Agenda

8.30 Coffee
9.00 (Room 4A) Christian Dunis Lecture: Andrew Harvey, University of Cambridge - Speculative markets: Bubbles or balloons?
Parallel Session 3: METHODS FOR FINANCIAL RISK (Room 4A)
10.30 Measures of fragility for tail risk models
11.00 Conditional method confidence set
11.30 Asymmetric models for realised covariances
12.00 Multivariate score models for realised volatility series
12.30 Robust statistical jump models
Parallel Session 4: ASSET PRICING (Room 2A)
10.30 Predicting winner and loser stocks: A classification approach
11.00 Predictive causal networks in corporate credit markets
11.30 Producing AI innovation and its value implications
12.00 Forecasting private company valuations using Machine Learning: Integrating structured data and deal narratives
12.30 Geopolitical rivalries and equity market uncertainty: Analysing the semiconductor sector
13.00 Lunch
Parallel Session 5: AI (Room 4A)
14.15 Beyond traditional models: Assessing the role of LSTM networks in volatility prediction
14.45 A digital twin for rational stock market traders: Application to the Dow Jones average index
15.15 Replicability of deep learning forecasts: From theory to practice
15.45 Machine learning mutual fund flows
Parallel Session 6: ASSET PRICING (Room 2A)
14.15 A moment-based approach to anomaly forecasts and statistical limits to arbitrage
14.45 Tail portfolio
15.15 Verification of the mechanism of financial bubble formation
Parallel Session 7: METHODS FOR FINANCIAL RISK (Room 10A)
14.15 Stock price movements as geodesics on a curved manifold
14.45 Long run return distributions: Empirical inference and uncertainty
15.15 Beyond random walks: Revealing the fractal memory of financial markets
15.45 Analysis of WD Gann's theory and forecasts: Implications for long-term investments
16.15 Coffee Break
Parallel Session 8: AI (Room 4A)
16.30 Agentic AI for advanced economic and financial analysis
17.00 SHAP-based recursive feature elimination and hyperparameter optimisation for enhanced financial stock forecasting (ONLINE)
17.30 LLMs for time series: An application for single stocks and statistical arbitrage
18.00 A deep learning framework for medium-term covariance forecasting in multi-asset portfolios
18.30 Predicting oil prices turning points using LPPL and MPGA
Parallel Session 9: GREEN FINANCE and ESG (Room 2A)
16.30 Unveiling the impact of PPPs, green bonds, social impact bonds, and microfinance
17.00 The greenium in the European banking sector: An application to the fixed income market
17.30 ESG performance and behaviour of financial institutions: Evidence from the London Stock Exchange
18.00 CSR, advertising expenditure, and firm performance
18.30 Enhancing the financial usability of implied temperature rise metrics: A statistical approach for standardising starting points