In this paper, we identify and document the empirical characteristics of the key drivers of convertible arbitrage as a strategy and how they impact the performance of convertible arbitrage hedge funds. We show that the returns of a buy-and-hedge strategy involving taking a long position in...

Forecasting based pricing of Weather Derivatives (WDs) is a new approach in valuation of contingent claims on nontradable underlyings. Standard techniques are based on historical weather data. Forward-looking information such as meteorological forecasts or the implied market price of risk (MPR)...

In this paper, we identify and document the empirical characteristics of the key drivers of convertible arbitrage as a strategy and how they impact the performance of convertible arbitrage hedge funds. We show that the returns of a buy-and-hedge strategy involving taking a long position in...

The risk of infrastructure investments is driven by unique factors that cannot be well described by standard asset class factor models. We thus create a nine-factor model based on infrastructure-specific risk exposure, i.e., market risk, size, value, momentum, cashflow volatility, leverage,...

In this paper, we identify and document the empirical characteristics of the key drivers of convertible arbitrage as a strategy and how they impact the performance of convertible arbitrage hedge funds. We show that the returns of a buy-and-hedge strategy involving taking a long position in...

This paper investigates the put-call parity (PCP) relation using options on futures on the Standard and Poor's 500 (S&P 500) Index using daily closing options and futures prices between 2nd January and 31st December, 2001. Results obtained demonstrate that the inclusion of transaction costs in...

In this paper, we present a brief description of multivariate GARCH models. Usually, their parameter estimates are obtained using maximum likelihood methods. Considering new methodological processes to model the volatilities of time series, we need to use another inference approach to get...

In this paper, we present a brief description of multivariate GARCH models. Usually, their parameter estimates are obtained using maximum likelihood methods. Considering new methodological processes to model the volatilities of time series, we need to use another inference approach to get...

We utilize the mixed exponential power asymmetric GARCH model where each component exhibits asymmetric conditional heteroskedasticity to model Shanghai Stock Exchange Composite Index daily returns. Thanks to extra component-specific shape parameters, it can better capture the tail behavior and...

We propose a modelling treatment for the option-implied risk neutral distribution (RND) which disaggregates its long-term and short-term dynamics. Long memory parameters calibrated on the RND moments serve as tractable mathematical constructs to filter out effects of smooth structural change...