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RISS 인기검색어
- 검색키워드
- 저자 : Liao Wang (검색결과 2 건)
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Impact of urban forests on housing prices in Nanjing
Liao Wang 서울시립대학교 국제도시과학대학원 2022 국내석사
This study conducts exploratory research on the impact of urban forests on housing prices to find out the relationship between housing prices and distance from the urban forest, so that to announce the value of urban forestry. The study takes Nanjing city as the case study, applies the hedonic prices method as the research guide, utilizes GIS technology as the tool to measure the distance, and the multiple linear regression method to explore the impact of urban forests on urban housing prices. During the study, all the residential areas (totally 125 units) in the south of Zhongshan scenic spot in Nanjing city within a 3km straight line distance from the mountain are chosen. The factors related to housing prices such as housing age, bus, subway, hospital, school, distance to CBD, and distance to the urban forest are considered. The result of the study shows that the effect of urban forests on housing prices is statistically significant. 1km far away from the urban forest, around 3375.80 Yuan/m2 will be lost. Thus, urban forests can bring obvious value and benefits to the city, so that to affect housing value and price. 본 연구는 도시숲이 주택가격에 미치는 영향에 대한 탐색적 연구를 통해 주택가격과 도시숲과의 거리 간 관계를 규명하고 도시임업의 가치를 알리고자 한다. 본 연구는 난징시를 사례 연구로 채택했고 헤도닉 가격방법(Hedonic Prices Method)을 연구 지침으로 적용했으며, 거리 측정 도구로 GIS 기술을 활용하고 도시숲이 도시 주택 가격에 미치는 영향을 파악하기 위해 다중 선형 회귀 방법을 사용했다. 연구가 진행되는 동안 산에서 직선거리 3km 이내 난징시 중산(Zhongshan) 경승지 남쪽에 위치한 모든 주거 지역(총 125개 주택)이 선택되었다. 주택연식, 버스, 지하철, 병원, 학교, 도심까지의 거리, 도시숲과의 거리 등 주택가격과 관련된 요인이 고려되었다. 연구 결과, 도시숲이 주택가격에 미치는 영향은 통계적으로 유의한 것으로 나타났다. 도시숲에서 1km 떨어진 곳의 경우, 약 3375.80 위안/m2가 손실되는 것으로 파악되었다. 따라서 도시숲은 도시에 명백한 가치와 이점을 가져다 줄 수 있으므로 주택 가치와 가격에 영향을 미칠 것으로 판단된다.
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Production Planning with Risk Hedging
Wang, Liao Columbia University ProQuest Dissertations & These 2017 해외박사(DDOD)
We study production planning integrated with risk hedging in a continuous-time stochastic setting. The (cumulative) demand process is modeled as a sum of two components: the demand rate is a general function in a tradable financial asset (which follows another stochastic process), and the noise component follows an independent Brownian motion. There are two decisions: a production quantity decision at the beginning of the planning horizon, and a dynamic hedging strategy throughout the horizon. Thus, the total terminal wealth has two components: production payoff, and profit/loss from the hedging strategy. The production quantity and hedging strategy are jointly optimized under the mean-variance and the shortfall criteria. For each risk objective, we derive the optimal hedging strategy in closed form and express the associated minimum risk as a function of the production quantity, the latter is then further optimized. With both production and hedging (jointly) optimized, we provide a complete characterization of the efficient frontier. By quantifying the risk reduction contributed by the hedging strategy, we demonstrate its substantial improvement over a production-only decision. To derive the mean-variance hedging strategy, we use a numeraire-based approach, and the derived optimal strategy consists of a risk mitigation component and an investment component. For the shortfall hedging, a convex duality method is used, and the optimal strategy takes the form of a put option and a digital option, which combine to close the gap from the target left by production (only). Furthermore, we extend the models and results by allowing multiple products, with demand rates depending on multiple assets. We also make extension by allowing the asset price to follow various stochastic processes (other than the geometric Brownian motion).
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