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In the real world, the variance of portfolio returns provides only a limited quantification of incurred risks, as the distributions of returns have “fat tails” and the dependence between assets are only imperfectly accounted for by the correlation matrix. Value‐at‐risk and other measures of risks have been developed to account for the larger moves allowed by non‐Gaussian distributions. In this article, the authors distinguish “small” risks from “large” risks, in order to suggest an alternative approach to portfolio optimization that simultaneously increases portfolio returns while minimizing the risk of low frequency, high severity events. This approach treats the variance or second‐order cumulant as a measure of “small” risks. In contrast, higher even‐order cumulants, starting with the fourth‐order cumulant, quantify the “large” risks. The authors employ these estimates of portfolio cumulants based on fat‐tailed distributions to rebalance portfolio exposures to mitigate large risks.

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

There are four categories of ABM in economics.

This paper suggests a methodological categorization of ABM works in economics.

This paper aims to explore the unavoidable role of Islamic spiritual intelligence in organisational sustainability. In the past two decades, increased unethical practices in organisations have resulted in the deterioration of their sustainability. Employees are continuously involved in unethical practices because of a lack of spirituality which is a serious concern for organisational sustainability.

This conceptual paper reviews relevant literature on Islamic spiritual intelligence and organisational sustainability to bridge a gap in the extant literature.

The review of the literature concluded that Islamic spiritual intelligence training must be included as a significant factor for employee development in the organisation. Islamic spiritual intelligence is coherent with the individual’s internal strength of having a pure heart and soul. A person with a pure heart and soul has a strong aspiration to act in an ethical way.

The review of literature is not detailed because of the dearth of information on Islamic spiritual intelligence training for organisational sustainability.

This paper will increase the understanding and link between Islamic spiritual intelligence and organisational sustainability. It suggests Islamic spiritual intelligence and its dimensions with the implication for future research in organisational sustainability.

This paper contributes to the literature related to the application of Islamic spiritual intelligence training programmes for employees, which will have a significant impact on organisational sustainability.

Speculative bubbles have been occurring periodically in local or global real-estate markets and are considered a potential cause of economic crises. In this context, the detection of explosive behaviors in the financial market and the implementation of early warning diagnosis tests are of critical importance. The recent increase in Brazilian housing prices has risen concerns that the Brazilian economy may have a speculative housing bubble. In the present chapter, we employ a recently proposed recursive unit root test in order to identify possible speculative bubbles in data from the Brazilian residential real-estate market. The empirical results show evidence for speculative price bubbles both in Rio de Janeiro and São Paulo, the two main Brazilian cities.

The purpose of this study is to discover and model the asymmetry in the price volatility of financial markets, in particular the foreign exchange markets as the first underlying applications.

The volatility of the financial market price is usually defined with the standard deviation or variance of the price or price returns. This standard definition of volatility is split into the upper part and the lower one, which are termed here as Yang volatility and Yin volatility. However, the definition of yin‐yang volatility depends on the scale of the time, thus the notion of scale space of price‐time is also introduced.

It turns out that the duality of yin‐yang volatility expresses not only the asymmetry of price volatility, but also the information about the trend. The yin‐yang volatilities in the scale space of price‐time provide a complete representation of the information about the multi‐level trends and asymmetric volatilities. Such a representation is useful for designing strategies in market risk management and technical trading. A trading robot (a complete automated trading system) was developed using yin‐yang volatility, its performance is shown to be non‐trivial. The notion and model of yin‐yang volatility has opened up new possibilities to rewrite the option pricing formulas, the GARCH models, as well as to develop new comprehensive models for foreign exchange markets.

The asymmetry of price volatility and the magnitude of volatility in the scale space of price‐time has yet to be united in a more coherent model.

The new model of yin‐yang volatility and scale space of price‐time provides a new theoretical structure for financial market risk. It is likely to enable a new generation of core technologies for market risk management and technical trading strategies.

This work is original. The new notion and model of yin‐yang volatility in scale space of price‐time has cracked up the core structure of the financial market risk. It is likely to open up new possibilities such as: a new portfolio theory with a new objective function to minimize the sum of the absolute yin‐volatilities of the asset returns, a new option pricing theory using yin‐yang volatility to replace the symmetric volatility, a new GARCH model aiming to model the dynamics of yin‐yang volatility instead of the symmetric volatility, new technical trading strategies as are shown in the paper.

The occurrence and unpredictability of speculative bubbles on financial markets, and their accompanying crashes, have confounded economists and economic historians worldwide. The purpose of this paper is to diagnose and detect the bursting of shipping bubbles ex ante, and to qualify the patterns of shipping price dynamics and the bubble mechanics, so that appropriate counter measures can be taken in advance to reduce side effects arising from bubbles.

Log periodic power law (LPPL) model, developed in the past decade, is used to detect large market falls or “crashes” through modeling of the shipping price dynamics on a selection of three historical shipping bubbles over the period of 1985 to 2016. The method is based on a nonlinear least squares estimation that yields predictions of the most probable time of the regime switching.

