Journal articles: 'Optimal Hedging'

1

Albuquerque, Rui. "Optimal currency hedging." Global Finance Journal 18, no. 1 (January 2007): 16–33. http://dx.doi.org/10.1016/j.gfj.2006.09.002.

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Cong, Jianfa, Ken Seng Tan, and Chengguo Weng. "VAR-BASED OPTIMAL PARTIAL HEDGING." ASTIN Bulletin 43, no. 3 (July 29, 2013): 271–99. http://dx.doi.org/10.1017/asb.2013.19.

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AbstractHedging is one of the most important topics in finance. When a financial market is complete, every contingent claim can be hedged perfectly to eliminate any potential future obligations. When the financial market is incomplete, the investor may eliminate his risk exposure by superhedging. In practice, both hedging strategies are not satisfactory due to their high implementation costs, which erode the chance of making any profit. A more practical and desirable strategy is to resort to the partial hedging, which hedges the future obligation only partially. The quantile hedging of Föllmer and Leukert (Finance and Stochastics, vol. 3, 1999, pp. 251–273), which maximizes the probability of a successful hedge for a given budget constraint, is an example of the partial hedging. Inspired by the principle underlying the partial hedging, this paper proposes a general partial hedging model by minimizing any desirable risk measure of the total risk exposure of an investor. By confining to the value-at-risk (VaR) measure, analytic optimal partial hedging strategies are derived. The optimal partial hedging strategy is either a knock-out call strategy or a bull call spread strategy, depending on the admissible classes of hedging strategies. Our proposed VaR-based partial hedging model has the advantage of its simplicity and robustness. The optimal hedging strategy is easy to determine. Furthermore, the structure of the optimal hedging strategy is independent of the assumed market model. This is in contrast to the quantile hedging, which is sensitive to the assumed model as well as the parameter values. Extensive numerical examples are provided to compare and contrast our proposed partial hedging to the quantile hedging.

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TSUZUKI, YUKIHIRO. "ON OPTIMAL SUPER-HEDGING AND SUB-HEDGING STRATEGIES." International Journal of Theoretical and Applied Finance 16, no. 06 (September 2013): 1350038. http://dx.doi.org/10.1142/s0219024913500386.

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This paper proposes optimal super-hedging and sub-hedging strategies for a derivative on two underlying assets without any specification of the underlying processes. Moreover, the strategies are free from any model of the dependency between the underlying asset prices. We derive the optimal pricing bounds by finding a joint distribution under which the derivative price is equal to the hedging portfolio's value; the portfolio consists of liquid derivatives on each of the underlying assets. As examples, we obtain new super-hedging and sub-hedging strategies for several exotic options such as quanto options, exchange options, basket options, forward starting options, and knock-out options.

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Leung, Tim, and Matthew Lorig. "Optimal static quadratic hedging." Quantitative Finance 16, no. 9 (April 22, 2016): 1341–55. http://dx.doi.org/10.1080/14697688.2016.1161229.

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5

Lioui, Abraham, and Patrice Poncet. "Optimal currency risk hedging." Journal of International Money and Finance 21, no. 2 (April 2002): 241–64. http://dx.doi.org/10.1016/s0261-5606(01)00045-6.

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6

Alexander, C. "Optimal hedging using cointegration." Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 357, no. 1758 (August 1999): 2039–58. http://dx.doi.org/10.1098/rsta.1999.0416.

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7

Kim, Hee Ho, and 김미 화. "Optimal Indirect Hedging and Price Conditions." Journal of Derivatives and Quantitative Studies 14, no. 1 (May 31, 2006): 61–88. http://dx.doi.org/10.1108/jdqs-01-2006-b0003.

