I provide a theoretical model for two empirical phenomena observed in the NYSE and Nasdaq markets. First is the bid-ask bounce recently studied by Heston, Korajczuk and Sadka (HKS, 2008) for high-frequency data. Second is a temporary liquidity squeeze observed by Madureira and Underwood (2008)...

The notion of bubbles is ubiquitous in the public discussion of finance. Yet, the empirical discovery of bubbles is notoriously difficult. The main shortcoming of the current approaches is that they rely on the estimation of the “fundamental value of an asset”, which is hard to estimate and...

In 2008, Epstein and Schneider formulated a microstructure-inspired theory in which one could determine price volatility through a number of other market parameters such as asset volatility, risk free rate and dividend rate. A particular feature of the Epstein-Schneider theory is an extremely...

This paper proposes and motivates a dynamical model of the Chinese stock market based on a linear regression in a dual state space connected to the original state space of correlations between the volume-at-price buckets by a Fourier transform. We apply our model to the price migration of...

The method of the Wigner-Ville function proposed by Wigner, (1932) and Ville (1947) is widely used in quantum statistical mechanics and signal processing and historically preceded the continuous-time wavelets. (Gabor, 1946) Here it is proposed for the studies of the financial time series. One of...

The extremely useful method of Malliavin calculus has not yet gained adequate popularity because of the complicated analytical apparatus of this method. The author attempts here to propose a simplified algebraic formalism similar to Malliavin calculus, but based on the notion of...

This is a teaching case related to the financial valuation of Boeing Co. based on 2011-2015 corporate reports. The case highlights serious anomaly with the Boeing Co. balance sheet in the period 2013-2015. Sample valuation projections for the Boeing stock for the period 2016-2019 are provided...

This paper develops a deep learning-based econometric methodology to determine the causality of the financial time series. This method is applied to the imbalances in daily transactions in individual stocks, as well as the ETFs reported to SEC with a nanosecond time stamp. Based on our method,...