2 citations · 2 across the 17 of their papers we have counts for
18 papers
Robustness or Crowding: Experimental Design for Trading Strategy Capacity
Alejandro Rodriguez Dominguez, Miquel Noguer i Alonso
How much capital a trading strategy can absorb before its edge disappears is a causal question about how much is deployed, but it is answered with observational proxies that rest o…
The Mathematics of Volatility Surfaces
Miquel Noguer i Alonso
This paper develops a unified mathematical theory of implied, local, and learned volatility surfaces. Total variance is an infinite-dimensional state constra…
Path Portfolio Optimization: Defect, Lift, and the Price of Path Complexity
Miquel Noguer i Alonso
This paper builds Path Portfolio Optimization: portfolio theory on a path-first framework in which the signature is the universal coordinate of the price path, and asks whether it…
Financial Epiplexity: A Theory of Learnable Market Structure under Bounded Computation
Miquel Noguer i Alonso
Financial markets are hard to predict, not because price moves are purely random, but because structure is strategic, capacity-constrained, and computationally difficult. Classical…
Tail Risk Management with Puts and Trend Following: A CVaR Framework for Crashes and Drawdowns
Miquel Noguer I Alonso, Ali Al Fallouji
Tail-risk management is not only an instrument-selection problem. It is an allocation problem across loss mechanisms: abrupt crash states, volatility repricing, and persistent draw…
A General Theory of Paths: Signatures, Jump Lifts, and Expected Signatures of Self-Exciting Processes
Miquel Noguer i Alonso
This paper develops a path-first theory using the signature as a universal coordinate for deterministic paths, rough paths, jump streams, and path-valued random variables. Geometri…
Pretrained Time-Series Foundation Models for Financial Return Forecasting
Miquel Noguer I Alonso, Rodolfo Pereira Franklin
Financial return forecasting is a difficult test case for time-series foundation models (TSFMs) due to low signal-to-noise ratios, structural breaks, heavy tails, and weak persiste…
The Mathematics of Modeling the Future
Miquel Noguer i Alonso
Modeling the future requires specifying conditional laws relative to an evolving information flow and describing their movement across time. This paper provides a unified mathemati…
The Mathematics of Heuristic Portfolio Optimization (HPO)
Miquel Noguer i Alonso
Practitioners allocate capital with forecast-light rules such as equal weight, inverse volatility, risk parity, HRP, and return-adjusted HRP (RA-HRP). This paper develops \emph{Heu…
The Mathematics of AI Winters: The mathematical Taxonomy of Paradigm Fragility in AI Winter
Miquel Noguer i Alonso, David Pacheco Aznar
Two major periods of reduced funding and confidence in artificial intelligence research, commonly called the first and second AI winters, are usually explained through engineering…
Markets Are Not Random, They Are Hard to Predict
Miquel Noguer i Alonso
Financial returns are often called ``random,'' but the word conflates ontic chance, epistemic ignorance, strategic feedback, and model instability. This essay argues that financial…
Derivative-Informed Operator Learning for Finance: On-the-Fly Greeks, Surfaces, Hedging, and Control
Miquel Noguer I Alonso
Financial decision systems require fast surrogate models for pricing, calibration, hedging, XVA, stress testing, and portfolio optimization. Standard neural surrogates reproduce pr…
Anticipatory Portfolio Optimization
Miquel Noguer i Alonso
A portfolio is \emph{anticipatory} when its optimizer acts on a richer model than the myopic, price-taking estimator used to calibrate it. Enrichment may be informational, via enla…
Distributional Portfolio Optimization (DPO): A Unified Framework for Distributions over Weights, Returns, and Parameters
Miquel Noguer i Alonso
Classical portfolio optimization treats expected returns, covariances, and allocations as deterministic. Modern practice replaces at least one by a distribution: a posterior over p…
A Unified Theory of Ownership Concentration, Overlap, and Dependence
Miquel Noguer i Alonso, Iro Tasitsiomi
Ownership concentration is not a scalar. For a normalized investor-stock matrix , it has three irreducible layers: concentration across investors, concentration across stocks, a…
Financial Information Theory
Miquel Noguer i Alonso
This paper introduces a comprehensive framework for Financial Information Theory by applying information-theoretic concepts such as entropy, Kullback-Leibler divergence, mutual inf…
Game Theory and Multi-Agent Reinforcement Learning : From Nash Equilibria to Evolutionary Dynamics
Neil De La Fuente, Miquel Noguer i Alonso, Guim Casadellà
This paper explores advanced topics in complex multi-agent systems building upon our previous work. We examine four fundamental challenges in Multi-Agent Reinforcement Learning (MA…
Deep Reinforcement Learning for Asset Allocation in US Equities
Miquel Noguer i Alonso, Sonam Srivastava
Reinforcement learning is a machine learning approach concerned with solving dynamic optimization problems in an almost model-free way by maximizing a reward function in state and…