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E-grāmata: Financial Economics and Econometrics

(The American College of Greece, Greece)
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Financial Economics and EconometricsPalielināt
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Financial Economics and Econometrics provides an overview of the core topics in theoretical and empirical finance, with an emphasis on applications and interpreting results.

Structured in five parts, the book covers financial data and univariate models; asset returns; interest rates, yields and spreads; volatility and correlation; and corporate finance and policy. Each chapter begins with a theory in financial economics, followed by econometric methodologies which have been used to explore the theory. Next, the chapter presents empirical evidence and discusses seminal papers on the topic. Boxes offer insights on how an idea can be applied to other disciplines such as management, marketing and medicine, showing the relevance of the material beyond finance. Readers are supported with plenty of worked examples and intuitive explanations throughout the book, while key takeaways, test your knowledge and test your intuition features at the end of each chapter also aid student learning.

Digital supplements including PowerPoint slides, computer codes supplements, an Instructors Manual and Solutions Manual are available for instructors. This textbook is suitable for upper-level undergraduate and graduate courses on financial economics, financial econometrics, empirical finance and related quantitative areas.

Recenzijas

"This unique textbook combines financial economics and financial econometrics at the theoretical and empirical standpoints. One additional novelty is the boxes demonstrating the linkages between Financial Economics/Econometrics with other disciplines such as Management and Marketing. The Computer Codes supplement (for Eviews, RATS, Stata and SPSS) is essential to students who wish to apply the econometric methodologies featured in the book. In all, this textbook can be required reading for undergraduate courses in other Business disciplines, MBA students as well as for financial professionals."

Eleftheria Kostika, Bank of Greece

"An in-depth and contemporary guide to empirical research in finance. This book is well-written and organized and is excellent reading for not only finance students but practitioners and those with an interest in financial data analysis. The topics this book covers are very contemporary and range from corporate finance and asset pricing to cryptocurrencies and fintech. For each topic covered, the book contains a plethora of examples and applications to real-world data."

Dimitrios Koutmos, Texas A&M University, USA

"The book is comprehensive starting from financial data calculations to most recent econometric developments and contemporary topics in financial economics. The author makes complex material understandable and provides examples with all popular econometric software. This book is a foundation stone for every economist who wants to learn and fully understand the dynamically expanding field of financial econometrics and appreciate the current issues in financial economics. Also, for anyone who has to teach finance and investments, this book is to be recommended."