It could be concluded that predictions by the LPPL model are quite dependent on the time at which they are conducted. Interestingly, the LPPL model could have predicted the substantial fall in the Baltic Dry Index during the recent global downturn, but not all crashes in the past. It is also found that the key ingredient that sets off an unsustainable growth process for shipping prices is the positive feedback. When the positive feedback starts, the burst of bubbles in shipping would be influenced by both endogenous and exogenous factors, which are crucial for the advanced warning of the market conversion.

The LPPL model has been first applied into the dry bulk shipping market to test a couple of shipping bubbles. The authors not only assess the predictability and robustness of the LPPL model but also expand the understanding of the model and explain patterns of shipping price dynamics and bubble mechanics.

Many governments are taking measures in support of small and medium-sized enterprises (SMEs) to mitigate the economic impact of the COVID-19 outbreak. This paper presents a theoretical model for evaluating various government measures, including insurance for bank loans, interest rate subsidy, bridge loans and relief of tax burdens.

This paper distinguishes a firm's intrinsic value and book value, where a firm can lose its intrinsic value when it encounters cash-flow crunch. Wang transform is applied to (1) calculating the appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs, (2) describing the frailty distribution for SMEs and (3) defining banks' underwriting capability and overlap index in risk selection.

Government support for SMEs can be in the form of an appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs.

More available data on bank loans would have helped strengthen the empirical studies.

This paper makes policy recommendations of establishing policy-oriented banks or investment funds dedicated to supporting SMEs, developing risk indices for SMEs to facilitate refined risk underwriting, providing SMEs with long-term tax relief and early-stage equity-type investments.

The model highlights the importance of providing bridge loans to SMEs during the COVID-19 disruption to prevent massive business closures.

This paper provides an analytical framework using Wang transform for analyzing the most effective form of government support for SMEs.

Option pricing is an integral part of modern financial risk management. The well-known Black and Scholes (1973) formula is commonly used for this purpose. The purpose of this paper is to extend their work to a situation in which the unconditional volatility of the original asset is increasing during a certain period of time.

The authors consider a market suffering from a financial crisis. The authors provide the solution for the equation of the underlying asset price as well as finding the hedging strategy. In addition, a closed formula of the pricing problem is proved for a particular case. Furthermore, the underlying price sensitivities are derived.

The suggested formulas are expected to make the valuation of options and the underlying hedging strategies during a financial crisis more precise. A numerical application is provided for determining the premium for a call and a put European option along with the underlying price sensitivities for each option.

An alternative option pricing model is introduced that performs better than existing ones, especially during a financial crisis.

This study aims to investigate the relationship between geopolitical risk (GPR) and gold price bubbles to determine whether rising GPR can drive deviations in the fundamental value of gold, thus leading to speculative bubbles.

Using a data set that spans from January 2002 to December 2023 and covers both GPR data and gold price data, this study applies the log-periodic power law singularity (LPPLS) model to identify gold price bubbles. The analysis explores the effects of GPR and its sub-indices – geopolitical risk–acts (GPRA) and geopolitical risk–threats (GPRT) – on gold price bubbles. The causal relationships are examined through logistic regression, Tobit modelling and machine learning, with a focus on different countries, including major gold producers and consumers.

The results indicate a significant relationship between GPR and gold price bubbles, particularly with GPRA, which exerts a stronger influence than GPRT does. Peaks in GPR often align with the formation of gold price bubbles, both positive and negative. Additionally, geopolitical instability in Russia has a significant effect on US gold price bubbles.

The findings provide valuable insights for investors and policymakers by emphasizing the importance of GPR in shaping gold price dynamics. Investors are advised to consider the nuanced roles of GPRA and GPRT when using gold as a hedge during periods of heightened geopolitical tension.

Understanding the role of GPR in gold price bubbles can help mitigate the financial risk associated with speculative bubbles, thereby offering a better framework for managing assets during geopolitical crises.

This study extends existing research by directly linking GPR with gold price bubbles via the LPPLS model, with a novel emphasis on the differentiation between GPRA and GPRT, providing new perspectives on the safe-haven role of gold during geopolitical uncertainty.

Standard financial risk management practices proved unable to provide an adequate understanding and a timely warning of the financial crisis. In particular, the theoretical foundations of risk management and the statistical calibration of risk models are called into question. Policy makers and practitioners respond by looking for new analytical approaches and tools to identify and address new sources of financial risk. Financial markets satisfy reasonable criteria of being considered complex adaptive systems, characterized by complex financial instruments and complex interactions among market actors. Policy makers and practitioners need to take both a micro and macro view of financial risk, identify proper transparency requirements on complex instruments, develop dynamic models of information generation that best approximate observed financial outcomes, and identify and address the causes and consequences of systemic risk. Complexity analysis can make a useful contribution. However, the methodological suitability of complexity theory for financial systems and by extension for risk management is still debatable. Alternative models drawn from the natural sciences and evolutionary theory are proposed.