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This paper empirically investigates whether cryptocurrencies might have a useful role in financial modelling and risk management in the energy markets. To do so, the causal relationship between movements on the energy markets (specifically the price of crude oil) and the value of cryptocurrencies is analysed by drawing on daily data from April 2013 to April 2019. We find that shocks to the US and European crude oil indices are strongly connected to the movements of most cryptocurrencies. Applying a non-parametric statistic, Transferring Entropy (an econophysics technique measuring information flow), we find that some cryptocurrencies (XEM, DOGE, VTC, XLM, USDT, XRP) can be used for hedging and portfolio diversification. Furthermore, the results reveal that the European crude oil index is a source of shocks on the cryptocurrency market while the US oil index appears to be a receiver of shocks.

Type of the article: Research Article AbstractThis study examines the impact of exchange rate fluctuations on banking and financial service indices in India. To validate this, five exchange rates are considered based on their relative share in the total foreign remittance inflows to India, viz., Arabian Dirham (AED/INR), Great Britain Pound (GBP/INR), Saudi Riyal (SAR/INR), Singapore Dollar (SGD/INR), and US Dollar (USD/INR). The study includes daily data of a decade (2015–2025), and employs various econometric techniques such as ADF test, Johansen cointegration, Vector Error Correction Model (VECM), and Impulse Response Function (IRF) for the analysis. The Johansen cointegration test indicates a long-run relationship between exchange rates and both the sectoral indices, as the probabilities are less than 0.05. The VECM analysis for both the Nifty Bank and Nifty FinServ identified USD/INR (2,308.66; 2,257.58) and SAR/INR (373.25; 360.73) as the dominant long-term drivers, whereas AED/INR (–2,671.406; –2,608.011) acts as a persistent structural anchor with a negative influence. In the short run, shocks in USD/INR and SGD/INR generate immediate positive effects, whereas volatility in AED/INR and SAR/INR leads to temporary negative deviations before the system converges back to the equilibrium. The impulse response function indicates that exchange rate shocks have temporary effects on both the indices, which dissipate quickly, reflecting rapid market adjustment and overall efficiency. The findings of this study will help policymakers to improve the exchange rate risk monitoring system and executives in banks and financial institutions to formulate their hedging strategies. For investors and portfolio managers, the findings suggest that currency movements can serve as early indicators of market fluctuations, thereby supporting more informed investment decisions.

This short piece is motivated by a desire to elucidate the role of mathematical modelling as applied in mathematical finance. It is argued that models are designed for the support of decisions in varied contexts forcing inconsistencies on occasion. The concept and validity of the idea of a true model is called into question, recognizing simultaneously that a model must be and will be applied. A sample of decisions helps to illustrate the issues.

In this paper, a deterministic inventory control model with deterioration is developed. Here, the deterioration rate follows stochastic deterioration, especially Weibull distribution deterioration. A time-dependent demand approach is introduced to show the applicability of our proposed model and to be up-to-date with respect to time. The main purpose of the paper is to investigate the optimal retailer’s replenishment decisions for deteriorating items including time-dependent demand for demonstrating more practical circumstances within economic-order quantity frameworks. Keeping in mind the criterion of modern era, we consider that the holding cost is totally dependent on time, and shortages are allowed for this model. Subject to the formulated model, we minimize the total inventory cost. The mathematical model is explored by numerical examples to validate the proposed model. A sensitivity analysis of the optimal solution with regard to important parameters is also carried out to elaborate the quality, e.g., stability, of our result and to possibly modify our model. The paper ends with a conclusion and an outlook to future studies.

Drawing on documentary sources and 114 interviews with market participants, this and a companion article discuss the development and use in finance of the Gaussian copula family of models, which are employed to estimate the probability distribution of losses on a pool of loans or bonds, and which were centrally involved in the credit crisis. This article, which explores how and why the Gaussian copula family developed in the way it did, employs the concept of 'evaluation culture', a set of practices, preferences and beliefs concerning how to determine the economic value of financial instruments that is shared by members of multiple organizations. We identify an evaluation culture, dominant within the derivatives departments of investment banks, which we call the 'culture of no-arbitrage modelling', and explore its relation to the development of Gaussian copula models. The article suggests that two themes from the science and technology studies literature on models (modelling as 'impure' bricolage, and modelling as articulating with heterogeneous objectives and constraints) help elucidate the history of Gaussian copula models in finance.

