Deep learning has been widely applied in computer vision,natural language processing,and audio-visual recognition.The overwhelming success of deep learning as a data processing technique has sparked the interest of th...Deep learning has been widely applied in computer vision,natural language processing,and audio-visual recognition.The overwhelming success of deep learning as a data processing technique has sparked the interest of the research community.Given the proliferation of Fintech in recent years,the use of deep learning in finance and banking services has become prevalent.However,a detailed survey of the applications of deep lerning in finance and banking is lacking in the existing literature.This study surveys and analyzes the literature on the application of deep lerning models in the key finance and banking domains to provide a systematic evaluation of the model preprocessing,input data,and model evaluation.Finally,we discuss three aspects that could affect the outcomes of financial deep learning models.This study provides academics and practitioners with insight and direction on the state-of-the-art of the application of deep learning models in finance and banking.展开更多
The newsvendor problem has been applied in various business settings. It is often assumed that the decision variable, i.e., order-up-to level, has no impacts on the holding costs for average inventory cycled in a give...The newsvendor problem has been applied in various business settings. It is often assumed that the decision variable, i.e., order-up-to level, has no impacts on the holding costs for average inventory cycled in a given period, which is the difference between beginning and ending inventory levels on hand in that period. The average holding cost for this portion of inventory is conveniently and approximately calcutated as half the product of the unit holding cost and the expectation of the demand in one period if it is assumed that the inventory is approximately evenly consumed. It is a good approximation when the unit holding cost is significantly lower than the unit backorder cost as this optimal solution to inventory level is able to guarantee a low probability of understocking. However, if this condition does not hold, the approximation may deviate from the actual cost and cannot measure the expected holding cost for this portion of inventory. This paper examines the impact of the cycle stock holding cost on the newsvendor model and the conditions under which this portion of cost is not negligible.展开更多
基金Supports from BNU-HKBU United International College Research Grant under Grant R202026.
文摘Deep learning has been widely applied in computer vision,natural language processing,and audio-visual recognition.The overwhelming success of deep learning as a data processing technique has sparked the interest of the research community.Given the proliferation of Fintech in recent years,the use of deep learning in finance and banking services has become prevalent.However,a detailed survey of the applications of deep lerning in finance and banking is lacking in the existing literature.This study surveys and analyzes the literature on the application of deep lerning models in the key finance and banking domains to provide a systematic evaluation of the model preprocessing,input data,and model evaluation.Finally,we discuss three aspects that could affect the outcomes of financial deep learning models.This study provides academics and practitioners with insight and direction on the state-of-the-art of the application of deep learning models in finance and banking.
文摘The newsvendor problem has been applied in various business settings. It is often assumed that the decision variable, i.e., order-up-to level, has no impacts on the holding costs for average inventory cycled in a given period, which is the difference between beginning and ending inventory levels on hand in that period. The average holding cost for this portion of inventory is conveniently and approximately calcutated as half the product of the unit holding cost and the expectation of the demand in one period if it is assumed that the inventory is approximately evenly consumed. It is a good approximation when the unit holding cost is significantly lower than the unit backorder cost as this optimal solution to inventory level is able to guarantee a low probability of understocking. However, if this condition does not hold, the approximation may deviate from the actual cost and cannot measure the expected holding cost for this portion of inventory. This paper examines the impact of the cycle stock holding cost on the newsvendor model and the conditions under which this portion of cost is not negligible.
