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Kelly, Bryan T.; Malamud, Semyon; Pedersen, Lasse Heje - 2020 - This version: June 8, 2020

We propose a new asset-pricing framework in which all securities' signals are used to predict each individual return. While the literature focuses on each security's own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes...

Persistent link: https://www.econbiz.de/10012271188

Complexity in Factor Pricing Models

Didisheim, Antoine; Ke, Shikun; Kelly, Bryan T.; … - 2023

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance—in terms of SDF Sharpe ratio and average pricing errors—is improving in model parameterization (or “complexity”). Our results predict that the best...

Persistent link: https://www.econbiz.de/10014254198

Comment on 'The Virtue of Complexity in Return Prediction'

Berk, Jonathan - 2023

Persistent link: https://www.econbiz.de/10014355380

Volatility, valuation ratios, and bubbles : an empirical measure of market sentiment

Gao, Can; Martin, Ian - 2021

We define a sentiment indicator based on option prices, valuation ratios and interest rates. The indicator can be interpreted as a lower bound on the expected growth in fundamentals that a rational investor would have to perceive in order to be happy to hold the market. The lower bound was...

Persistent link: https://www.econbiz.de/10012489383

Does Historical Volatility Term Structure Contain Valuable Information for Predicting Volatility and Index Futures?

Jablecki, Juliusz - 2014

We suggest that the term structure of volatility futures (e.g. VIX futures) shows a clear pattern of dependence on the current level of VIX index. At the low level of VIX (below 20) the term structure is highly upward sloping; at the high VIX level (over 30) it is strongly downward sloping. We...

Persistent link: https://www.econbiz.de/10013046744

Can we use volatility to diagnose financial bubbles? : lessons from 40 historical bubbles

Sornette, Didier; Cauwels, Peter; Smilyanov, Georgi - 2017

We inspect the price volatility before, during, and after financial asset bubbles in order to uncover possible … volatility increase before a crash, but we do not see this as a consistent behavior. We examine forty well-known bubbles and … studied bubbles, the crash follows a period of lower volatility, reminiscent of the idiom of a “lull before the storm”. This …

Persistent link: https://www.econbiz.de/10011762277

Forecast of Bitcoin – Can It Become a Major Currency or Is It Just Another Bubble?

Dinges, Christian - 2018

Bitcoin has been described as a decentralized, partially anonymous, virtual currency, not backed by any government or other legal entity. Bitcoins are highly liquid, have low transaction costs, and are very volatile. This paper will look at the behavior of the value of Bitcoins, forecast the...

Persistent link: https://www.econbiz.de/10014116834

Disappointment Aversion, Term Structure, and Predictability Puzzles in Bond Markets

Augustin, Patrick - 2016

We solve a dynamic general equilibrium model with generalized disappointment aversion preferences and continuous state endowment dynamics. We apply the framework to the term structure of interest rates and show that the model generates an upward sloping term structure of nominal interest rates,...

Persistent link: https://www.econbiz.de/10013005999

Causal and Predictive Market Views and Stress-Testing

Vorobets, Anton - 2023

This article introduces a very flexible framework for causal and predictive market views and stress-testing. The framework elegantly combines Bayesian networks (BNs) and Entropy Pooling (EP). In the new framework, BNs are used to generate a finite set of joint causal views / stress-tests for the...

Persistent link: https://www.econbiz.de/10014350645

Quantitative forecast model for the application of the Black-Litterman approach

Becker, Franziska; Gürtler, Marc - 2008 - This Version: 2010-11-10

The estimation of expected security returns is one of the major tasks for the practical implementation of the Markowitz portfolio optimization. Against this background, in 1992 Black and Litterman developed an approach based on (theoretically established) expected equili-brium returns which...

Persistent link: https://www.econbiz.de/10009487257

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