RP94-217 No. 18 Use of Crop Futures and Options by the Nontrader

Crop producers make a number of decisions that are market related. They may be categorized as financial decisions, production decisions, or marketing decisions. All three decisions depend on what prices are likely to be at some specific time in the future. The marketing decisions is complex. This research publication discusses the number of alternatives that are available even for the producer who does not directly buy or sell futures or options contracts.

Firm Market Performance and Volatility in a National Real Estate Sector

We present empirical evidence using daily data for stock prices for 17 real estate companies traded in the Sao Paulo, Brazil stock exchange. from August 26, 2006 to March 31, 2010. We use the U.S. house price bubble, financial crisis and risk measures to instrument for momentums and reversals in the domestic real estate sector. We find evidence of conditional premium persistence and conditional volatility persistence in the market. We find that the conditional risk-return relationship in the sector is consistent with the prospect theory of risk attitudes in this period. Certain companies seem to be operating on a perceived potential industry return above the target, while most others are below the target, and the whole sector is below target on average. (C) 2011 Elsevier Inc. All rights reserved.

Forward implied volatility expansions in LSV models

In this work we address the problem of finding formulas for efficient and reliable analytical approximation for the calculation of forward implied volatility in LSV models, a problem which is reduced to the calculation of option prices as an expansion of the price of the same financial asset in a Black-Scholes dynamic. Our approach involves an expansion of the differential operator, whose solution represents the price in local stochastic volatility dynamics. Further calculations then allow to obtain an expansion of the implied volatility without the aid of any special function or expensive from the computational point of view, in order to obtain explicit formulas fast to calculate but also as accurate as possible.

Pricing in stochastic-local volatility models with default

In recent years is becoming increasingly important to handle credit risk. Credit risk is the risk associated with the possibility of bankruptcy. More precisely, if a derivative provides for a payment at cert time T but before that time the counterparty defaults, at maturity the payment cannot be effectively performed, so the owner of the contract loses it entirely or a part of it. It means that the payoff of the derivative, and consequently its price, depends on the underlying of the basic derivative and on the risk of bankruptcy of the counterparty. To value and to hedge credit risk in a consistent way, one needs to develop a quantitative model. We have studied analytical approximation formulas and numerical methods such as Monte Carlo method in order to calculate the price of a bond. We have illustrated how to obtain fast and accurate pricing approximations by expanding the drift and diffusion as a Taylor series and we have compared the second and third order approximation of the Bond and Call price with an accurate Monte Carlo simulation. We have analysed JDCEV model with constant or stochastic interest rate. We have provided numerical examples that illustrate the effectiveness and versatility of our methods. We have used Wolfram Mathematica and Matlab.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Target Price Accuracy

This study analyzes the accuracy of forecasted target prices within analysts’ reports. We compute a measure for target price forecast accuracy that evaluates the ability of analysts to exactly forecast the ex-ante (unknown) 12-month stock price. Furthermore, we determine factors that explain this accuracy. Target price accuracy is negatively related to analyst-specific optimism and stock-specific risk (measured by volatility and price-to-book ratio). However, target price accuracy is positively related to the level of detail of each report, company size and the reputation of the investment bank. The potential conflicts of interests between an analyst and a covered company do not bias forecast accuracy.

Live Cattle Futures and Options: How Have They Done?

Futures did reduce price risk. Hedging produced a higher minimum return and higher return at the 25th percentile (75% of the returns are better than this figure) than did the cash market. The 50th percentile, or median return, was higher for yearlings in the cash market than hedged cattle, and the calves had mixed results. Although the differences are not great, there have been months when the option strategies performed better than cash or futures, (i.e., January–April and September–October), and there are months when they did not fare well (i.e., June–August).

Analysis of the Iberian Power Forward Price Formation

The price formation of the Iberian Energy Derivatives Market-the power futures market-starting in July 2006, is assessed until November 2011, through the evolution of the difference between forward and spot prices in the delivery period (“ex-post forward risk premium”) and the comparison with the forward generation costs from natural gas (“clean spark spread”). The premium tends to be positive in all existing mechanisms (futures, Over-the-Counter and auctions for catering part of the last resort supplies). Since year 2011, the values are smaller due to regulatorily recognized prices for coal power plants. The power futures are strongly correlated with European gas prices. The spreads built with prompt contracts tend also to be positive. The biggest ones are for the month contract, followed by the quarter contract and then by the year contract. Therefore, gas fired generation companies can maximize profits trading with contracts of shorter maturity.