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This study examines the indirect hedging strategy and its price ccndition against exchange risk for the export firms which can not directly hedge due to non-existence of appropriate futures market for the export market currency. The export firms would manipulate their mark-up rate as real hedging against exchange risk in the incomplete export market. Real options tend to reduce the uncertainty of an export profit curve in nonlinear manner and thus, substitute for the financial hedging. As a result, the optimal hedging strategy for the firms exporting to the incomplete market is an under hedge combining short futures and long put. The long put is a substitute with short futures and required to cover the nonlinear risk of export profit derived by real options. Indirect hedging would increase the expected profit by reducing risk, while a sufficient and necessary condition for the optimal indirect hedging depends on exchange volatility and a magnitude of put premium relative to an expected excercise loss.

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8

Lee, Cheng-Few, Kehluh Wang, and Yan Long Chen. "Hedging and Optimal Hedge Ratios for International Index Futures Markets." Review of Pacific Basin Financial Markets and Policies 12, no. 04 (December 2009): 593–610. http://dx.doi.org/10.1142/s0219091509001769.

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This empirical study utilizes four static hedging models (OLS Minimum Variance Hedge Ratio, Mean-Variance Hedge Ratio, Sharpe Hedge Ratio, and MEG Hedge Ratio) and one dynamic hedging model (bivariate GARCH Minimum Variance Hedge Ratio) to find the optimal hedge ratios for Taiwan Stock Index Futures, S&P 500 Stock Index Futures, Nikkei 225 Stock Index Futures, Hang Seng Index Futures, Singapore Straits Times Index Futures, and Korean KOSPI 200 Index Futures. The effectiveness of these ratios is also evaluated. The results indicate that the methods of conducting optimal hedging in different markets are not identical. However, the empirical results confirm that stock index futures are effective direct hedging instruments, regardless of hedging schemes or hedging horizons.

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9

Di Tella, Paolo, Martin Haubold, and Martin Keller-Ressel. "Semi-static variance-optimal hedging in stochastic volatility models with Fourier representation." Journal of Applied Probability 56, no. 3 (September 2019): 787–809. http://dx.doi.org/10.1017/jpr.2019.41.

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AbstractWe introduce variance-optimal semi-static hedging strategies for a given contingent claim. To obtain a tractable formula for the expected squared hedging error and the optimal hedging strategy we use a Fourier approach in a multidimensional factor model. We apply the theory to set up a variance-optimal semi-static hedging strategy for a variance swap in the Heston model, which is affine, in the 3/2 model, which is not, and in a market model including jumps.

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10

Arruda, Nelson, Alain Bergeron, and Mark Kritzman. "Optimal Currency Hedging: Horizon Matters." Journal of Alternative Investments 23, no. 4 (March 1, 2021): 122–30. http://dx.doi.org/10.3905/jai.2021.1.126.

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11

Chiu, Wan-Yi. "Optimal hedging of CARA investors." Journal of Statistics and Management Systems 16, no. 4-5 (September 2013): 339–48. http://dx.doi.org/10.1080/09720510.2013.838447.

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12

Agliardi, Rossella. "Optimal hedging through limit orders." Stochastic Models 32, no. 4 (June 8, 2016): 593–605. http://dx.doi.org/10.1080/15326349.2016.1188014.

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13

Crosby, John. "Optimal hedging of variance derivatives." European Journal of Finance 20, no. 2 (June 18, 2012): 150–80. http://dx.doi.org/10.1080/1351847x.2012.689774.

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14

Rémillard, Bruno, and Sylvain Rubenthaler. "Optimal hedging in discrete time." Quantitative Finance 13, no. 6 (June 2013): 819–25. http://dx.doi.org/10.1080/14697688.2012.745012.

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15

Stutzer, Michael. "Optimal hedging via large deviation." Physica A: Statistical Mechanics and its Applications 392, no. 15 (August 2013): 3177–82. http://dx.doi.org/10.1016/j.physa.2013.03.022.

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16

Monoyios, M. "Optimal hedging and parameter uncertainty." IMA Journal of Management Mathematics 18, no. 4 (April 26, 2007): 331–51. http://dx.doi.org/10.1093/imaman/dpm022.

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17

Gobet, Emmanuel, and Nicolas Landon. "Almost sure optimal hedging strategy." Annals of Applied Probability 24, no. 4 (August 2014): 1652–90. http://dx.doi.org/10.1214/13-aap959.