The paper studies a two-echelon supply chain comprising of one manufacturer and two competing retailers with sales price dependent demand and random arrival of the customers. The manufacturer acts as the supplier who specifies wholesale price for the retailers and the retailers compete with each other announcing different sales prices. We analyse a single-period newsvendor type model to determine the optimal order quantity, considering the competing retailers’ strategies.The unsold items at the retailers are buyback to the manufacturer at less price than the sales prices.On the other hand, the retailers face shortages as the demand is uncertain in nature. The profit functions of manufacturer and two retailers are analyzed and compared following Stakelberg, Bertrand, Cournot–Bertrand and integrated approaches. Moreover, distribution-free model is analyzed for integrated profit of the chain. A numerical example is given to illustrate the theoretical results developed in each case. Computational results show that it is always beneficial in integrated system for the members of the chain.

The purpose of this work is to show some advanced concepts related to Excel based financial modelling. Microsoft Excel(TM) is a very powerful tool and most of the time we do not utilize its full potential. Of course, any advanced concepts require the basic knowledge which most of us have and then build on it. It is only by hands-on experimentation that one learns the art of constructing an efficient worksheet. The two volumes of this book cover dynamic charting, macros, goal seek, solver, the routine Excel functions commonly used, the lesser known Excel functions, the Excel's financial functions and so on. The introduction of macros in these books is not exhaustive but the purpose of what is presented is to show you the power of Excel and how it can be utilized to automate most repetitive calculations at a click of a button. For those who use Excel on a daily basis in financial modeling and project/investment evaluations, this book is a must.

The purpose of this work is to show some advanced concepts related to Excel based financial modelling. Microsoft Excel(TM) is a very powerful tool and most of the time we do not utilize its full potential. Of course, any advanced concepts require the basic knowledge which most of us have and then build on it. It is only by hands-on experimentation that one learns the art of constructing an efficient worksheet. The two volumes of this book cover dynamic charting, macros, goal seek, solver, the routine Excel functions commonly used, the lesser known Excel functions, the Excel's financial functions and so on. The introduction of macros in these books is not exhaustive but the purpose of what is presented is to show you the power of Excel and how it can be utilized to automate most repetitive calculations at a click of a button. For those who use Excel on a daily basis in financial modeling and project/investment evaluations, this book is a must.

Purpose Financial firms are looking for better ways to harness the power of data analytics to improve their decision quality in the financial modeling era. This study aims to explore key factors influencing big data analytics-driven financial decision quality which has been given scant attention in the relevant literature. Design/methodology/approach The authors empirically examined the interrelations between five factors including technology capability, data capability, information quality, data-driven insights and financial decision quality drawing on quantitative data collected from Jordanian financial firms using a cross-sectional questionnaire survey. Findings The SmartPLS analysis outcomes revealed that both technology capability and data capability have a positive and direct influence on information quality and data-driven insights without any direct influence on financial decision quality. The findings also point to the importance and influence of information quality and data-driven insights on high-quality financial decisions. Originality/value The study for the first time enriches the knowledge and relevant literature by exploring the critical factors affecting big data-driven financial decision quality in the financial modeling context.

An individual investor has to decide how to allocate his/her savings from a retirement perspective. This problem covers a long-term horizon. In this paper we consider a 40-year horizon formulating a multi-criteria multistage program with stochastic dominance constraints in an intermediate stage and in the final stage. As we are dealing with a real problem and we have formulated the model in cooperation with a commercial Italian bank, the intermediate stage corresponds to a possible withdrawal allowed by the Italian pension system. The sources of uncertainty considered are: the financial returns, the interest rate evolution, the investor’s salary process and a considerable withdrawal event. We include a set of portfolio constraints according to the pension plan regulation. The objective of the model is to minimize the Average Value at Risk Deviation measure and to satisfy wealth goals. Three different wealth target formulations are considered: a deterministic wealth target (i.e. a comparison between the accumulated average wealth and a fixed threshold) and two stochastic dominance relations—the first order and the second order—introducing a benchmark portfolio and then requiring the optimal portfolio to dominate the benchmark. In particular, we prove that solutions obtained under stochastic dominance constraints ensure a safer allocation while still guaranteeing good returns. Moreover, we show how the withdrawal event affects the solution in terms of allocation in each of the three frameworks. Finally, the sensitivity and convergence of the stochastic solutions and computational issues are investigated.