Impact of planning delays and other holding costs on housing affordability

Housing affordability is gaining increasing prominence in the Australian socioeconomic landscape, despite strong economic growth and prosperity. It is a major consideration for any new development. However, it is multi-dimensional, has many facets, is complex and interwoven. One factor widely held to impact housing affordability is holding costs. Although it is only one contributor, the nature and extent of its impact requires clarification. It is certainly more multifarious than simple calculation of the interest or opportunity cost of land holding. For example, preliminary analysis suggests that even small shifts in the regulatory assessment period can significantly affect housing affordability. Other costs associated with “holding” also impact housing affordability, however these costs cannot always be easily identified. Nevertheless it can be said that ultimately the real impact is felt by those whom can least afford it - new home buyers whom can be relatively easily pushed into the realms of un-affordability

Financial Hedging and Optimal Procurement Policies under Correlated Price and Demand

We consider a firm that procures an input commodity to produce an output commodity to sell to the end retailer. The retailer's demand for the output commodity is negatively correlated with the price of the output commodity. The firm can sell the output commodity to the retailer through a spot, forward or an index-based contract. Input and output commodity prices are also correlated and follow a joint stochastic price process. The firm maximizes shareholder value by jointly determining optimal procurement and hedging policies. We show that partial hedging dominates both perfect hedging and no-hedging when input price, output price, and demand are correlated. We characterize the optimal financial hedging and procurement policies as a function of the term structure of the commodity prices, the correlation between the input and output prices, and the firm's operating characteristics. In addition, our analysis illustrates that hedging is most beneficial when output price volatility is high and input price volatility is low. Our model is tested on futures price data for corn and ethanol from the Chicago Mercantile Exchange. © 2017 Production and Operations Management Societ

Understanding the Fine Structure of Electricity Prices.

This paper analyzes the special features of electricity spot prices derived from the physics of this commodity and from the economics of supply and demand in a market pool. Besides mean-reversion, a property they share with other commodities, power prices exhibit the unique feature of spikes in trajectories. We introduce a class of discontinuous processes exhibiting a jump-reversion component to properly represent these sharp upward moves shortly followed by drops of similar magnitude. Our approach allows to capture - for the first time to our knowledge - both the trajectorial and the statistical properties of electricity pool prices. The quality of the fitting is illustrated on a database of major US power markets.Energy price risk; Simulation; Calibration; Statistical estimations; Jump diffusions; Electricity prices;

Irreversibility, uncertainty, and investment

Includes bibliographical references (p. 58-62).Support provided by M.I.T.'s Center for Energy Policy Research, and by the World Bank. Support provided by the National Science Foundation. SES-8318990by Robert S. Pindyck

Irreversibility, uncertainty and investment

Most investment expenditures have two important characteristics. First, they are largely irreversible; the firm cannot disinvest, so the expenditures are sunk costs. Second, they can be delayed, allowing the firm to wait for new information about prices, costs, and other marketing conditions before committing resources. An emerging literature has shown that this has important implications for investment decisions, and for the determinants of investment spending. Irreversible investment is especially sensitive to risk, whether with respect to future cash flows, interest rates, or the ultimate cost of the investment. Thus if a policy goal is to stimulate investment, stability and credibility may be more important than tax incentives or interest rates. This paper presents some simple models of irreversible investment, and shows how optimal investment rules and the valuation of projects and firms can be obtained from contingent claims analysis, or alternatively from dynamic programming. It demonstrates some strengths and limitations of the methodology, and shows how the resulting investment rules depend on various parameters that come from the market environment. It also reviews a number of results and insights that have appeared in the literature recently, and discusses possible policy implications.Supported by the M.I.T.'s Center for Energy Policy Research and the World Bank. Supported by the National Science Foundation

A study on options hedge against purchase cost fluctuation in supply contracts.

He, Huifen.Thesis (M.Phil.)--Chinese University of Hong Kong, 2008.Includes bibliographical references (leaves 44-48).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Literature Review --- p.4Chapter 1.2.1 --- Supply Contracts under Price Uncertainty --- p.5Chapter 1.2.2 --- Dual Sourcing --- p.6Chapter 1.2.3 --- Risk Aversion in Inventory Management --- p.6Chapter 1.2.4 --- Hedging Operational Risk Using Financial Instruments --- p.7Chapter 1.2.5 --- Financial Literature --- p.9Chapter 1.3 --- Organization of the Thesis --- p.10Chapter 2 --- A Risk-Neutral Model --- p.12Chapter 2.1 --- Framework and Assumptions --- p.12Chapter 2.2 --- "Price, Forward and Convenience Yield" --- p.14Chapter 2.2.1 --- Stochastic Model of Price --- p.14Chapter 2.2.2 --- Marginal Convenience Yield --- p.16Chapter 2.3 --- Optimality Equations --- p.17Chapter 2.4 --- The Structure of the Optimal Policy --- p.21Chapter 2.4.1 --- One-period. Optimal Hedge Decision Rule --- p.21Chapter 2.4.2 --- One-period Optimal Orderings Decision Rule --- p.23Chapter 2.4.3 --- Optimal Policy --- p.24Chapter 3 --- A Risk-Averse Model --- p.28Chapter 3.1 --- Risk Aversion Modeling and Utility Function --- p.28Chapter 3.2 --- Multi-Period Inventory Modelling --- p.31Chapter 3.3 --- Exponential Utility Model --- p.33Chapter 3.4 --- Optimal Ordering and Hedging Policy for Multi-Period Problem --- p.37Chapter 4 --- Conclusion and Future Research --- p.40Bibliography --- p.44Chapter A --- Appendix --- p.49Chapter A.l --- Notation --- p.49Chapter A.2 --- K-Concavity --- p.5