Conference Agenda

Conventional assessments of market efficiency in emerging economies often conflate exploitable predictable patterns with structural instability. This study challenges this monolithic view by examining the evolutionary efficiency of five major Latin American currency markets (2000–2025) through the lens of the Adaptive Market Hypothesis (AMH). Using a rolling-window Multifractal Detrended Fluctuation Analysis (MF-DFA) paired with a surrogate-based spectrum decomposition, we isolate the distinct sources of market complexity: long-range temporal correlations (memory) versus distributional extremes (fat tails). Our results uncover a critical “Efficiency Paradox” exemplified by the Mexican Peso (MXN): despite exhibiting the region’s highest efficiency in price discovery, its departure from the random walk is driven decisively by unpriced tail risk (68%) rather than exploitable memory. Conversely, the Peruvian Sol (PEN) displays structural inefficiency driven by persistence, likely an artifact of central bank smoothing interventions. These findings demonstrate that in liquid emerging markets, the disappearance of arbitrage opportunities does not imply stability; rather, it signals a regime shift where risk migrates to the tails, rendering standard linear models (e.g., Gaussian VaR) inadequate for capturing structural fragility.

A defining feature of monetary unions is the persistence of differences in investors’ portfolio choices. Even under common institutions and similar transaction costs, investors display stable preferences across asset categories, often reflected in home bias and other systematic portfolio patterns. This paper examines the macroeconomic consequences of convergence in financial preferences within a monetary union. We analyze the case in which bond preferences in Spain gradually align with those observed in Germany, and vice versa, using these countries as representative examples of the core and the periphery in the EMU. We show that the direction of convergence is decisive. When preferences shift toward those of Spain, union-wide private debt expands, long-run GDP declines, and macro-financial volatility rises, although inflation volatility falls. Welfare increases for the monetary union as a whole in this scenario, with Germany capturing the largest gains and Spain benefiting more modestly. By contrast, convergence toward German bond preferences reduces union-wide private debt and output volatility but generates only moderate welfare gains for Germany and sizeable welfare losses for Spain. These results show that financial convergence does not yield uniform benefits: its effects depend critically on the direction of convergence and reveal a trade-off between welfare and stability.

Social media networks have become integral to modern information exchange. This study develops a conceptual framework to examine how non-financial influencers, and more importantly the characteristics of their audiences, affect firms through investor attention and stock market outcomes. We find that influencers can significantly increase investor attention, especially when audiences are geographically concentrated, affluent, and socioeconomically aligned with investors, or when firm visibility and traditional information channels are weak. These attention shocks generate short-lived market effects, including narrower bid–ask spreads and transitory abnormal returns. The effects are stronger when engagement originates from audience groups that are more likely to invest or are socially aligned with active investors, such as higher-income or more educated audiences. The rapid decay of these responses indicates that attention affects markets primarily through participation and liquidity channels rather than durable information transmission. Overall, results suggest that social media exposure serves as a partial substitute for formal disclosures, underscoring the growing importance of informal attention networks in shaping information flows and market performance in the digital economy.

We develop a term-structure model of analysts' earnings forecasts that embeds a latent state of analyst-firm-level uncertainty to construct a measure of long-run belief dispersion. We show that conventional cross-sectional dispersion in short-horizon earnings forecasts, although typically regarded as scale-invariant, becomes positively associated with stock price levels after controlling for firm fundamentals. In contrast, our model-implied dispersion in valuation beliefs is negatively related to price because it increases with analyst overoptimism. We identify earnings uncertainty as a belief-based channel that amplifies valuation disagreement and interacts with nominal price illusion, leading investors to perceive low-priced stocks as having higher earnings growth potential. We further show that analysts' earnings uncertainty predicts investors' ex-ante uncertainty, as reflected in option-implied volatility prior to earnings announcements. Overall, our results indicate that investors' expectation noise can be explained by information frictions arising from analysts' belief bias, complementing existing firm-level uncertainty measures based on downside risk.