Based on the Partial Distribution (Feng Dai, 2001), a new model to price an asset (MPA) is given. Going a step further, this paper puts forward the Multivariate Partial Distribution (MPD) for the first time. By use of MPD, we could gain a new kind of model for pricing the group assets (MPGA), in...

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...

The risk and return characteristics of a highly diversified investment portfolio are examined in an effort to best assess its potential by means that incorporate both conventional risk estimation and performance evaluation. Estimation of performance variability and downside risk often assumes a...

I derive a generalized version of the fundamental law of active management under some weak conditions. I show that the original fundamental law of Grinold and various extensions are special cases of the result presented in this paper. I also show that cross-sectional ICs are usually different...

In the paper we introduce an empirical approximation of the log-optimal investment strategy that guarantees an almost optimal growth rate of investments. The proposed strategy also considers the effects of portfolio rearrangement costs on growth optimality and advises a suboptimal portfolio for...

In this article we present an efficient optimization for calculating the exposure and CVA for large portfolios of vanilla swaps. It is based on a "thin-out" procedure applied to fixed payment streams, which reduces a very frequent stream of payments to a much less frequent one. The procedure...

The purpose of this document is to review a variety of liquidity measures actively used by academics and practitioners, and to stress their advantages and limits. We focus on bond market that is an Over-The-Counter (OTC) dealer market. In a typical OTC transaction, a buyer or seller contacts an...

The sample covariance matrix is known to contain substantial statistical noise, making it inappropriate for use in financial decision making. Leading researchers have proposed various filtering methods that attempt to reduce the level of noise in the covariance matrix estimator. In most cases,...

We examine machine learning and factor-based portfolio optimization. We find that factors based on autoencoder neural networks exhibit a weaker relationship with commonly used characteristic-sorted portfolios than popular dimensionality reduction techniques. Machine learning methods also lead to...