GREGORIOU

The McGraw-Hill Companies, Inc.

Copyright © 2010 The McGraw-Hill Companies, Inc.
All rights reserved.

ISBN: 978-0-07-174353-2

Contents

EDITOR
CONTRIBUTORS
ACKNOWLEDGMENTS
PART I EXECUTION AND MOMENTUM TRADING
CHAPTER 1 PERFORMANCE LEAKAGE AND VALUE DISCOUNTS ON THE TORONTO STOCK 
EXCHANGE Lawrence Kryzanowski and Skander Lazrak
CHAPTER 2 INFORMED TRADING IN PARALLEL AUCTION AND DEALER MARKETS: THE 
CASE OF THE LONDON STOCK EXCHANGE Pankaj K. Jain, Christine Jiang, Thomas 
H. McInish, and Nareerat Taechapiroontong
CHAPTER 3 MOMENTUM TRADING FOR THE PRIVATE INVESTOR Alexander Molchanov 
and Philip A. Stork
CHAPTER 4 TRADING IN TURBULENT MARKETS: DOES MOMENTUM WORK? Tim A. 
Herberger and Daniel M. Kohlert
CHAPTER 5 THE FINANCIAL FUTURES MOMENTUM Juan Ayora and Hipòlit Torró
CHAPTER 6 ORDER PLACEMENT STRATEGIES IN DIFFERENT MARKET STRUCTURES: A 
PRIMER Giovanni Petrella
PART II TECHNICAL TRADING
CHAPTER 7 PROFITABILITY OF TECHNICAL TRADING RULES IN AN EMERGING MARKET 
Dimitris Kenourgios and Spyros Papathanasiou
CHAPTER 8 TESTING TECHNICAL TRADING RULES AS PORTFOLIO SELECTION 
STRATEGIES Vlad Pavlov and Stan Hurn
CHAPTER 9 DO TECHNICAL TRADING RULES INCREASE THE PROBABILITY OF WINNING? 
EMPIRICAL EVIDENCE FROM THE FOREIGN EXCHANGE MARKET Alexandre Repkine
CHAPTER 10 TECHNICAL ANALYSIS IN TURBULENT FINANCIAL MARKETS: DOES 
NONLINEARITY ASSIST? Mohamed El Hedi Arouri, Fredj Jawadi, and Duc Khuong 
Nguyen
CHAPTER 11 PROFITING FROM THE DUAL-MOVING AVERAGE CROSSOVER WITH 
EXPONENTIAL SMOOTHING Camillo Lento
CHAPTER 12 SHAREHOLDER DEMANDS AND THE DELAWARE DERIVATIVE ACTION Edward 
Pekarek
PART III EXCHANGE-TRADED FUND STRATEGIES
CHAPTER 13 LEVERAGED EXCHANGE-TRADED FUNDS AND THEIR TRADING STRATEGIES 
Narat Charupat
CHAPTER 14 ON THE IMPACT OF EXCHANGE-TRADED FUNDS OVER NOISE TRADING: 
EVIDENCE FROM EUROPEAN STOCK EXCHANGES Vasileios Kallinterakis and 
Sarvinjit Kaur
CHAPTER 15 PENETRATING FIXED-INCOME EXCHANGE-TRADED FUNDS Gerasimos G. 
Rompotis
CHAPTER 16 SMOOTH TRANSITION AUTOREGRESSIVE MODELS FOR THE DAY-OF-THE-WEEK 
EFFECT: AN APPLICATION TO THE S&P 500 INDEX Eleftherios Giovanis
PART IV FOREIGN EXCHANGE MARKETS, ALGORITHMIC TRADING, AND RISK
CHAPTER 17 DISPARITY OF USD INTERBANK INTEREST RATES IN HONG KONG AND 
SINGAPORE: IS THERE ANY ARBITRAGE OPPORTUNITY? Michael C. S. Wong and 
Wilson F. Chan
CHAPTER 18 FOREX TRADING OPPORTUNITIES THROUGH PRICES UNDER CLIMATE CHANGE 
 Jack Penm and R. D. Terrell
CHAPTER 19 THE IMPACT OF ALGORITHMIC TRADING MODELS ON THE STOCK MARKET 
Ohannes G. Paskelian
CHAPTER 20 TRADING IN RISK DIMENSIONS Lester Ingber
CHAPTER 21 DEVELOPMENT OF A RISK-MONITORING TOOL DEDICATED TO COMMODITY 
TRADING Emmanuel Fragnière, Helen O'Gorman, and Laura Whitney
PART V TRADING VOLUME AND BEHAVIOR
CHAPTER 22 SECURITIES TRADING, ASYMMETRIC INFORMATION, AND MARKET 
TRANSPARENCY Mark D. Flood, Kees G. Koedijk, Mathijs A. van Dijk, and 
Irma W. van Leeuwen
CHAPTER 23 ARBITRAGE RISK AND THE HIGH-VOLUME RETURN PREMIUM G. Geoffrey 
Booth and Umit G. Gurun
CHAPTER 24 THE IMPACT OF HARD VERSUS SOFT INFORMATION ON TRADING VOLUME: 
EVIDENCE FROM MANAGEMENT EARNINGS FORECASTS Paul Brockman and James 
Cicon
CHAPTER 25 MODELING BUBBLES AND ANTI-BUBBLES IN BEAR MARKETS: A 
MEDIUM-TERM TRADING ANALYSIS Dean Fantazzini
CHAPTER 26 STRATEGIC FINANCIAL INTERMEDIARIES WITH BROKERAGE ACTIVITIES 
Laurent Germain, Fabrice Rousseau, and Anne Vanhems
CHAPTER 27 FINANCIAL MARKETS, INVESTMENT ANALYSIS, AND TRADING IN PRIMARY 
AND SECONDARY MARKETS André F. Gygax
CHAPTER 28 TRADING AND OVERCONFIDENCE Ryan Garvey and Fei Wu
CHAPTER 29 CORRELATED ASSET TRADING AND DISCLOSURE OF PRIVATE INFORMATION 
Ariadna Dumitrescu
INDEX

