We consider ARCH processes with persistent covariates and provide asymptotic theories that explain how such covariates affect various characteristics of volatility. Specifically, we propose and study a volatility model, named ARCH-NNH model, that is an ARCH(1) process with a nonlinear function...

This paper presents an analytically tractable and practically-oriented model of non-linear dynamics of a multi-asset market in the limit of a large number of assets. The asset price dynamics are driven by money flows into the market from external investors, and their price impact. This leads to...

In this paper, we intend to gain an understanding of the drivers of stock convexity, also known as gamma. First, using a bottom-up – firm-level – approach, we showcase that stock fundamentals, in particular metrics related to value (captured by the price-to-book ratio) and historical...

The bedrock of financial economics is that there should be a tradeoff between risk and reward: an investment with low risk should have a low expected return, while one that could make you rich should also be one which could lose you a lot of money. A lot of research in finance is focused on...

This paper finds that jurisdictional gaps in cryptocurrency regulation, including regulatory uncertainty and the receptiveness of the legal standing, taxation, and anti–money laundering laws, have incremental explanatory power for the cross-jurisdiction price disparity of the same...

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models’ accuracy is high enough. Therefore, in this study, we propose a novel way to improve the...

Machine Learning algorithms have been widely used and proven effective in financial markets. In this paper, we introduced a Machine Learning model set trained on the residual factors from the Fama-French three-factor model (Fama and French, 1992) to find significant alpha factors. To include...

The central question addressed in this note is whether it is better to sell (and re-purchase) appreciated assets now and pay today's long-term capital gains tax rate, or wait to realize gains in the future and pay a likely higher capital gains tax rate. The authors argue that a framework based...

We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher...

This paper estimates dynamic factors from the term structure of credit spreads and the term structure of equity option implied volatilities, and it provides a comprehensive characterization of the dynamic relationships among those credit spread factors and equity volatility factors. The paper...