Giuseppe Orlando- Doctor of Philosophy
- University of Bari Aldo Moro
Giuseppe Orlando
- Doctor of Philosophy
- University of Bari Aldo Moro
About
198
Publications
41,474
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902
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Introduction
Giuseppe Orlando currently works at the Department of Economics and Mathematics (DEM), Università degli Studi di Bari "Aldo Moro". Giuseppe does research in Economics, Finance and Econometrics. His current projects are on Business Cycles Modeling, Banking Clearing Problems and Interest Rates Forecasting.
Current institution
Additional affiliations
August 2008 - March 2014
February 2006 - July 2008
StatPro
Position
- Consultant
January 2000 - January 2006
Education
September 2000 - March 2003
September 1996 - June 1998
October 1989 - December 1995
Publications
Publications (198)
This paper, written with the intention of formulating a macroeconomic model of trade cycles - following Kaldor’s approach - explains the fluctuations of economic systems by using the most modern mathematical instruments. The reason for choosing a chaotic model will become clear as will the implications which follow during the treatment. Finally, ha...
This paper, following Kaldor’s approach, is written with the intention of interpreting fluctuations of economic systems (i.e trade cycles). In particular, a new discretized Kaldor model is proposed, which is also useful to explain what appears to be random and unpredictable, such as economic shocks. Moreover, by using numerical analysis, the chaoti...
Trade cycles are complex phenomena oscillating because of economic downturns and expansions. The features of the underlying dynamics have been studied over real data (FRED, OECD, BEA and other databases) and simulated time series generated from a Kaldor-Kalecki model. Recurrence quantification analysis (RQA) detects state changes without necessitat...
To predict the volatility of crude oil Brent price, we propose a novel econometric model where the explanatory variables are a combination of macroeconomic variables (i.e. price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distrib...
This research introduces a novel approach to estimating the economic impact of natural catastrophes (NatCats) by correlating log-loss severity, modeled using a Vasicek process, with the frequency of occurrences following a geometric Brownian
motion. The novelty lies in combining these two processes to dynamically capture the relationship between th...
In this work, we summarize ongoing research aimed at designing a conservative stochastic model to accurately predict renewable energy generation while addressing fluctuations and imbalances in power supply. ▶ Focus: Minimizing deficits by ensuring positively skewed deviations clustering around zero. ▶ Results: Reduced forecasting errors, cost savin...
The CIR# model is an advanced forecasting tool that enhances the original Cox-Ingersoll-Ross model by addressing volatility, regime shifts, and negative interest rates. It uses ARIMA residuals instead of Brownian motion, improving accuracy and reducing computational costs. While initially designed for forecasting interest rates, the model is also h...
In this study, we introduce a conservative model designed to accurately predict renewable energy generation while addressing fluctuations and imbalances in power supply. We employ a time-inhomogeneous Vasicek model driven by both a skew Brownian motion and a compound Poisson process, providing proof of solution existence, uniqueness, and mean rever...
To predict the volatility of crude oil Brent price, we propose a novel econometric model 1 where the explanatory variables are a combination of macroeconomic variables (i.e. price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distr...
Entropy serves as a measure of chaos in systems by representing the average rate of information loss about a phase point’s position on the attractor. When dealing with a multifractal system, a single exponent cannot fully describe its dynamics, necessitating a continuous spectrum of exponents, known as the singularity spectrum. From an investor’s p...
Objective: The study aims to predict financial losses and volatility resulting
from natural disasters over a period of 1 to 15 years.
Volatility Impact: Volatility can cause significant fluctuations in Profit and
Loss (P&L) for affected companies due to unexpected events.
Novelty: A new model for correlating occurrence frequencies with volatility
a...
This study addresses market concentration among major corporations, highlighting the utility of relative entropy for understanding diversification strategies. It introduces entropic value at risk (EVaR) as a coherent risk measure, which is an upper bound to the conditional value at risk (CVaR), and explores its generalization, relativistic value at...
Entropy serves as a measure of chaos in systems by representing the average rate of information loss about a phase point’s position on the attractor. When dealing with a multifractal system, a single exponent cannot fully describe its dynamics, necessitating a continuous spectrum of exponents, known as the singularity spectrum. From an investor’s p...