Excerpt

<h2>CHAPTER 1</h2><p><b>PERFORMANCE LEAKAGE AND VALUE DISCOUNTS ON THE TORONTO STOCK EXCHANGE</b></p><p>Lawrence Kryzanowski and Skander Lazrak</p><br><p><b>ABSTRACT</b></p><p>Various measures of liquidity are estimated for common and preferred shares(individual firms and exchange-traded funds), units (trusts and limitedpartnerships), notes (index linked and principal protected), and warrants listedon the Toronto Stock Exchange. We document significant differences in potentialand actual trade execution costs intra- and inter-security type and across timethat impact on the net benefits of trading for different levels of tradingpatience, the valuation discounts of non-granular portfolios under various moreor less patient exit strategies, and the likely performance drag frominvestments in different security types or the average security in that securitytype. We also provide an illustration of how trade execution costs are affectedadversely by worries of a global recession.</p><br><p><b>INTRODUCTION</b></p><p>Since the performance of all investment decisions are directly affected by thequality of effecting such decisions in the marketplace and varies within andacross security types, all investors must carefully balance the marginalbenefits and costs of each transaction. Such costs include commissions, fees,execution, and opportunity costs. Execution quality reflects various tradingdemands for immediate liquidity (speed) based on different investment styles andon the availability and cost of such liquidity at each point in time. The latterincludes the expected and actual impact of investor trade on market prices andon the cost and likelihood of concluding the remainder of a trade. Sinceexecution quality is most often unobservable, it is imputed from the data eitheras the difference between the actual trade execution price and the price thatwould have existed in the absence of the trade or as the difference (referred toas performance leakage) between the quoted or actual trade price and itscounterpart in the absence of trade costs (referred to as the "fair" price). Thetime to complete a trade for a fixed concession from the "fair" price is anotherdimension of execution quality, which can not be measured using most availabledatabases (such as the one used herein) that do not provide information on ordersubmissions and their subsequent fill history. Execution quality also affectsthe pricing of securities through its impact on value discounts.</p><p>Trade activity measures of liquidity include (un)signed number and dollar valueof shares traded and the number of trades. Metrics for measuring expected oractual trade execution costs include quoted, effective and realized spreads, andquoted depths. Hasbrouck (2009) provides a good review of various measures oftrade and market impact costs using daily data.</p><p>Earlier research focuses on the measurement of execution cost (e.g., Collins andFabozzi, 1991), on the impact of execution costs on the speed and method bywhich institutional investors should implement buy and sell decisions (e.g.,Bodurtha and Quinn, 1990; Wagner and Edwards, 1993; Wilcox, 1993), and ontrading costs in different international markets (e.g., Kothare and Laux, 1995).More recent studies examine the effects of changes in exchange rules onexecution costs across trading platforms (e.g., Venkataraman, 2001; SEC, 2001;Bessembinder, 2003; Boehmer, 2005) and on institutional differences (Eleswarapuand Venkataraman, 2006).</p><p>To our knowledge, few published studies examine the trade execution costperformance of security types other than stocks, bonds, and highly liquidderivatives. This study is the first to examine trade execution costs for allthe security types on the Toronto Stock Exchange (TSX). We expect to findsignificant differences in execution costs for a dichotomization of trades bysecurity type.</p><p>The remainder of this chapter is organized as follows. The second section ofthis chapter discusses the sample and data. This chapter's third sectionpresents the measures of market quality. The fourth section presents theempirical estimates of market quality; and the fifth section concludes thechapter.