Preface
Preface
Foreword
Preface
Acknowledgements
The evolution of models
The foundations of risk and uncertainty
Uncertainty: a taxonomy
Model risk and uncertainty: a survey of the institutional landscape
Model specification risk and uncertainty
Model operation risk and uncertainty
Data, models and their purpose
Artificial intelligence in finance: a synthesis of human and machine
A deeper dive into machine learning methods: their opportunities, limitations, risks and uncertainties
Measurement of risk and estimation of uncertainty in prediction models
Using models under risk and uncertainty
When models fail
Epilogue: models and the future
Every day confirms my belief of the inconsistency of all human characters, and of the little dependence that can be placed on the appearance of merit or sense.
Jane Austen, Pride and Prejudice
The “inconsistency of all human characters” offers an apt perspective on the behaviour of financial markets: their swings, reversals and seeming contradictions inextricably tied to the unpredictability of human decision-making. It is thus fitting that this book seeks to reflect on such inconsistency in the year marking the 250th anniversary of Austen’s birth.
Despite the inconsistency of human behaviour, economic and financial models seek to explain and predict market behaviour through patterns and regularities, whether observed or assumed. The tension at the intersection of the unpredictable nature of human behaviour and the disciplined logic of models lies at the heart of this book, as we explore the boundary between measurable risk and its less quantifiable cousin, uncertainty. We invite the reader to join us as we examine the tools of traditional statistics and econometrics, the expanding frontier of machine learning and artificial intelligence, and the principles of decision-making under
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