Temperature Anomalies and Climate Physical Risk in Portfolio Construction

Articolo

Apr 27 2026
Temperature Anomalies and Climate Physical Risk in Portfolio Construction

Michele Azzone, Carlo Bechi, Gabriele Sbaiz

1. Introduction

The increasing frequency, severity, and unpredictability of natural disasters and chronic climate threats pose unprecedented challenges to global financial markets. Traditional asset pricing models and portfolio management frameworks often struggle to incorporate the stochastic nature of physical climate risks.

Currently, investors attempting to hedge against physical climate risk often rely on static, country-level vulnerability indices or long-term macroeconomic projections. These approaches fail to capture the high-frequency, dynamic nature of extreme weather events and their heterogeneous impacts across different industries and individual firms. The motivation of this research is to bridge this gap by connecting firm-specific asset intensity with the time-varying probability of extreme temperature anomalies, ultimately allowing for dynamic risk mitigation within a quantitative portfolio construction paradigm.

The core hypothesis is that while market participants are increasingly aware of transition risks (e.g., regulatory changes, carbon taxes), the immediate and localized impacts of physical climate shocks—such as floods, extreme heatwaves, and storms—are not yet fully priced into global equity variations. Addressing this requires granular data and a departure from standard variance models.

3. Methodology

3.1. Panel Regression Analysis and Sectoral Impact

The foundation of the study is a robust panel regression analysis conducted on historical sectoral returns. We focus on extreme temperature events, formalizing them as localized temperature anomalies. By regressing sectoral equity returns against these anomalies, we provide strong statistical evidence that extreme temperature shocks exert a quantifiable negative effect on the majority of economic sectors. Notably, the empirical findings show statistically significant adverse impacts not only in traditionally exposed sectors like agriculture or industrials, but also in sectors such as Retailers and Software & IT Services, highlighting the widespread vulnerability of supply chains and technological infrastructure.

3.2. Novel Climate Risk Metrics: CRE and CEV

To operationalize these findings for portfolio optimization, we introduce two novel, dynamic metrics designed to measure the environmental vulnerability of an investment portfolio:

  • Climate Risk Exposure (CRE): A measure of the expected impact of temperature anomalies on a portfolio, taking into account the firm-specific asset intensity and geographic distribution of operations. It represents the aggregate vulnerability of the portfolio to realized and expected physical climate shocks.
  • Climate Exposure Volatility (CEV): A metric capturing the variance or uncertainty associated with the portfolio’s climate risk exposure. This highlights that climate risk is not static; the probability of extreme events varies over time, and CEV measures the stability of the portfolio’s climate resilience.

By utilizing realized temperature anomalies and multiplying them by climate-normalized asset weights, the metrics are aggregated geographically to produce a robust monthly indicator of risk. These indices provide a much more responsive tool compared to static ESG scores.

3.3. Multi-Objective Portfolio Optimization

The core contribution of the paper is the integration of CRE and CEV into a multi-objective portfolio optimization framework. This novel approach extends the classical Markowitz Mean-Variance paradigm by adding climate risk dimensions. Investors are no longer restricted to optimizing the trade-off between expected financial return and financial variance; they can now actively minimize Climate Exposure Volatility (CEV) or constrain Climate Risk Exposure (CRE). This allows for the construction of portfolios that are explicitly resilient to physical climate shocks while maintaining desired levels of financial diversification.

4. Backtesting

To show the practical benefits of the proposed methodology, we conduct an extensive backtesting analysis over the period from January 2020 to April 2025.

The study compares three distinct portfolio strategies to evaluate the trade-offs between traditional optimization and climate-aware frameworks. By plotting the evolution of CEV across these three strategies, we discuss how active management of climate risk exposure leads to superior resilience during periods of heightened climatic stress.

The out-of-sample performance metrics reveal that incorporating CRE and CEV into the investment process does not come at an unacceptable cost to financial returns. Instead, the climate-aware strategies perform competitively relative to traditional benchmarks, while offering significantly lower drawdown profiles during periods characterized by high global temperature anomalies and associated natural disasters. The inclusion of firm-specific physical footprints allows for highly targeted reallocations that preserve the core equity premium.

5. Conclusion

We provide a highly practical, statistically grounded methodology for addressing one of the most pressing risks in modern quantitative finance. By introducing dynamic, firm-level and temperature-driven metrics (CRE and CEV) and embedding them into a multi-objective optimization framework, we offer a blueprint for constructing resilient global equity portfolios. This approach empowers asset managers to systematically mitigate the adverse effects of physical climate risk, ensuring long-term portfolio stability without sacrificing the benefits of broad market diversification.

