Financial markets: principles of modelling forecasting and decision-making (Lodz, 2012). - ОГЛАВЛЕНИЕ / CONTENTS
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ОбложкаFinancial markets: principles of modelling forecasting and decision-making / ed. by W.Milo; G.Szafrański, P.Wdowiński. - Łódź: Wydawnictwo Uniwersytetu Łódzkiego, 2012. - 165 p.: ill. - (FindEcon Monograph Series; N 10). - Incl. bibl. ref. - ISBN 978-83-7525-677-2
 

Оглавление / Contents
 
Introduction
   (Władysław Milo, Grzegorz Szafrański and Piotr Wdowiński) .... 7
1  The New Architecture of European Financial Regulatory and
   Supervision Framework (Stanisław Kluza) ..................... 11
   1.1  Introduction ........................................... 11
   1.2  More or Less Europe? ................................... 11
   1.3  System-Weighted Financial Institutions ................. 14
   1.4  The European System of Deposit Guarantee ............... 16
   1.5  Conclusion ............................................. 18
   References .................................................. 18
2  Investor Protection and Disclosure. Quantitative Evidence
   (Marek Gruszczyński) ........................................ 19
   2.1  Introduction: Investor Protection Issues ............... 19
   2.2  Investor Protection and Legal System ................... 20
   2.3  Accounting Disclosure, Corporate Governance and
        Investor Protection .................................... 21
   2.4  Measuring the Level of Disclosure ...................... 22
   2.5  What Are the Research Areas in the Context of
        Disclosure? ............................................ 24
   2.6  Research on the Association between Disclosure and
        Investor Protection .................................... 25
        2.6.1 .Comparative Cross-Country Studies ............... 25
        2.6.2  Research on Specific Type of Disclosure ......... 27
        2.6.3  Single Country Studies .......................... 28
   2.7  Polish Corporate Disclosure Index (PCDI) and Investor
        Protection ............................................. 29
        2.7.1  Composition of PCDI ............................. 29
        2.7.2  PCDI for the Companies Listed on Warsaw Stock
               Exchange ........................................ 31
        2.7.3  PCDI and Investor Protection .................... 32
   2.8  Final Remarks .......................................... 33
   References .................................................. 34
3  Divergent Patterns of Value Relevance (Karol Marek
   Klimczak and Grzegorz Szafrański) ........................... 37
   3.1  Introduction ........................................... 37
   3.2  Hypothesis Development ................................. 39
   3.3  Reporting Regimes in Germany and France ................ 43
   3.4  Panel Framework ........................................ 45
   3.5  Data ................................................... 48
   3.6  Empirical Results ...................................... 49
   3.7  Discussion ............................................. 54
   3.8  Conclusion ............................................. 56
   References .................................................. 56
4  Disaggregated Foreign Trade, Exchange Rate and Growth in
   Poland: Simulation and Optimal Control (Piotr Wdowiński) .... 59
   4.1  Introduction ........................................... 59
   4.2  The Model .............................................. 60
   4.3  Estimation Results ..................................... 61
        4.3.1  Harmonized Consumer Price Index ................. 62
        4.3.2  Producer Price Index ............................ 63
        4.3.3  Private Consumption ............................. 64
        4.3.4  Interbank 3-Month Interest Rate ................. 64
        4.3.5  Exchange Rates .................................. 64
        4.3.6  Unemployment Rate ............................... 65
        4.3.7  Wages in Enterprise Sector ...................... 65
        4.3.8  Imports and Exports ............................. 66
        4.3.9  Summary of Estimation Results ................... 67
   4.4  Simulation Analysis .................................... 68
        4.4.1  The Yield Rate of Open Market Operations ........ 69
        4.4.2  Price of Crude Oil .............................. 70
        4.4.3  Government Consumption in the EU-15 ............. 70
        4.4.4  Exchange Rate Euro/Dollar ....................... 71
        4.4.5  EMU Scenario .................................... 71
   4.5  Optimal Control ........................................ 72
        4.5.1  GDP ............................................. 73
        4.5.2  CPI Inflation ................................... 74
        4.5.3  Unemployment Rate ............................... 75
        4.5.4  Real Wages ...................................... 75
        4.5.5  Exports of Goods and Services ................... 76
        4.5.6  Trade Balance ................................... 76
        4.5.7  Imports in SITC 7 ............................... 77
