Risk-averse expected utility maximization implies that the pricing kernel must be a non-increasing function of aggregate wealth. However, empirical research has found that the pricing kernel frequently displays a locally increasing portion in aggregate wealth. This is known as the pricing kernel...

Over-the-counter (OTC) traders cannot pursue the two fundamental objectives of portfolio management, the identification of portfolio market risk and return and its diversification. The result of this major market shortcoming is a complex, systemically risky market disequilibrium. The tradable...

Banks must manage their trading books, not just value them. Pricing includes valuation adjustments collectively known as XVA (at least credit, funding, capital and tax), so management must also include XVA. In trading book management we focus on pricing, hedging, and allocation of prices or...

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We...

The objective of this paper is to analyze the procedures used by multinational enterprises to distribute the income generated by its foreign subsidiaries, and how they allocate the taxes paid on this income through the fiscal jurisdiction in which they operate, from the institution based view....

The 30-year U.S. swap spreads have been negative since September 2008. We offer a novel explanation for this persistent anomaly. Through an illustrative model, we show that underfunded pension plans optimally use swaps for duration hedging. Combined with dealer banks' balance sheet constraints,...

We show that if sophisticated institutional managers and individual investors perceive tail-risks differently, then a new explanation for the pricing kernel puzzle emerges. We show, by example, that even a tiny difference in tail-risk perception by the two investor types can explain the pricing...

Artificial Neural Networks (ANNs) have recently been proposed as accurate and fast approximators in various derivatives pricing applications. ANNs typically excel in fitting functions they approximate at the input parameters they are trained on, and often are quite good in interpolating between...

Potential Future Exposure (PFE) is a standard risk metric for managing business unit counterparty credit risk but there is debate on how it should be calculated. The debate has been whether to use one of many historical ("physical") measures (one per calibration setup), or one of many...