Link to the preprint: https://arxiv.org/abs/2604.11143

Pricing and Hedging Financial Derivatives in Merger&Acquisition Deals with Price Impact

Articolo

Apr 25 2026
Pricing and Hedging Financial Derivatives in Merger&Acquisition Deals with Price Impact

Authors: Emilio Barucci, Yuheng Lan, Daniele Marazzina.

This paper investigates the optimal execution and pricing of financial contracts commonly used in merger and acquisition (M&A) transactions, focusing on agreements between a broker and a counterparty. In particular, we analyze three classes of contracts: linear instruments such as Total Return Swaps (TRS), nonlinear structures such as collar contracts, and path-dependent contracts based on Time-Weighted Average Price (TWAP).

In M&A operations, acquiring firms often rely on derivatives rather than direct stock purchases to build positions in a target company while mitigating market impact and complying with regulatory constraints. Through such contracts, the broker intermediates the acquisition process by gradually executing trades in the underlying asset and managing inventory. These arrangements provide flexibility but also introduce significant challenges in pricing, hedging, and execution due to market illiquidity and price impact.

We develop a framework in which the broker determines both the optimal trading strategy and the contract fee using an indifference utility approach. The model incorporates both temporary and permanent linear market impact, capturing the feedback effect of trading activity on asset prices. Within this setting, the broker simultaneously hedges the derivative exposure and manages inventory over the contract’s lifetime, under either cash settlement or physical delivery.

Our analysis extends existing literature on illiquid derivative pricing by considering a broader class of payoff structures, including linear, nonlinear, and path-dependent contracts. We show that the nature of settlement plays a crucial role. Cash-settled contracts are systematically more expensive than physically delivered ones. The intuition is that, under cash settlement, the broker must unwind the hedging position at maturity, incurring additional market impact costs, whereas physical delivery aligns the hedging activity with the final obligation.

A central contribution of the paper is the analysis of market manipulation and statistical arbitrage opportunities arising from these contracts. We demonstrate that linear cash-settled contracts are particularly vulnerable to manipulation. The broker’s trading incentives are time-inconsistent: early in the contract, trading is driven by hedging needs, while near maturity, inventory liquidation dominates. This shift can induce trading patterns that exploit price impact, leading to profitable round-trip strategies (statistical arbitrage). In contrast, physically delivered contracts significantly reduce these opportunities, as the broker’s trading remains aligned with the need to accumulate shares for delivery.

We further show that nonlinear contracts, such as collars, introduce additional complexity, as optimal trading strategies become state-dependent and react dynamically to price movements. Similarly, TWAP-based contracts, due to their path dependence, can also generate manipulation incentives and statistical arbitrage opportunities, as the broker may influence the average price through strategic execution.

Overall, the paper delivers two key findings. First, cash settlement increases the cost of contracts relative to physical delivery due to the necessity of position unwinding under market impact. Second, cash-settled and path-dependent contracts are more prone to manipulation and statistical arbitrage, while physical delivery provides a more robust structure by aligning incentives between hedging and execution.

These results contribute to the literature on derivative pricing under illiquidity and to the growing body of work on market manipulation in price impact models, offering practical insights for the design and regulation of M&A-related financial contracts

http://arxiv.org/abs/2604.21581

Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

Articolo

Apr 17 2026
Navigating Supply Shocks: Sector Resilience and Production Prices Through Stochastic Input–Output Modeling

Authors: Giovanni Amici, Gianluca Fusai, Anna Maria Gambaro, Daniele Marazzina.

This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature-related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein–Uhlenbeck process, into the production network of interdependent industries, the model captures how physical shocks (e.g., extreme climate events or geopolitical disruptions) propagate through input–output (IO) linkages and affect sectoral price dynamics. The framework extends traditional IO models with advanced stochastic and dynamic features, enabling a quantification of both direct and indirect transmission channels of supply-cost shocks to production prices. Contributing to the literature on stochastic IO and Markovian networks, the model introduces the concept of divisible shocks, allowing for finer-grained simulation of adaptation responses and resilience across sectors. Empirical calibration leverages real-world economic data, including IO tables and historical industrial price indices. Sensitivity analyses are conducted using distributional risk measures, offering new tools for climate stress testing and medium to long-term risk assessment. Our findings support the optimal design of supply risk management strategies, including policy interventions and decentralized adaptation incentives for systemic stability under environmental stress.

https://onlinelibrary.wiley.com/doi/10.1111/mafi.70029

Forecasting Bitcoin price movements using multivariate Hawkes processes and limit order book data