        4.5.8  Exports to Selected Countries ................... 77
        4.5.9  The Share of Exports to Selected Countries in
               Total Exports ................................... 78
        4.5.10 Exports to Germany .............................. 78
        4.5.11 The Share of Exports to Germany in Total
               Exports ......................................... 79
        4.5.12 Summary of Optimal Control Experiments .......... 80
   4.6  Conclusions ............................................ 81
   Appendix A. Description of Variables ........................ 81
   Appendix B. Simulation Errors ............................... 83
   References .................................................. 85
5  Using Linear Filters for Detecting Cycles in Survey Data
   (Zuzanna Wośko) ............................................. 87
   5.1  Introduction ........................................... 87
   5.2  Indicators of the Climate of Business in Poland ........ 88
   5.3  Linear Filters ......................................... 90
   5.4  Pitfalls of Filtering .................................. 96
   5.5  Data Generating Process and Results of Filtering ....... 99
   5.6  Conclusions ........................................... 104
   References ................................................. 105
6  Multifactor Mutual Fund Performance Evaluation Based on
   the Panel Data Estimation (Joanna Olbryś) .................. 107
   6.1  Introduction .......................................... 107
   6.2  A Brief Literature Review ............................. 108
   6.3  Classical Market-Timing Models ........................ 109
        6.3.1  The T-M Model .................................. 109
        6.3.2  The H-M Model .................................. 110
   6.4  Three-Factor Market-Timing Models ..................... 111
        6.4.1  Fama and French's Spread Variables SMB and
               HML on the Polish Market ....................... 112
        6.4.2  Three-Factor T-M Model With F&F Spread
               Variables (T-M-FF Model) ....................... 113
        6.4.3  Three-Factor H-M Model With F&F Spread
               Variables (H-M-FF Model) ....................... 113
   6.5  Estimation Method - Seemingly Unrelated Regression
        Model (SUR) ........................................... 113
   6.6  Data .................................................. 114
   6.7  Empirical Results ..................................... 115
   6.8  Conclusions ........................................... 118
   References .................................................
7  Jumps in Stock Returns: Evidence from the Polish Stock
   Exchange (Barbara Będowska-Sójka) .......................... 121
   7.1  Introduction .......................................... 121
   7.2  Jumps Detection Methodology: Lee-Mykland Test ......... 122
   7.3  Periodicity in Intraday Data (Non-Parametric
        Approach) ............................................. 124
   7.4  The Sample Description ................................ 126
   7.5  Results: Jump Detection and Events .................... 128
        7.5.1  Jump Detection: The Frequency and Timing ....... 128
        7.5.2  Identification ................................. 130
               7.5.2.1  Jumps in KGHM Return Series ........... 131
               7.5.2.2  Jumps in Other Return Series .......... 134
   7.6  Conclusions ........................................... 134
   References ................................................. 135
8  High Frequency Data Aggregation in Value-at-Risk Models:
   Is Daily Data Enough? (Milda Pranckevičiūtė) ............... 137
   8.1  Introduction .......................................... 137
   8.2  Data Aggregation in Value-at-Risk ..................... 139
        8.2.1  Loss Distribution .............................. 139
        8.2.2  Aggregation of High Frequency Data ............. 140
        8.2.3  Value-at-Risk .................................. 141
               8.2.3.1  Historical Value-at-Risk .............. 142
               8.2.3.2  Parametric Value-at-Risk .............. 142
   8.3  Numerical Example ..................................... 143
        8.3.1  Pointwise FX Rates Aggregation ................. 143
        8.3.2  Daily versus Aggregated VaR .................... 147
   8.4  Conclusions ........................................... 148
   References ................................................. 149
9  Estimating Value-at-Risk for Energy Markets (Blanko Łęt) ... 151
   9.1  Introduction .......................................... 151
   9.2  Definition of Value-at-Risk ........................... 152
   9.3  Methodology ........................................... 153
   9.4  Back Testing .......................................... 156
   9.5  The Data .............................................. 157
   9.6  Empirical Findings .................................... 158
   9.7  Conclusions ........................................... 165
   References ................................................. 165


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