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18

Brooks, Chris, Alešs Černý, and Joëlle Miffre. "Optimal hedging with higher moments." Journal of Futures Markets 32, no. 10 (July 15, 2011): 909–44. http://dx.doi.org/10.1002/fut.20542.

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19

Shanker, Latha. "Optimal hedging under indivisible choices." Journal of Futures Markets 13, no. 3 (May 1993): 237–59. http://dx.doi.org/10.1002/fut.3990130303.

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20

Wolf, Avner. "Optimal hedging with futures options." Journal of Economics and Business 39, no. 2 (May 1987): 141–58. http://dx.doi.org/10.1016/0148-6195(87)90013-0.

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21

Hull, John, and Alan White. "Optimal delta hedging for options." Journal of Banking & Finance 82 (September 2017): 180–90. http://dx.doi.org/10.1016/j.jbankfin.2017.05.006.

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22

Dewally, Michaël, and Luke Marriott. "Effective Basemetal Hedging: The Optimal Hedge Ratio and Hedging Horizon." Journal of Risk and Financial Management 1, no. 1 (December 31, 2008): 41–76. http://dx.doi.org/10.3390/jrfm1010041.

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23

Yu, Mei, Qian Gao, Zijian Liu, Yike Zhou, and Dan Ralescu. "A Study on the Optimal Portfolio Strategies Under Inflation." Journal of Systems Science and Information 3, no. 2 (April 25, 2015): 111–32. http://dx.doi.org/10.1515/jssi-2015-0111.

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AbstractThis paper tests the inflation hedging ability of four categories of important financial assets in China: Commodity futures, real estate, gold and industry stock and select the assets that have significant inflation hedging effect. Then the authors construct the mean-variance model under the inflation factor, using the selected assets to construct the inflation hedging portfolio, solving the model and obtain the optimal investment strategy with inflation protection function. The result shows that the portfolio constructed by the model have more stable real returns and its inflation hedging ability can be even better if the short selling restriction of stocks is eliminated.

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24

Bhatia, Nikhil, Roshan Srivastav, and Kasthrirengan Srinivasan. "Season-Dependent Hedging Policies for Reservoir Operation—A Comparison Study." Water 10, no. 10 (September 22, 2018): 1311. http://dx.doi.org/10.3390/w10101311.

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During periods of significant water shortage or when drought is impending, it is customary to implement some kind of water supply reduction measures with a view to prevent the occurrence of severe shortages (vulnerability) in the near future. In the case of operation of a water supply reservoir, this reduction of water supply is affected by hedging schemes or hedging policies. This research work aims to compare the popular hedging policies: (i) linear two-point hedging; (ii) modified two-point hedging; and, (iii) discrete hedging based on time-varying and constant hedging parameters. A parameterization-simulation-optimization (PSO) framework is employed for the selection of the parameters of the compromising hedging policies. The multi-objective evolutionary search-based technique (Non-dominated Sorting based Genetic Algorithm-II) was used to identify the Pareto-optimal front of hedging policies that seek to obtain the trade-off between shortage ratio and vulnerability. The case example used for illustration is the Hemavathy reservoir in Karnataka, India. It is observed that the Pareto-optimal front that was obtained from time-varying hedging policies show significant improvement in reservoir performance when compared to constant hedging policies. The variation in the monthly parameters of the time-variant hedging policies shows a strong correlation with monthly inflows and available water.

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25

Rao, Vadhindran. "Multiperiod Hedging using Futures: Mean Reversion and the Optimal Hedging Path." Journal of Risk and Financial Management 4, no. 1 (December 31, 2011): 133–61. http://dx.doi.org/10.3390/jrfm4010133.

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26

Castelino, Mark G., Jack C. Francis, and Avner Wolf. "Cross-Hedging: Basis Risk and Choice of the Optimal Hedging Vehicle." Financial Review 26, no. 2 (May 1991): 179–210. http://dx.doi.org/10.1111/j.1540-6288.1991.tb00376.x.

