April 3,2023

Using Variable Coefficient Model to Estimated Sailing Price

——COMAP Mathematical Contest in Modeling (MCM)

Completed in collaboration with Shuai Wu and Boxi Wang

About the process

In the Mathematical Contest in Modeling (MCM) in the United States, our team chose to develop a pricing model for the Hong Kong second-hand sailboat market. During the intense four-day competition, we gathered global data on second-hand sailboat prices. By integrating the strengths and weaknesses of machine learning and multiple regression methods, we constructed a comprehensive second-hand sailboat evaluation model. My primary responsibility was the development of this model, breaking down the pricing issue into key factors and isolating the brand impact as a separate coefficient. Using the Semi-parametric Model, we conducted an in-depth analysis of the actual conditions of sailboats, effectively mitigating the influence of brand premiums. Additionally, I managed data collection, the construction of the brand model, algorithm coding, and participated in the graphical design of the paper, ensuring the consistency and professionalism of our overall thesis.

Figure: The Overall Structure of the Article.

Abstract

Nowadays, with the increasing development of the world economy, sailing has been used by more and more people as a new way of entertainment, which makes the second-hand sailing market expand rapidly. To explore the pricing reasons for second- hand sailing boats in the market, we model the pricing of second-hand sailing boats.

Firstly, we get the factors that affect the price of sailboats, including sailboats’ pa- rameters and regional influences. Firstly, correlation analysis is carried out among various parameters. Finally, the LWL, draft, water, S.A., fuel, GDP, the number of har- bor, travel, and temperature index is selected as the index of model establishment, and regression analysis is carried out. It is obtained that LWL, draft, water, GDP, labor, and travel are roughly linear with it, and fuel, S.A., and temperature have a complex nonlinear relationship with price. Then, using the version parameter model, the model formula of price and parameter is obtained.

In the second question, we choose four indicators that can portray the influence of region on ship value and simulate them following the model of the first question to derive the differences in the influence of different regions on ship prices and select representative examples for analysis. In the third question, we collected data on sail- boat transactions in Hong Kong and tested the model using the second question, and found that the correction coefficients derived in the second question did not apply to prices in Hong Kong. By adjusting the correction coefficients, we obtain more accurate prediction results and based on this, we discuss the difference between Monohulled Sailboats and Catamarans regarding the regional impact.

Finally, we give some interesting facts and advise Hong Kong brokers about the sailing boat market.

Keywords: variable coefficient model; price estimating;region influence.

You could download this paper.