Konstantinos Syriopoulos, Zayed University, United Arab Emirates

List of figures xxiii
List of tables xxvii
List of boxes xxix
Preface xxxi
Acknowledgments xxxv
Part I Characteristics of financial data and univariate models 1(178)
1 Introduction to financial economics and econometrics
3(10)
1 What is financial economics?
3(2)
2 What is financial econometrics?
5(2)
3 What are quantitative finance and financial engineering?
7(1)
4 Financial economics and econometrics and other disciplines
7(1)
5 Plan of the book
8(5)
2 How to write a research paper
13(10)
Introduction
13(1)
1 Finding a topic
14(1)
2 Literature review
15(1)
3 Methodology
15(1)
4 Data
16(1)
5 Empirical analysis and discussion
17(1)
6 Summary and conclusions
17(1)
7 Finance journals and data sources
18(3)
8 Putting it all together
21(2)
3 The characteristics of financial series
23(44)
Introduction
23(1)
1 Macro vs. financial data
23(1)
2 Distributional properties of financial series
24(21)
2.1 Raw vs. transformed series
25(4)
2.2 Descriptive statistics
29(9)
2.3 Graphical illustrations
38(5)
2.4 Some empirical evidence
43(2)
3 Stylized facts of financial series
45(14)
3.1 Linear dependencies
45(1)
3.2 Nonstationarity
46(3)
3.3 Calendar effects
49(1)
3.4 Long memory
50(1)
3.5 Nonlinearities
51(4)
3.6 Chaos
55(1)
3.7 Other characteristics
56(13)
3.7.1 Scaling
56(1)
3.7.2 Volume
57(1)
3.7.3 Extreme values
58(1)
Key takeaways
59(2)
Test your knowledge
61(1)
Test your intuition
62(5)
4 Univariate properties of financial time series
67(58)
1 Introduction
67(2)
2 Nonstationarity
69(6)
2.1 Nonstationary models
71(4)
3 Stationarity and processes
75(41)
3.1 Making a series stationary
77(3)
Differencing
78(1)
Curve fitting
78(2)
3.2 Autoregressive model
80(4)
3.2.1 Autocorrelation function
82(1)
3.2.2 Partial autocorrelation function
83(1)
3.3 Moving average model
84(3)
3.4 ARMA model
87(3)
3.4.1 Causality in ARMA(p,q)
89(1)
3.5 Building AR, MA and AR(I)MA models
90(1)
3.6 The Box-Jenkins approach
91(35)
3.6.1 Model identification
91(1)
Graphical approach
91(10)
3.6.2 Econometric approach
101(5)
3.6.3 Model estimation
106(1)
3.6.4 Model validation
107(1)
3.6.5 Forecasting
107(2)
3.6.6 Some comments on ARMA specifications
109(1)
An example
110(5)
3.6.7 Overview of modeling and forecasting time series
115(1)
4 Some empirical evidence
116(1)
Key takeaways
117(1)
Test your knowledge
118(3)
Test your intuition
121(4)
5 Short- and long-run relationships among time series
125(54)
1 Introduction
125(1)
2 Short-term relationships
126(6)
2.1 Covariance and correlation
126(2)
2.2 Causality
128(4)
2.2.1 Granger causality
130(1)
2.2.2 Application
131(1)
2.2.3 Early evidence on causality among stock prices and macro variables
132(1)
3 Unit roots
132(12)
3.1 Motivation
132(2)
3.2 Dickey-Fuller unit root tests
134(1)
3.3 Phillips-Perron unit root test
135(2)
3.4 Kwiatkowski, Phillips, Schmidt and Shin unit root test
137(1)
3.5 Ng and Perron unit root test
138(1)
3.6 On the inclusions of a constant and/or a trend
138(1)
3.7 An example
139(2)
3.8 Unit root testing under structural breaks
141(2)
3.8.1 Some issues
141(1)
3.8.2 Some examples
142(1)
3.9 Empirical evidence
143(1)
4 Cointegration
144(22)
4.1 Motivation
144(1)
4.2 Cointegration tests
145(21)
4.2.1 The Engle and Granger cointegration approach
146(3)
4.2.2 Some examples of cointegration and economic equilibrium
149(1)
Stock prices and dividends
149(1)
Purchasing power parity
150(1)
Consumption, income and wealth
151(1)
Money demand
152(1)
Relationships among interest rates
153(1)
4.2.3 The residuals-based cointegration approach
153(1)
4.2.3 The Phillips-Ouliaris cointegration test
154(1)
4.2.4 The Durbin-Watson cointegrating statistic test
154(1)
4.2.5 Autoregressive distributed lag (ADL) model
155(1)
An example
155(1)
4.2.6 The Johansen approach
156(3)
4.2.7 Rolling-sample cointegration
