As an extension to the Fama and French three factor model (FF), this paper investigates the time-varying risk premiums of sector exchange traded funds (ETF) under a Markov regime-switching framework. In addition to the three style factors in the FF model, three macro factors: changes in market...

Standard delta hedging fails to exactly replicate a European call option in the presence of transaction costs. We study a pricing and hedging model similar to the delta hedging strategy with an endogenous volatility parameter for the calculation of delta over time. The endogenous volatility...

We consider the presence of regimes in currency markets and their implications for interest rate parity. A weak form of interest rate parity is postulated and tested which assumes that the hedged risk premiums are identical within each regime across currencies. Both the in-sample (January 2002 -...

This paper presents a dynamic model of optimal currency returns with a hidden Markov regime switching process. We postulate a weak form of interest rate parity that the hedged risk premiums on currency investments are identical within each regime across all currencies. Both the in-sample and the...

This paper develops a dynamic portfolio selection model incorporating economic uncertainty for business cycles. It is assumed that the financial market at each point in time is defined by a hidden Markov model, which is characterized by the overall equity market returns and volatility. The risk...

The electrification of international shipping has gained attention from the global maritime industry in an effort to reduce pollution and greenhouse gas emissions. Despite rapidly falling battery prices and improvements in battery technologies, electric vehicles (both marine- and land-based...

The electrification of international shipping has gained attention from the global maritime industry in an effort to reduce pollution and greenhouse gas emissions. Despite rapidly falling battery prices and improvements in battery technologies, electric vehicles (both marine- and land-based...

We use deep distributional reinforcement learning (RL) to develop hedging strategies for a trader responsible for derivatives dependent on a particular underlying asset. The transaction costs associated with trading the underlying asset are usually quite small. Traders therefore tend to carry...

We consider a trader who is responsible for managing a portfolio of derivatives that evolves stochastically and depends on a single underlying asset. We use reinforcement learning to develop a strategy for bringing options into the portfolio to manage gamma and vega risk. The options are subject...