Deviation of an asset price from its fundamental value, commonly referred to as a price bubble, is a well-known phenomenon in financial markets. Mathematically, a bubble arises when the deflated price process transitions from a martingale to a strict local martingale. This paper explores price...

Machine learning applications in finance commonly employ feature decorrelation techniques developed for generic statistical problems. We investigate whether this practice appropriately addresses the unique characteristics of financial data, where correlations often encode fundamental economic...

This paper aims to develop optional semimartingale methods in risk theory to allow for a larger class of risk models. Optional semimartingales are left-continuous with right-limit stochastic processes defined on a probability space where the usual conditions - completeness and right-continuity...

Certain fixed-income securities, such as callable bonds and mortgage-backed securities subject to prepayment, typically exhibit negative convexity at low yields and cannot be adequately immunized through duration and convexity-matching alone. To address this residual risk, we examine the...

This paper proposes an alternative solution to the problem related to the risk that banks incur in the protection of deposits. This solution lies in the use by banks of contingent convertible leasing contracts to face financial distress situations by solidifying their own funds and thus...

We study the shape of the Bachelier-implied volatility of a spread option on two assets following correlated local volatility models. This includes the limiting case of spread options on two correlated Black-Scholes (BS) assets. We give an analytical result for the at-the-money (ATM) skew of the...

The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk, return) = (−infinity, +infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected returns and very negative downside risk...

This study aims to develop an accurate option pricing model for car leases by introducing a put option valuation framework based on the Weibull distribution. Traditional models typically assume asset values follow a lognormal distribution, failing to capture the left-skewed nature and bounded...

This study examines whether changes in the implied volatility of stock options have cross-sectional predictability for future changes in credit default swap (CDS) spreads in the Korean market. The major findings are as follows. First, in the CDS portfolio analysis, when buying a portfolio with...

This study explores an innovative approach to incorporating option strategies into equity portfolios. It presents an alternative direction that institutional investors could take to overcome their current challenges, in a context where traditionally diversified portfolios of only equity and...

We utilize Bayesian model averaging to estimate a stochastic discount factor (SDF) for single-stock options. A Bayesian model averaging SDF outperforms reduced-form benchmark models in-sample and out-of-sample in pricing option return anomalies and portfolios. We document that the SDF is dense...

The popular Wishart (WI) processes, first introduced by Bru in 1991, exhibit convenient analytical properties for modeling asset prices, particularly a closed-form characteristic function, and the ability to jointly model stochastic volatility and correlation. These features tend to increase...

This paper demonstrates that perfectly calibrating a multi-asset model to observed market prices of all basket call options is insufficient to uniquely determine the price of a best-of call option. Previous research on multi-asset option pricing has primarily focused on complete market settings...

In this paper, we study perpetual American put options with a generalized standard put payoff and establish sufficient conditions for the existence and uniqueness of the solution to the associated pricing problem. As a key tool, we express the Black-Scholes operator in terms of elasticity. This...

This paper enhances the calibration procedure for pricing spread options with liquidity risk. The novelty is the use of Chebyshev interpolation to fit the prices.Numerical experiments reveal that the calibrated parameters are close to the ones obtained by a previous work. However, the fit...

We analyze a market-wide panel dataset on retail options trading from India, a market with an 80% share in option contracts traded worldwide. Retail traders both concentrated in and dominate index options trading. They exhibit short-term speculative behavior with significant day trading, short-...

This study examines the performance dynamics of U.S. options exchange-traded funds (ETFs), whose investment strategy involves options contracts. Analyzing monthly returns data from February 2014 to April 2023, we evaluate the risk-adjusted performance, volatility, and market sensitivity of U.S....

Objective:This study investigates gender differences in risk-taking behaviour, specifically in entrepreneurial decision-making, in line with the Lehman Sisters Hypothesis. The research, motivated by the 2008 Polish currency options crisis, seeks to understand the factors driving risky decisions,...

This work explores the potential of different machine learning (ML) algorithms in the valuation of American options (Aos), contrasting them with the Longstaff-Schwartz (L-S) model. To carry out this research, the algorithms K-Nearest Neighbors (KNN), Random Forest (RF), Multi-Layer Perceptron...

This study unravels the transmission of volatility spillovers between NIFTY 50 spot prices and the options market, addressing a significant gap in existing studies. It captures how market connectedness evolved during the pre-COVID, COVID and post-COVID periods, offering fresh insights into price...

In this paper, I study trading activities prior to M&A announcements pertaining to the rivals of the merging firms. I find that not only acquirers and targets experience increases in abnormal trading activities in stock and option markets, but also their rivals. The rise in option trading is...

Modeling implied volatility (IV) is important for option pricing, hedging, and risk management. Previous studies of deterministic implied volatility functions (DIVFs) propose two parameters, moneyness and time to maturity, to estimate implied volatility. Recent DIVF models have included factors...

We derive methods for risk-neutral pricing of multi-asset options, when log-returns jointly follow a multivariate tempered stable distribution. These lead to processes that are more realistic than the better known Brownian motion and stable processes. Further, we introduce the diagonal tempered...

This paper addresses the challenges associated with pricing exotic options, specifically path-dependent ones, with a focus on the limitations of standard Monte Carlo simulations and the advantages provided by Conditional Monte Carlo methods, introduced by Babsiri and Noel in 1998. Path dependent...