Search Results (17)

This study investigated the interplay between exchange rate volatility, inflation rates, and real interest rates on Zambia’s economic growth from 1992 to 2022, utilizing annualized time series data. The study was necessitated by the limited published literature and relatively varying findings on the variables’ relationships in resource-dependent countries, such as Zambia. Diagnostic tests, including stationarity and co-integration analyses, were employed to determine integration orders and potential long-run relationships. The linear and nonlinear autoregressive distributed lag models were employed to assess short- and long-run dynamics of the variables on economic growth. The results established a positive short-run relationship between inflation rates and Gross Domestic Product (GDP) growth in the linear autoregressive distributive lag model, while an inverse relationship was observed in the nonlinear autoregressive distributive lag model, suggesting that negative shocks in inflation rates had a highly significant positive impact on economic growth. Furthermore, interest rates exhibited a positive relationship with economic growth, further suggesting that positive shocks had a greater significant direct effect on economic growth in comparison to negative shocks in the short and long run, respectively. Finally, exchange rates in both models exhibited an inverse relationship with economic growth irrespective of positive or negative shocks in the long run, highlighting the adverse effect of exchange rate volatility on economic growth prospects in developing countries, such as Zambia. The speed of adjustment to convergence following any disruptions was determined to be 75.18% (ARDL) and 89.19% (NARDL), highlighting relatively fast speeds of adjustments from any short-run disruptions. Notably, some of the policy recommendations included regular assessments of exchange rate volatility influences on import prices, domestic inflation, and production costs in key sectors. Additionally, the implementation of currency hedging options and forwards as well as bulking of foreign exchange reserves will ensure the stability of exchange rates against other major currencies in various economic conditions. Full article

Uncertain fractional differential equations (UFDEs) are excellent tools for describing complicated dynamic systems. This study analyzes the valuation problems of currency options based on UFDE under the optimistic value criterion. Firstly, a new uncertain fractional currency model is formulated to describe the dynamics of the foreign exchange rate. Then, the pricing formulae of European, American, and Asian currency options are obtained under the optimistic value criterion. Numerical simulations are performed to discuss the properties of the option prices with respect to some parameters. Finally, a real-world example is provided to show that the uncertain fractional currency model is superior to the classical stochastic model. Full article

In option pricing, we often deal with options whose payoffs depend on multiple factors such as foreign exchange rates, stocks, etc. Usually, this leads to a knowledge of the joint distributions and complicated integration procedures. This paper develops an alternative approach that converts the option pricing problem into a dual one and presents a solution to the problem in the optional semimartingale setting. The paper contains several examples which illustrate its results in terms of the parameters of models and options. Full article

Cacao swollen shoot disease (CSSD) caused by complexes of cacao swollen shoot badnaviruses (family Caulimoviridae, genus Badnavirus) remains highly prevalent and devastating in West Africa. The disease continues to impact substantially on cacao yield loss, cacao tree mortality, and decline in foreign exchange income from cacao bean sales. Currently, the disease is estimated to have a prevalence rate of over 30% in Ghana, as assessed in the ongoing third country-wide surveillance program. Although achievements from past research interventions have greatly elucidated the etiology, biology, epidemiology, diagnostics, and management of the disease, there are some outstanding knowledge gaps. The role of these information gaps and their effect on CSSD epidemiology and prevalence remain unanswered. This paper summarizes existing scientific knowledge from past research achievements that have provided elucidation on CSSD epidemiology, management options, and guided future research. The discussion highlights the need for multidisciplinary research with modern tools and institutional collaborators to holistically bring clarity on knowledge gaps on pathogen biology, virus–host-–vector interactions, role of environmental and soil nutrient effects on CSSD severity, evolution pattern, role of alternative hosts on virus species diversity, vector population dynamics, and their overall impact on CSSD prevalence and integrated management in cacao plantations. Full article

