Liquidity and resolution of uncertainty in the European carbon futures market

Abstract

International audienceWe investigate whether liquidity introduces or helps resolve uncertainty in Phase I and the first year of Phase II of the European carbon futures market. We propose a distinction between ‘absolute’ or overall liquidity and that which is ‘relative’ to a benchmark. For this purpose, we suggest volume-weighted duration as a natural measure of trading intensity as a proxy for liquidity, and we model it as a rescaled temporal point process. The new model is called Autoregressive Conditional Weighted Duration (ACWD) and is shown to outperform its discrete modelling counterparts. Liquidity is found to play a dual role, with higher relative liquidity introducing uncertainty and higher absolute liquidity accelerating uncertainty resolution, thus, enhancing market efficiency

Visible and Invisible Forces. What Drives the Intensity of Trading in the European Carbon Market?

“…The primary objective is to identify whether observable factors, such as trading volume (Dufour and Engle, 2000) and trading frequency (e.g., Engle and Russell, 1998), or unobservable factors, captured by distributions with progressively nesting properties, contribute more to trading intensity clustering (e.g., Kalaitzoglou and Ibrahim, 2013a). According to the empirical findings it is the observable factors that exhibit a higher explanatory power of the data generation process of trading intensity, suggesting that greater market transparency -the main objective of MiFID II -would ameliorate the predictive power of liquidity models and thus, it would contribute through liquidity to higher market efficiency (Kalaitzoglou and Ibrahim, 2015) and better price discovery (Medina et al 2014). 1 In more detail, the European Carbon market, known as the "European Union Greenhouse Gas Emission Trading System" (EU ETS), is the regulatory response of the European Union to the Kyoto Protocol (1997) and creates a new "commodity" market that has become the most important mechanism in reducing emissions.…”

“…Consequently, the overall quantity of available EUAs is politically influenced and their trading is affected both by the organised venues, as well as by the OTC market. Recently, the introduction of the MiFID II regulation, with its suggested increased transparency, is expected to affect market liquidity (e.g., Rannou and Barneto, 2016) and through it market efficiency (Kalaitzoglou and Ibrahim, 2015) and price discovery (Medina et al 2014). Consequently, an empirical investigation of intraday trading patterns could provide a further insight on the expected impact of increased transparency on liquidity.…”

“…In the context of the EU ETS, several studies (e.g., Bredin et al, 2014;Ibrahim and Kalaitzoglou, 2016) examine the interaction between duration, volume and price and report a positive correlation between the intensity of trading and price change. Kalaitzoglou and Ibrahim (2015) unify volume and duration into a new, rescaled time variable, proxy for trading intensity and report that deviations from the conditionally expected levels are associated with information inflow and the induction of uncertainty in the price discovery process. Following the propositions of Easley and O'Hara (1992), Kalaitzoglou and Ibrahim (2013a) investigate this further and report a link between these deviations and the existence of different types of market participants with respect to their association to information.…”

“…An empirical investigation of the drivers of intraday liquidity, in the form of duration and volume, is conducted, aiming at identifying the main determinants of the trading intensity process, with respect to observable or unobservable market factors. This is done by testing the fitting of different specifications of trading intensity using the Autoregressive-Conditional-Weighted-Duration (ACWD) framework (Kalaitzoglou and Ibrahim, 2015). This framework describes the DGP of trading intensity, modelled as a rescaled point process, combining both duration and volume into one variable.…”

The market quality of commodity futures markets

“…Haugom and Ray (2017) measure the liquidity of oil futures using the daily trading volume on futures markets. Kalaitzoglou and Ibrahim (2015) measure the liquidity of the European carbon futures market with the conditional weighted trading volume. Cai, Hudson, and Keasey (2004), Bortoli, Frino and Jarecic (2010), and Liu, Hua, and An (2016) use price, trading volume, and duration to measure liquidity, with both low‐frequency and high‐frequency data.…”