GIAKOUMATOS STEFANOS
PROFESSOR
iVBORw0KGgoAAAANSUhEUgAAASwAAAEsCAYAAAB5fY51AAAACXBIWXMAAC4jAAAuIwF4pT92AAAKT2lDQ1BQaG90b3Nob3AgSUNDIHByb2ZpbGUAAHjanVNnVFPpFj333vRCS4iAlEtvUhUIIFJCi4AUkSYqIQkQSoghodkVUcERRUUEG8igiAOOjoCMFVEsDIoK2AfkIaKOg6OIisr74Xuja9a89+bN/rXXPues852zzwfACAyWSDNRNYAMqUIeEeCDx8TG4eQuQIEKJHAAEAizZCFz/SMBAPh+PDwrIsAHvgABeNMLCADATZvAMByH/w/qQplcAYCEAcB0kThLCIAUAEB6jkKmAEBGAYCdmCZTAKAEAGDLY2LjAFAtAGAnf+bTAICd+Jl7AQBblCEVAaCRACATZYhEAGg7AKzPVopFAFgwABRmS8Q5ANgtADBJV2ZIALC3AMDOEAuyAAgMADBRiIUpAAR7AGDIIyN4AISZABRG8lc88SuuEOcqAAB4mbI8uSQ5RYFbCC1xB1dXLh4ozkkXKxQ2YQJhmkAuwnmZGTKBNA/g88wAAKCRFRHgg/P9eM4Ors7ONo62Dl8t6r8G/yJiYuP+5c+rcEAAAOF0ftH+LC+zGoA7BoBt/qIl7gRoXgugdfeLZrIPQLUAoOnaV/Nw+H48PEWhkLnZ2eXk5NhKxEJbYcpXff5nwl/AV/1s+X48/Pf14L7iJIEyXYFHBPjgwsz0TKUcz5IJhGLc5o9H/LcL//wd0yLESWK5WCoU41EScY5EmozzMqUiiUKSKcUl0v9k4t8s+wM+3zUAsGo+AXuRLahdYwP2SycQWHTA4vcAAPK7b8HUKAgDgGiD4c93/+8//UegJQCAZkmScQAAXkQkLlTKsz/HCAAARKCBKrBBG/TBGCzABhzBBdzBC/xgNoRCJMTCQhBCCmSAHHJgKayCQiiGzbAdKmAv1EAdNMBRaIaTcA4uwlW4Dj1wD/phCJ7BKLyBCQRByAgTYSHaiAFiilgjjggXmYX4IcFIBBKLJCDJiBRRIkuRNUgxUopUIFVIHfI9cgI5h1xGupE7yAAygvyGvEcxlIGyUT3UDLVDuag3GoRGogvQZHQxmo8WoJvQcrQaPYw2oefQq2gP2o8+Q8cwwOgYBzPEbDAuxsNCsTgsCZNjy7EirAyrxhqwVqwDu4n1Y8+xdwQSgUXACTYEd0IgYR5BSFhMWE7YSKggHCQ0EdoJNwkDhFHCJyKTqEu0JroR+cQYYjIxh1hILCPWEo8TLxB7iEPENyQSiUMyJ7mQAkmxpFTSEtJG0m5SI+ksqZs0SBojk8naZGuyBzmULCAryIXkneTD5DPkG+Qh8lsKnWJAcaT4U+IoUspqShnlEOU05QZlmDJBVaOaUt2ooVQRNY9aQq2htlKvUYeoEzR1mjnNgxZJS6WtopXTGmgXaPdpr+h0uhHdlR5Ol9BX0svpR+iX6AP0dwwNhhWDx4hnKBmbGAcYZxl3GK+YTKYZ04sZx1QwNzHrmOeZD5lvVVgqtip8FZHKCpVKlSaVGyovVKmqpqreqgtV81XLVI+pXlN9rkZVM1PjqQnUlqtVqp1Q61MbU2epO6iHqmeob1Q/pH5Z/YkGWcNMw09DpFGgsV/jvMYgC2MZs3gsIWsNq4Z1gTXEJrHN2Xx2KruY/R27iz2qqaE5QzNKM1ezUvOUZj8H45hx+Jx0TgnnKKeX836K3hTvKeIpG6Y0TLkxZVxrqpaXllirSKtRq0frvTau7aedpr1Fu1n7gQ5Bx0onXCdHZ4/OBZ3nU9lT3acKpxZNPTr1ri6qa6UbobtEd79up+6Ynr5egJ5Mb6feeb3n+hx9L/1U/W36p/VHDFgGswwkBtsMzhg8xTVxbzwdL8fb8VFDXcNAQ6VhlWGX4YSRudE8o9VGjUYPjGnGXOMk423GbcajJgYmISZLTepN7ppSTbmmKaY7TDtMx83MzaLN1pk1mz0x1zLnm+eb15vft2BaeFostqi2uGVJsuRaplnutrxuhVo5WaVYVVpds0atna0l1rutu6cRp7lOk06rntZnw7Dxtsm2qbcZsOXYBtuutm22fWFnYhdnt8Wuw+6TvZN9un2N/T0HDYfZDqsdWh1+c7RyFDpWOt6azpzuP33F9JbpL2dYzxDP2DPjthPLKcRpnVOb00dnF2e5c4PziIuJS4LLLpc+Lpsbxt3IveRKdPVxXeF60vWdm7Obwu2o26/uNu5p7ofcn8w0nymeWTNz0MPIQ+BR5dE/C5+VMGvfrH5PQ0+BZ7XnIy9jL5FXrdewt6V3qvdh7xc+9j5yn+M+4zw33jLeWV/MN8C3yLfLT8Nvnl+F30N/I/9k/3r/0QCngCUBZwOJgUGBWwL7+Hp8Ib+OPzrbZfay2e1BjKC5QRVBj4KtguXBrSFoyOyQrSH355jOkc5pDoVQfujW0Adh5mGLw34MJ4WHhVeGP45wiFga0TGXNXfR3ENz30T6RJZE3ptnMU85ry1KNSo+qi5qPNo3ujS6P8YuZlnM1VidWElsSxw5LiquNm5svt/87fOH4p3iC+N7F5gvyF1weaHOwvSFpxapLhIsOpZATIhOOJTwQRAqqBaMJfITdyWOCnnCHcJnIi/RNtGI2ENcKh5O8kgqTXqS7JG8NXkkxTOlLOW5hCepkLxMDUzdmzqeFpp2IG0yPTq9MYOSkZBxQqohTZO2Z+pn5mZ2y6xlhbL+xW6Lty8elQfJa7OQrAVZLQq2QqboVFoo1yoHsmdlV2a/zYnKOZarnivN7cyzytuQN5zvn//tEsIS4ZK2pYZLVy0dWOa9rGo5sjxxedsK4xUFK4ZWBqw8uIq2Km3VT6vtV5eufr0mek1rgV7ByoLBtQFr6wtVCuWFfevc1+1dT1gvWd+1YfqGnRs+FYmKrhTbF5cVf9go3HjlG4dvyr+Z3JS0qavEuWTPZtJm6ebeLZ5bDpaql+aXDm4N2dq0Dd9WtO319kXbL5fNKNu7g7ZDuaO/PLi8ZafJzs07P1SkVPRU+lQ27tLdtWHX+G7R7ht7vPY07NXbW7z3/T7JvttVAVVN1WbVZftJ+7P3P66Jqun4lvttXa1ObXHtxwPSA/0HIw6217nU1R3SPVRSj9Yr60cOxx++/p3vdy0NNg1VjZzG4iNwRHnk6fcJ3/ceDTradox7rOEH0x92HWcdL2pCmvKaRptTmvtbYlu6T8w+0dbq3nr8R9sfD5w0PFl5SvNUyWna6YLTk2fyz4ydlZ19fi753GDborZ752PO32oPb++6EHTh0kX/i+c7vDvOXPK4dPKy2+UTV7hXmq86X23qdOo8/pPTT8e7nLuarrlca7nuer21e2b36RueN87d9L158Rb/1tWeOT3dvfN6b/fF9/XfFt1+cif9zsu72Xcn7q28T7xf9EDtQdlD3YfVP1v+3Njv3H9qwHeg89HcR/cGhYPP/pH1jw9DBY+Zj8uGDYbrnjg+OTniP3L96fynQ89kzyaeF/6i/suuFxYvfvjV69fO0ZjRoZfyl5O/bXyl/erA6xmv28bCxh6+yXgzMV70VvvtwXfcdx3vo98PT+R8IH8o/2j5sfVT0Kf7kxmTk/8EA5jz/GMzLdsAAFMNaVRYdFhNTDpjb20uYWRvYmUueG1wAAAAAAA8P3hwYWNrZXQgYmVnaW49Iu+7vyIgaWQ9Ilc1TTBNcENlaGlIenJlU3pOVGN6a2M5ZCI/Pgo8eDp4bXBtZXRhIHhtbG5zOng9ImFkb2JlOm5zOm1ldGEvIiB4OnhtcHRrPSJBZG9iZSBYTVAgQ29yZSA1LjYtYzEzMiA3OS4xNTkyODQsIDIwMTYvMDQvMTktMTM6MTM6NDAgICAgICAgICI+CiAgIDxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+CiAgICAgIDxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSIiCiAgICAgICAgICAgIHhtbG5zOmRjPSJodHRwOi8vcHVybC5vcmcvZGMvZWxlbWVudHMvMS4xLyIKICAgICAgICAgICAgeG1