In this paper, we study a simplified approach to determine the pricing formula for vulnerable options involving two correlated underlying assets. We utilize an intensity-based model to describe the credit risk associated with these vulnerable options. Without the change of measure technique, we derive pricing formulas for vulnerable options involving two underlying assets based on the probabilistic approach. We provide closed-form pricing formulas for two specific types of options: the vulnerable exchange option and the vulnerable foreign equity option. Finally, we present numerical results to demonstrate the accuracy of our formulas using the Monte-Carlo method and the effect of various parameters on the price of options. Full article

In this study, we propose a semiparametric, parsimonious value-at-risk forecasting model, based on quantile regression and machine learning methods, combined with readily available market prices of option contracts from the over-the-counter foreign exchange rate interbank market. We aim at improving existing methods for VaR prediction of currency investments using machine learning. We employ two different methods, i.e., ensemble methods and neural networks. Explanatory variables are implied volatilities with plausible economic interpretation. The forward-looking nature of the model, achieved by the application of implied volatilities as risk factors, ensures that new information is rapidly reflected in value-at-risk estimates. To the best of our knowledge, this study is the first to utilize information in the volatility surface, combined with machine learning and quantile regression, for VaR prediction of currency investments. The proposed ensemble models achieve good estimates across all quantiles. The light gradient boosting machine model and the categorical boosting model both yield estimates which are better than, or equal to, those of the benchmark model. In general, neural network models are quite unstable. Full article

With ownership estimates of up to 25%, Turkey is at the forefront of cryptocurrency adoption, rendering it an interesting example to study the proclaimed use cases of cryptocurrencies. Using exploratory factor analysis based on a sample of 715 Turkish cryptocurrency owners, we identified 3 different owner groups and their underlying motives. The first group (payment users) looks at cryptocurrency as an option for payments, thereby disregarding its speculative element, while the second group (crypto investors) can best be described as experienced investors holding cryptocurrency as part of their investment strategy. The third group (crypto traders) consists of risk-tolerant traders. Further analyses show that groups not only differentiate by demographics, income and education, but also by factors such as ideology, purchase intention and the use of domestic or foreign exchanges. The results contribute to the understanding of Turkish cryptocurrency owners, their intrinsic and extrinsic motivations and can be incorporated into the pending regulatory processes in the country. The findings suggest that cryptocurrencies have outgrown the use case of mere speculation in Turkey. Those in the group of Turkish payment users are identified as potential lead users whose current needs may represent common needs for crypto users in similar markets in the future. These findings motivate further research on the diffusion and usage patterns of cryptocurrency in emerging markets and innovation in general in the context of lead markets. Full article

The foreign exchange market comprises the largest global volume, so the pricing of foreign exchange options has always been a hot issue in the foreign exchange market. This paper treats the exchange rate as an uncertain process that is described by an uncertain fractional differential equation, and establishes a new uncertain fractional currency model. The uncertain process is driven by Liu process, and, with the application of the Mittag-Leffler function, the solution of the fractional differential equation in a Caputo sense is presented. Then, according to the uncertain fractional currency model, the pricing formulas of European and American currency options are given. Lastly, the two numerical examples of European and American currency options are given; the price of the currency option increased when p changed from 1.0 to 1.1, and prices with different p were all decreasing functions of exercise price K. Full article

Astonishingly little attention has been paid in academic literature to the 2008–2009 foreign exchange (FX) options debacle in Poland, the scale of which was unheard of. It affected not only an individual organization but a significant part of economy, being an example of a situation in which operational risk at the company level could have impacted systemic risk. The research provides evidence of the dark side of financial innovations through an analysis of a countrywide case on an emerging market, utilizing a primary qualitative content analysis (QCA) of over 750 documents (including press releases, public authorities’ accounts, and corporate statements). It documents that the FX options debacle was caused by financial institutions which shrouded some aspects of innovative securities or took advantage of information asymmetry to exploit uninformed clients. The study concludes that both adequate legal regulations and proper operational risk management are crucial to avoid similar corporate failures. Full article