159(1)
4.2.8 A trivariate VECM
160(1)
4.2.9 An example
161(3)
4.2.10 Advances in cointegration
164(2)
5 Cross (auto)correlations
166(4)
5.1 Definition
166(1)
5.2 Motivation
166(1)
5.3 Implementation and interpretation
167(2)
5.3.1 An example
168(1)
5.4 Some empirical evidence
169(1)
Key takeaways
170(2)
Test your knowledge
172(1)
Test your intuition
173(6)
Part II Asset returns 179(186)
6 The efficient market hypothesis and tests
181(60)
Introduction
181(1)
1 The efficient market hypothesis (EMH)
182(19)
1.1 Preliminaries
182(3)
1.2 Forms of market efficiency
185(6)
1.3 Tests of market efficiency
191(2)
1.3.1 Nonparametric tests
193(3)
Run(s) test
193(1)
Unit root tests
194(2)
1.3.2 Parametric tests
196(5)
Variance ratio tests
196(3)
Serial correlation tests
199(2)
2 Other tests of market efficiency
201(11)
2.1 Preliminaries
201(2)
2.2 Event study methodology
203(9)
2.2.1 Abnormal returns
203(1)
Cumulative abnormal returns
203(1)
Buy-and-hold abnormal returns
205(1)
Jensen's alpha
206(1)
2.2.2 Complications
207(1)
On computing expected and normal returns
207(1)
On setting the statistical hypotheses
208(1)
Other potential issues
209(1)
2.2.3 Event study design
210(2)
3 Other models for testing the EMH
212(6)
3.1 Univariate models
212(2)
3.2 Multivariate models
214(2)
3.3 Other models
216(2)
4 Selected empirical evidence
218(7)
4.1 Short-term patterns in stock returns
218(2)
4.2 Long-term patterns in stock returns
220(4)
4.3 Market anomalies
224(1)
5 Where do we stand now on EMH?
225(3)
Key takeaways
228(2)
Test your knowledge
230(2)
Test your intuition
232(9)
7 The capital asset pricing model and its variants
241(60)
Introduction
241(1)
1 Theoretical motivation
242(15)
1.1 Risk aversion, portfolio risk and diversification
242(3)
1.2 Mean-variance model in brief
245(2)
1.3 Assumptions of CAPM
247(1)
1.4 Derivation of CAPM
248(4)
1.5 The security market line
252(2)
1.6 The zero-beta model
254(1)
1.7 Some issues with CAPM
255(2)
2 Econometric methodologies
257(22)
2.1 The simple linear regression model
257(3)
2.2 CAPM specifications
260(1)
2.2.1 Time-series specifications
260(7)
The Single Factor Model
260(7)
2.2.2 Cross-section regression specifications
267(7)
The Black, Jensen and Scholes approach
268(1)
The Fama-MacBeth methodology
269(3)
M-CAPM vs. B-CAPM vs. SL-CAP
272(1)
The Fama-French methodologies
273(1)
2.2.3 The generalized method of moments approach
274(2)
2.3 Empirical evidence on CAPM
276(3)
2.3.1 Roll's critique
278(1)
3 Some extensions/variants of CAPM
279(10)
3.1 Merton's intertemporal CAPM
279(2)
3.2 The consumption CAPM
281(3)
3.3 The X-CAPM
284(1)
3.4 The liquidity CAPM
285(2)
3.5 The international CAPM
287(1)
3.6 The H-CAPM
288(1)
4 The equity premium puzzle
289(2)
4.1 The problem
289(1)
4.2 Explaining the puzzle
290(1)
Key takeaways
291(3)
Test your knowledge
294(1)
Test your intuition
295(6)
8 Multifactor models and the Arbitrage Pricing Theory
301(64)
Introduction
301(1)
1 Categories of factor models
302(3)
1.1 Macroeconomic factor models
303(1)
1.2 Fundamental factor models
304(1)
1.3 Statistical factor models
304(1)
2 Factor-construction methodologies
305(7)
2.1 Autoregressive process
306(1)
2.2 Moving average process
306(1)
2.3 ARMA process
307(1)
2.4 Time-series regression methodology
308(1)
2.5 Cross-section regression methodology
309(1)
2.6 Factor and principal components analyses
310(2)
2.6.1 Factor analysis
310(1)
2.5.2 Principal component analysis
311(1)
3 Determining the number of factors
312(3)
3.1 Some empirical evidence
314(1)
4 The Arbitrage Pricing Theory
315(16)
4.1 Assumptions
315(1)
4.2 Differences between APT and CAPM
316(1)
4.3 The specification
317(1)
4.4 Factor sensitivities
317(2)
4.5 What are the common or systematic factors?
319(1)
4.6 Empirical tests and applications of APT
319(3)
4.7 Empirical analyses of APT
322(3)
