The emergence of FinTech lending companies can be attributed to the convergence of factors such as the widespread use of the internet, advancements in machine learning, and a decline in trust towards traditional banking systems following the financial crisis of 2006-08. These companies have...

We give a general treatment of the Vanna-Volga mark-to-market volatility smile correction in application to pricing of contracts with European exercise on a single underlying. The method remains applicable in cases of delayed or misaligned expiries and absolute dividends. It is also applied to...

Using an outlier identification methodology this study assesses the impact of extreme news and economic announcements have on the daily log-returns of 16 commodity spot price series and 25 commodity index series and their conditional volatility. Between January 1, 1997 and December 31, 2007, the...

We introduce a method for volatility computation from listed prices of American options on an underlying close to log-normal. From prices of American calls and puts, traded at an exchange at multiple strikes we compute the underlying volatility and implied volatility of an untraded European...

In this paper we have assessed an influence of the NYSE Stock Exchange indexes (DJIA and NASDAQ) and European Stock indexes (DAX and FTSE) on the Warsaw Stock Exchange index WIG within a framework of a GARCH model. By applying a procedure of checking predictive quality of econometric models as...

In this study, we aim to build better risk models for energy commodities by employing statistical procedures to identify outliers in the prices for all crude oil and natural gas futures contracts traded on the CME over the period of December 2003 through March 2017. Our results show that it is...

Recent advances in machine learning are finding commercial applications across many industries, not least the finance industry. This paper focuses on applications in one of the core functions of finance, the investment process. This includes return forecasting, risk modelling and portfolio...

We adopt a family of nonparametric Cressie-Read estimators to price options based on relative pricing using the underlying asset returns. We use option models with stochastic volatility and jumps to investigate the ability of each member in this family to price options with different moneynesses...

The LIBOR Market Model (LMM or BGM) has become one of the most popular models for pricing interest rate products. It is commonly believed that Monte-Carlo simulation is the only viable method available for the LIBOR Market Model. In this article, however, we propose a lattice (or tree) approach...

This research paper tries to detect the nonlinearity and chaos structure in the South East Asia Countries Capital Markets. The capital markets of three South East Asia Countries are chosen: Indonesia, Philippine, and Singapore. Daily return data of Capital Markets composite indices are observed:...