This study introduces the intraday implied volatility (IV) for pricing the Australian dollar (AUD) options. The IV is estimated using the at-the-money one-month, two-month, and three-month maturity AUD options traded in the opening, midday, and closing period of a trading day. The Mincer-Zarnowitz regression test evaluates the predictive power of IV to forecast the foreign exchange volatility for the within-week, one-week, and one-month horizon. The mean absolute error, mean squared error, and root mean squared error measures are employed to assess the performance of IV in estimating the price of currency options for the within-week, one-week, and one-month horizon. This study reveals four critical findings. First, a three-month maturity IV does not contain vital information for pricing options. Second, IV incorporated information is not relevant to compute the value of options for a horizon of less than a week. Third, IV in the closing period of Monday or Tuesday subsumes most of the essential information to estimate options price. Fourth, the shorter (longer) maturity IV provides critical information to price options for the shorter (longer) horizon. The intraday IV is a new dimension of unobservable volatility in accurately pricing currency options for researchers and practitioners. Full article

The portfolio optimization problem generally refers to creating an investment portfolio or asset allocation that achieves an optimal balance of expected risk and return. These portfolio returns are traditionally assumed to be continuous random variables. In An Entropy-Based Approach to Portfolio Optimization, we introduced a novel non-parametric optimization method based on Shannon entropy, called return-entropy portfolio optimization (REPO), which offers a simple and fast optimization algorithm for assets with continuous returns. Here, in this paper, we would like to extend the REPO approach to the optimization problem for assets with discrete distributed returns, such as those from a Bernoulli distribution like binary options. Under a discrete probability distribution, portfolios of binary options can be viewed as repeated short-term investments with an optimal buy/sell strategy or general betting strategy. Upon the outcome of each contract, the portfolio incurs a profit (success) or loss (failure). This is similar to a series of gambling wagers. Portfolio selection under this setting can be formulated as a new optimization problem called discrete entropic portfolio optimization (DEPO). DEPO creates optimal portfolios for discrete return assets based on expected growth rate and relative entropy. We show how a portfolio of binary options provides an ideal general setting for this kind of portfolio selection. As an example we apply DEPO to a portfolio of short-term foreign exchange currency pair binary options from the NADEX exchange platform and show how it outperforms leading Kelly criterion strategies. We also provide an additional example of a gambling application using a portfolio of sports bets over the course of an NFL season and present the advantages of DEPO over competing Kelly criterion strategies. Full article

High-frequency trading is a method of intervention on the financial markets that uses sophisticated software tools, and sometimes also hardware, with which to implement high-frequency negotiations, guided by mathematical algorithms, that act on markets for shares, options, bonds, derivative instruments, commodities, and so on. HFT strategies have reached considerable volumes of commercial traffic, so much so that it is estimated that they are responsible for most of the transaction traffic of some stock exchanges, with percentages that, in some cases, exceed 70% of the total. One of the main issues of the HFT systems is the prediction of the medium-short term trend. For this reason, many algorithms have been proposed in literature. The author proposes in this work the use of an algorithm based both on supervised Deep Learning and on a Reinforcement Learning algorithm for forecasting the short-term trend in the currency FOREX (FOReign EXchange) market to maximize the return on investment in an HFT algorithm. With an average accuracy of about 85%, the proposed algorithm is able to predict the medium-short term trend of a currency cross based on the historical trend of this and by means of correlation data with other currency crosses using techniques known in the financial field with the term arbitrage. The final part of the proposed pipeline includes a grid trading engine which, based on the aforementioned trend predictions, will perform high frequency operations in order to maximize profit and minimize drawdown. The trading system has been validated over several financial years and on the EUR/USD cross confirming the high performance in terms of Return of Investment (98.23%) in addition to a reduced drawdown (15.97 %) which confirms its financial sustainability. Full article

