arXiv subjects

Michele Azzone

Publications and source records attributed to Michele Azzone.

12 recordsLinked to original sources

arXiv2026

Temperature Anomalies and Climate Physical Risk in Portfolio Construction

Driven by the increasing frequency and intensity of natural disasters and chronic climate threats, we investigate the impact of physical climate risk on global equity portfolios. By employing a panel regression analysis on sectoral returns, we provide statistical evidence that extreme temperature events exert a negative effect on most sectors. We introduce two novel metrics based on these temperature anomalies, Climate Risk Exposure and Climate Exposure Volatility, in order to measure the environmental vulnerability of a portfolio. Unlike available static country-level indices, these metrics incorporate the time varying probability of extreme events and their relations with firm-specific asset intensity. We integrate these measures into a multi-objective portfolio optimization framework. This approach extends the traditional Mean-Variance paradigm, allowing investors to construct portfolios that are resilient to physical climate shocks without sacrificing diversification. Finally, we conduct a backtesting analysis to show the practical benefits of incorporating these climate risk metrics into the investment process, evaluating how climate-aware strategies perform relative to traditional benchmarks.

q-fin.PM↗

arXiv2025

Central Bank Digital Currency, Flight-to-Quality, and Bank-Runs in an Agent-Based Model

We analyse financial stability and welfare impacts associated with the introduction of a Central Bank Digital Currency (CBDC) in a macroeconomic agent-based model. The model considers firms, banks, and households interacting on labour, goods, credit, and interbank markets. Households move their liquidity from deposits to CBDC based on the perceived riskiness of their banks. We find that the introduction of CBDC exacerbates bank-runs and may lead to financial instability phenomena. The effect can be changed by introducing a limit on CBDC holdings. The adoption of CBDC has little effect on macroeconomic variables but the interest rate on loans to firms goes up and credit goes down in a limited way. CBDC leads to a redistribution of wealth from firms and banks to households with a higher bank default rate. CBDC may have negative welfare effects, but a bound on holding enables a welfare improvement.

econ.GN↗

arXiv2025

Physical Climate Risk in Asset Management

Climate-related phenomena are increasingly affecting regions worldwide, manifesting as floods, water scarcity, and heat waves, significantly impairing companies' assets and productivity. It is essential for asset managers to quantify the exposure of their portfolios to such risk. To this aim, we develop a framework based on the Vasicek model for credit risk that introduces downward jumps due to climate phenomena in a company asset's dynamics. These negative shocks are designed to mirror the negative effect of extreme climate events. The model calibration relies on companies' asset intensity and geographical exposure. We apply the new multivariate firm value model with jumps to assess the impact of climate-related extreme events on expected and unexpected portfolio losses. Our findings indicate that expected losses increase over time, with pronounced differences in exposure observed across sectoral indices. From an environmental policy perspective, these results suggest the need for additional capital buffers to offset losses arising from physical climate risks, particularly in sectors with high asset intensity.

q-fin.RM↗

arXiv2024

Asset management with an ESG mandate

We investigate the portfolio frontier and risk premia in equilibrium when institutional investors aim to minimize the tracking error variance under an ESG score mandate. If a negative ESG premium is priced in the market, this mandate can reduce portfolio inefficiency when the return over-performance target is limited. In equilibrium, with asset managers endowed with an ESG mandate and mean-variance investors, a negative ESG premium arises. A result that is supported by empirical data. The negative ESG premium is due to the ESG constraint imposed on institutional investors and is not associated with a risk factor.

q-fin.PM↗

arXiv2024

Hedging carbon risk with a network approach

Sustainable investing refers to the integration of environmental and social aspects in investors' decisions. We propose a novel methodology based on the Triangulated Maximally Filtered Graph and node2vec algorithms to construct an hedging portfolio for climate risk, represented by various risk factors, among which the CO2 and the ESG ones. The CO2 factor is strongly correlated consistently over time with the Utility sector, which is the most carbon intensive in the S&P 500 index. Conversely, identifying a group of sectors linked to the ESG factor proves challenging. As a consequence, while it is possible to obtain an efficient hedging portfolio strategy with our methodology for the carbon factor, the same cannot be achieved for the ESG one. The ESG scores appears to be an indicator too broadly defined for market applications. These results support the idea that bank capital requirements should take into account carbon risk.

q-fin.PM↗

arXiv2024

The puzzle of Carbon Allowance spread

A growing number of contributions in the literature have identified a puzzle in the European carbon allowance (EUA) market. Specifically, a persistent cost-of-carry spread (C-spread) over the risk-free rate has been observed. We are the first to explain the anomalous C-spread with the credit spread of the corporates involved in the emission trading scheme. We obtain statistical evidence that the C-spread is cointegrated with both this credit spread and the risk-free interest rate. This finding has a relevant policy implication: the most effective solution to solve the market anomaly is including the EUA in the list of European Central Bank eligible collateral for refinancing operations. This change in the ECB monetary policy operations would greatly benefit the carbon market and the EU green transition.

q-fin.ST↗

arXiv2023

Is (independent) subordination relevant in option pricing?

