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Performing financial studies : a methodological cookbook
- Author / Creator
- Available as
- Physical
Details
Checking for availability...
- Creator
- Michael J. Seiler
- Format
- Books
- Language
- English
- Publication
-
- Upper Saddle River, NJ : Prentice Hall, [2004]
- ©2004
- Physical Details
-
- xiii, 432 pages : illustrations ; 26 cm
- ISBNs
- 0130479810, 9780130479815
- OCLC
- ocm50693349
- Includes index.
- Chapter 1 Understanding Your Data 1 -- 1.1 Nonmetric Data 1.1.1 Nominal Data 1.1.2 Ordinal Data 2 -- 1.2 Metric Data 1.2.1 Interval Data 1.2.2 Continuous (Ratio) Data 3 -- Chapter 2 Preparing Your Data for Analysis 4 -- 2.1 Getting Data Off the Internet and into Excel 2.2 Preparing Data in Excel 13 -- 2.3 Getting Data into EViews 20 -- 2.4 Getting Data into SPSS 31 -- 2.5 Screening the Data for Typos and Outliers 35 -- 2.6 Transforming/Computing Financial Variables 48 -- 2.6.1 Calculating Returns 50 -- 2.6.2 Calculating Excess Returns 63 -- 2.6.3 Tying Up Loose Ends: Labels and Decimal Points 68 -- Part II Basic Financial Statistics/Methodologies 73 -- Chapter 3 Correlation 3.2 Performing a Correlation with Metric Variables 3.3 Performing a Correlation with Nonmetric Variables 77 -- Chapter 4 Autocorrelation 82 -- Chapter 5 Partial Autocorrelation 88 -- 5.1 Purpose of a Partial Autocorrelation Test Chapter 6 Autocorrelation for Nonparametric Data (Wald-Wolfowitz Runs Test) 94 -- Chapter 7 T-Test 98 -- 7.2 Performing a One-Sample T-Test 99 -- 7.3 Performing an Independent-Samples T-Test 104 -- 7.4 Performing a Paired-Samples T-Test 108 -- Chapter 8 Analysis of Variance 115 -- 8.2 Performing an ANOVA 8.3 Post Hoc Tests 118 -- 8.3.1 Equal Variances Assumed vs. Unequal Variances Assumed 120 -- Chapter 9 Regression 128 -- 9.2 Performing a Linear Regression 9.3 Testing for Multicollinearity 139 -- 9.4 Performing a Two-Stage Least Squares Regression 147 -- 9.4.1 Performing a 2SLS Regression in SPSS 148 -- 9.4.2 Performing a 2SLS Regression in EViews 158 -- Chapter 10 Factor Analysis 165 -- 10.3 Using Factor Scores in a Regression 178 -- 10.4 Using a Summated Scale in a Regression 184 -- Chapter 11 Calculating a Stock's Beta 196 -- 11.3 Interpreting Beta 201 -- Chapter 12 Predictive Ability 202 -- 12.2 Measuring Predictive Ability Using Ordinal Rankings 12.3 Measuring Predictive Ability Using Raw Returns 215 -- Part III Advanced Financial Techniques/Methodologies 217 -- Chapter 13 Event Studies 13.2.1 Identify the Event Date 13.2.2 Define the Event Window 218 -- 13.2.3 Define the Estimation Period 13.2.4 Select the Sample of Firms 219 -- 13.2.5 Calculate Normal (or Nonevent) Returns 220 -- 13.2.5.1 Mean Return 13.2.5.2 Market Return 13.2.5.3 Proxy (or Control) Portfolio Return 221 -- 13.2.5.4 Risk-Adjusted Return 13.2.6 Calculate ARs 222 -- 13.2.7 Calculate CARs 13.2.8 Determine the Statistical Significance of the ARs and CARs 13.3.5 Calculating Normal (or Nonevent) Returns 225 -- 13.3.6 Calculating ARs, CARs, and Their Significance 13.3.6.1 Setting up the Event Study in Excel 13.3.6.2 Performing Intermediate Calculations 244 -- 13.3.6.3 Calculating Total SAR 253 -- 13.3.6.4 Calculating the Cumulative TSAR 267 -- Chapter 14 Unit Root Test 279 -- Chapter 15 Granger Causality 289 -- 15.3 Number of Lags 294 -- 15.4 Limitations of Granger Causality 295 -- Chapter 16 Cointegration 296 -- 16.2.1 Verifying That the Series Are Integrated 299 -- 16.2.2 Continuing with the Cointegration Test 302 -- 16.2.3 Using Centered (Orthogonalized) Seasonal Dummy Variables 308 -- Chapter 17 Vector Autoregression 311 -- 17.2 Performing a VAR Chapter 18 Vector Error Correction 317 -- 18.2 Performing a VEC Chapter 19 ARCH/GARCH 326 -- 19.2.1 Verifying the Correct Model Specification 332 -- 19.2.1.1 The Mean Equation 333 -- 19.2.1.2 The Variance Equation 335 -- 19.2.1.3 Testing for ARCH Effects 336 -- 19.3 Creating an Adjusted Series Free from ARCH/GARCH 338 -- 19.4 Variations of ARCH/GARCH 342 -- 19.4.1 Threshold ARCH 19.4.2 Exponential GARCH 19.4.3 ARCH-in-Mean 19.4.4 Component ARCH 343 -- 19.4.5 Asymmetric Component Chapter 20 Programming a Binomial Option Pricing Model 344 -- 20.2 Programming a Binomial European Call Option 20.3 Programming a Binomial European Put Option 359 -- 20.4 Programming a Binomial American Call Option 361 -- 20.5 Programming a Binomial American Put Option 365 -- Chapter 21 Programming a Black-Scholes Option Pricing Model 370 -- 21.1 Programming a Call Option without Dividends Using Black-Scholes 21.2 Programming a Put Option without Dividends Using Black-Scholes 377 -- 21.3 Programming a Call Option with Dividends Using Black-Scholes 380 -- 21.3.1 Continuous Dividends 21.3.2 Discrete Dividends 386 -- 21.4 Programming a Put Option with Dividends Using Black-Scholes 393 -- 21.4.1 21.4.2 21.5 Understanding the Effects of Inputs on Call and Put Options 394 -- 21.5.1 Stock Price 21.5.2 Exercise (or Strike) Price 396 -- 21.5.3 Volatility 21.5.4 Time to Maturity 397 -- 21.5.5 Risk-Free Rate 398 -- 21.5.6 Dividends 399 -- Part IV Writing a Financial Study 403 -- 22.1 Cover Page and Abstract 22.2 Introduction 22.3 Literature Review 22.4 Data 404 -- 22.5 Methodology 22.6 Results 22.7 Summary and Conclusions 22.8 References 22.9 Tables 405 -- Chapter 23 Bringing Output into Microsoft Word 406 -- 23.1 Bringing SPSS Output into Microsoft Word 23.2 Bringing Excel Output into Microsoft Word 411 -- 23.3 Bringing EViews Output into Microsoft Word 415 -- Appendix Dataset Descriptions 418