Showing posts with label Econometrics. Show all posts
Showing posts with label Econometrics. Show all posts

Friday, March 27, 2009

Expert Political Judgment



The expert on experts is Philip Tetlock, a professor at the University of California, Berkeley. His 2005 book, “Expert Political Judgment,” is based on two decades of tracking some 82,000 predictions by 284 experts. The experts’ forecasts were tracked both on the subjects of their specialties and on subjects that they knew little about.

The result? The predictions of experts were, on average, only a tiny bit better than random guesses — the equivalent of a chimpanzee throwing darts at a board.

“It made virtually no difference whether participants had doctorates, whether they were economists, political scientists, journalists or historians, whether they had policy experience or access to classified information, or whether they had logged many or few years of experience,” Mr. Tetlock wrote....

Mr. Tetlock called experts such as these the “hedgehogs,” after a famous distinction by the late Sir Isaiah Berlin (my favorite philosopher) between hedgehogs and foxes. Hedgehogs tend to have a focused worldview, an ideological leaning, strong convictions; foxes are more cautious, more centrist, more likely to adjust their views, more pragmatic, more prone to self-doubt, more inclined to see complexity and nuance. And it turns out that while foxes don’t give great sound-bites, they are far more likely to get things right....

So what about a system to evaluate us prognosticators? Professor Tetlock suggests that various foundations might try to create a “trans-ideological Consumer Reports for punditry,” monitoring and evaluating the records of various experts and pundits as a public service. I agree: Hold us accountable!

-Learning How to Think

Sunday, January 25, 2009

Can we anticipate future correlations?


Anticipating Correlations: A New Paradigm for Risk Management
Robert Engle

TABLE OF CONTENTS:

Introduction vii

Chapter 1: Correlation Economics 1
1.1 Introduction 1
1.2 How Big Are Correlations? 3
1.3 The Economics of Correlations 6
1.4 An Economic Model of Correlations 9
1.5 Additional Influences on Correlations 13

Chapter 2: Correlations in Theory 15
2.1 Conditional Correlations 15
2.2 Copulas 17
2.3 Dependence Measures 21
2.4 On the Value of Accurate Correlations 25

Chapter 3: Models for Correlation 29
3.1 The Moving Average and the Exponential Smoother 30
3.2 Vector GARCH 32
3.3 Matrix Formulations and Results for Vector GARCH 33
3.4 Constant Conditional Correlation 37
3.5 Orthogonal GARCH 37
3.6 Dynamic Conditional Correlation 39
3.7 Alternative Approaches and Expanded Data Sets 41

Chapter 4: Dynamic Conditional Correlation 43
4.1 DE-GARCHING 43
4.2 Estimating the Quasi-Correlations 45
4.3 Rescaling in DCC 48
4.4 Estimation of the DCC Model 55

Chapter 5: DCC Performance 59
5.1 Monte Carlo Performance of DCC 59
5.2 Empirical Performance 61
Chapter 6: The MacGyver Method 74
Chapter 7: Generalized DCC Models 80
7.1 Theoretical Specification 80
7.2 Estimating Correlations for Global Stock and Bond Returns 83

Chapter 8: FACTOR DCC 88
8.1 Formulation of Factor Versions of DCC 88
8.2 Estimation of Factor Models 93

Chapter 9: Anticipating Correlations 103
9.1 Forecasting 103
9.2 Long-Run Forecasting 108
9.3 Hedging Performance In-Sample 111
9.4 Out-of-Sample Hedging 112
9.5 Forecasting Risk in the Summer of 2007 117

Chapter 10: Credit Risk and Correlations 122
Chapter 11: Econometric Analysis of the DCC Model 130
11.1 Variance Targeting 130
11.2 Correlation Targeting 131
11.3 Asymptotic Distribution of DCC 134
Chapter 12: Conclusions 137


Related;
FT Business School: Global Financial Volatility
Why are current risk measures so low, when we think there are serious financial risks? Nobel prize-winning economist Robert Engle, professor of finance and director of the Centre for Financial Econometrics at NYU’s Stern School of Business, presents how volatility can be used to assess risk. He explains how ARCH and GARCH can measure time-varying volatility.