Bibliographic record
Abstract
Citation (2017), "Index", Growing Presence of Real Options in Global Financial Markets (Research in Finance, Vol. 33), Emerald Publishing Limited, Bingley, pp. 205-210. https://doi.org/10.1108/S0196-382120170000033011 Publisher: Emerald Publishing Limited Copyright © 2018 Emerald Publishing Limited INDEX Accounting variables, 128 Acquisitions, 4 ACX. See Ang, Chen, and Xing (ACX) Altman’s Z-score, 163 AMEX, 79 Analysis of variance (ANOVA) test, 63 Ang, Chen, and Xing (ACX) DA-preference-based model, 76 relative beta vs. modified beta, 99–101 ANOVA test. See Analysis of variance (ANOVA) test AP option. See Average-price (AP) option Asian-Pacific markets, 125 Asian-Pacific region, 127 Asian stock markets equity market and accounting data, 128 Asia-Pacific economies, 188 Asset pricing models, 124–127 Fama-French three-factor, 151 markets, comparison, 152–155 regression analysis, 133 Asset pricing models, regression analysis of, 133 AT&T-DirecTV, 2 DirectTV, valuation of, 6–10 merger and acquisition (M&A) activities, 3–6 SBC Global and BellSouth Corp., 2 Average-price (AP) option, 10 Bank defaults, 187 Banking Stability Index (BSI), 183, 186, 187, 189, 192, 194–200 balance sheets, 189 banking sector performance, 187–188 fragility and instability in emerging countries, 185, 199 generalized methods of moments (GMM), 189–192 hypotheses, 194–195 check-up, 197–199 income statements, 189 literature, 187–189 log transformation, 194 measures, 187 methodology/construction, 192–193 period, 2003-2011, 189 research model, 193–194 sample, 189 two-step system GMM estimator, 195–198 variables bank lending behavior, 200 description, 192 z-score to measure, 186 Bank lending behavior, 194, 196 Banks’ profitability, 188 Bell companies, 4 BE/ME factor, 124, 128 O-score portfolios, 128 ratio, 128 testing of factor models, 134–151 Betas, 76–101 Black and Scholes (B&S) model, 13 Blended portfolio, 133 Bloomberg, 86 BM&F Bovespa and Johannesbourg Stock Exchange, 183, 184 Bond rating agencies, 173 Book-to-market, 77, 79, 81–87, 90, 91, 93, 94, 96–101 patterns, 133–134 risk factors, 124 BSE, 500, 52 BSI. See Banking Stability Index (BSI) B&S model. See Black and Scholes (B&S) model Canadian financial system, 187 Canadian policymakers, 187 Capital Asset Pricing Model (CAPM), 11, 76–79, 81, 83, 84, 86, 87, 89, 101, 124 BE/ME variable, 81 beta, 76–79, 83, 86, 89, 99 cross-sectional results, 82 data and methodology, 77–80 equivalence of up beta and down beta., 80 modified beta processes, 84 momentum/Fama-French factors, 89–91 robustness check, 91–99 size and book-to-market, 85–89 up-down beta, 81, 83 Capital budgeting analyst, 114, 118 CAPM. See Capital Asset Pricing Model (CAPM) Carhart four-factor model, 154 Carhart model, 133, 155 communications, 6 momentum, 125, 126, 151, 153 Coca-Cola Company, 25 annual cash dividends paid, 26 internal rate of return, 26 frequency distribution of, 27 year-over-year percentage change, 26 Coefficient for sales (SALES), 40 Cointegration test, 45, 56–61 Common stock outstanding (CSH), 40 COMPUSTAT database, 38 Constant growth model, 22 Contingent claims, 3 Contingent pricing, 107 Correlation matrix, 167 Covariance matrix estimating, 111–112 Credit risk, 195 Cross-sectional stock returns, 77, 82, 83, 88, 93, 94, 96–99, 101 Czech National Bank, 188 Data, Variables, and Estimation methods, 46 DCF. See Discounted cash flow (DCF) DE. See Debt to equity (DE) Debt, 47 financing, 54 maturity, 163 empirical studies, 163 private placements of, 159 structure, 160 Debt to equity (DE), 34 Derivatives, on bank, 182 Direct broadcast satellite (DBS) services market, 4 DirecTV’s stock prices, 11 DirecTV’s valuation model application of, 10–15 stock, 3 Discounted cash flow (DCF) analysis, 20, 112 approach, 117 investment, 106 analysis tools, 106 techniques, 115, 116 Dividend discount