Testing Futures Market Efficiency and Optimal Hedge Ratio Estimation: Evidence from Futures and Options on RTS

This study investigates futures market efficiency and optimal hedge ratio estimation. First, cointegration between spot and futures prices is studied using Johansen method, with two different model specifications. If prices are found cointegrated, restrictions on cointegrating vector and adjustment coefficients are imposed, to account for unbiasedness, weak exogeneity and prediction hypothesis. Second, optimal hedge ratios are estimated using static OLS, and time-varying DVEC and CCC models. In-sample and out-of-sample results for one, two and five period ahead are reported. The futures used in thesis are RTS index, EUR/RUB exchange rate and Brent oil, traded in Futures and options on RTS.(FORTS) For in-sample period, data points were acquired from start of trading of each futures contract, RTS index from August 2005, EUR/RUB exchange rate March 2009 and Brent oil October 2008, lasting till end of May 2011. Out-of-sample period covers start of June 2011, till end of December 2011. Our results indicate that all three asset pairs, spot and futures, are cointegrated. We found RTS index futures to be unbiased predictor of spot price, mixed evidence for exchange rate, and for Brent oil futures unbiasedness was not supported. Weak exogeneity results for all pairs indicated spot price to lead in price discovery process. Prediction hypothesis, unbiasedness and weak exogeneity of futures, was rejected for all asset pairs. Variance reduction results varied between assets, in-sample in range of 40-85 percent and out-of sample in range of 40-96 percent. Differences between models were found small, except for Brent oil in which OLS clearly dominated. Out-of-sample results indicated exceptionally high variance reduction for RTS index, approximately 95 percent.

Razão ótima de hedge em função do horizonte de hedge e da periodicicidade dos dados : uma aplicação no mercado de boi gordo brasileiro

As observações relatadas por Myers e Thompson, em seu artigo “Generalized Optimal Hedge Ratio Estimation” de 1989, foram analisadas neste estudo utilizando o boi gordo como a commodity de interesse. Myers e Thompson, demonstraram teórica e empiricamente, ser inapropriado o uso do coeficiente angular da regressão simples, dos preços à vista sobre os preços futuros como forma de estimar a razão ótima de hedge. Porém, sob condições especiais, a regressão simples com a mudança dos preços resultou em valores plausíveis, próximos àqueles determinados por um modelo geral. Este modelo geral, foi desenvolvido com o intuito de estabelecer os parâmetros para comparar as diferentes abordagens na estimativa da razão ótima de hedge. O coeficiente angular da reta da regressão simples e a razão ótima de hedge tem definições similares, pois ambos são o resultado da divisão entre a matriz de covariância dos preços, à vista e futuros e a variância dos preços futuros. No entanto, na razão ótima de hedge estes valores refletem o momento condicional, enquanto que na regressão simples são valores não condicionais. O problema portanto, está em poder estimar a matriz condicional de covariância, entre os preços à vista e futuros e a variância condicional dos preços futuros, com as informações relevantes no momento da tomada de decisão do hedge. Neste estudo utilizou-se o modelo de cointegração com o termo de correção de erros, para simular o modelo geral. O Indicador ESALQ/BM&F foi utilizado como a série representativa dos preços à vista, enquanto que para os preços futuros, foram utilizados os valores do ajuste diário dos contratos de boi gordo, referentes ao primeiro e quarto vencimentos, negociados na Bolsa Mercantil e de Futuros - BM&F. Os objetivos do presente estudo foram: investigar se as observações feitas por Myers e Thompson eram válidas para o caso do boi gordo brasileiro, observar o efeito do horizonte de hedge sobre a razão ótima de hedge e o efeito da utilização das séries diárias e das séries semanais sobre a estimativa da razão ótima de hedge. Trabalhos anteriores realizados com as séries históricas dos preços do boi gordo, consideraram apenas os contratos referentes ao primeiro vencimento. Ampliar o horizonte de hedge é importante, uma vez que as atividades realizadas pelos agentes tomam mais do que 30 dias. Exemplo disto é a atividade de engorda do boi, que pode levar até 120 dias entre a compra do boi magro e a venda do boi gordo. Demonstrou-se neste estudo, que o uso das séries semanais, é o mais apropriado, dado a diminuição substancial da autocorrelação serial. Demonstrou-se também, que as regressões com as mudanças dos preços, resultaram em estimativas da razão de hedge próximas daquelas obtidas com o modelo geral e que estas diminuem com o aumento do horizonte de hedge.