Modelling and testing volatility spillovers in oil and financial markets for USA, UK and China

The primary purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely UK and USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in UK and USA. The paper will also analyze the Chinese financial markets, where the data are more recent. The empirical analysis will be based on the diagonal BEKK model, from which the conditional covariances will be used for testing co-volatility spillovers, and policy recommendations. Based on these results, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

An econometric analysis of ETF and ETF futures in financial and energy markets using generated regressors

It is well known that that there is an intrinsic link between the financial and energy sectors, which can be analyzed through their spillover effects, which are measures of how the shocks to returns in different assets affect each other’s subsequent volatility in both spot and futures markets. Financial derivatives, which are not only highly representative of the underlying indices but can also be traded on both the spot and futures markets, include Exchange Traded Funds (ETFs), which is a tradable spot index whose aim is to replicate the return of an underlying benchmark index. When ETF futures are not available to examine spillover effects, “generated regressors” may be used to construct both Financial ETF futures and Energy ETF futures. The purpose of the paper is to investigate the covolatility spillovers within and across the US energy and financial sectors in both spot and futures markets, by using “generated regressors” and a multivariate conditional volatility model, namely Diagonal BEKK. The daily data used are from 1998/12/23 to 2016/4/22. The data set is analyzed in its entirety, and also subdivided into three subset time periods. The empirical results show there is a significant relationship between the Financial ETF and Energy ETF in the spot and futures markets. Therefore, financial and energy ETFs are suitable for constructing a financial portfolio from an optimal risk management perspective, and also for dynamic hedging purposes.

Analysis of hedging and other operations in wool and wool top futures /

"Up-dates a similar report, Price risks for wool and wool products, and means of reducing them, based on data for the 8 years 1947-54, and published in 1957, as U.S. Dept. of Agriculture Technical bulletin no.1163."

Price risks for cotton and cotton products and means of reducing them /

"Updates Technical bulletin no. 602, Relation of cotton prices to prices of futures, contracts, and protection afforded by trading in futures."

A note on execution costs for stock index futures: Information versus liquidity effects

This paper examines execution costs and the impact of trade size for stock index futures using price-volume transaction data from the London International Financial Futures and Options Exchange. Consistent with Subrahmanyam [Rev. Financ. Stud. 4 (1991) 11] we find that effective half spreads in the stock index futures market are small compared to stock markets, and that trades in stock index futures have only a small permanent price impact. This result is important as it helps to better understand the success of equity index products such as index futures and Exchange Traded Funds. We also find that there is no asymmetry in the post-trade price reaction between purchases and sales for stock index futures across various trade sizes. This result is consistent with the conjecture in Chan and Lakonishok [J. Financ. Econ. 33 (1993) 173] that the asymmetry surrounding block trades in stock markets is due to the high cost of short selling and the general reluctance of traders to short sell on stock markets. (C) 2004 Elsevier B.V. All rights reserved.

Canonical valuation of options in the presence of stochastic volatility

Proposed by M. Stutzer (1996), canonical valuation is a new method for valuing derivative securities under the risk-neutral framework. It is non-parametric, simple to apply, and, unlike many alternative approaches, does not require any option data. Although canonical valuation has great potential, its applicability in realistic scenarios has not yet been widely tested. This article documents the ability of canonical valuation to price derivatives in a number of settings. In a constant-volatility world, canonical estimates of option prices struggle to match a Black-Scholes estimate based on historical volatility. However, in a more realistic stochastic-volatility setting, canonical valuation outperforms the Black-Scholes model. As the volatility generating process becomes further removed from the constant-volatility world, the relative performance edge of canonical valuation is more evident. In general, the results are encouraging that canonical valuation is a useful technique for valuing derivatives. (C) 2005 Wiley Periodicals, Inc.

Stock repurchases and treasury share sales: Do they stabilize price and enhance liquidity?

The article studies the impact of a firm’s trading in its own shares on the volatility and market liquidity of the firm’s stock in the Italian stock market. In the study, both stock repurchases and treasury share sales executed on the open market are defined as trading in own shares. The study finds that Italian firms can reduce the volatility of their stock and boost market liquidity by trading their own shares.