Day trading profit maximization with multi-task learning and technical analysis
نویسندگان
چکیده
منابع مشابه
Sample Complexity of Multi-Item Profit Maximization
We study the design of pricing mechanisms and auctions when the mechanism designer does not know the distribution of buyers’ values. Instead the mechanism designer receives a set of samples from this distribution and his goal is to use the sample to design a pricing mechanism or auction with high expected profit. We provide generalization guarantees which bound the difference between average pr...
متن کاملProfit Maximization Based on Customer Satisfaction Level in a Multi- Layer Multi-Product Supply Chain
This paper concerns with a mathematical model considering customer satisfaction requirements in a supply chain. The model tradeoffs the supply chain ability to fulfill the customers’ requirements and the limited budget in a variety of production phases. The decisions made here help to determine the profit provider price and economic quantity while the effective supplier and priori requireme...
متن کاملProfit maximization with bankruptcy and variable scale
In a diffusion model of an enterprise with variable scale, conditions are given for the maximization of ‘profit’ (expected total discounted withdrawals) to lead to bankruptcy almost surely. The optimal withdrawal policy is an ‘overflow policy’: the withdrawal rate is zero if the asset level is below a ‘barrier’, and equal to the maximum rate if the asset level is at least equal to the barrier. ...
متن کاملProfit Maximization Multi-item Inventory Models Considering Trade Credit and Sales Learning Curve
In this paper we consider a multi-item distribution channel subject to supplier’s credit period and retailer’s promotional effort with sales learning curve. We determine the retailer’s promotional effort for each item and the joint replenishment cycle in both decentralized and centralized decision models. We show that the profits for both parties increase under the centralized decision model wh...
متن کاملOnline Learning and Profit Maximization from Revealed Preferences
We consider the problem of learning from revealed preferences in an online setting. In our framework, each period a consumer buys an optimal bundle of goods from a merchant according to her (linear) utility function and current prices, subject to a budget constraint. The merchant observes only the purchased goods, and seeks to adapt prices to optimize his profits. We give an efficient algorithm...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Machine Learning
سال: 2014
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-014-5480-x