State price density estimation with an application to the recovery theorem

This article introduces a model to estimate the risk-neutral density of stock prices derived from option prices. To estimate a complete risk-neutral density, current estimation techniques use a single mathematical model to interpolate option prices on two dimensions: strike price and time-to-maturity. Instead, this model uses B-splines with at-the-money knots for the strike price interpolation and a mixed lognormal function that depends on the option expiration horizon for the time-to-maturity interpolation. The results of this “hybrid” methodology are significantly better than other risk-neutral density extrapolation methods when applied to the recovery theorem.

Assigning of land location and land price to land parcel using ArcGIS engine

Assigning a state price to each land parcel is a frequent and yet important task in the state management of land parcels. Land price is issued for each street. For each street, land price is divided according to level of location 1, 2, 3 and 4. Parcel is assigned to which location level depending on its walking distance to nearest street, and passed minimum alley’s width, etc. The task of valuing land parcels is cumbersome because the number of land parcels to be priced is huge. To alleviate this burden for government staff, a step by step processing model is developed to automatically determine the location level of a particular parcel. Using ArcGIS Engine library and VB.NET programming language, the steps in the proposed model are built into functions in a specialized module for land valuation. Experiment in assigning location level and land prices of Tam Hiep ward, Bien Hoa city, Dong Nai province shows that 91,73% of parcels are assigned the same location level as the location on the issued land location map. The experiment demonstrates the effectiveness and correctness of the proposed model in automatically determining location levels and corresponding prices of land parcels.

The State Price Density Implied by Crude Oil Futures and Option Prices

Both large oil price increases and decreases are associated with deteriorating economic conditions. The projection of the state price density (SPD) onto oil returns estimated from oil futures and option prices displays a U-shaped pattern. Because investors assign high state prices to large negative and large positive oil returns, the U-shaped SPD may steepen in either tail when economic conditions deteriorate. The positive return region of the SPD is more closely related to economic conditions. The oil SPD contains information about economic conditions and future security returns that is distinct from the information in the stock index SPD.

Nonparametric Estimation of Fractional Option Pricing Model

The establishment of the fractional Black–Scholes option pricing model is under a major condition with the normal distribution for the state price density (SPD) function. However, the fractional Brownian motion is deemed to not be martingale with a long memory effect of the underlying asset, so that the estimation of the state price density (SPD) function is far from simple. This paper proposes a convenient approach to get the fractional option pricing model by changing variables. Further, the option price is transformed as the integral function of the cumulative density function (CDF), so it is not necessary to estimate the distribution function individually by complex approaches. Finally, it encourages to estimate the fractional option pricing model by the way of nonparametric regression and makes empirical analysis with the traded 50 ETF option data in Shanghai Stock Exchange (SSE).

Price Stickiness under Stochastic Demand

This study develops a two-period model in which the manufacturer determines a price floor and sets production output prior to resolution of uncertainty. The closer the distance between the minimum price and the high-demand-state price, the higher the degree of price rigidity. Solving for the minimum resale price and production output, the model indicates that asymmetric price transmission could be a characteristic of competitive markets. The retail price in a highly concentrated retail market might be lower than that in a retail market with fierce competition. The relationship between price adjustments and the market competition suggests that the reason underlying price rigidity should be considered while formulating the antitrust and monetary policies.