Time-series regressions
323(2)
4.8 International APT
325(1)
4.9 Some notable APT applications
326(5)
Chen, Roll and Ross
326(2)
Chan, Chen and Hsieh
328(1)
Some comments on the CRR and CCH papers
328(1)
Flannery and Protopapadakis
329(2)
5 Important multifactor models
331(5)
5.1 The Fama and French three-factor model
331(2)
5.2 The expanded FF three-factor model
333(1)
5.3 The FF five-factor model
334(1)
5.4 The Carhart four-factor model
335(1)
6 Other multifactor models
336(5)
6.1 The Pastor-Stambaugh model
336(1)
6.2 The Burmeister, Roll and Ross model
337(1)
6.3 The Fung-Hsieh factor models
338(2)
6.4 The Hou, Xue and Zhang q-factor model
340(1)
7 Some econometric issues and methodologies
341(8)
7.1 Heteroscedasticity
341(4)
7.1.1 The White test
342(1)
7.1.2 The Goldfeld-Quandt test
343(1)
7.1.3 The generalized least squares approach
344(1)
7.2 Serial correlation
345(2)
7.2.1 The Cochrane-Orcutt approach
346(1)
7.3 Quantile regression
347(2)
7.4 Rolling regression
349(1)
8 Some final comments on multifactor models
349(3)
Key takeaways
352(3)
Test your knowledge
355(1)
Test your intuition
356(9)
Part III Interest rates, yields and spreads 365(102)
9 The risks and the term structure of interest rates
367(50)
Introduction
367(1)
1 Interest-rate determination
368(6)
1.1 The loanable funds theory
369(3)
1.2 The liquidity preference theory
372(2)
2 US Treasury bills and inflation
374(2)
3 Money and capital market rates
376(4)
3.1 Money market rates
377(1)
3.2 Capital market rates
378(2)
4 The risk structure of interest rates
380(1)
5 The term structure of interest rates
381(8)
5.1 The yield curve
382(3)
5.1.1 Spot and forward rates
383(1)
5.1.2 Slopes of the yield curve
384(1)
5.2 Swap rate yield curve
385(1)
5.3 Theories of the term structure of interest rates
385(3)
5.3.1 The expectations theory
386(1)
5.3.2 The liquidity preference theory
387(1)
5.3.3 The preferred habitat theory
387(1)
5.3.4 The market segmentation theory
388(1)
5.4 Practical importance of the yield curve
388(1)
6 Some empirical evidence on the term structure
389(2)
7 Interest rate models
391(12)
7.1 Some basic concepts
391(2)
7.2 Single-factor, short interest rate models
393(4)
7.2.1 The Vasicek (1977) models
393(1)
7.2.2 The Rendleman-Bartter (1980) model
394(1)
7.2.3 The Hull and White (1987, 1990) model
394(1)
7.2.4 The Cox-Ingersoll-Ross (1985) model
395(1)
7.2.5 The Ho and Lee (1986) model
395(1)
7.2.6 The Dothan (1978) model
395(1)
7.2.7 The Black-Derman-Toy (1990) model
396(1)
7.2.8 The Black and Karasinski (1991) model
396(1)
7.2.9 The Heath et al. (1992) model
396(1)
7.2.10 The Kalotay-Williams-Fabozzi (1993) model
397(1)
7.2.11 The Squared Gaussian Model
397(1)
7.3 Evaluation of one-factor, short rate models
397(2)
7.4 Multifactor interest rate models
399(3)
7.4.1 The Brennan and Schwartz (1979) model
400(1)
7.4.2 The Richard (1978) model
400(1)
7.4.3 The Longstaff and Schwartz (1992) model
401(1)
7.4.4 The Chen (1996a,b) model
401(1)
7.5 The LIBOR market-rate model
402(1)
8 Some empirical evidence
403(3)
Key takeaways
406(3)
Test your knowledge
409(1)
Test your intuition
409(8)
10 Yields, spreads and exchange rates
417(50)
Introduction
417(1)
1 Bond yields and spreads
418(6)
1.1 Bond prices and yields
418(1)
1.2 Bond yield spreads
419(2)
1.3 Some spreads and their meaning
421(3)
2 The economic significance of yield spreads
424(8)
2.1 Yield spreads and economic magnitudes
424(7)
2.2 Spreads and risk components
431(1)
3 Econometric modeling
432(6)
3.1 Logit model
432(1)
3.2 Probit model
433(2)
3.2.1 Interpretation and application
434(1)
3.3 Multinomial models
435(2)
3.4 Cointegration among spreads
437(1)
4 Exchange rates
438(9)
4.1 Some important laws
438(6)
4.1.1 The law of one price
438(1)
4.1.2 The theory of purchasing power parity
438(2)
4.1.3 Demand and supply analysis
440(1)
4.1.4 The interest rate parity theorem