This study introduces the CIR3 model, a three-factor stochastic model with correlated trends and volatilities for modeling and forecasting credit default swap (CDS) spreads. We first establish a pathwise unique global strong solution for this model and generalize the Feller condition to ensure positivity. Then, we rewrite our SDEs system in an equi...
The objective of our study is to predict the financial losses that may result from natural disasters, along with their level of volatility, over a period of 1 to 15 years. Volatility can lead to significant fluctuations in Profit and Loss (P&L) for companies that are affected by unexpected events. To achieve this goal, we created a novel two-factor...
In this study, we introduce a conservative model designed to accurately predict renewable energy generation while addressing fluctuations and imbalances in power supply. We employ a time-inhomogeneous Vasicek model driven by both a skew Brownian motion and a compound Poisson process, providing proofs of solution existence , uniqueness, and mean rev...
This work aims to extend previous research on how a trifactorial stochastic model, which we call CIR3\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$CIR^3$$\end{documen...
This study introduces the CIR3 model, a three-factor stochastic model with correlated trends and volatilities for modeling and forecasting credit default swap (CDS) spreads. We first establish a pathwise unique global strong solution for this model and generalize the Feller condition to ensure positivity. Then, we rewrite our SDEs system in an equi...
This work illustrates a three-factor model referred to as the CIR3 model, where both the trend and the volatility are stochastic and correlated. For the said model we prove that a pathwise unique global strong solution exists. We present a generalization of the Feller condition to ensure that each factor remains positive up to a Markov time determi...
This analysis explores the dynamics of ESG (Environmental, Social, & Governance) practices, stakeholder democracy, and social responsibility in the contemporary business landscape. Examining the transformative potential of ESG practices, the paper addresses skepticism, emphasizesautonomy in decision-making, and scrutinizes the influence of the busi...
The research aims to propose a new model that estimates the impact of natural disasters (NatCats) by correlating losses (using a Vasicek model) with occurrences (following a geometric Brownian motion). To assess the economic impact of chronic
exposure to natural disasters, it is essential to evaluate the severity and frequency of catastrophic event...
In this study, we devise a time-inhomogeneous Vasicek model driven by both a skew Brownian motion and a compound Poisson process, providing proofs of solution existence, uniqueness, and mean reversion.
This work provides a comprehensive overview of Exchange-Traded Products (ETPs), focusing on their emergence as a preferred investment option for investors prioritizing asset allocation over stock picking. It discusses market practices, performance standards like GIPS, and the transformative impact of ETPs since their introduction in Canada in 1990....
This paper proposes a model for domestic interest rates during a currency crisis by comparing stochastic and machine learning approaches, using Brazil’s 1999 currency devaluation as a test case. The crisis, triggered by economic imbalances and exacerbated by the Asian and Russian financial crises, led to significant capital outflows and a shift to...
Our study introduces a novel approach using Value-at-Risk (VaR) for validating re-newable energy forecasts, addressing critical gaps in existing methodologies. We analyze absolute forecasting errors using Terna’s 2023 data, focusing on mitigating power generation imbalances and minimizing economic losses. By setting a stringent confidence level of...
This analysis explores the dynamics of ESG practices, stakeholder democracy, and social responsibility in the contemporary business landscape. Examining the transformative potential of ESG practices, the paper addresses skepticism, emphasizes autonomy in decision-making, and scrutinizes the influence of the business community in politics. It also d...
This analysis explores the dynamics of ESG practices, stakeholder democracy, and social responsibility in the contemporary business landscape. Examining the trans-formative potential of ESG practices, the paper addresses skepticism, emphasizes autonomy in decision-making, and scrutinizes the influence of the business community in politics. It also...
This study delves into the impact of natural disasters on affected populations and underscores the imperative of reducing disaster-related fatalities through proactive strategies. On average, approximately 45,000 individuals succumb annually to natural disasters amid a surge in economic losses. The research explores catastrophe models for loss proj...
