光華講壇——社會(huì)名流與企業(yè)家論壇第6682期
主題：全球勝任力講座（第23期）Deep Learning in Quantitative Finance 金融智能：量化金融中的深度學(xué)習(xí)
主講人：Imperial College London Panos Parpas
主持人：特拉華數(shù)據(jù)科學(xué)學(xué)院 余欣
時(shí)間：11月24日 21:00
舉辦地點(diǎn)：https://us06web.zoom.us/j/81921528531 會(huì)議號(hào): 819 2152 8531
主辦單位：特拉華數(shù)據(jù)科學(xué)學(xué)院 科研處
主講人簡(jiǎn)介：
Dr. Panos Parpas is a Professor of Computational Optimisation at the Department of Computing, Imperial College London. Before joining Imperial College, he was a postdoctoral fellow at MIT (2009-2011). Before that, he was a quantitative associate at Credit-Suisse (2007-2009). He is interested in the development and analysis of algorithms for large scale optimisation problems. He is also interested in exploiting the structure of large scale models arising in applications. His research has been published in leading journals such as SIAM Journal of Optimization, SIAM Journal of Scientific computing, SIAM Journal on Mathematical Finance among others. He has presented his research in several meetings, conferences and seminars and is frequently involved in the organisation of specialist workshops and meetings. He is an associate editor for two journals and was awarded a JP Morgan Faculty Award in 2019 and 2021.
Panos Parpas博士現(xiàn)任倫敦帝國(guó)理工學(xué)院計(jì)算系教授。在加入帝國(guó)理工學(xué)院之前，Panos Parpas是麻省理工學(xué)院的博士后(2009-2011)。在此之前，他是瑞士信貸(credit suisse)的量化研究員(2007-2009)。教授研究興趣聚焦大規(guī)模優(yōu)化問(wèn)題的算法開(kāi)發(fā)和分析、應(yīng)用中出現(xiàn)的大型模型結(jié)構(gòu)。他的研究發(fā)表在SIAM Journal of Optimization, SIAM Journal of Scientific computing, SIAM Journal on Mathematical Finance等頂級(jí)國(guó)際學(xué)術(shù)期刊上。教授同時(shí)是兩家期刊的副主編，并于2019年和2021年獲得摩根大通學(xué)院獎(jiǎng)。
內(nèi)容簡(jiǎn)介：
In the financial industry in the era of big data, financial innovations represented by quantitative trading, risk control and management, and robo-advisors are surging, and the gain of innovative results is inseparable from the development of practical programming software. Among many programming languages, Matlab, C++, and Python are the most widely used. In this seminar you will have the opportunity to be introduced to the fundamental models and mathematical theories. In particular, in this module you will have the opportunity to learn to understand the time value of money, price derivatives using arbitrage pricing theory, optimally design investment strategies that trade-off risk with rewards, and use efficient numerical methods to solve optimisation models and simulate stochastic processes.
在大數(shù)據(jù)和AI時(shí)代的金融行業(yè)，以量化交易、風(fēng)險(xiǎn)控制與管理、AI顧問(wèn)為代表的智能金融創(chuàng)新方興未艾，創(chuàng)新成果的獲得離不開(kāi)實(shí)用編程軟件的開(kāi)發(fā)。在許多機(jī)器學(xué)習(xí)算法編程語(yǔ)言中，Matlab、C++和Python是使用最廣泛的。在本次講座中將有機(jī)會(huì)了解基本模型和數(shù)學(xué)理論，了解金錢(qián)的時(shí)間價(jià)值、基于套利定價(jià)理論的價(jià)格衍生品、在風(fēng)險(xiǎn)與回報(bào)之間進(jìn)行權(quán)衡以?xún)?yōu)化設(shè)計(jì)投資策略、以及使用有效的數(shù)值方法求解優(yōu)化模型并模擬隨機(jī)過(guò)程。
