Trading Frictions and House Price Dynamics

We model liquidity in housing markets. The model provides a simple characterization for the joint process of prices, sales, and inventory. We compare the implications of the model to certain properties of housing markets. The model can generate the large price changes and the positive correlation between prices and sales that we see in the data. Unlike the data, prices are negatively autocorrelated and high inventory predicts price appreciation. We investigate several amendments to the model. Informational frictions show promise.     

An Analysis of Changes in Specialist Inventories and Quotations

We develop a dynamic model of market making incorporating inventory and information effects. The market maker is both a dealer and an investor, quoting prices that induce mean reversion in inventory toward targets determined by portfolio considerations. We test the model with inventory data from a New York Stock Exchange specialist. Specialist inventories exhibit slow mean reversion, with a half-life of over 49 days, suggesting weak inventory effects. However, after controlling for shifts in desired inventories, the half-life falls to 7.3 days. Further, quote revisions are negatively related to specialist trades and are positively related to the information conveyed by order imbalances.     

Life in the pits: competitive market making and inventory control

We use futures transaction data to investigate cross-sectionalrelationships between market-maker inventory positions and tradeactivity. The investigating documents strongly that traderscontrol inventory throughout the trading day. Despite this evidenceof inventory management, typical inventory control models predictthat market-maker reservation prices are negatively influencedby inventory. Surprisingly, our evidence shows, as a strongand consistent empirical regularity, that correlations betweeninventory and reservation prices are positive. We interpretthe evidence as consistent with active position takeing by futuresmarket floor traders.     

Inventories and the automobile market

This article studies the within‐model‐year pricing, production, and inventory management of new automobiles. Using new monthly data on U.S. transaction prices, we document that, for the typical vehicle, prices fall over the model year at a 9.0% annual rate. Concurrently, both sales and inventories are hump shaped. To explain these time series, we formulate an industry model for new automobiles in which inventory and pricing decisions are made simultaneously. The model predicts that automakers' build‐to‐stock inventory management policy substantially influences the time series of prices and sales, accounting for four tenths of the price decline observed over the model year.     

Sales and consumer inventory

Temporary price reductions (sales) are common for many goods and naturally result in a large increase in the quantity sold. We explore whether the data support the hypothesis that these increases are, at least partly, due to demand anticipation: at low prices, consumers store for future consumption. This effect, if present, has broad economic implications. We test the predictions of an inventory model using scanner data with two years of household purchases. The results are consistent with an inventory model and suggest that static demand estimates may overestimate price sensitivity.     

An Examination of Changes in Specialists' Posted Price Schedules

New York Stock Exchange specialists disseminate informationto market participants by displaying price schedules consistingof bid prices, ask prices, bid depths, and ask depths. We examinehow specialists update these price schedules in a simultaneousequations model. We find that changes in the best prices anddepths on the limit order book have a significant impact onthe posted price schedule, while the effects of transactionsand order activity are secondary. Furthermore, we show thatspecialists revise prices and depths differently, but find noevidence that they revise the price schedule in response tochanges in inventory.     

Trade wedges,inventories, and international business cycles

The large, persistent fluctuations in international trade that cannot be explained in standard models by changes in expenditures and relative prices are often attributed to trade wedges. We show that these trade wedges can reflect the decisions of importers to change their inventory holdings. We find that a two-country model of international business cycles with an inventory management decision can generate trade flows and wedges consistent with the data. Moreover, matching trade flows alters the international transmission of business cycles. Specifically, real net exports become countercyclical and consumption is less correlated across countries than in standard models. We also show that ignoring inventories as a source of trade wedges substantially overstates the role of trade wedges in business cycle fluctuations.     

Oil Futures Prices in a Production Economy with Investment Constraints

We document a new stylized fact, that the relationship between the volatility of oil futures prices and the slope of the forward curve is nonmonotone and has a V-shape. This pattern cannot be generated by standard models that emphasize storage. We develop an equilibrium model of oil production in which investment is irreversible and capacity constrained. Investment constraints affect firms' investment decisions and imply that the supply elasticity changes over time. Since demand shocks must be absorbed by changes in prices or changes in supply, time-varying supply elasticity results in time-varying volatility of futures prices. Estimating this model, we show it is quantitatively consistent with the V-shape relationship between the volatility of futures prices and the slope of the forward curve.     