Entropy serves as a measure of chaos in systems by representing the average rate of information loss about a phase point's position on the attractor. When dealing with a multifractal system, a single exponent cannot fully describe its dynamics, necessitating a continuous spectrum of exponents, known as the singularity spectrum. From an investor's p...
This study delves into the impact of natural disasters on affected populations and underscores the imperative of reducing disaster-related fatalities through proactive strategies. On average, approximately 45,000 individuals succumb annually to natural disasters amid a surge in economic losses. The research explores catastrophe models for loss proj...
Purpose
This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially wh...
In this paper, we suggest a new approach to find any prime numbers up to a given *. n ∈ The proposed procedure does not work like a sieve and is easy to implement as it only uses assignments and subtractions which lead to improvements in memory requirements and upgradeable runtime performance. This is because, also, the algorithm suits well paral...
We demonstrate that the CIR# model effectively handles the
challenges posed by tourism time series when they exhibit characteristics such as positive kurtosis, non-normality, autocorrelation, and heteroskedasticity. This suitability for future purposes makes it valuable for tourism stakeholders who require reliable forecasts, particularly during pe...
Passive asset management has emerged in the last decades because, in most cases, active portfolio managers are not able to beat their benchmark. Skewed distributions are witnessed every day in financial markets and the need to model them is gaining momentum. This article deals with passive management of skewed distributed assets and suggests how to...
We evaluate Brunnermeier’s theory of resilience in the context of complex system dynamics where, however, there can be local and global resilience, vulnerability, loss of resilience, cycles, disruptive contractions, and persistent traps. In the paper, we refer to three time scales. First, for shorter time scales, for the short-run market dynamics,...
![Transient trajectories of risk ρt\documentclass[12pt]{minimal}...](publication/372393395/figure/fig5/AS:11431281181544889@1692065782794/Transient-trajectories-of-risk-rtdocumentclass12ptminimal-usepackageamsmath_Q320.jpg)
The goal is to investigate the dynamics of banks’ share prices and related financials that lead to potential disruptions to credit and the economy. We adopt a classic macroeconomic equilibrium model with households, banks, and non-financial companies and explain both market valuations and endogenous debt constraints in terms of risk. Heterogeneous...
This work illustrates a tri-factor model referred to as the CIR 3 model, where both the trend and the volatility are stochastic and correlated. For the said model we prove that a pathwise unique global strong solution exists. We present a generalization of the Feller condition to ensure that each factor remains positive up to a Markov time determin...
This research aims to propose the so-called CIR#, which takes its cue from the well- known Cox-Ingersoll-Ross (CIR) model originally devised for pricing, as a general econometric model. To this end, we present the results on two very different time series such as Polish interest rates (subject to market sentiments) and seasonal tourism (subject to...
In this paper, we consider the Heston-CIR model with Lévy process for pricing in the foreign exchange (FX) market by providing a new formula that better fits the distribution of prices. To do that, first, we study the existence and uniqueness of the solution to this model. Second, we examine the strong convergence of the Lévy process with stochasti...
This work deals with the Cobb-Douglas production function and related assumptions. The function has been at the center of the so-called "capital controversy" and the object of a good deal of econometric research. We argue that while in the early days when the function was proposed the literature found several confirmations, from the late 1970s to n...
HOW QUANTITATIVE EASING MADE MONETARY POLICY INEFFECTIVE
This work summarizes recent advances in modelling and econometrics for alternative directions in macroeconomics and cycle theories. Starting from the definition of a cycle and continuing with a historical overview, some basic nonlinear models of the business cycle are introduced. Furthermore, some dynamic stochastic models of general equilibrium (D...
In the field of cryptography, many algorithms rely on the computation of modular multi-plicative inverses to ensure the security of their systems. In this study, we build upon our previous research by introducing a novel sequence, (z j) j≥0 , that can calculate the modular inverse of a given pair of integers (a, n), i.e., a −1 ; mod, n. The computa...
The main objective of this work is to test whether some stochastic models typically used in financial markets could be applied to the COVID-19 pandemic. To this end, we have implemented the ARIMAX and Cox-Ingersoll-Ross (CIR) models originally designed for interest rate pricing but transformed by us into a forecasting tool. For the latter, which we...