</p><br><p><b>SAMPLE AND DATA</b></p><p>Our initial sample contains all 2,300 listed securities on the TSX for the firsttwo calendar months of 2008; namely, 1,300 common shares, 15 shares listed inUSD, 256 preferred shares, 396 units including income trusts units, 149debentures, 119 warrants, and 65 NT_NO notes including asset-linked, principalprotected notes sponsored by the Royal Bank. As is common practice in theliterature and reporting in the financial press (e.g., <i>Globe and Mail</i>)and following the definition of the SEC regarding penny shares available at<b>http://www.sec.gov/answers/penny.htm</b>, tthe common share sample is splitin two based on those trading at or above $5 per share (Common >$5) and thosetrading atttt less that $5 per share (Common <$5) based on the time-series meanprice of each common share.</p><p>Trading data are extracted from the TSX's Trades and Quotes (TAQ) database. Asin Chordia, Roll, and Subrahmanyam (2001), the data are cleaned by removing: (i)quotes/trades outside regular trading hours of 9:30 to 16:00 EST; (ii) tradeswith negative numbers of shares or trading prices; (iii) trades with delayeddelivery, special settlement and/or delivery, or subject to special restrictionsand conditions; (iv) bids exceeding offers or either with nil prices or volumes;and (v) quoted percentage spreads exceeding 30 percent. These filters delete2.74 percent and 5.41 percent of the initial 202,710,358 quotes and 27,276,955trades, respectively.</p><br><p><b>MEASURES OF PERFORMANCE LEAKAGE AND VALUE DISCOUNTS</b></p><p>Our first measure is the quoted spread, <i>QS<sub>i,t</sub></i>, for security<i>i</i> at time <i>t</i> or <i>QS<sub>i,t</sub> =(Ask<sub>i,t</sub> - Bid<sub>i,t</sub>)</i>/[0.5<i>(Ask<sub>i,t</sub> + Bid<sub>i,t</sub>)</i>],where the denominator is the midspread. Our second measure is superior to thefirst for a patient investor given that limit orders can improve on the postedquotes of registered traders on the TSX. Thus, the effective spread,<i>ES<sub>i,tk</sub></i>, is given by <i>ES<sub>i,t</sub> = 2 x[(Price<sub>i,t</sub> - MidSpread Pre<sub>i,t</sub>)/MidSpreadPre<sub>i,t</sub>] x I<sub>i,t</sub></i> where <i>I<sub>i,t</sub></i> is atrade indicator variable equal to +1 for buyer initiated (purchase) trades and?1 for seller initiated (sale) trades. Since benchmark quotes need to beobserved when the trade decision is made and these times are not observable andquotes may move after submitting even small orders, a five-second lag is used todetermine the pretrade benchmark midspread as recommended by Bessembinder(2003).</p><p>Since the identity of the trade initiator is unobservable empirically, the Leeand Ready (1991) algorithm is used to sign the transactions. The trade isassumed to be buyer- (seller-) initiated when the traded price is higher (lower)than the prevailing midquote or if the last nonzero price change (tick) ispositive (negative) for trade prices at the prevailing midquote (tick rule).Contemporaneous quotes (i.e., quotes for a zero-second lag) are used to computebenchmark midquotes for trade signing purposes (Ellis, Michaely, and O'Hara,2000; Bessembinder, 2003).</p><p>Effective spreads are compensation for both the probability of adverseinformation and order execution. The former represents the loss incurred bymarket makers to better informed traders as prices move against the marketmakers. The realized spread is not only a better measure of compensation fortrade execution but a better indicator of market liquidity and trading qualityfrom the market-maker's perspective. To estimate the realized spread and thuseliminate the loss to better informed traders, the trading price is comparedwith a benchmark or a midquote that occurs sometime after the trading takesplace. This measures the market-maker's profit if she or he rebalances inventoryafter making the initial trade. As in Huang and Stoll (1996) and Bessembinder(2003), benchmark quotes for both <i>k</i> = 5 and 30 minutes after trades(i.e., <i>MidSpreadPost<sub>i,t,k</sub></i>) are used herein. Daily closingquotes are used for trades occurring within the last <i>k</i> = 5 or 30 minutesof a trading session. The realized spread, <i>RS<sub>i,t,k</sub></i>, is givenby: <i>RS<sub>i,t,k</sub> = 2 x [(Price<sub>i,t</sub> -MidSpreadPost<sub>i,t,k</sub>)/MidSpread Pre<sub>i,t</sub>] xI<sub>i,t</sub></i>. Thus, the price impact of a trade,<i>PI<sub>i,t,k</sub></i>, is given by the difference between the effectivespread and the realized spread, <i>ES<sub>i,t</sub> - RS<sub>i,t,k</sub></i>,or <i>PI<sub>i,t,k</sub> = 2 x [(MidSpreadPost<sub>i,t,k</sub> -MidSpreadPost<sub>i,t,k</sub>)/MidSpread Pre<sub>i,t</sub>] xI<sub>i,t</sub></i>.