We address the problem of asset pricing in a market where there are no risky assets. Previous work developed a theoretical model for a shadow riskless rate (SRR) for such a market, based on the drift component of the state-price deflator for that asset universe. Assuming that asset prices are...

Using the Donsker-Prokhorov invariance principle, we extend the Kim-Stoyanov-Rachev-Fabozzi option pricing model to allow for variably-spaced trading instances, an important consideration for short-sellers of options. Applying the Cherny-Shiryaev-Yor invariance principles, we formulate a new...

We present a unified, market-complete model that integrates both Bachelier and Black- Scholes-Merton frameworks for asset pricing. The model allows for the study, within a unified framework, of asset pricing in a natural world that experiences the possibility of negative security prices or...

This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize conditional value-at-risk and investigate two performance attributes, asset allocation (AA) and the selection effect (SE), as constraints on asset...

In this paper we investigate how a deep learning machine learning model can be applied to improve Bitcoin price forecasting and trading by incorporating unstructured information from financial news. The two-stage model we propose outperforms other machine learning models significantly. In the...

In this paper, we empirically investigate the impact of intensified competition on rating quality in the credit rating market for residential mortgage-backed securities (RMBS) in the period 2017-2020. We provide evidence that competition between large credit rating agencies (CRAs) (Moody's and...

There appears to be a consensus that the recent instability in global financial markets may be attributable in part to the failure of financial modeling. More specifically, current risk models have failed to properly assess the risks associated with large adverse stock price behavior. In this...

Recently, a body of academic literature has focused on the area of stable distributions and their application potential for improving our understanding of the risk of hedge funds. At the same time, research has sprung up that applies standard Bayesian methods to hedge fund evaluation. Little or...