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243
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Introduction
My interests are in the field of forecasting and my purpose is to advance both its theory and practice through the M Competitions and M Conferences.
Skills and Expertise
Additional affiliations
June 2017 - present
August 1970 - August 2009
June 2014 - June 2017
Publications
Publications (243)
High blood pressure (HBP) or hypertension (HTN) is one of the leading causes of cardiovascular (CV) morbidity and mortality throughout the world. Despite this fact, there is widespread agreement that the treatment of HBP, over the last half century, has been a great achievement. However, after the release of the new Joint National Committee on Prev...
In this study, the authors used 111 time series to examine the accuracy of various forecasting methods, particularly time-series methods. The study shows, at least for time series, why some methods achieve greater accuracy than others for different types of data. The authors offer some explanation of the seemingly conflicting conclusions of past em...
This special section aims to demonstrate the limited predictability and high level of uncertainty in practically all important areas of our lives, and the implications of this. It summarizes the huge body of solid empirical evidence accumulated over the past several decades that proves the disastrous consequences of inaccurate forecasts in areas ra...
Reliable forecasts are key to decisions in areas ranging from supply chain management to capacity planning in service industries. It is encouraging then that recent decades have seen dramatic advances in forecasting methods which have the potential to significantly increase forecast accuracy and improve operational and financial performance. Howeve...
Artificial Intelligence (AI), as its name implies, is another form of intelligence analogous to our own Human Intelligence (HI). There is growing agreement that based on advances in deep reinforcement learning, AI has surpassed HI in some specific areas such as games and image/speech recognition. At the same time, there is disagreement among leadin...
ChatGPT, a state-of-the-art large language model (LLM), is revolutionizing the AI field by exhibiting humanlike skills in a range of tasks that include understanding and answering natural language questions, translating languages, writing code, passing professional exams, and even composing poetry, among its other abilities. ChatGPT has gained an i...
The purpose of this paper is to test empirically the value currently added by Deep Learning (DL) approaches in time series forecasting by comparing the accuracy of some state-of-the-art DL methods with that of popular Machine Learning (ML) and statistical ones. The paper consists of three main parts. The first part summarizes the results of a past...
Daily SKU demand forecasting is a challenging task as it usually involves predicting irregular series that are characterized by intermittency and erraticness. This is particularly true when forecasting at low cross-sectional levels, such as at a store or warehouse level, or dealing with slow-moving items. Yet, accurate forecasts are necessary for s...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...
In this study, we present the results of the M5 “Accuracy” competition, which was the first of two parallel challenges in the latest M competition with the aim of advancing the theory and practice of forecasting. The main objective in the M5 “Accuracy” competition was to accurately predict 42,840 time series representing the hierarchical unit sales...
This paper describes the M5 “Uncertainty” competition, the second of two parallel challenges of the latest M competition, aiming to advance the theory and practice of forecasting. The particular objective of the M5 “Uncertainty” competition was to accurately forecast the uncertainty distributions of the realized values of 42,840 time series that re...
Forecasting competitions are the equivalent of laboratory experimentation widely used in physical and life sciences. They provide useful, objective information to improve the theory and practice of forecasting, advancing the field, expanding its usage, and enhancing its value to decision and policymakers. We describe 10 design attributes to be cons...
The scientific method consists of making hypotheses or predictions and then carrying out experiments to test them once the actual results have become available, in order to learn from both successes and mistakes. This approach was followed in the M4 competition with positive results and has been repeated in the M5, with its organizers submitting th...
The main objective of the M5 competition, which focused on forecasting the hierarchical unit sales of Walmart, was to evaluate the accuracy and uncertainty of forecasting methods in the field to identify best practices and highlight their practical implications. However, can the findings of the M5 competition be generalized and exploited by retail...
The M5 competition follows the previous four M competitions, whose purpose is to learn from empirical evidence how to improve forecasting performance and advance the theory and practice of forecasting. M5 focused on a retail sales forecasting application with the objective to produce the most accurate point forecasts for 42,840 time series that rep...
Supply chain management depends heavily on uncertain point forecasts of product sales. In order to deal with such uncertainty and optimize safety stock levels, methods that can estimate the right part of the sales distribution are required. Given the limited work that has been done in the field of probabilistic product sales forecasting, we propose...
The main objective of the M5 competition, which focused on forecasting the hierarchical unit sales of Walmart, was to evaluate the accuracy and uncertainty of forecasting methods in the field in order to identify best practices and highlight their practical implications. However, whether the findings of the M5 competition can be generalized and exp...