Articolo

Apr 17 2026
Forecasting Bitcoin price movements using multivariate Hawkes processes and limit order book data

Authors: Davide Raffaelli, Raffaele Giuseppe Cestari, Daniele Marazzina, Simone Formentin
 
Forecasting short-term returns of Bitcoin is a key challenge in high-frequency trading, due to the cryptocurrency’s extreme volatility, market microstructure complexity, and non-stationary behavior. Limit Order Book (LOB) data offer a rich source of high-resolution information that can improve predictive models beyond what is possible using price series alone. In this study, we investigate the BTC/USD trading pair and develop two return sign forecasting approaches based on multivariate Hawkes processes (MHP), leveraging LOB event streams collected in real time from a centralized exchange. Our first method integrates an MHP with a Continuous-time Output Error (COE) model to jointly model event timing and return dynamics in irregularly sampled data. The second approach directly forecasts return sign and timing via an extended MHP. Empirical results show that the hybrid MHP–COE pipeline consistently outperforms the pure Hawkes-based model in both prediction accuracy and simulated trading profitability. We also evaluate the methods’ computational efficiency to assess their viability in real-world high-frequency environments.

https://link.springer.com/article/10.1007/s10203-026-00570-z

Marco Gross and Richard Senner “From Par to Pressure: Liquidity, Redemptions, and Fire Sales with a Systemic Stablecoin”
International Monetary Fund, Working paper n° 26/5

Articolo

Mar 26 2026
Marco Gross and Richard Senner “From Par to Pressure: Liquidity, Redemptions, and Fire Sales with a Systemic Stablecoin”International Monetary Fund, Working paper n° 26/5

Abstract: Fiat-backed stablecoins are expanding, and their issuers may attain systemic relevance as reserve portfolios grow and as they may become increasingly intertwined with financial markets. This paper analyzes the resulting risks and the design choices that can mitigate them. A detailed financial-economics discussion forms the core of the paper. It is paired with a model that captures the feedback loop between a systemic stablecoin and financial markets: redemptions deplete reserves, may prompt asset sales, depress bond market prices, thereby erode a stablecoin issuer’s solvency, and in turn trigger further redemptions. The model links design dials—capital and liquidity buffers, reserve composition, redemption gates, and others—to outcomes such as run frequency, fire sale intensity, and bond market volatility. The economics discussion and model analysis conclude that robust prudential design can substantially stabilize stablecoins and their surrounding market environment.

https://www.imf.org/en/publications/wp/issues/2026/01/16/from-par-to-pressure-liquidity-redemptions-and-fire-sales-with-a-systemic-stablecoin-573271

Eugenio M. Cerutti, Martina Hengge and Takaaki Sagawa, “Stablecoin Shocks”
International Monetary Fund, Working paper n° 26/44

Articolo

Mar 26 2026
Eugenio M. Cerutti, Martina Hengge and Takaaki Sagawa, “Stablecoin Shocks”International Monetary Fund, Working paper n° 26/44

Abstract: We develop novel measures of stablecoin shocks and use them to identify the causal effects of stablecoin adoption on U.S. financial markets. Combining a daily narrative dataset of stablecoin-specific news with changes in the combined market capitalization of USDC and USDT, we measure high-frequency movements in stablecoin market capitalization and implement heteroskedasticity-based identification within an event-study and SVAR-IV framework. Stablecoin demand shocks have triggered persistent declines in short term Treasury yields, a depreciation of the U.S. dollar, and gradual spillovers into crypto and equity markets. We also document heterogeneous effects across firms: payment providers benefit from greater stablecoin adoption, whereas banks—including community and small banks—show no evidence of priced disintermediation risk. Our findings highlight stablecoin demand as a novel channel of asset-market transmission.

https://www.imf.org/en/publications/wp/issues/2026/03/06/stablecoin-shocks-574528

Youming Liu, Francisco Rivadeneyra and Edona Reshidi, “Public vs. Private Payment Platforms: Market Impacts and Optimal Policy”
Bank of Canada, Working paper n° 2026-10

Articolo

Mar 26 2026
Youming Liu, Francisco Rivadeneyra and Edona Reshidi, “Public vs. Private Payment Platforms: Market Impacts and Optimal Policy” Bank of Canada, Working paper n° 2026-10

