scholarly journals From finance to ITS: traffic data fusion based on Markowitz' portfolio theory

2015 ◽  
Vol 50 (2) ◽  
pp. 145-164 ◽  
Author(s):  
Thorsten Neumann ◽  
Rüdiger Ebendt ◽  
Günter Kuhns
Keyword(s):  
Data Fusion ◽  
Portfolio Theory ◽  
Traffic Data ◽  
Markowitz Portfolio

scholarly journals Application of Markowitz Portfolio Theory by Building Optimal Portfolio on the US Stock Market

2017 ◽  
pp. 24-42
Author(s):  
Martin Širůček ◽  
Lukáš Křen
Keyword(s):  
Portfolio Theory ◽  
Capital Asset Pricing ◽  
Asset Pricing Model ◽  
Dow Jones Industrial Average ◽  
Markowitz Portfolio ◽  
The Us ◽  
Capm Model ◽  
Optimal Approach ◽  
Investment Portfolios ◽  
High Beta

This chapter is focused on building investment portfolios by using the Markowitz Portfolio Theory (MPT). Derivation based on the Capital Asset Pricing Model (CAPM) is used to calculate the weights of individual securities in portfolios. The calculated portfolios include a portfolio copying the benchmark made using the CAPM model, portfolio with low and high beta coefficients, and a random portfolio. Only stocks were selected for the examined sample from all the asset classes. Stocks in each portfolio are put together according to predefined criteria. All stocks were selected from Dow Jones Industrial Average (DJIA) index which serves as a benchmark, too. Portfolios were compared based on their risk and return profiles. The results of this work will provide general recommendations on the optimal approach to choose securities for an investor's portfolio.

Bus Efficiency Evaluation Method Based on Traffic Data and AVL Data Fusion

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Zhenning Dong ◽  
Caiyi Hu ◽  
Zhongwei Mao ◽  
Yuelong Su ◽  
Yi Zhao
Keyword(s):  
Data Fusion ◽  
Evaluation Method ◽  
Efficiency Evaluation ◽  
Traffic Data

scholarly journals Reliable Estimation of Urban Link Travel Time Using Multi-Sensor Data Fusion

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 267
Author(s):  
Yajuan Guo ◽  
Licai Yang
Keyword(s):  
Data Fusion ◽  
Travel Time ◽  
Sensor Data ◽  
License Plate ◽  
Traffic Data ◽  
Characteristic Analysis ◽  
Reliable Estimation ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Link Travel Time

Travel time is one of the most critical indexes to describe urban traffic operating states. How to obtain accurate and robust travel time estimates, so as to facilitate to make traffic control decision-making for administrators and trip-planning for travelers, is an urgent issue of wide concern. This paper proposes a reliable estimation method of urban link travel time using multi-sensor data fusion. Utilizing the characteristic analysis of each individual traffic sensor data, we first extract link travel time from license plate recognition data, geomagnetic detector data and floating car data, respectively, and find that their distribution patterns are similar and follow logarithmic normal distribution. Then, a support degree algorithm based on similarity function and a credibility algorithm based on membership function are developed, aiming to overcome the conflicts among multi-sensor traffic data and the uncertainties of single-sensor traffic data. The reliable fusion weights for each type of traffic sensor data are further determined by integrating the corresponding support degree with credibility. A case study was conducted using real-world data from a link of Jingshi Road in Jinan, China and demonstrated that the proposed method can effectively improve the accuracy and reliability of link travel time estimations in urban road systems.

Study on Data Fusion Model with Multi-Source Heterogeneous Traffic Data

ICTIS 2011 ◽  
2011 ◽  
Author(s):  
Feng-cui Qiu ◽  
En-jian Yao ◽  
Yang Yang ◽  
Xin Li ◽  
Yi Zhang
Keyword(s):  
Data Fusion ◽  
Heterogeneous Traffic ◽  
Traffic Data ◽  
Fusion Model
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