In this paper, we suggest a new approach to find any prime numbers up to a given *. n ∈ The proposed procedure does not work like a sieve and is easy to implement as it only uses assignments and subtractions which lead to improvements in memory requirements and upgradeable runtime performance. This is because, also, the algorithm suits well paral...
The main objective of this work is to test whether some stochastic models typically used in financial markets could be applied to the COVID-19 pandemic. To this end we have implemented the ARIMAX and Cox-Ingersoll-Ross (CIR) models originally designed for interest rate pricing but transformed by us into a forecasting tool. For the latter, which we...
Kaldor-Kalecki model is one of the first models that use non-linear functions to explain the chaotic behaviour of the economic system. Re-elaborating the model we tried to prove the existence of a Bautin bifurcation for the discrete version of the model with an adaptation of the mathematical calculations to the discrete case
This work aims to conduct an analysis of the techniques for assessing and managing
emerging risks that impact the insurance sector and to investigate issues related to climate change. The investigation took into account the regulatory obligations that arise for the Company to determine the pricing of the products and the underwriting
policies for t...
The main objective of this work is to test whether some stochastic models typically used in financial markets could be applied to the COVID-19 pandemic. To this end we have implemented the ARIMAX and Cox-Ingersoll-Ross (CIR) models originally designed for interest rate pricing but transformed by us into a forecasting tool. For the latter, which we...
We evaluate Brunnermeir’s Theory of Resilience in the context of complex system dynamics where there however can be local and global resilience, vulnerability, loss of resilience, cycles, disruptive contractions, and persistent traps. In the paper, we refer to three-time scales. First, for shorter time scales, for the short-run market dynamics, we...
This work aims to extend previous research on how a trifactorial stochastic model, which we call CIR^3, can be turned into a forecasting tool for energy time series. In particular, in this work, we intend to predict changes in the industrial production of electric and gas utilities.
The model accounts for several stylized facts such as the mean re...
This work delves into aggregate production and the well-known Cobb-Douglas function, along with related assumptions, which were considered contradictory because they allow for reswitching and reverse capital deepening. The matter has been at the center of the so-called ’capital controversy’ and the subject of a significant amount of research. We ar...
This work illustrates a tri-factor model referred to as the CIR3 model, where both thetrend and the volatility are stochastic and correlated. For the said model we provethat a pathwise unique global strong solution exists. We present a generalizationof the Feller condition to ensure that each factor remains positive up to a Markovtime determined by...
This paper delves into the impact of natural disasters on affected populations and underscores the imperative of reducing disaster-related fatalities through proactive strategies. On average, approximately 45,000 individuals succumb annually to natural disasters amid a surge in economic losses. The paper explores catastrophe models for loss project...
Portfolio selection models based on second-order stochastic dominance (SSD) have the advantage of providing portfolios that reflect the behavior of risk-averse investors without the need to specify the utility function. Several scholars apply SSD conditions with respect to a reference distribution, typically that of the market index, to find its do...
We present a work by Guerrero and Orlando (2022) where we:
Show that a time-dependent local stochastic volatility (SLV) model can be
reduced to a system of autonomous PDEs that can be solved using the heat
kernel, by means of the Wei-Norman factorization method and Lie algebraic
techniques.
Compare the results of traditional Monte Carlo simulations...
Many processes in nature are the result of many coupled individual subsystems (like population dynamics or neurosystems). Not always such systems exhibit simple stable behaviors that in the past science has mostly focused on. Often, these systems are characterized by bursts of seemingly stochastic activity, interrupted by quieter periods. The hypot...
In this paper, we present a generalized stochastic three-factor model to forecast changes in the industrial production of energy materials. This approach is new as, by deriving a stochastic process correlated with its mean and volatility, we convert it into an uncorrelated auxiliary process through Lamperti transformations. We show that the propose...
We address the probability of default (PD) of Italian banks. Although the probability of default (PD) modeling has reached a great maturity in both academia and business, for the Italian case we demonstrate that banks' available PD models would be misleading if today applied directly to Italian banks. We argue that what determines the PD of Italian...