Monroe (1978) demonstrates that any local semimartingale can be represented as a time-changed Brownian Motion (BM). A natural question arises: does this representation theorem hold when the BM and the time-change are independent? We prove that a local semimartingale is not equivalent to a BM with a time-change that is independent from the BM. Our result is obtained utilizing a class of additive processes: the additive normal tempered stable (ATS). This class of processes exhibits an exceptional ability to accurately calibrate the equity volatility surface. We notice that the sub-class of additive processes that can be obtained with an independent additive subordination is incompatible with market data and shows significantly worse calibration performances than the ATS, especially on short time maturities. These results have been observed every business day in a semester on a dataset of S&P 500 and EURO STOXX 50 options.

q-fin.MF↗

arXiv2023

A fast Monte Carlo scheme for additive processes and option pricing

In this paper, we present a very fast Monte Carlo scheme for additive processes: the computational time is of the same order of magnitude of standard algorithms for Brownian motions. We analyze in detail numerical error sources and propose a technique that reduces the two major sources of error. We also compare our results with a benchmark method: the jump simulation with Gaussian approximation. We show an application to additive normal tempered stable processes, a class of additive processes that calibrates ``exactly" the implied volatility surface.Numerical results are relevant. This fast algorithm is also an accurate tool for pricing path-dependent discretely-monitoring options with errors of one bp or below.

q-fin.CP↗

arXiv2022

Synthetic forwards and cost of funding in the equity derivative market

This study introduces a new technique to recover the implicit discount factor in the derivative market using only European put and call prices: this discount is grounded in actual transactions in active markets. Moreover, this study identifies the implied cost of funding, over OIS, of major market players. Does a liquid equity market allow arbitrage? The key idea is that the (unique) forward contract -- built using the put-call parity relation -- contains information about the market discount factor: by no-arbitrage conditions we identify the implicit interest rate such that the forward contract value does not depend on the strike. The procedure is applied to options on S&P 500 and EURO STOXX 50 indices. There is statistical evidence that, in the EURO STOXX 50 market, the implicit interest rate curve coincides with the EUR OIS one, while, in the S&P 500 market, a cost of funding of, on average, 34 basis points is added on top of the USD OIS curve.

q-fin.MF↗

arXiv2022

Additive normal tempered stable processes for equity derivatives and power law scaling

We introduce a simple model for equity index derivatives. The model generalizes well known Lèvy Normal Tempered Stable processes (e.g. NIG and VG) with time dependent parameters. It accurately fits Equity index implied volatility surfaces in the whole time range of quoted instruments, including small time horizon (few days) and long time horizon options (years). We prove that the model is an Additive process that is constructed using an Additive subordinator. This allows us to use classical Lèvy-type pricing techniques. We discuss the calibration issues in detail and we show that, in terms of mean squared error, calibration is on average two orders of magnitude better than both Lèvy processes and Self-similar alternatives. We show that even if the model loses the classical stationarity property of Lèvy processes, it presents interesting scaling properties for the calibrated parameters.

q-fin.MF↗

arXiv2022

Neural Network Middle-Term Probabilistic Forecasting of Daily Power Consumption

Middle-term horizon (months to a year) power consumption prediction is a main challenge in the energy sector, in particular when probabilistic forecasting is considered. We propose a new modelling approach that incorporates trend, seasonality and weather conditions, as explicative variables in a shallow Neural Network with an autoregressive feature. We obtain excellent results for density forecast on the one-year test set applying it to the daily power consumption in New England U.S.A.. The quality of the achieved power consumption probabilistic forecasting has been verified, on the one hand, comparing the results to other standard models for density forecasting and, on the other hand, considering measures that are frequently used in the energy sector as pinball loss and CI backtesting.

stat.ME↗

arXiv2021

Short-time implied volatility of additive normal tempered stable processes

Empirical studies have emphasized that the equity implied volatility is characterized by a negative skew inversely proportional to the square root of the time-to-maturity. We examine the short-time-to-maturity behavior of the implied volatility smile for pure jump exponential additive processes. An excellent calibration of the equity volatility surfaces has been achieved by a class of these additive processes with power-law scaling. The two power-law scaling parameters are $β$, related to the variance of jumps, and $δ$, related to the smile asymmetry. It has been observed, in option market data, that $β=1$ and $δ=-1/2$. In this paper, we prove that the implied volatility of these additive processes is consistent, in the short-time, with the equity market empirical characteristics if and only if $β=1$ and $δ=-1/2$.

q-fin.MF↗