Rent pricing decision support mathematical model for finance leases under effective risks

Abstract

Nowadays, leasing has become an increasingly important and popular method for equipment acquisition. But, because of the rent pricing difficulties and some risks that affect the lessor and lessee's decision making, there are many people that still tend to buy equipment instead of lease it. In this paper we explore how risk can affect the leasing issue support mathematical model. For this purpose, we consider three types of risk; Credit risk, Transaction risk and Risk based pricing. In particular, our focus was on how to make decision about rent pricing in a leasing problem with different customers, various quality levels and different pricing methods. Finally, the mathematical model has been solved by Genetic Algorithm that is a search heuristic to optimize the problem. This algorithm was coded in MATLAB ® R2012a to provide the best set of results.

A Generalised Model of Ground Lease Pricing

“…Pope et al [31] investigated the risk related to a leasehold property from the investor's point of view. A similar topic was investigated by Rabbani et al [32]. Sevelka [33] studied the influence of the rent reset clause on the valuation in the ground lease problem.…”

A Nexus Between Financial Leverage and Performance of Textile Sector of Pakistan

“…Capital structure theories as pecking order theory, tradeoff theory and agency theories were initially developed to describe capital structure and characteristics of large firms (Daskalakis and Thanou, 2010). Extant of studies probed out the impact of FL on FP (Gweji and Karanja, 2014;Mwangi et al, 2014;Laurent, 2002) and also in Pakistan (Tauseef et al, 2015;Rabbani et al, 2015;Rehman, 2013) but there is a scarcity of findings in textile sector of Pakistan.…”

“…The outcomes of study revealed that ROA is negatively and significantly connected with tangibility, Size and debt to equity ratio (DER). Rabbani et al, (2015) conducted a research to investigate the FL effect on firm's performance in Pakistan. The study used the secondary data of 10 selected companies from cement sector and service sector as a sample over the period of 2006 to 2012, FL (FL) was used as dependent variable and size, profitability (ROA) and Growth of the firms (FG) selected as independent variables.…”