Algorithmic Differentiation (AD), also known as automatic differentiation, computes the derivative(s) of computer code. It was pioneered by (Giles and Glasserman, 2006) and produces exact derivatives with low latency. AD is well presented in finance, see (Capriotti, 2010), (NAG, n.d.) and...

We present Algorithmic Adjoint Differentiation (AAD), also known as Automatic Adjoint Differentiation, which computes the derivative(s) of computer code. In finance this leads to a relatively new and novel approach, pioneered by (Giles and Glasserman, 2006), to compute financial risks. When...

In this paper, a continuous-time, structural model of a dealer-bank is presented to derive fair value equations for credit-risky financial products that are not perfectly hedged. The impact these contracts have on the dealer-bank's earnings volatility, and consequently, their solvency and...

The aim of this manuscript is to provide the mathematical and statistical foundations of actuarial learning. This is key to most actuarial tasks like insurance pricing, product development, claims reserving and risk management. The basic approach to these tasks is regression modeling. This...

Most people have consumer loans during their lives, making it important that consumer credit legislation is effective. Legislation in many countries is based on the US Truth-in-Lending Act (TILA). Conventional financial analysis underlying the TILA argues the annual percentage rate (APR) is the...

This article maintains that the annual percentage rate (APR) is not an adequate measure of the cost of a consumer loan and therefore the central role of APR in consumer credit legislation should end. For decades, researchers, consumer groups and financial institutions have argued for simpler...

We consider a large trader liquidating a portfolio using a transparent trading venue with price impact and a dark pool with execution uncertainty. The optimal execution strategy uses both venues continuously, with dark pool orders over-/underrepresenting the portfolio size depending on return...

We propose a novel intraday instantaneous volatility measure which utilises sequences of drawdowns and drawups non-equidistantly spaced in physical time as indicators of high-frequency activity of financial markets. The sequences are re-expressed in terms of directional-change intrinsic time...

A portfolio of independent, but not identically distributed, returns is optimized under the variance risk measure, in the high-dimensional limit where the number N of the different assets in the portfolio and the sample size T are assumed large with their ratio r=N/T kept finite, with a ban on...