Financial Econometrics and Market Risks Workshop: check out the programme (8 April in Lille) and register!

Key information

• Name of the event: From Derivatives to Decarbonization: New Chapters in Financial Econometrics and Market Risks
• Date: April 8, 2025
• Location: EDHEC campus Lille, Education building, room E-305 (3rd floor)
• Event Hours: 9:00 am - 5:30 pm

 

Registration & contact

If you are interested, you can register free of charge directly online using the dedicated form. If you have any questions, please do not hesitate to contact Olga Molodilo, who is in charge of this event alongside Arnaud Dufays (EDHEC Associate Professor) and Florian Pelgrin (EDHEC Professor), Scientific organisers of the workshop.

 

Speakers at a Glance

The event will feature eight distinguished speakers:

Olivier Scaillet, Keynote Speaker (Geneva Finance Research Institute of the University of Geneva): Latent Factor Analysis in Short Panels

Abraham Lioui (EDHEC Business School): Which Carbon factor?

Jeroen Rombouts (ESSEC Business School): Modeling Higher Moments and Risk Premiums for S&P 500 Returns

Serge Darolles (Université Paris-Dauphine): Forecasting Intra-daily Volume in Large Panels of Assets

Elise Gourier (ESSEC Business School): The Cost of ESG Rating Uncertainty

Roberto Reno (ESSEC Business School): 0DTE Option Pricing

Mirco Rubin (EDHEC Business School): Do Public Equities Span Private Equity Returns?

Andréas Heinen (CY Cergy Paris Université): Permanent and Transitory Jumps in a Limit Order Book in the Presence of High Frequency Traders

 

The event is designed to be a laboratory of ideas, where in-depth debates and constructive exchanges can inspire new avenues of research or joint projects between researchers. The various highlights (plenary sessions, coffee breaks, lunch buffet and networking evening) are designed to encourage interaction between participants. They allow researchers to discuss the latest innovations and initiate future collaborations.

 

Detailed Schedule

 

(9 am - 9.30 am) Welcome coffee

 

(9.30 am) Opening word by Arnaud Dufays (EDHEC Business School)

 

(9.30 am - 10.45 am) First session

• Roberto Reno (ESSEC Business School)

0DTE Option Pricing

Co-authors: Frederico M. Bandi (John Hopkins University) and Nicola Fusari (Johns Hopkins Carey Business School)

Abstract: The market for ultra short-tenor (zero days-to-expiry or 0DTE) options has grown exponentially over the last few years. In 2023, daily volume in 0DTEs reached over 45% of overall daily option volume. After briefly describing this exploding new market, we present a novel pricing formula designed to capture the shape of the 0DTE implied volatility surface. Pricing hinges on an Edgeworth-like expansion of the conditional characteristic function of the continuous portion of the underlying’s price process. The expansion shifts probability mass from an otherwise locally Gaussian return density by adding time-varying skewness (through leverage) and time-varying kurtosis (through the volatility-of-volatility). The expansion is local in time and, therefore, naturally suited to price ultra short-tenor instruments, like 0DTEs. We document considerable (1) price and (2) hedging improvements as compared to state-of-the-art specifications. We conclude by providing suggestive results on nearly instantaneous predictability by estimating 0DTE-based return/variance risk premia.

 

• Andréas Heinen (CY Cergy Paris Université)

Permanent and Transitory Jumps in a Limit Order Book in the Presence of High Frequency Traders

Co-author: Nathaniel Gbenro

Abstract: We analyze the drivers of permanent and transitory jumps identifed using the Lee and Mykland [2012] approach in a high-frequency data set including the limit order book (LOB), as well as the orders submitted by high frequency traders (HFTs), occasional HFTs and non-HFTs during 64 days, for 10 actively traded stocks on the New York Stock Exchange (NYSE) Euronext Paris Bourse. Our findings are that: (i) overall, jumps are driven by an imbalance in the limit order book, and are preceded by an explosion in traded volume; (ii) transitory jumps are sensitive to liquidity, and happen following periods of unusually high volatility in returns and bid-ask spreads; (iii) in contrast, permanent jumps follow periods of informed trading with a persistent widening of the bid-ask spread, an imbalance in the LOB, and a reduction in liquidity in the direction opposite to the jump; (iv) HFTs seem to be able to read these signs, trade in the direction of the permanent jump and make positive profits, at the expense of other market participants; (v) HFTs do not rely exclusively on trades, but also on limit orders inside the spread, which contribute more to price  discovery than their market orders.

 

(10.45 am - 11.15 am) Coffee break

 

(11.15 am - 12.30 pm) Second session

• Abraham Lioui (EDHEC Business School)

Which Carbon factor?

Co-author: Sanjay Misra (ICT University)

Abstract: The value-weighted carbon factor shows a negative carbon premium, whereas the emissions-weighted carbon factor yields a positive premium. The discrepancies between these two approaches in measuring the carbon premium stem from several key factors: (i) the absence of leverage in the value-weighted case, contrasted with the non-fully-funded nature of the emissions-weighted factor; (ii) differences in the size factors used to neutralize the carbon factor’s exposure to size; and (iii) the lack of full decarbonization in both factor constructions. Harmonizing these methodologies uncovers a significant carbon premium when using the emissions-weighted factor, but not with intensity-weighted or value-weighted factors. This result is further reinforced, both economically and statistically, when the value-weighted and intensity-weighted carbon factors are included in the traditional set of risk factors for calculating the alpha of emissions-weighted carbon factors. The conclusions hold consistently using effective timing of carbon emissions release across variations, including disclosed versus estimated emissions, different industry adjustments, and other robustness checks.

