Classical quantitative finance models such as the Geometric Brownian Motion or its later extensions such as local or stochastic volatility models do not make sense when seen from a physics-based perspective, as they are all equivalent to a negative mass oscillator with a noise. This paper...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

Portfolio ChoiceIntroductionUtilityMean-variance analysisThe Binomial ModelOne-period modelMulti-period modelA General Discrete-Time ModelOne-period modelMulti-period modelBrownian MotionIntroductionHitting-time distributionsGirsanov's theoremBrownian motion as a limitStochastic calculusThe...

In establishing the foundation of their investment process, global equity investors typically adopt a framework along geographic and/or industry dimensions. The chosen framework is then applied to the whole investment process including alpha generation, portfolio construction, and risk...

In this paper we address three main objections of behavioral finance to the theory of rational finance, considered as “anomalies” the theory of rational finance cannot explain: (i) Predictability of asset returns; (ii) The Equity Premium; (iii) The Volatility Puzzle. We offer resolutions of...

Most retirement withdrawal rate studies are either based on historical data or use a particular assumption about portfolio returns unique to the study in question. But planners may have their own capital market expectations for future returns from stocks, bonds, and other assets they deem...