</p><p>Since the effective/realized spreads or price impact can be negative due to themeasurement of the trade sign variable at a different time compared with theprevailing or subsequent quote, we also use an alternative for these spreadmeasures that relies on their absolute values. For instance, the alternativemeasure of the effective spread, <i>AES<sub>i,t</sub>, is: AES<sub>i,t</sub> =2 x |(Price<sub>i,t</sub> - MidSpread Pre<sub>i,t</sub>)/MidSpreadPre<sub>i,t</sub>|</i>.</p><p>The quoted dollar depth, which is the capacity of a market to absorb trades withlittle or no price impact, also is measured to assess liquidity and marketexecution quality. As quotes represent prices at which market makers are willingto trade at a prespecified maximum trading size, we assume that this size is thehighest possible volume before an order eats up the available liquidity at theinside quotes and quotes need to be moved up or down depending on tradedirection. We measure depth <i>QD<sub>i,t</sub></i>, as the average quotedorder flow size at both the inside bid and ask or <i>QD<sub>i,t</sub>, = 0.5(Bid<sub>i,t</sub> x BidSize<sub>i,t</sub> + Ask<sub>i,t</sub> xAskSize<sub>i,t</sub>)</i>.</p><br><p><b>EMPIRICAL ESTIMATES FOR THE TSX</b></p><p>The relative quoted and effective spreads for all the securities listed on theTSX and seven subsamples differentiated by security type (and price in the caseof common shares) are reported in <b>Table 1.1</b>. As expected, the lowestmedian spreads are for common shares with prices above $5 (Common >$5), followedby the asset-linked notes (NT_NO) for relative quoted spreads (QS) and preferredshares for the two measures of relative and average effective spreads (ES andAES). The highest median spreads are for Warrants. To illustrate, the medianeffective spreads are 0.31 percent and 6.88 percent for Common with prices above$5 and Warrants, respectively.</p><p>NT_NO and Common >$5 are among the two lowest mean spreads with Common >$5 onlyoccupying the lowest mean spread for the ES measure. Warrants have the highestmean spreads for each of the three measures. The relatively high trading costsassociated with Warrants is primarily due to the relatively low traded prices ofWarrants (mean of $1.79 compared with $13.24 for all other securities).Securities denominated in USD have the second highest mean and median spreadsfor all three measures. To illustrate, the median USD effective spread is 4.19percent.</p><p>As expected, considerable variation exists in the spread measures within eachsecurity type. The NT_NO followed by Common >$5 have the lowest variation (e.g.,effective spread sigmas of 0.76 percent and 1.22 percent, respectively).Warrants and USD have the highest variations for all three spread measures withUSD in the top spot only for QS (6.89 percent). As expected, the spreaddistributions are right-skewed so that the medians are always lower than theirmean counterparts. While a small percentage of the effective spreads using thesigning algorithm are negative, as expected due to signing error, this is notthe case when the alternate measure of the effective spread AES is calculated.</p><br><p><b>Table 1.1 Quoted and Effective Spreads for Canadian Securities</p><p>Table 1.1</b> provides summary statistics for relative (%) quoted spreads or QSand effective spreads or ES (as defined in the text where the prefix A whenadded to ES refers to alternate measure) for TSX listed securities during thefirst two months of 2008. The final data set consists of 197,159,687 quotes and25,800,483 trades.