The field of computational finance is evolving ever faster. This book collects a number of novel contributions on the use of computational methods and techniques for modelling financial asset prices, returns, and volatility, and on the use of numerical methods for pricing, hedging, and risk...

This study sets out a new methodology to exemplify, through a set of risk metrics called the Greeks, impact of a bond’s structured provisions (e.g., call, put, and conversion options) on its risk characteristics and its propensity for agency conflicts. The methodology is assessed by applying...

The main objective of this study is to determine a lease agreement to finance an investment project and a solution for managing credit risk. This study investigates three types of contingent leases to reduce the costs associated with bankruptcy and compensate for the lessor's position. A leasing...

As life expectancy increases, pension plans face growing longevity risk. Standardized longevity-linked securities such as survivor contracts allow pension plans to transfer this risk to capital markets. However, more consensus is needed on the appropriate mortality model and premium principle to...

This paper investigates the performance and characteristics of survivor stocks in the S&P 500 index. Using both in-sample and out-of-sample comparisons, survivor stocks outperformed this market index by a considerable margin. Relative to other S&P 500 index companies, survivor stocks tend to be...

The goal of this study is to test the validity of the prospect theory in the Borsa Istanbul (BIST) over the sample period September 2009 to December 2019. The prospect theory values of the stocks are generated from their historical return distributions following the method by Barberis et al....

In this paper, we document the importance of memory in machine learning (ML)-based models relying on firm characteristics for asset pricing. We find that predictive algorithms perform best when they are trained on long samples, with long-term returns as dependent variables. In addition, we...

We use supervised learning to identify factors that predict the cross-section of returns and maximum drawdown for stocks in the US equity market. Our data run from January 1970 to December 2019 and our analysis includes ordinary least squares, penalized linear regressions, tree-based models, and...

I study the effect of heterogeneous beliefs about asset prices on the long-term behavior of financial markets. Starting from the ideas of Abreu and Brunnermeier (2003), a two-dimensional system of differential equations is developed. The first dynamic variable is the asset price growth rate. The...