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...

This paper studies the nature of volatility spillovers across countries from the per-spective of network theory and by relying on data of US-listed ETFs. I use a Lasso-related technique to estimate the International Volatility Network (IVN) where the nodes correspond to large-cap international...

The hidden nature of causality is a puzzling, yet critical notion for effective decision-making. Financial markets are characterized by fluctuating interdependencies which seldom give rise to emergent phenomena such as bubbles or crashes. In this paper, we propose a method based on symbolic...

This paper develops methods and a framework of financial market theory. We model financial markets as a system of agents which perform market transactions with other agents under the action of numerous expectations. Agents' expectations are formed of economic and financial variables, market...

This paper presents a quantitative model of financial transactions between economic agents on economic space. Risk ratings of economic agents play role of their coordinates. Aggregate amounts of agent's financial variables at point x define macro financial variables as functions of time and...

Financial constraints are expected to be severe in Vietnam, especially for private firms, but there is limited quantitative evidence for the size of financial constraints experienced by SOEs and private firms and the resulting efficiency losses. This paper investigates the size of the capital...

We explore in this paper the use of deep signature models to predict equity financial time series returns. First, we use signature transformations to model the underlying shape of the input equity returns; further assuming the underlying shape remains the same, we predict future values based on...

I provide a measure of time-varying tail risk in credit markets based on a dynamic power-law model. Credit tail risk is estimated from extreme price fluctuations of credit default swaps (CDS) on government debt. Tail returns are described by a power-law for core and peripheral countries within...

While attention is a predictor for digital asset prices, and jumps in Bitcoin prices are well-known, we know little about its alternatives. Studying high frequency crypto data gives us the unique possibility to confirm that cross market digital asset returns are driven by high frequency jumps...