A taxa ótima de hedge no mercado brasileiro do boi gordo: uma abordagem com BEKK, DCC e BEKK com dummies de safra e entressafra

Esta dissertação tem três objetivos. O primeiro é encontrar o melhor método para se calcular a taxa ótima de “hedge” no mercado brasileiro do boi gordo. Para isso, foram testados cinco modelos: BEKK, DCC de Tse e Tsui (2002), DCC de Engle e Sheppard (2001), BEKK com dummy de safra e BEKK com dummy de entressafra. O segundo é calcular o diferencial de razões de “hedge” entre a safra e entressafra, pois a taxa de “hedge” na entressafra deve ser maior devido a uma maior incerteza sobre um possível choque de oferta, o que afetaria negativamente os custos dos frigoríficos. O terceiro e último objetivo é desvendar o porquê da literatura brasileira de taxa ótima de “hedge” estar encontrando estimativas muito pequenas das taxas quando comparadas às realizadas no mercado. Conclui-se que os modelos DCC’s são os que, no geral, obtém um desempenho melhor pelo critério de redução de variância e aumento do índice de Sharpe e que a taxa de “hedge” na entressafra não deve ser maior que na safra. Nota-se também que a quebra da expectativa intertemporal com a mudança de contratos faz com que a variância da série dos retornos futuros aumente muito, diminuindo assim a taxa de “hedge”.

Eficiência e razão de hedge: uma análise dos mercados futuro brasileiros de boi, café, etanol, milho e soja

This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop

Eficiência e razão de hedge: uma análise dos mercados futuro brasileiros de boi, café, etanol, milho e soja

This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop

Eficiência e razão de hedge: uma análise dos mercados futuro brasileiros de boi, café, etanol, milho e soja

This research aims to investigate the Hedge Efficiency and Optimal Hedge Ratio for the future market of cattle, coffee, ethanol, corn and soybean. This paper uses the Optimal Hedge Ratio and Hedge Effectiveness through multivariate GARCH models with error correction, attempting to the possible phenomenon of Optimal Hedge Ratio differential during the crop and intercrop period. The Optimal Hedge Ratio must be bigger in the intercrop period due to the uncertainty related to a possible supply shock (LAZZARINI, 2010). Among the future contracts studied in this research, the coffee, ethanol and soybean contracts were not object of this phenomenon investigation, yet. Furthermore, the corn and ethanol contracts were not object of researches which deal with Dynamic Hedging Strategy. This paper distinguishes itself for including the GARCH model with error correction, which it was never considered when the possible Optimal Hedge Ratio differential during the crop and intercrop period were investigated. The commodities quotation were used as future price in the market future of BM&FBOVESPA and as spot market, the CEPEA index, in the period from May 2010 to June 2013 to cattle, coffee, ethanol and corn, and to August 2012 to soybean, with daily frequency. Similar results were achieved for all the commodities. There is a long term relationship among the spot market and future market, bicausality and the spot market and future market of cattle, coffee, ethanol and corn, and unicausality of the future price of soybean on spot price. The Optimal Hedge Ratio was estimated from three different strategies: linear regression by MQO, BEKK-GARCH diagonal model, and BEKK-GARCH diagonal with intercrop dummy. The MQO regression model, pointed out the Hedge inefficiency, taking into consideration that the Optimal Hedge presented was too low. The second model represents the strategy of dynamic hedge, which collected time variations in the Optimal Hedge. The last Hedge strategy did not detect Optimal Hedge Ratio differential between the crop and intercrop period, therefore, unlikely what they expected, the investor do not need increase his/her investment in the future market during the intercrop