An Entropic Dynamics of exchange rates is laid down to model the dynamics of foreign exchange rates, FX, and European Options on FX. The main objective is to represent an alternative framework to model dynamics. Entropic inference is an inductive inference framework equipped with proper tools to handle situations where incomplete information is available. Entropic Dynamics is an application of entropic inference, which is equipped with the entropic notion of time to model dynamics. The scale invariance is a symmetry of the dynamics of exchange rates, which is manifested in our formalism. To make the formalism manifestly invariant under this symmetry, we arrive at choosing the logarithm of the exchange rate as the proper variable to model. By taking into account the relevant information about the exchange rates, we derive the Geometric Brownian Motion, GBM, of the exchange rate, which is manifestly invariant under the scale transformation. Securities should be valued such that there is no arbitrage opportunity. To this end, we derive a risk-neutral measure to value European Options on FX. The resulting model is the celebrated Garman–Kohlhagen model. Full article

Many aspects of the present and future effects on the UK economy, industry, and households, of Brexit have been researched. One thing which appears certain about Brexit is the shadow of uncertainty it casts on the future of business in the UK and its telling effects on the UK economy. It is believed that Brexit has negatively affected the level of investments in the UK, including investments in energy and crucially the upstream oil and gas, with the UK North Sea being starved of investments since 2014, leading already to increased energy bills. The UK is a net importer of natural gas—a major source of its energy, with some dependence on supplies from interconnectors from Europe. At the same time, UK energy companies participate in the common energy market which enables them to undertake arbitrage trading under the common market rules. However, both of these benefits could be lost under a Brexit scenario where the UK and EU come to a no-deal or hard border arrangement. Meanwhile, domestic production of energy in the UK has declined for nearly two decades now and import bills for natural gas are growing—they were £14.2 billion in 2017; £11.7 billion in 2016 and £13.4 billion in 2015—with Government projections indicating an upward trajectory for natural gas imports. It is however believed that the UK has great potential to exploit shale gas to her advantage in order to reduce her reliance on foreign energy which is: (1) less predictable in terms of supply and price affordability and (2) dependent on exchange rates—a primary means through which energy prices increased in 2016/17 post-Brexit referendum vote. The current study extends discussions on shale gas to cover a review of the potential of natural gas from shale formations to cushion UK households against further erratic gas prices due to Brexit and also assesses the potential effects Brexit may have had on the level of investments in shale gas, in order to suggest policy options for government consideration. Contrary to popular studies, we find evidence to suggest that shale gas has the potential to reduce energy prices for UK businesses and households at commercial extractions, under both hard and soft Brexit scenarios, but with more benefits under hard Brexit. Importantly, we find that from 2008 to 2017, average UK net export of natural gas was 5,191 GWh per year to the EU. We also find and argue that Brexit may have starved the nascent fracking industry of investments in a similar way it did to investments in conventional oil and gas and could have increased investor risk premium for shale gas development, the ultimate effect of which was a categorisation of fracking (company stock) as riskier asset for investors on the London Stock Exchange. We recommend that shale gas development be expedited to maximise its benefits to UK energy consumers post-Brexit or economic benefits from the resource could be diminished by rising operator costs due to delays and effects of the public’s perceived negative opinion of the method of extraction. Full article

Much of the debate around a potential British exit (Brexit) from the European Union has centred on the potential macroeconomic impact. In this paper, we instead focus on understanding market expectations for price action around the Brexit referendum date. Extracting implied distributions from the GBPUSD option volatility surface, we originally estimated, based on our visual observation of implied probability densities available up to 13 June 2016, that the market expected that a vote to leave could result in a move in the GBPUSD exchange rate from 1.4390 (spot reference on 10 June 2016) down to a range in 1.10 to 1.30, i.e., a 10–25% decline—very probably with highly volatile price action. To quantify this more objectively, we construct a mixture model corresponding to two scenarios for the GBPUSD exchange rate after the referendum vote, one scenario for “remain” and one for “leave”. Calibrating this model to four months of market data, from 24 February to 22 June 2016, we find that a “leave” vote was associated with a predicted devaluation of the British pound to approximately 1.37 USD per GBP, a 4.5% devaluation, and quite consistent with the observed post-referendum exchange rate move down from 1.4877 to 1.3622. We contrast the behaviour of the GBPUSD option market in the run-up to the Brexit vote with that during the 2014 Scottish Independence referendum, finding the potential impact of Brexit to be considerably higher. Full article