441(1)
4.1.5 The covered interest rate parity
442(1)
4.1.6 The uncovered interest rate parity
442(1)
4.1.7 The forward rate unbiasedness condition
443(1)
4.1.8 The real interest rate parity
444(1)
4.2 Some empirical evidence
444(1)
4.3 The forward premium puzzle
445(2)
5 Some econometric methodologies
447(5)
5.1 Simultaneous equations
447(1)
5.2 The indirect least squares method
448(2)
5.2.1 The identification issue
449(1)
5.3 The 2-stage least squares approach
450(1)
5.4 The instrumental variables approach
450(1)
5.5 VARNEC models
451(1)
An illustration
452(5)
Key takeaways
457(3)
Test your knowledge
460(1)
Test your intuition
461(6)
Part IV Volatility and correlation 467(98)
11 Volatility modeling and forecasting
469(50)
1 Introduction
469(4)
2 Volatility and returns
473(4)
2.1 Empirical regularities of volatility
473(2)
2.2 Sources of volatility and stock returns
475(1)
2.3 Implied vs. realized volatility
476(1)
3 Volatility models
477(14)
3.1 ARCH model
477(2)
3.2 GARCH model
479(4)
An illustration of ARCH and GARCH models
481(2)
3.3 (G)ARCH-M
483(2)
3.4 Exponential GARCH
485(1)
3.5 The Glosten et al. (1993) model
485(1)
3.6 Threshold (G)ARCH
486(1)
3.7 Asymmetric Power ARCH
486(1)
3.8 Other GARCH-type models
487(1)
Some illustrations using the aforementioned models
488(1)
3.9 Tests for asymmetries
488(1)
3.10 News impact curves
489(2)
3.11 Model building
491(1)
4 Forecasting volatility
491(6)
4.1 Exponential smoothing
492(1)
4.2 Exponentially weighted moving average
492(1)
4.3 GARCH-type models
493(2)
4.4 Some empirical evidence
495(2)
5 Other variants of GARCH models
497(2)
6 Stochastic volatility
499(3)
7 Realized variance
502(2)
8 Volatility as an asset class
504(2)
Key takeaways
506(4)
Test your knowledge
510(1)
Test your intuition
511(8)
12 Correlation modeling
519(46)
1 Introduction
519(2)
2 Covariance and correlation
521(11)
2.1 Covariances and correlations
521(7)
A portfolio example
526(1)
An example of CAPM beta
527(1)
A hedge ratio example
527(1)
2.2 Some general discussion on correlation and covariance
528(1)
2.3 Simple covariance models
529(1)
2.3.1 Implied covariance and correlation model
529(1)
2.3.2 Exponentially weighted moving average covariance model
529(1)
2.3.3 GARCH-covariance model
530(1)
2.4 Contagion and interdependence (spillovers)
530(2)
2.4.1 Theories of contagion and spillovers
530(1)
2.4.2 A simple model to measure contagion and spillovers
531(1)
3 Multivariate GARCH models
532(15)
3.1 VECH models
533(1)
3.2 The BEKK model
534(1)
3.3 Factor GARCH models
535(1)
3.4 The constant conditional correlation GARCH model
536(1)
3.5 The dynamic conditional-correlation GARCH model
536(1)
3.6 Dynamic equicorrelation model
537(1)
3.7 Asymmetric MGARCH
538(1)
3.8 The copula-MGARCH model
538(9)
Applications of some MGARCH models
539(8)
4 Regime-switching models
547(8)
4.1 Markov-switching models
548(2)
4.2 Markov-switching (G)ARCH models
550(3)
4.3 Some financial applications
553(2)
Key takeaways
555(2)
Test your knowledge
557(2)
Test your intuition
559(6)
Part V Topics in financial management 565(154)
13 Capital structure and dividend decisions
567(62)
1 Introduction
567(1)
2 Theories of capital structure
568(8)
2.1 The trade-off theory
569(2)
2.1.1 Costs of bankruptcy
570(1)
2.2 The pecking order theory
571(1)
2.3 The free-cash flow theory
572(1)
2.4 Other theories of capital structure
573(3)
3 Methodologies used in capital structure
576(10)
3.1 Linear, multiple discriminant analysis
577(3)
3.1.1 Altman's Z-score models
577(3)
3.2 Categorical-variable models
580(2)
3.2.1 Censored and truncated variables
581(1)
3.3 Panel analysis
582(2)
3.3.1 The fixed-effects model
583(1)
3.3.2 The random-effects model
583(1)
3.4 Econometric issues
584(2)
4 Empirical evidence on capital structure and additional insights
586(4)