Pricing Foreign Exchange Options Under Intervention by Absorption Modeling

We consider option pricing for a foreign exchange (FX) rate where interventions by an authority may take place when the rate approaches to a certain level at the down side. We formulate the forward FX model by a diffusion process which is stopped by a hitting time of an absorption boundary. Moreover, for a deterministic volatility case with a moving absorption whose level is described by an ordinary differential equation, we obtain closed-form formulas for prices of a European put option and a digital option, and Greeks of the put option. Furthermore, we show an extension of the pricing formula to the case where the intervention level is unknown. In numerical examples, we show option prices for different strikes for the absorption model and the extended model. We compare the model prices with the market prices for EURCHF options traded before January 2015 with the absorption model, and also show experiments of the extended model as an application to the pricing under uncertain views on the intervention.     

Theory of Storage and the Pricing of Commodity Claims

We extend the literature on commodity pricing by incorporating a link between the spread of forward prices and spot price volatility suggested by the theory of storage. Our model has closed form solutions that are generalizations of the two-factor model of Gibson–Schwartz (1990). We estimate the model on daily copper spot and forward prices using the Kalman filter methodology. Our findings confirm the link between the forward spread and volatility, but also show that the Gibson–Schwartz (1990) model prices forward contracts almost as well. In the pricing of option contracts, however, there are significant differences between the models.     

Should we Fear the Shadow? House Prices,Shadow Inventory,and the Nascent Housing Recovery

Although a broad-based increase in house prices has been observed over the past year, not everyone is convinced the rise of house prices will persist and lead to a steady recovery of the economy. The main reason for this skepticism is uncertainty about the “shadow inventory”: foreclosed homes held by investors or as REOs, which have not yet hit the market but likely will as market prices rise. The volume of shadow inventory itself in local markets is largely unknown, as is its impact on the housing market. This study quantifies the size of the shadow inventory and investigates the spatial impact of the out-flow of shadow inventory. The scope of our study is a set of housing markets (AZ, CA, and FL) that vary in both their historic housing price volatility as well as institutional factors - such as foreclosure law statutes - that may influence the relationship between the shadow inventory and house price dynamics. To address the endogeneity that characterizes the spatial interaction of house prices and the out-flow of the shadow inventory, we utilize a simultaneous equation system of spatial autoregressions (SESSAR). The model is estimated using measures of the shadow inventory derived from DataQuick’s national transaction history database and county-level house price indices provided by Black Knight. Lastly, because our estimate - as well as all other existing estimates - of the shadow inventory relies upon string matching algorithms to identify entry into and exit out of REO status, we validate the accuracy of our measures of REOs using loss mitigation data from the OCC Mortgage Metrics database.     

Trading and Manipulation Around Seasoned Equity Offerings

We investigate the potential for manipulation due to the interaction between secondary market trading prior to a seasoned equity offering (SO) and the pricing of the offering. Informed traders acting strategically may attempt to manipulate offering prices by selling shares prior to the SO, and profit subsequently from lower prices in the offering. The model predicts increased selling prior to a SO, leading to increases in the market maker's inventory and temporary price decreases. Further, since manipulation conceals information, the ratio of temporary to permanent components of the price movements is predicted to increase.     

Oil convenience yields estimated under demand/supply shock

This paper extends the call option model of Milonas and Thomadakis (1997) to estimate oil convenience yields with futures prices. We define the business cycle of a seasonal commodity with demand/supply shocks and find that the convenience yield for crude oil exhibits seasonal behavior. The convenience yield for West Texas Intermediate (WTI) crude oil is the highest in the summer, while that for Brent crude oil is the highest in the winter. This implies that WTI crude oil is more sensitive to high summer demand and that Brent crude oil is more sensitive to shortages in winter supply. Convenience yields are negatively related to the inventory level of the underlying crude oil and positively related to interest rates due to the business cycle. We also show that convenience yields may explain price spread between WTI crude oil and Brent crude oil. Our computed convenience yields are consistent with Fama and French (1988) in that oil prices are more volatile than futures prices at low inventory level, verifying the Samuelson (1965) hypothesis that future prices are less variables than spot prices at lower inventory levels.

Pricing a class of exotic commodity options in a multi-factor jump-diffusion model

In a recent paper, Crosby introduced a multi-factor jump-diffusion model which would allow futures (or forward) commodity prices to be modelled in a way which captured empirically observed features of the commodity and commodity options markets. However, the model focused on modelling a single individual underlying commodity. In this paper, we investigate an extension of this model which would allow the prices of multiple commodities to be modelled simultaneously in a simple but realistic fashion. We then price a class of simple exotic options whose payoff depends on the difference (or ratio) between the prices of two different commodities (for example, spread options), or between the prices of two different (i.e. with different tenors) futures contracts on the same underlying commodity, or between the prices of a single futures contract as observed at two different calendar times (for example, forward start or cliquet options). We show that it is possible, using a Fourier transform-based algorithm, to derive a single unifying form for the prices of all these aforementioned exotic options and some of their generalizations. Although we focus on pricing options within the model of Crosby, most of our results would be applicable to other models where the relevant ‘extended’ characteristic function is available in analytical form.     