Forecasting competitions are the equivalent of laboratory experimentation widely used in physical and life sciences. They provide useful, objective information to improve the theory and practice of forecasting, advancing the field, expanding its usage and enhancing its value to decision and policymakers. We describe ten design attributes to be cons...
The M5 forecasting competition is the latest and most widely contested since the first M competition in 1979. Numerous articles have been written appraising the structure of the competitions and the value of their results for forecasting methodology and practice. Mike Gilliland's discussion of the prior competition-the M4-in Foresight's Spring 2020...
The M5 competition follows the previous four M competitions, whose purpose is to learn from empirical evidence how to improve forecasting performance and advance the theory and practice of forecasting. M5 focused on a retail sales forecasting application with the objective to produce the most accurate point forecasts for 42,840 time series that rep...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life...
Forecasting the outcome of outbreaks as early and as accurately as possible is crucial for decision making and policy implementations. A significant challenge faced by forecasters is that not all outbreaks and epidemics turn into pandemics making the prediction of their severity difficult. At the same time, the decisions made to enforce lockdowns a...
The M4 competition identified innovative forecasting methods, advancing the theory and practice of forecasting. One of the most promising innovations of M4 was the utilization of cross-learning approaches that allow models to learn from multiple series how to accurately predict individual ones. In this paper, we investigate the potential of cross-l...
This paper describes the M5 "Uncertainty'' competition, the second of two parallel challenges of the latest M competition whose aim is to advance the theory and practice of forecasting. The particular objective of the M5 "Uncertainty'' competition was to precisely estimate the uncertainty distribution of the realized values of 42,840 time series th...
The M5 competition follows on from the four previous M competitions, organized by Spyros Makridakis, whose purpose has been to advance the theory and practice of forecasting. The M5 differs from the previous four ones in five ways. First, it uses hierarchical unit sales data, generously made available by Walmart, starting at the product-store level...
This paper describes the M5 Accuracy competition, the first of two parallel challenges of the latest M competition whose objective is to advance the theory and practice of forecasting. The M5 Accuracy competition focused on a retail sales forecasting application and extended the results of the previous four competitions by: (a) significantly expand...
The Theta method became popular due to its superior performance in the M3 forecasting competition. Since then, although it has been shown that Theta provides accurate forecasts for various types of data, being a solid benchmark to beat, limited research has been conducted to exploit its full potential and generalize its reach. This paper examines t...
What will be the global impact of the novel coronavirus (COVID-19)? Answering this question requires accurate forecasting the spread of confirmed cases as well as analysis of the number of deaths and recoveries. Forecasting, however, requires ample historical data. At the same time, no prediction is certain as the future rarely repeats itself in th...
Blockchain is a new technology, often referred to as the Internet of Value. As with all new technologies, there is no consensus on its potential value, with some people claiming that it will bring more disruptive changes than the Internet and others contesting the extent of its importance. Despite predictions that the future is perilous, there is e...
A presentation about Human Intelligence (HI) Vs. Artificial Intelligence (AI) and Intelligence Augmentation (IA) and their future implications
Science is caught up in a replication crisis which has negative implications for published findings that cannot be reproduced by other researchers. However, such is not the case with the M4 Competition, which not only provided the means of effectively reproducing its submissions, but also preregistered ten predictions/hypotheses about its expected...
This paper provides a non-systematic review of the progress of forecasting in social settings. It is aimed at someone outside the field of forecasting who wants to understand and appreciate the results of the M4 Competition, and forms a survey paper regarding the state of the art of this discipline. It discusses the recorded improvements in forecas...
The M4 Competition follows on from the three previous M competitions, the purpose of which was to learn from empirical evidence both how to improve the forecasting accuracy and how such learning could be used to advance the theory and practice of forecasting. The aim of M4 was to replicate and extend the three previous competitions by: (a) signific...
Responses to discussions and commentaries (M4 forecasting competition)
In the last several years, technological progress has accelerated rapidly. Artificial intelligence (AI) has brought self-driving cars to our streets, super-automation to our factories, deep learning algorithms that beat world champions, image recognition programs that diagnose cancer more accurately than experienced oncologists can, voice recogniti...
Management in the 21st Century 4 Spyros Makridakis This paper predicts the type of business firms and managers most likely to emerge in the 21st century. The forecasts are based on rationalprinciples which avoid the common mistakes made in the past by long-term forecasters. Such forecasts are developed by examining long-term patterns in human histo...