sbnM6eG1wPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvIgogICAgICAgICAgICB4bWxuczp4bXBNTT0iaHR0cDovL25zLmFkb2JlLmNvbS94YXAvMS4wL21tLyIKICAgICAgICAgICAgeG1sbnM6c3RSZWY9Imh0dHA6Ly9ucy5hZG9iZS5jb20veGFwLzEuMC9zVHlwZS9SZXNvdXJjZVJlZiMiCiAgICAgICAgICAgIHhtbG5zOnN0RXZ0PSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvc1R5cGUvUmVzb3VyY2VFdmVudCMiCiAgICAgICAgICAgIHhtbG5zOmlsbHVzdHJhdG9yPSJodHRwOi8vbnMuYWRvYmUuY29tL2lsbHVzdHJhdG9yLzEuMC8iCiAgICAgICAgICAgIHhtbG5zOnhtcFRQZz0iaHR0cDovL25zLmFkb2JlLmNvbS94YXAvMS4wL3QvcGcvIgogICAgICAgICAgICB4bWxuczpzdERpbT0iaHR0cDovL25zLmFkb2JlLmNvbS94YXAvMS4wL3NUeXBlL0RpbWVuc2lvbnMjIgogICAgICAgICAgICB4bWxuczp4bXBHPSJodHRwOi8vbnMuYWRvYmUuY29tL3hhcC8xLjAvZy8iCiAgICAgICAgICAgIHhtbG5zOnBkZj0iaHR0cDovL25zLmFkb2JlLmNvbS9wZGYvMS4zLyIKICAgICAgICAgICAgeG1sbnM6cGhvdG9zaG9wPSJodHRwOi8vbnMuYWRvYmUuY29tL3Bob3Rvc2hvcC8xLjAvIgogICAgICAgICAgICB4bWxuczp0aWZmPSJodHRwOi8vbnMuYWRvYmUuY29tL3RpZmYvMS4wLyIK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
DEPARTMENT OF ACCOUNTING AND FINANCE - KALAMATA
Ε-mail: stefanos (at) uop (dot) gr
Τηλέφωνο: 27210-45-301
Short CV
Stefanos Giakoumatos is Professor at the Department of Accounting and Finance of the University of Peloponnese, where he teaches Statistics, Quantitative Methods, Financial Derivatives and Decision Making at undergraduate and postgraduate level. He obtained his degrees (Bachelor, Master and Ph.D.) from the Department of Statistics in Athens University of Economics and Business. In the past, Prof. Giakoumatos has been employed as Statistical Analyst in private sector (Intralot SA, TNS Metrisis) and in public sector (EL.STAT), he was researcher in European research programs and he is member of research committee of ILO (International Labor Organization).
His research interests, include Data Modelling in Finance and Social Silences, Markov Chain Monte Carlo Methods and Time Series Analysis.
Science Interest:
Data Modelling in Finance and Social Silences, Markov Chain Monte Carlo Methods, Decision making under uncertainty, and Time Series Analysis.