4.1 Empirical evidence on capital structure theories
586(2)
4.2 Additional research on capital structure
588(2)
5 Dividend policies and theories
590(11)
5.1 The Modigliani and Miller dividend irrelevance proposition
592(2)
5.2 The information content of dividends
594(2)
5.2.1 The signaling theory
595(1)
5.3 The clientele effect theory
596(1)
5.4 The tax effect theory
597(1)
5.5 The transactions cost-induced effect
598(1)
5.6 The bird-in-the-hand theory
598(1)
5.7 The agency cost or the free-cash flow hypothesis
599(1)
5.8 The residual dividend theory
600(1)
5.9 The firm life-cycle theory of dividend payout
600(1)
5.10 The dividend-smoothing theory
601(1)
6 Empirical evidence on dividend theories
601(12)
6.1 Empirical tests of dividend theories
602(6)
6.2 Other tests of dividend policies literature
608(2)
6.3 A brief recap of dividend theories and empirical evidence
610(3)
Key takeaways
613(7)
Test your knowledge
620(1)
Test your intuition
621(8)
14 Mergers, acquisitions and corporate restructurings
629(46)
1 Introduction
629(2)
2 Mergers, acquisitions and restructurings
631(11)
2.1 Motives for mergers
631(5)
2.1.1 Economies of scale, scope and integration
631(1)
2.1.2 Achieving efficiencies
632(1)
2.1.3 Tax advantages
633(1)
2.1.4 Other motives
633(3)
2.2 Acquisitions
636(2)
2.2.1 Gains from an acquisition
638(1)
2.3 Corporate restructuring
638(4)
2.3.1 Reasons for corporate restructuring
639(1)
Divestitures
639(1)
Spin-offs
639(1)
Equity carve-outs
640(1)
Split-offs
641(1)
Liquidation
641(1)
Privatization
641(1)
2.3.2 The distressed exchange restructuring theory
641(1)
3 Econometric methodologies in M&A investigations
642(4)
3.1 Conditional logit
642(2)
3.2 Survival analysis
644(2)
4 Empirical evidence on mergers and acquisitions
646(8)
4.1 Announcement event studies
646(2)
4.2 Pre- and post-merger firm performance
648(1)
4.3 Impact of a merger or acquisition on financial performance
649(2)
4.4 Market valuation and merger activity
651(1)
4.5 Selected international evidence on mergers and acquisitions
652(2)
5 Studies using conditional logit, tobit and survival analysis
654(5)
5.1 Studies having used the conditional logit
654(2)
5.2 Studies having used the Tobit model
656(1)
5.3 Studies having used survival analysis
657(2)
6 Empirical evidence on corporate restructuring
659(2)
Key takeaways
661(4)
Test your knowledge
665(1)
Test Your intuition
666(9)
15 Contemporary topics in financial economics
675(44)
1 Introduction
675(1)
2 Market microstructure
676(10)
2.1 Price discovery and formation
677(2)
2.2 Market structure and design
679(2)
2.3 Market transparency
681(1)
2.4 Trader anonymity
681(1)
2.5 High-frequency trading
682(4)
2.5.1 Traditional market-making vs. HFT market-making
683(1)
2.5.2 HFT strategies
683(3)
3 Empirical evidence on market microstructure and high-frequency trading
686(5)
3.1 Selected research on market microstructure
686(3)
3.2 Selected empirical evidence on high-frequency trading
689(2)
4 Econometric methodologies
691(6)
4.1 The state-space model
691(1)
4.2 The autoregressive conditional duration model
692(1)
4.3 The differences-in-differences specification
693(2)
An application
694(1)
4.4 CoVaR
695(2)
5 Cryptocurrencies
697(4)
5.1 Some statistical characteristics of cryptocurrencies
698(2)
5.2 Cryptos as an asset class and linkages with other financial assets
700(1)
5.3 Other attributes of cryptocurrencies
701(1)
6 Financial technology
701(6)
6.1 Fintech and banking
702(2)
6.2 Research on fintech
704(3)
6.3 The future of fintech
707(1)
Key takeaways
707(4)
Test your knowledge
711(1)
Test your intuition
711(8)
Index 719
Nikiforos T. Laopodis is a finance professor in the School of Business and Economics at the American College of Greece, Athens, Greece.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97810005060512e.html
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