In order to evaluate the performance of new forecasting methods, forecasters typically exploit past forecasting competitions data. Through the years, numerous studies have based their conclusions on such datasets, making any mis-performing method unlikely to receive further attention. Yet, it has been reported that these datasets might not be indic...
The M4 Competition is the continuation of three previous ones organized by Spyros Makridakis whose purpose has been to identify the most accurate forecasting method(s) for different types of predictions. M Competitions have attracted great interest in both the academic literature and among practitioners and have provided objective evidence of the m...
Comparing ML with statistical forecasting methods
This editorial has two parts. The first one describes a personal experience about our attempt to replicate a forecasting study, as well as the rejection of a submitted paper, in our view due to lack of objectivity. The second part discusses the need for reproducibility and replicability in forecasting research and provides suggestions for promoting...
The M4 competition is the continuation of three previous competitions started more than 45 years ago whose purpose was to learn how to improve forecasting accuracy, and how such learning can be applied to advance the theory and practice of forecasting. The purpose of M4 was to replicate the results of the previous ones and extend them into three di...
Containing tables A1 and A2, presenting the analytical results of the forecasting models used in the present study.
The accuracy is evaluated per forecasting horizon first according to sMAPE, and then to MASE.
(PDF)
Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting hori...
Should we screen the population routinely for the presence of breast or prostatic cancer? This simple proposition masks a landscape of complexities, including the economics of screening, the prevalence and probability of the disease, desired frequencies of intervention and a willingness to adopt preventive screening. These 'risk factors' form part...
Announcing the Makridakis 4 or M4 Competition
The published version of this working paper can be found at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194889
The impact of the industrial and digital (information) revolutions has, undoubtedly, been substantial on practically all aspects of our society, life, firms and employment. Will the forthcoming AI revolution produce similar, far-reaching effects? By examining analogous inventions of the industrial, digital and AI revolutions, this article claims th...
The evaluation of torsional effects on multistory buildings remains an open issue, despite considerable research efforts and numerous publications. In this study, a large number of multiple test structures are considered with normally distributed topological attributes, in order to quantify the statistically derived relationships between the torsio...
The evaluation of torsional effects on multistory buildings remains an open issue, despite considerable research efforts and numerous publications. In this study, a large number of multiple test structures are considered with normally distributed topological attributes, in order to quantify the statistically derived relationships between the torsio...
This work aims to assess and compare the computational efficiency of the regression analysis and genetic algorithms, in terms of accuracy and computational time. The scope is to specify the optimum attributes of the isolator system. The test case results obtained through the incremental dynamic analysis of the existing Sodium building, studied duri...
The origins of forecasting can be traced back to the beginning of human civilization with attempts to predict the weather, although forecasting as a field first appeared in the 1940s and attracted more followers from the early 1950s, when the need for predictions emerged in different fields of endeavor. It expanded considerably in the 1960s and 197...
A paper surveying forecasting and uncertainty in various fields of endavour.
Inforecasting we must assume constancy of patterns/relationships in order to forecast. This assumption is often ignored making the predictions totaly wrong.
Positive illusions are associated with unrealistic optimism about the future and an inflated assessment of one's abilities. They are prevalent in normal life and are considered essential for maintaining a healthy mental state, although, there are disagreements to the extent to which people demonstrate these positive illusions and whether they are b...
Positive illusions are associated with unrealistic optimism about the future and an inflated assessment of one’s abilities. They are prevalent in normal life and are considered essential for maintaining a healthy mental state, although, there are disagreements to the extent to which people demonstrate these positive illusions and whether they are b...
Positive illusions are associated with unrealistic optimism about the future and an inflated assessment of one's abilities. They are prevalent in normal life and are considered essential for maintaining a healthy mental state, although, there are disagreements to the extent to which people demonstrate these positive illusions and whether they are b...
Forecasting as a scientific discipline has progressed a lot in the last 40 years, with Nobel prizes being awarded for seminal work in the field, most notably to Engle, Granger and Kahneman. Despite these advances, even today we are unable to answer a very simple question, the one that is always the first tabled during discussions with practitioners...
The field of forecasting has improved significantly in recent years but we need to learn from history about what we can and cannot predict, and develop plans that are sensitive to surprises. Unfortunately, there are many things we cannot predict and uncertainty is much greater than most of us are willing to accept. This article aims at helping mana...
This conclusion aims to summarize the major issues surrounding forecasting, as well as the extensive empirical evidence proving our inability to accurately predict the future. In addition, it discusses our resistance to accepting such inaccurate predictions, while putting forwards a number of ideas aimed at a complex world where accurate forecastin...