Abstract: We study competition between a welfare-maximizing public platform and a profit-maximizing private platform in a two-sided payment market. We characterize the public platform’s optimal pricing and show that it balances the benefits of increased competition against the welfare costs of network fragmentation. While introducing a public platform generally raises aggregate welfare and financial inclusion, the competing private platform may respond by raising its fees, disadvantaging merchants that continue to accept payments from the private platform. Finally, we show that cost-recovery and zero-fee mandates constrain public pricing, making welfare improvements uncertain and conditional on network effects, user switching behavior, and the degree of platform differentiation.

https://www.bankofcanada.ca/2026/03/staff-working-paper-2026-10

Hyun Song Shin, “Tokenomics and blockchain fragmentation”
Bank for International Settlements, Working Paper n° 1335

Articolo

Mar 26 2026
Hyun Song Shin, “Tokenomics and blockchain fragmentation” Bank for International Settlements, Working Paper n° 1335

Abstract: Money is a coordination device underpinned by strong network effects: the more others accept a form of money, the more I wish to adopt it too. The decentralisation agenda of public permissionless blockchains undercuts these network effects and leads to fragmentation of the monetary landscape. Validators who maintain the blockchain need to be rewarded to play their role with the necessary reward increasing in the degree of dependence on other validators’ actions to sustain consensus. Since these rewards must ultimately be borne by users through congestion rents, capacity constraints are a feature, not a bug, especially for blockchains with more stringent standards for consensus. New blockchains with less stringent thresholds for consensus enter the market to serve users priced out of incumbent chains. The resulting fragmentation undercuts the very network effects that give money its social value. Stablecoins inherit this fragmentation from the blockchains on which they reside. The analysis has broader implications for the future of the monetary system.

https://www.bis.org/publ/work1335.pdf

Martin Summer, “Privacy by design for public digital money”
Oesterreichische Nationalbank (Austrian National Bank), Working paper n° 278

Articolo

Mar 26 2026
Martin Summer, “Privacy by design for public digital money”Oesterreichische Nationalbank (Austrian National Bank), Working paper n° 278

Abstract: As central banks explore issuing digital currencies for public use, a critical design challenge is how to protect the privacy of the granular data trails digital payments leave behind. While privacy is widely recognised as a goal, policy debates often frame it as a trade-off with crime prevention—limiting ambition and reinforcing legacy design choices that assume privacy and enforcement are fundamentally incompatible. This risks replicating the data practices of commercial platforms in public infrastructure. This paper charts an alternative approach. Recent advances in privacy-enhancing technologies (PETs) now enable both strong privacy protections and verifiable compliance through programmable, rule-based auditability. By embedding such capabilities directly into system architecture, central banks can make privacy a built-in feature of digital money—strengthening institutional trust. Building on recent advances in cryptography and strategic analysis, we offer a conceptual framework that treats privacy and auditability as distinct design dimensions, and distil three design principles for privacy-protective CBDCs that remain compatible with enforcement needs. We also introduce a “PET dashboard” that maps specific technologies to CBDC system layers, highlighting where collaboration across central banks, academia, and industry is most needed.

https://www.oenb.at/dam/jcr%3A90b7d3b1-249d-44ea-8710-99be17978c5d/wp-278.pdf

Juan S. Mora-Sanguinetti, Cristina Peñasco and Rok Spruk, “THE IMPACT OF “GREEN REGULATION” ON FIRMS’ INNOVATION”
Banco de España, Working Paper n° 2611

Articolo

Mar 26 2026
Juan S. Mora-Sanguinetti, Cristina Peñasco and Rok Spruk, “THE IMPACT OF “GREEN REGULATION” ON FIRMS’ INNOVATION”Banco de España, Working Paper n° 2611

Abstract: This paper analyses the impact of “green regulations” – i.e. those aimed at mitigating the effects of climate change and environmental externalities – on innovation, using a novel regulatory database covering the period 2008-2022 for Spain. The database identifies regulations at both the national and regional levels through textual analysis. Employing a panel data approach, we assess how different types of environmental regulations – particularly those related to renewable energy – affect firm-level innovation activities. Our findings indicate that national-level green regulations have a positive effect on innovation, whereas regional-level regulations show mixed or negligible impacts. Importantly, the interaction between national and regional regulations, measuring the simultaneous production of legal texts at both levels, can foster innovation but at a reduced pace with respect to the sole production of regulation at the national level. Given the results for regional-level regulation, our findings provide evidence in favour of the hypothesis that regulatory fragmentation due to unequal, overlapping, inconsistent or conflicting procedure across jurisdictions may diminish these benefits.

https://www.bde.es/wbe/en/publicaciones/analisis-economico-investigacion/documentos-trabajo/the-impact-of-green-regulation-on-firms-innovation.html