In this paper, we consider the Heston-CIR model with L\'{e}vy process for pricing in the foreign exchange (FX) market by providing a new formula that better fits the distribution of prices. To do that, first, we study the existence and uniqueness of the solution to this model. Second, we examine the strong convergence of the L\'{e}vy process with s...
This work aims to forecast (over 1, 5 and 15 years) the extremes, the expected value and the volatility of natural disasters occurrences. To achieve this objective we adopt a generalized two‐factor square‐root model linking together occurrences and volatility through stochastic correlation (Brownian motion). We use a generalized Pareto distribution...
VI edition of the workshop on Finance and Markets: geopolitics and energy security
Sanctions, an old way of making war
Risk Management, Solvency and IFRS for insurance companies
Risk Management for Assets and Private Funds - Challenges and Solutions
The nearest exit may be behind you. Resources and energy security: the way out may be behind us
Among professionals and academics alike, it is well known that active portfolio management is unable to provide additional risk-adjusted returns relative to their benchmarks. For this reason, passive wealth management has emerged in recent decades to offer returns close to benchmarks at a lower cost. In this article, we first refine the existing re...
In this note we highlight some features of the CIR2 model we have developed, which is a generalised two-factor square root model (i.e. a model where, under certain conditions, both losses and volatility are positive and where volatility increases with the level of loss). In the framework we present, calculation of the mean and variance of loss are...
The gist of this work is to propose a minimum tracking error portfolio that could be adopted not only as an automated alternative to ETFs but, it could also be potentially used to anticipate market changes in the target index. This goal has been achieved by adopting skew Brownian motion as a general framework. The proposed solution has been decline...
![fα(x)\documentclass[12pt]{minimal} \usepackage{amsmath}...](publication/358270124/figure/fig1/AS:1118879707332609@1643773118582/faxdocumentclass12ptminimal-usepackageamsmath-usepackagewasysym_Q320.jpg)
![(a) Rulkov variable x^\documentclass[12pt]{minimal}...](publication/358270124/figure/fig4/AS:1118879707344907@1643773118774/a-Rulkov-variable-xdocumentclass12ptminimal-usepackageamsmath_Q320.jpg)
We ask whether empirical finance market data (Financial Stress Index, swap and equity, emerging and developed, corporate and government, short and long maturity), with their recently observed alternations between calm periods and financial turmoil, could be described by a low-dimensional deterministic model, or whether this requests a stochastic ap...
This work deals with corporate dynamics as they emerge from mutual interaction between firms competing on the market. As it is commonly observed, corporate dynamics may oscillate between periods of fierce competition and calmer periods when companies settle in their niche. This is much like mutual synchronization and chaos regularization of bursts...
The objective of this paper is the study of the dynamical properties analysis of an original specification of the classical Cournot heterogeneous model with optimal response; specifically, a new approach that considers ordinal utility instead of cardinal monetary amounts is proposed where the classical decision of quantity is disentangled from the...
The book offers an overview of credit risk modeling and management. A three-step approach is adopted with the contents, after introducing the essential concepts of both mathematics and finance.
Initially the focus is on the modeling of credit risk parameters mainly at the level of individual debtor and transaction, after which the book delves into...
Executive summary In this work, we summarize some results obtained with a generalized two-factor square root model that we call CIR 2. The idea is to predict, over different time horizons, the expected value of financial losses due to natural disasters in conjunction with their volatility. This is because the latter is responsible for large swings...
In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the heat kernel, by means of the Wei-Norman factorization method and Lie algebraic techniques. Then, we compare the results of traditional Monte Carlo simulations with the explicit solutions obt...
Questions
Question (1)
To predict the volatility of crude oil Brent price, we propose a novel econometric model 1 where the explanatory variables are a combination of macroeconomic variables (i.e. price pressure), trade data (freight shipment index), and market sentiment (gold volatility). The model is proposed in two alternative variants: first, we assume Gaussian distributed quantities; alternatively, we consider the potential presence of skewness and adopt a Skew–Brownian process. We show that the suggested approach outperforms the selected baseline model as well as other models proposed in the literature, especially when turbulent periods occur.
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