Trading patterns in the European Carbon Market: the role of trading intensity and OTC transactions

International audienceThis paper examines the effect of trading intensity and OTC transactions on expected market conditions in the early development period of the European Carbon futures market. Past duration and trading intensity are used as information related order flow variables in modelling time between transactions in two new specifications of Autocorrelation Conditional Duration (ACD) models. This allows for specific investigation of non-linear asymmetric effects on expected duration and the impact of OTC transactions. Evidence is presented of two main types of trading episodes of increased and decreased trading intensity. Both have a significant impact on price volatility, which increases further if an OTC transaction intrudes. OTC transactions also play a dual role. They slow down trading activity in the short term (over the next five transactions) but increase it substantially in the long term (over ten transactions). Both the liquidity and information price impact components increase following an OTC trade, but the information impact is greater. Price volatility calms down faster than liquidity effects following an OTC trade, and this is more pronounced in ECX and in Phase II. The combined evidence points towards increased market depth, efficiency and maturity of the trading environment

Carry Trades and Commodity Risk Factors

This paper investigates the importance of commodity prices to the returns of currency carry trade portfolios. We adopt a recently developed empirical factor model to capture commodity commonalities and heterogeneity. Agricultural material and metal price risk factors are found to have explanatory power on the cross-section of currency returns, while commodity common and oil factors do not. Although stock market risk is strongly linked to currencies in developed countries, the agricultural material factor is more important for emerging currencies compared to the stock market factor. This suggests that emerging currencies are somewhat segmented from a common financial market shock

Common Information in Carry Trade Risk Factors

Carry returns have been widely observed in the FX market. This study exploits the common information embedded in several factors previously identified as relevant to carry trade returns. We find that the extracted common factor successfully models the time series and cross-sectional characteristics of carry returns. Empirical evidence is presented that the common factor produces smaller pricing errors than other well known factors, such as innovations of exchange rate volatility and the downside stock market excess return. Our results also suggest that stock market risk is somewhat segmented from FX market risk

Asset Prices and Capital Share Risks: Theory and Evidence

An asset pricing model using long-run capital share growth risk has recently been found to successfully explain U.S. stock returns. Our paper adopts a recursive preference utility framework to derive an heterogeneous asset pricing model with capital share risks.While modeling capital share risks, we account for the elevated consumption volatility of high income stockholders. Capital risks have strong volatility effects in our recursive asset pricing model. Empirical evidence is presented in which capital share growth is also a source of risk for stock return volatility. We uncover contrasting unconditional and conditional asset pricing evidence for capital share risks

The Time-Varying Risk Price of Currency Carry Trades

Recent studies show that carry trade returns are predictable and this predictability reflects changes in expected returns. Changes in expected returns may be related to time variation in betas and risk prices. We investigate this issue in carry trades and find clear evidence of time-varying risk prices for the carry factor (HMLFX). The results further indicate that time-varying risk prices are more important than time-varying betas for the carry trade asset pricing model. This suggests that investors overreact to changes in economic states

Common Information in Carry Trade Risk Factors

Carry returns have been widely observed in the FX market. This study exploits the common information embedded in several factors previously identified as relevant to carry trade returns. We find that the extracted common factor successfully models the time series and cross-sectional characteristics of carry returns. Empirical evidence is presented that the common factor produces smaller pricing errors than other well known factors, such as innovations of exchange rate volatility and the downside stock market excess return. Our results also suggest that stock market risk is somewhat segmented from FX market risk

Carry Trades and Commodity Risk Factors

This paper investigates the importance of commodity prices to the returns of currency carry trade portfolios. We adopt a recently developed empirical factor model to capture commodity commonalities and heterogeneity. Agricultural material and metal price risk factors are found to have explanatory power on the cross-section of currency returns, while commodity common and oil factors do not. Although stock market risk is strongly linked to currencies in developed countries, the agricultural material factor is more important for emerging currencies compared to the stock market factor. This suggests that emerging currencies are somewhat segmented from a common financial market shock

A Stock Market Trading System Based on Foreign and Domestic Information

This paper investigates whether a particular magnitude and direction of inter-regional return signal transmission dominates the performance of domestic trading in American, European and Australasian stock markets. A trading system design, based on fuzzy logic rules, combines direct and indirect channels of foreign information transmission, modelled by stochastic parameter regressions, with domestic momentum information to generate stock market trading signals. Filters that control for magnitude and direction of trading signals are then used to investigate incremental impact on economic performance of the proposed investment system. The results indicate that at reasonable levels of transaction costs very profitable trades that are fewer in number do not increase investment performance as much as trades based on foreign information of a specific low-to-medium daily return magnitude of 0.5% to 0.75%. These information-based strategies are profitable on risk-adjusted bases and relative to a market, but performance declines considerably when traded instruments are used

Inter-regional and region-specific transmission of international stock market returns: The role of foreign information

This paper uses stochastic-parameter regressions to analyze the role of foreign information on the return equivalent of the heat wave and meteor shower hypotheses of Engle et al. [Engle, R.F., Ito, T., Lin, W., 1990 Meteor showers or heat waves? Heteroscedastic intra-daily volatility in the foreign exchange market. Econometrica 59, 525–542]. The impact of foreign information on the level and intensity of signal transmission within and between international stock markets is assessed. It is found that signals are transmitted directly from some markets to others and indirectly through other markets. Transmission across regions is stronger than within regions, but most relationships vary over time. Foreign information plays an important role, and can be used profitably in out-of-sample trading, but some stock markets are immune to the effect of information from others

Why do carbon prices and price volatility change?

International audienceAn asymmetric information microstructural pricing model is proposed in which price responses to information and liquidity vary with every transaction. bid-ask quotes and price components account for learning by incorporating changing expectations of the rate of transacted volume (trading intensity) and the risk level of incoming trades. Analysis of European carbon futures transactions finds expected trading intensity to simultaneously increase the information component and decrease the liquidity component of price changes, but at different rates. This explains some conflicting results in prior literature. Further, the expected persistence in trading intensity explains the majority of the autocorrelations in the level and the conditional variance of price change; helps predict hourly patterns in returns, variance and the bid-ask spread; and differentiates the price impact of buy versus sell and continuing versus reversing trades