approach, 20 Dividend discount model, 21, 22, 24 internal rate of return, 23–24 return, internal rate of, 23–24 two-stage, 22 use of, 24 Dividend-enhanced convertible stocks (DECS), 7 Dividend generation process, 23 Dividend history, 20 Dividend payment patterns, 33, 34, 37, 41 data collection, 38 descriptive statistics, 38–40 empirical models, 37 and firm characteristics, relationship, 34–36 future research, 41 hypotheses, 36–37 probit analysis, 40 limitations, 41 sample selection, 38 Dividend payout patterns, 34, 36 DJIA. See Dow Jones Industrial Average (DJIA) Dow Jones Industrial Average (DJIA), 21, 27, 28 companies, 25 20 DJIA, 27 DJIA30, 55 Down beta, 78–102 EFN model. See External funds needed (EFN) model Emerging countries, 182, 183 evolution of derivatives, 183–185 fragility and instability of banks, 185, 199 Equity, 47 controlled firms, 53 market, 125, 128, 155 Errors-in-variables (EIV) problems, 91 Exchange option approach, integrates finance/strategy, 115–117 model, 114 External financing, 44 External funds needed (EFN) model, 44, 47–54, 59, 63, 66 cointegration regression, 61 dependent variable, 55 development to incorporate capital structure, 46–47 Granger causality, 64–66 independent variable, 55 statistical tests, 55–56 sustainable growth rates, 62–64 Fama-French factors, 77, 153 three-factor model, 126, 133, 151, 152, 155 Fama-MacBeth regressions, 99 Federal Communications Commission (FCC), 2 Financial crisis, 182, 185 Financial distress, 124, 125, 127, 128, 131, 133, 134, 152, 154 metrics, 124 risk-based four-factor model, 125 Financial measure, 34 Financial stress index (FSI), 187 Firm size continuum, 175 Flexible manufacturing system (FMS), 107 option to switch among multiple states, 107 Forecasting dividends, 20 Fortune, 500, 38 Future cash flows, 107 Future prices, 112, 114 Generalized method of moments (GMM), 95, 183, 189, 191, 192 estimator technique, 183 two-step system, 197, 198 Generic model, 108–111 Gibbons, Ross, and Shanken (GRS), 133 tests, 152 Global financial tsunami, 188 GMM. See Generalized method of moments (GMM) GNP price-level index, 131 Goodness-of-fit tests, 154 Gram-Charlier expansion, of Taylor series, 111 Granger causality, 64–66 Growth portfolio, 133 Herfindahl-Hirschman Index, 192 High O-score portfolio (HO), 133, 134 High-quality firms, 162 HML portfolios, 89, 133 groupings, 131–133 Index of bank stability (BSI). See Bank Stability Index Information, switching among different levels, 112–115 Institutional investors, 37 Internal rate of return, 21, 25 dividend discount model, 23–24 several dividend-paying stocks, 27–28 Internet, 3 Intrinsic value, 20 current market price, 22 DirecTV stock, 11, 14 probability distribution of, 21 on VWAP option model, 12 Iranian firms, 54 Japanese markets, 124, 128 Johannesbourg Stock Exchange (JSE), 184 Johansen’s cointegration test, 56, 60, 61 Johnson model, 110, 111 Ken French’s website, 87 Liabilities, 46 Liquidity, 54 of assets, 48, 49 liquidation value, 49 risk models, 163, 176 LLCW estimate O-score risk parameters, 127 LLCW financial distress model, 126, 151 LLCW four-factor model, 152, 154 LLCW model, 127, 128, 133, 152, 153 Loan-loss provisions (LLPs), 192 Loans, vulnerability of, 195 Lognormal-distributed assets, 110 Loss aversion (LA) preferences, 76 Low O-score portfolio (LO), 134 Low-quality firms, 162 LTE capabilities, 4 Malaysian firms, 151 Marked-to-market, 162 Market portfolio return, 126 Market-to-book ratio, 164 Maturity regression, 168 Maturity structure, 160–164, 175 considerations, 163–164 contracting hypothesis, 162 liquidity risk hypothesis, 163 signaling hypothesis, 162–163 tax hypothesis, 163 Maximum Eigenvalue approaches, 59 Merger and acquisition (M&A) activities, 3 Mergers, 2–11, 14, 15 Modified beta, 95, 99 Momentum factor (MOM), 77, 79, 80, 86–92, 93, 94, 96, 126–127, 153 Monte Carlo simulation, 21 