</p><p>A comparison of the mean, median, and sigma values for common shares tradingbelow and above $5 exemplifies the much higher trade costs associated with so-called"penny" stocks (e.g., median ES of 2.31 percent versus 0.31 percent andsigma of 4.16 percent versus 1.22 percent, respectively). This may haveimplications for small cap investing in national markets smaller than in theUnited States.</p><p>The relative realized spreads for the various samples are reported in <b>Table1.2</b>. With four exceptions (RS5 and RS30 for both USD and NT_NO), the meansare greater than their median counterparts, which indicates right-skeweddistributions. The median relative realized spreads are lowest for Common >$5followed by Preferreds for all but the ARS30 (Alteranative Realized Spread basedon quotes 30 minutes after trades) measure where the lowest median is forPreferreds followed by NT_NO. To illustrate, the median RS5 and RS30 values are0.43 percent and 0.41 percent, respectively, for Common >$5. The highest medianrelative realized spreads are for Warrants. This is followed by Common <$5 forRS5 and by USD for the other three relative realized spread measures.</p><br><p><b>Table 1.2 Realized Spreads</b></p><p>Table 1.2 provides summary statistics for (%) realized spreads or RS (as definedin the text where the prefax A refers to alternate measure and the suffix 5 and30 refer to quotes 5 and 30 minutes, respectively, after trades) for TSX listedsecurities during the first two months of 2008.</p><p>The lowest mean RS5 and RS30 are for USD and NT_NO, respectively, followed byrespectively NT_NO and Common >$5. In contrast, the lowest mean ARS5 and ARS30are for Preferreds followed by Common >$5 and NT_NO, respectively. Warrantsalways have the highest mean relative realized spreads followed by Common <$5for RS5 and RS30 and by USD for ARS5 and ARS30, respectively. Thus, the choiceof how to calculate the relative realized spread has an impact on the rankingsof this measure across security types.</p><p>The lowest sigmas are found for NT_NO for all four relative realized spreadmeasures, followed by units for RS5 and Common >$5 for the other three measures.Once again, Warrants have the highest relative realized spreads followed by USDfor the two 5-minute measures and Common <$5 for the two 30-minute measures. Toillustrate, the sigmas for RS5 and RS30 for Warrants are 8.42 percent and 9.41percent, respectively.</p><p>The quoted depth-traded volumes (share numbers and dollars) and the number oftrades for the various samples are reported in <b>Table 1.3</b>. All thedistributions are right-skewed. The lowest mean, median, and sigma of quoteddepth (QD), share volume (Shares vol) and number of trades are for Warrants,NT_NO, and NT_NO, respectively. With two exceptions, the highest mean, median,and sigma of these three measures are for Common >$5. The exceptions are NT_NOfor the median QD and Common <$5 for the median Shares vol.</p><p>The high depth for the index linked notes shows that dealers have minimalconcerns about trading against informed traders as private information isnegligible about the entire index compared with individual securities. The highmedian of penny stock trading volume measured in number of shares is due to thelarger round lot sizes of stocks trading below $1 and the need to trade moreshares of a lower priced share to achieve a comparable dollar volume as fornon-penny shares. Despite their high depths and low trading costs compared withother security types, the notes offered by the Royal Bank are not heavily tradedas the exchange-traded funds are more popular instruments. Units are the secondmost actively traded security type on the TSX. The income trust vehicle, whichpasses through its income untaxed, was a popular investment choice due to yieldsconsiderably higher than those on fixed income securities (Kryzanowski and Lu,2009).</p><p><i>(Continues...)</i>

(Continues...)

Excerpted from The Handbook of Trading by GREG N. GREGORIOU. Copyright © 2010 by The McGraw-Hill Companies, Inc.. Excerpted by permission of The McGraw-Hill Companies, Inc..
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

Edition details

• Publisher: McGraw Hill
• Publication date: 2010
• Language: English
• ISBN 10: 0071743537
• ISBN 13: 9780071743532
• Binding: Hardcover
• Number of pages: 497