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174 records from EconBiz based on author Name
1. Subsidies, land size and agricultural output
abstractIn this paper we make a two-fold contribution. We first examine the impact of agricultural subsidies on Greece, using a detailed, micro-panel dataset for four years, 2008, 2010, 2012, and 2014. Our analysis is illuminating at least two aspects of subsidies: first, it suggests that an incentive scheme for promoting a larger farm size would have a probable positive effect on agricultural value-added; second, that subsidies today produce the larger impact on future value-added for the top two percentiles of the subsidy distribution. The adjacent contribution is the presentation of a new theoretical model on subsidies where we examine the impact of land size and taxes on them. We estimate the model's hyperparameters, using Greek data from the FADN database. Our new theoretical results, combined with the empirical analysis on the first part, suggest that agricultural subsidies are of dubious economic value, in magnitude and effect, and distort the incentives for returns-to-scale and increased working hours in Greek agriculture.
Kyriazi, Foteini; Thomakos, Dimitrios D.; Rezitis, Antonis;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
2. Introducing the GVAR-GARCH model : evidence from financial markets
Prelorentzos, Arsenios-Georgios N.; Konstantakis, Konstantinos N.; Michaēlidēs, Panagiōtēs G.; Xidonas, Panos; Goutte, Stéphane; Thomakos, Dimitrios D.;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 3. On functional log portfolios
Thomakos, Dimitrios D.; Yahlomi, Rafael; Karaoulanis, Dimitrios;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
4. The origins of forward-looking decision making : cybernetics, operational research, and the foundations of forecasting
abstractThe massive explosion of literature, theory, and methods on all aspects of decision-analytics, machine learning and artificial intelligence, over the past 20 or so years has brought a rapid specialization in each of the substrata of the fields that are using them. The sharp focus on empirical usage of these methods across applications, and the consequent trivialization from data only-driven improvements and multiple method comparisons, have diverted attention from foundational and epistemological concerns and questions, leading to pure empiricism - due to, but not exclusively, increases and availability of computing power. Tapping into the, equally massive, history and literature of the earliest developments from pioneers in the fields of cybernetics, operations research, and forecasting, we re-establish the links to the past on the origins of business and predictive analytics. Using interdisciplinary-sourced material we bring attention to the significance of these early developments and to the need for a return to these early sources in re-establishing our connection with the fundamental principles and questions that define meaningful, forward-looking, decision-making.
Thomakos, Dimitrios D.; Xidonas, Panos;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
5. The Development and Evolution of Mean-Variance Efficient Portfolios in the US and Japan : 30 Years After the Markowitz and Ziemba Applications
abstractIn 1992, John Mulvey co-edited a Special Issue, entitled “Financial Engineering”, in the Annals of Operations Research. In that issue, Guerard, Takano, and Yamane (1992) reported mean-variance efficient portfolios for the Japanese and U.S. equity markets and showed that the use of a regression-weighted composite model of earnings, book value, cash flow, sales, and their relative variables and forecasted earnings, outperformed their respective equity benchmarks by approximately 400 basis points annually. William T. (Bill) Ziemba was the referee of the Guerard et al. (1992) paper. Markowitz and Xu (1994) tested the composite model strategy and found that its excess returns were statistically significant from a variety of models tested, and the composite model strategy was not the result of data mining. Thirty years after the issue, we report factor backtesting results and robust regression modeling in creating optimized US and Japanese portfolio results for the 2000-2022 period, a combination of methods and the latest commercially available multi-factor models for portfolio selection. Recent publications by Markowitz, Guerard, and Xu report additional support for the absence of data mining. Furthermore, the weighted latent root regression modeling is still relevant. Our results suggest that stock selection models can be effectively employed to deliver excess returns. The authors believe that financial anomalies exist, persist, and most likely will exist and can be profitably exploited. However, the use of changing risk models could be a source of confusion in portfolio selection attribution. Quantitative investing requires constant implementation and discipline to maximize client wealth
Guerard, John Baynard; Thomakos, Dimitrios D.; Kyriazi, Foteini; Beheshti, Bijan;2023
Availability: Link Link
6. Climate change economics and the determinants of carbon emissions' futures returns : a regime-driven ARDL model
Kotsompolis, Giorgos; Konstantakis, Konstantinos N.; Xidonas, Panos; Michaēlidēs, Panagiōtēs G.; Thomakos, Dimitrios D.;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
7. 'On the Predictability of the DJIA and S&P500 Indices'
abstractWe obtained from Standard and Poor’s Corporation, the complete 126-year history of the Dow Jones Industrial Average (DJIA) daily closing prices. We are applying rolling window averaging and adaptive learning methodologies, coupled with robust estimation methods, to examine which are the best forecasting models over a broad range of economic and financial conditions during the life of the index, based on daily and monthly stock index prices and daily, monthly, and semi-annual stock returns. Why is an AR(1) model a reasonable benchmark of stock prices? Why do we have it? What should be our forecasting benchmarks? Let us briefly re-visit the history of stock price research and efficient markets. Do we find forecasting improvements from the Hendry-Castle-Doornik-Clements approach using robust forecasting methodologies and saturation variables in the prices of the index? Given that the DJIA fell over 15% during the first half of 2022, is this one of the worst six-month periods ever? What has happened to the Dow, historically, during such periods in the past with regards to six-month, one-year, and three-year-ahead stock returns? Is capitalism dead or doomed? We report statistically significant forecasting improvement from saturation and robust forecasting techniques during the 1896 -June 2022 period. We report forecasted stock returns for the next 6 months and three years that are bullish. In the King’s English, June 30, 2022 was another excellent common stock buying opportunity and capitalism is not dead
Guerard, John; Thomakos, Dimitrios D.; Kyriazi, Foteini; Mamais, Konstantinos;2022
Availability: Link Link
8. Superforecasting reality check : evidence from a small pool of experts and expedited identification
Katsagounos, Ilias; Thomakos, Dimitrios D.; Litsiou, Konstantia; Nikolopoulos, Konstantinos;2021
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
Citations: 8 (based on OpenCitations)
9. Return signal momentum
Papailias, Fotis; Liu, Jiadong; Thomakos, Dimitrios D.;2021
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
Citations: 8 (based on OpenCitations)
10. ShoTS forecasting : short time series forecasting for management research
Thomakos, Dimitrios D.; Wood, Geoffrey T.; Ioakimidis, Marilou; Papagiannakis, Giorgos;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
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