Insider Trading and Real Investment

In this paper I analyze the effects of insider trading on real investmentand the insurance role of financial markets. There is a single entrepreneurwho, at a first stage, chooses the level of investment in a risky business.At the second stage, an asset with random payoff is issued and then the entrepreneurreceives some privileged information on the likely realization of productionreturn. At the third stage, trading occurs on the asset market, where theentrepreneur faces the aggregate demand coming from a continuum of rationaluniformed traders and some noise traders. I compare the equilibrium withinsider trading (when the entrepreneur trades on her inside information in theasset market) with the equilibrium in the same market without insider trading. Ifind that permitting insider trading tends to decrease the level of realinvestment. Moreover, the asset market is thinner and the entrepreneur's netsupply of the asset and the hedge ratio are lower, although the asset priceis more informative and volatile.

The Effectiveness of Currency Hedging Strategies. Case: Imatra Boards Business Unit of Stora Enso Corp.

Tutkimus tarkastelee vaihtoehtoisia termiinisuojaustrategioita metsäteollisuuden alan tulosyksikössä. Jälkitestauksen tarkoituksena on arvioida vaihtoehtoisten strategioiden tuloksellisuutta suojata case-yrityksen kassavirtoja seuraavan kolmen arviointikriteerin avulla: yksittäisten vieraan valuutan määräisten kassavirtojen vaihtelu; koko vieraan valuutan määräisen kassavirran vaihtelu; suojausvoitot ja -tappiot. Tutkimuksen teoreettinen viitekehys tarkastelee yrityksen päätöksentekoa, valuuttariskien suojausprosessia sekä esittelee yrityksen vaihtoehtoisia suojausstrategioita. Tutkimuksen empiirinen aineisto pohjautuu case- yrityksen historiallisiin myyntilukuihin ja on kerätty yrityksen tietojärjestelmästä. Muu tutkimuksessa käytetty dataon kerätty eri tietokannoista. Tutkimuksen tulokset osoittavat, että suojaaminen vähentää kassavirtojen vaihtelua. Suojaamisen taloudelliset tulokset ovat kuitenkin erittäin riippuvaisia valitusta suojausstrategiasta, joka voi johtaa merkittäviin suojausvoittoihin, mutta yhtä hyvin myos merkittäviin tappioihin. Johdon näkemykset ja riskitoleranssi määrittelevät mitä strategiaa yrityksessä tullaan viime kädessä noudattamaan.

Dynamic Hedging with Credit Default Swaps: Empirical Evidence from the European Monetary Union

This thesis investigates the effectiveness of time-varying hedging during the financial crisis of 2007 and the European Debt Crisis of 2010. In addition, the seven test economies are part of the European Monetary Union and these countries are in different economical states. Time-varying hedge ratio was constructed using conditional variances and correlations, which were created by using multivariate GARCH models. Here we have used three different underlying portfolios: national equity markets, government bond markets and the combination of these two. These underlying portfolios were hedged by using credit default swaps. Empirical part includes the in-sample and out-of-sample analysis, which are constructed by using constant and dynamic models. Moreover, almost in every case dynamic models outperform the constant ones in the determination of the hedge ratio. We could not find any statistically significant evidence to support the use of asymmetric dynamic conditional correlation model. In addition, our findings are in line with prior literature and support the use of time-varying hedge ratio. Finally, we found that in some cases credit default swaps are not suitable instruments for hedging and they act more as a speculative instrument.

Variance reduction properties of dynamic hedging models - empirical evidence from BRICS countries

This Master’s Thesis analyses the effectiveness of different hedging models on BRICS (Brazil, Russia, India, China, and South Africa) countries. Hedging performance is examined by comparing two different dynamic hedging models to conventional OLS regression based model. The dynamic hedging models being employed are Constant Conditional Correlation (CCC) GARCH(1,1) and Dynamic Conditional Correlation (DCC) GARCH(1,1) with Student’s t-distribution. In order to capture the period of both Great Moderation and the latest financial crisis, the sample period extends from 2003 to 2014. To determine whether dynamic models outperform the conventional one, the reduction of portfolio variance for in-sample data with contemporaneous hedge ratios is first determined and then the holding period of the portfolios is extended to one and two days. In addition, the accuracy of hedge ratio forecasts is examined on the basis of out-of-sample variance reduction. The results are mixed and suggest that dynamic hedging models may not provide enough benefits to justify harder estimation and daily portfolio adjustment. In this sense, the results are consistent with the existing literature.