Moody-KMV’s Expected Default Risk Frequency, 124 NASDAQ, 79 NASDAQ100, 55 National Rural Telecommunications Cooperative, 5 Net present value (NPV), 109, 161 News Corp., 5 Nigeria, bank stability index, 189 N-probit analyses, 37, 38, 40 NYSE, 79 Obama administration, 4 OHL coefficients, 152 Ohlson O-score model, 127, 131 financial distress, 131 parameters, 125 OLS. See Ordinary least squares (OLS) On-balance sheet interest rate risk, 196 Option-pricing model, 10, 106, 107, 114 Option pricing theory, 107 Ordinary least squares (OLS), 95 estimation, 168 O-Score, 128, 131, 133–134 coefficient estimates, 132 financial distress, 124 factor, 128–130 model, 131 probability, 131 risk measurement, 131 Pearson correlation coefficients, 39 Pecking order theory (POT), 44, 47–54 cointegration regression, 61 dividend payout, 51–53 financial flexibility, 49–51 fixed assets, used as collaterals, 48–49 and growth, 53–54 Johansen’s cointegration test, 57–61 objective of study, 45 statistical tests, 55–56 study contributes to current literature, 45–46 support to cointegration test, 61 sustainable sales growth rate, association between, 54–55 tangible assets, 48 vector error correction model, 56–57 Percentage change of the gross domestic product (PCGDP), 194 Pettengill, Sundaram, and Mathur (PSM), 79 Portfolios time-series tests, 134 Post-crisis period, 189 POT. See Pecking order theory (POT) Pre-crisis period, 197 Private debt markets, 160 Private placements, 159–161, 164, 166, 168–171, 173, 175, 176 correlation matrix, 167 debt corporate, 160 empirical studies of, 160 high-quality issuers, 175 maturity theories, 173 sample distribution, 165–166 Securities Data Company (SDC-Platinum), 164 tax rates, 161 two-stage least squares regressions of maturity, 169 firms with credit rating, 172, 174 firms without credit rating, 172, 174 Rule 144A vs. Non-Rule 144A, 170, 171 two-stage least squares regressions, 169 variables, descriptive statistics, 166 Real options, 107, 112, 113 Regression Equation Specification Error Test (RESET), 55 Regression mean square errors (RMSEs), 81, 92 Return on asset (ROA) profitability, 193 Return on equity (ROE), 36 Romanian financial system, 188 S&P 500 exchange, 21 Schervish’s algorithm, 110 Securities Data Company (SDC), 164, 166 Size, 77, 79, 80, 82 Size-and-book-to-market-sorted portfolios, 83 SMB, 89 Stocks graphical representation, 29 non-dominated, 28 returns, 128 stock-for-stock transaction, 5 valuation, 21, 23 Switching among Different Levels of Information, 107 Taylor series, 111 Telecommunications, 2, 5, 14 The Option to Switch among Multiple States, 107 Time-series regressions, 135–151 Time Warner Cable (TWC), 2 T-Mobile, 2, 4 Tse algorithm, 112 Turkish banking system, 185 Two-stage least squares (2SLS) regressions, 169, 171, 172, 174 United States Satellite Broadcasting, 5 Vector Error Correction Model (VECM), 56, 58 Verizon Communications, 5 Vodafone, 5 Volume-weighted average price (VWAP) model, 3, 10, 13 World Bank database, 189 Zero strike options, 110 Book Chapters Prelims Evaluating Conditions and Terms of the AT&T and DirecTV Merger Stock Valuation Using the Dividend Discount Model: An Internal Rate of Return Approach The Relationship Between Dividend Payment Patterns and Firm Characteristics An Empirical Assessment of the Reality of Pecking Order Theory Modified Beta and Cross-Sectional Stock Returns Options to Choose Among the Most Profitable of Several States in the Physical Realm and the Information Realm Stock Returns and Financial Distress Risk: Evidence from the Asian-Pacific Markets The Maturity Structure of Private Placements of Debt What is the Effect of Derivatives on the Index of Bank Stability in Emerging Countries? Evidence and Discussion Index
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.646 | 0.633 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".