 

• Jeroen Rombouts (ESSEC Business School)

Modeling Higher Moments and Risk Premiums for S&P 500 Returns

Abstract: We study the impact of additional option pricing model factors on the level, term structure and conditional properties of index return moments and their risk premiums. When comparing models, higher moments are more informative than model-implied equity premiums, variances, and variance risk premiums. Based on estimates from a joint option and return likelihood obtained using novel estimation techniques, we relate these model properties to differences in option and return fit. Including three stochastic volatility factors greatly improves option fit. The resulting time series of skewness and kurtosis better match non-parametric benchmarks and the model generates larger skewness and kurtosis risk premiums, but it struggles to match the term structure of higher moments. Return jumps improve the modeling of the term structure of skewness and kurtosis and generate larger and more variable skewness and kurtosis risk premia at short horizons, but do not improve option fit in the presence of three stochastic volatility factors.

 

(12.30 pm - 2 pm) Lunch break

 

(2 pm - 4 pm) Third session

• Serge Darolles (Université Paris-Dauphine)

Forecasting Intra-daily Volume in Large Panels of Assets

Co-authors: Christian Brownlees (Universitat Pompeu Fabra), Ignacio Crespo (CUNEF University), and Gaelle Le Fol (Université Paris Dauphine-PSL)

Abstract: Intra-daily trading volume forecasts are a key input for several trade execution algorithms. In this study we introduce an intra-daily trading volume forecasting methodology for large panels of assets that combines factor models with sparse vector autoregressions. The highlight of the approach is that it allows to capture both the common market-wide factors driving trading activity as well as the sparse network of spillover effects among individual assets. We apply the methodology to predict the intra-daily trading volume of a panel of constituents of the STOXX 600 index for a range of intra-daily frequencies ranging from 5 minutes to 30 minutes. We assess both the statistical accuracy as well as the economic value of the predictions relative to a number of benchmarks. In particular, we assess the economic value of the prediction through a VWAP trade execution exercise. Results show that our proposed methodology delivers both statistical and economic gains, with the largest improvements being associated with the most interconnected stocks

 

• Elise Gourier (ESSEC Business School):

The Cost of ESG Rating Uncertainty

Co-author: Menglong Na (ESSEC Business School)

Abstract: More than thirty trillion dollars are allocated to ESG assets, despite the uncertainty on the true sustainability level of firms. We show within a dynamic portfolio allocation model that the effect of this uncertainty on investors' portfolios and welfare strongly depends on their preferences. Based on institutional investors' holdings, we identify two types of investors with non-pecuniary preferences: green investors whose utility increases with the estimated sustainability of firms, and threshold investors, whose non-pecuniary preferences only depend on whether a firm's estimated sustainability level is below or above a threshold. We show that the uncertainty of the ESG rating is twice as costly for green investors than for threshold investors.

 

 

• Mirco Rubin (EDHEC Business School)

Do Public Equities Span Private Equity Returns?

Co-authors: Eric Ghysels (UNC Kenan-Flagler Business School) and Oleg Gredil (Tulane University, A. B. Freeman School of Business)

Abstract: We characterize the factors common between public and private equity (PE) returns as well as the factors specific to private and public returns, respectively. Using a comprehensive dataset of PE funds and recent advances in PE fund returns nowcasting at high frequency and factor extraction in a grouped data setting, we show that, albeit over 90% of PE returns may be explained by factors common with the matched public equities, the remaining variation exhibits robust factors that are distinct to PE. These PE-specific factors significantly increase a portfolio’s Sharpe ratio through higher expected return and better diversification. The optimal allocation to PE is positive at the 95% confidence level—at 11 to 24% of risky portfolio, depending on the public equity portfolio characteristics—even after accounting for sampling error and imposing the no-shorting constraint within the PE portfolio. Additionally, we show that the two most commonly used datasets on PE fund returns have virtually identical common factors with public equities, but over half of their PE-specific variation is distinct from one another. Our approach ensures that the alpha we find cannot be mimicked by a tailored-enough portfolio of listed equities.

 

(4 pm - 4.30 pm) Coffee break

 

(4.30 pm - 5.30 pm) Keynote lecture

• Olivier Scaillet (Geneva Finance Research Institute of the University of Geneva)

Latent Factor Analysis in Short Panels

Co-authors: Alain-Philippe Fortin and Patrick Gagliardini (University of Lugano)

Abstract: We develop inferential tools for latent factor analysis in short panels. The pseudo maximum likelihood setting under a large cross-sectional dimension n and a fixed time series dimension T relies on a diagonal T x T covariance matrix of the errors without imposing sphericity nor Gaussianity. We outline the asymptotic distributions of the latent factor and error covariance estimates as well as of an asymptotically uniformly most powerful invariant (AUMPI) test for the number of factors based on the likelihood ratio statistic. We derive the AUMPI characterization from inequalities ensuring the monotone likelihood ratio property for positive definite quadratic forms in normal variables. An empirical application to a large panel of monthly U.S. stock returns separates month after month systematic and idiosyncratic risks in short subperiods of bear vs. bull market based on the selected number of factors. We observe an uptrend in the paths of total and idiosyncratic volatilities while the systematic risk explains a large part of the cross-sectional total variance in bear markets but is not driven by a single factor. Rank tests show that observed factors, even beyond the traditional ones, struggle spanning latent factors with a discrepancy between the dimensions of the two factor spaces decreasing over time.

 

(5.30 pm) Closing word by Florian Pelgrin (EDHEC Business School)