Optimal hedging with higher moments

This study proposes a utility-based framework for the determination of optimal hedge ratios (OHRs) that can allow for the impact of higher moments on hedging decisions. We examine the entire hyperbolic absolute risk aversion family of utilities which include quadratic, logarithmic, power, and exponential utility functions. We find that for both moderate and large spot (commodity) exposures, the performance of out-of-sample hedges constructed allowing for nonzero higher moments is better than the performance of the simpler OLS hedge ratio. The picture is, however, not uniform throughout our seven spot commodities as there is one instance (cotton) for which the modeling of higher moments decreases welfare out-of-sample relative to the simpler OLS. We support our empirical findings by a theoretical analysis of optimal hedging decisions and we uncover a novel link between OHRs and the minimax hedge ratio, that is the ratio which minimizes the largest loss of the hedged position. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark

Dynamic hedging in Markov regimes

This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.

Avaliação do mercado futuro do milho brasileiro como mecanismo de apoio à comercialização para os produtores de Goiás

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Agronegócios, 2016.

Chasing performance persistence of hedge funds

The thesis examines the performance persistence of hedge funds using complement methodologies (namely cross-sectional regressions, quantile portfolio analysis and Spearman rank correlation test). In addition, six performance ranking metrics and six different combinations of selection and holding periods are compared. The data is gathered from HFI and Tremont databases covering over 14,000 hedge funds and time horizon is set from January 1996 to December 2007. The results suggest that there definitely exists performance persistence among hedge funds and the strength and existence of persistence vary among fund styles. The persistence depends on the metrics and combination of selection and prediction period applied. According to the results, the combination of 36-month selection and holding period outperforms other five period combinations in capturing performance persistence within the sample. Furthermore, model-free performance metrics capture persistence more sensitively than model-specific metrics. The study is the first one ever to use MVR as a performance ranking metric, and surprisingly MVR is more sensitive to detect persistence than other performance metrics employed.

Monte Carlo Hypothesis Testing with The Sharpe Ratio

The purpose of this master thesis was to perform simulations that involve use of random number while testing hypotheses especially on two samples populations being compared weather by their means, variances or Sharpe ratios. Specifically, we simulated some well known distributions by Matlab and check out the accuracy of an hypothesis testing. Furthermore, we went deeper and check what could happen once the bootstrapping method as described by Effrons is applied on the simulated data. In addition to that, one well known RobustSharpe hypothesis testing stated in the paper of Ledoit and Wolf was applied to measure the statistical significance performance between two investment founds basing on testing weather there is a statistically significant difference between their Sharpe Ratios or not. We collected many literatures about our topic and perform by Matlab many simulated random numbers as possible to put out our purpose; As results we come out with a good understanding that testing are not always accurate; for instance while testing weather two normal distributed random vectors come from the same normal distribution. The Jacque-Berra test for normality showed that for the normal random vector r1 and r2, only 94,7% and 95,7% respectively are coming from normal distribution in contrast 5,3% and 4,3% failed to shown the truth already known; but when we introduce the bootstrapping methods by Effrons while estimating pvalues where the hypothesis decision is based, the accuracy of the test was 100% successful. From the above results the reports showed that bootstrapping methods while testing or estimating some statistics should always considered because at most cases the outcome are accurate and errors are minimized in the computation. Also the RobustSharpe test which is known to use one of the bootstrapping methods, studentised one, were applied first on different simulated data including distribution of many kind and different shape secondly, on real data, Hedge and Mutual funds. The test performed quite well to agree with the existence of statistical significance difference between their Sharpe ratios as described in the paper of Ledoit andWolf.