The Optimal Pricing Policy of a Monopolistic Marketmaker in the Equity Market

This paper presents a stochastic optimization model for marketmaking in security markets with a single dealer. Buy and sell orders are assumed to arrive at rates that are functions of the ask and bid prices. The dealer incurs both proportional and fixed transaction costs as well as portfolio costs. Methods of dynamic programming and semi-Markov Decision Processes are used to characterize optimal pricing policies and to perform sensitivity analysis. Both bid and ask prices are nonincreasing functions of the dealer's inventory. Spread is unrelated to inventory position but positively related to order size. Computational examples demonstrate various results.     

Spot price modeling and the valuation of electricity forward contracts: The role of demand and capacity

We propose a model where wholesale electricity prices are explained by two state variables: demand and capacity. We derive analytical expressions to price forward contracts and to calculate the forward premium. We apply our model to the PJM, England and Wales, and Nord Pool markets. Our empirical findings indicate that volatility of demand is seasonal and that the market price of demand risk is also seasonal and positive, both of which exert an upward (seasonal) pressure on the price of forward contracts. We assume that both volatility of capacity and the market price of capacity risk are constant and find that, depending on the market and period under study, it could either exert an upward or downward pressure on forward prices. In all markets we find that the forward premium exhibits a seasonal pattern. During the months of high volatility of demand, forward contracts trade at a premium. During months of low volatility of demand, forwards can either trade at a relatively small premium or, even in some cases, at a discount, i.e. they exhibit a negative forward premium.     

Electricity Forward Prices: A High-Frequency Empirical Analysis

We conduct an empirical analysis of forward prices in the PJM electricity market using a high‐frequency data set of hourly spot and day‐ahead forward prices. We find that there are significant risk premia in electricity forward prices. These premia vary systematically throughout the day and are directly related to economic risk factors, such as the volatility of unexpected changes in demand, spot prices, and total revenues. These results support the hypothesis that electricity forward prices in the Pennsylvania, New Jersey, and Maryland market are determined rationally by risk‐averse economic agents.     

Exploring the transmission mechanism of speculative and inventory arbitrage activity to commodity price volatility. Novel evidence for the US economy

In the realm of monetary policy, we explore the transmission mechanism that relates speculative activity, inventory arbitrage activity, and commodity price volatility. In this direction, an ARMA-GARCH model is adopted to test this transmission effect on seven commodities using weekly U.S. data for the period 2008:12 to 2018:6. The results suggest that inventory arbitrage activities transmit monetary policy's effect onto commodities by strengthening the effect of the real interest rate on commodities' prices; in the case of palladium and crude oil's price conditional variances however the opposite effect is established. Speculative activities transmit monetary policy's effect mainly on commodities by increasing the positive effect of the real interest rate on metals and crude oil's prices, and on palladium and crude oil's price conditional variances. Our results show that inventory arbitrage activities are negatively related with commodities' prices, whilst speculative activities are positively related with commodities' prices. The two activities appear to exert mixed effects on commodities' price conditional volatilities. Additional evidence indicates that the relationship between the real interest rate and commodities' prices is positive and significant when unconventional monetary policy is considered, whilst we find that the real interest rate does not have any significant impact on most commodities' price conditional volatilities.     

Business Cycles and the Behavior of Metals Prices

The theory of storage says that the marginal convenience yield on inventory falls at a decreasing rate as inventory increases. The authors test this hypothesis by examining the relative variation of spot and futures prices for metals. As the hypothesis implies, futures prices are less variable than spot prices when inventory is low, but spot and futures prices have similar variability when inventory is high. The theory of storage also explains inversions of “normal” futures-spot price relations around business-cycle peaks. Positive demand shocks around peaks reduce metal inventories and, as the theory predicts, generate large convenience yields and price inversions.     

The determinants of a cross market arbitrage opportunity: theory and evidence for the European bond market

This paper examines the determinants of cross-platform arbitrage profits. We develop a structural model that enables us to decompose the likelihood of an arbitrage opportunity into three distinct factors: the fixed cost to trade the opportunity, the level at which one of the platforms delays a price update and the impact of the order flow on the quoted prices (inventory and asymmetric information effects). We then investigate the predictions from the theoretical model for the European Bond market with the estimation of a probit model. Our main finding is that the results found in the empirical part corroborate strongly the predictions from the structural model. The event of a cross market arbitrage opportunity has a certain degree of predictability where an optimal ex ante scenario is represented by a low level of spreads on both platforms, a time of the day close to the end of trading hours and a high volume of trade.