The food commodity price increases beginning in 2001 and culminating in the food crisis of 2007/08 reflected a combination of several factors, including economic growth, biofuel expansion, exchange rate fluctuations, and energy price inflation. To quantify these influences, the authors developed...

Improvement of energy efficiency is one of the main options to reduce energy demand and to reduce greenhouse gas emissions in Ukraine. However, large-scale deployment of energy efficient technologies has been constrained by several financial, technical, information, behavioral, and institutional...

The transport sector offers limited options to reduce greenhouse gas emissions as compared with other sectors, such as power generation and industrial sectors. To understand the potential reduction of energy consumption and associated emissions through fuel substitution or transportation service...

We study Bitcoin (BTC) trading at the CME and four settlement spot exchanges that transact $146 million per day in the BTC/USD pair. Spot market median trade sizes are under $1,300 but exceed $18,000 on the CME. Bid-ask spreads average 0.0298%.Trade sizes of over $1 million move markets by less...

We rely on a unique set of high-frequency factors to robustly estimate an intraday Stochastic Discount Factor (SDF). Exploiting the precisely timed jumps in the estimated SDF together with real-time newswire data, we identify and precise the news that is priced. We find that news related to...

I construct a novel dataset of 224 high-frequency factor portfolios in order to study the cross-section of expected returns in a continuous-time setting. I estimate the continuous and semijump risk premia for each of these factors. I find that jump and semijump risk are often priced and command...

We document strong intraday market return predictability based on lagged high-frequencycross-sectional returns of the factor zoo. Our results rely crucially on LASSO to regularize our predictive regressions along with techniques from financial econometrics to differentiate between continuous and...

We provide strong empirical evidence for time-series predictability of the intraday return on the aggregate market portfolio based on lagged high-frequency cross-sectional returns from the factor zoo. Our results rely crucially on the use of modern Machine Learning techniques to regularize the...

In this appendix, I include additional information about my dataset, empirical results, and theoretical results. First, I begin by giving more detail on how I construct my high-frequency portfolios. I also motivate my portfolio construction methodology and compare my high-frequency portfolios...