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27

Josephy, Norman, Lucia Kimball, and Victoria Steblovskaya. "Optimal Hedging and Pricing of Equity-Linked Life Insurance Contracts in a Discrete-Time Incomplete Market." Journal of Probability and Statistics 2011 (2011): 1–23. http://dx.doi.org/10.1155/2011/850727.

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We present a method of optimal hedging and pricing of equity-linked life insurance products in an incomplete discrete-time financial market. A pure endowment life insurance contract with guarantee is used as an example. The financial market incompleteness is caused by the assumption that the underlying risky asset price ratios are distributed in a compact interval, generalizing the assumptions of multinomial incomplete market models. For a range of initial hedging capitals for the embedded financial option, we numerically solve an optimal hedging problem and determine a risk-return profile of each optimal non-self-financing hedging strategy. The fair price of the insurance contract is determined according to the insurer's risk-return preferences. Illustrative numerical results of testing our algorithm on hypothetical insurance contracts are documented. A discussion and a test of a hedging strategy recalibration technique for long-term contracts are presented.

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28

Zhou, Changfeng, and Huan Cai. "Optimal Hedging Strategies for Natural Gas." International Journal of Economics and Finance 12, no. 8 (June 20, 2020): 1. http://dx.doi.org/10.5539/ijef.v12n8p1.

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This study examines the optimal hedge performance between natural gas market and crude oil, ECO, gold and US-bonds markets. To calculate optimal hedge ratios and hedging effectiveness, we apply several multivariate volatility models, namely CCC, DCC, cDCC and bayesDCC. The empirical results show that crude oil is the best asset to hedge natural gas followed by gold and ECO. This is a new result relative to the existing literature on natural gas prices. Additionally, we find that the bayesDCC model has the best performance on optimal hedge ratios (OHRs) calculation in terms of hedging effectiveness. Our findings will hold important financial risk management implications and asset portfolio for those invest in natural gas market.

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29

Chen, Wei, and Jimmy Skoglund. "Optimal hedging of funding liquidity risk." Journal of Risk 16, no. 3 (February 2014): 85–111. http://dx.doi.org/10.21314/jor.2014.292.

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30

BRIYS, ERIC, MICHEL CROUHY, and HARRIS SCHLESINGER. "Optimal Hedging under Intertemporally Dependent Preferences." Journal of Finance 45, no. 4 (September 1990): 1315–24. http://dx.doi.org/10.1111/j.1540-6261.1990.tb02440.x.

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31

LENCE, SERGIO H., and DERMOT J. HAYES. "Optimal Hedging Under Forward-Looking Behaviour." Economic Record 71, no. 4 (December 1995): 329–42. http://dx.doi.org/10.1111/j.1475-4932.1995.tb02678.x.

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32

Ankirchner, Stefan, Peter Imkeller, and Alexandre Popier. "Optimal Cross Hedging of Insurance Derivatives." Stochastic Analysis and Applications 26, no. 4 (June 30, 2008): 679–709. http://dx.doi.org/10.1080/07362990802128230.

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33

Di Tella, Paolo, Martin Haubold, and Martin Keller‐Ressel. "Semistatic and sparse variance‐optimal hedging." Mathematical Finance 30, no. 2 (April 2020): 403–25. http://dx.doi.org/10.1111/mafi.12235.

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34

Schweizer, Martin. "Variance-Optimal Hedging in Discrete Time." Mathematics of Operations Research 20, no. 1 (February 1995): 1–32. http://dx.doi.org/10.1287/moor.20.1.1.

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35

Rao, Vadhindran K. "Preference-free optimal hedging using futures." Economics Letters 66, no. 2 (February 2000): 223–28. http://dx.doi.org/10.1016/s0165-1765(99)00195-0.

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36

Clewlow, Les, and Stewart Hodges. "Optimal delta-hedging under transactions costs." Journal of Economic Dynamics and Control 21, no. 8-9 (June 1997): 1353–76. http://dx.doi.org/10.1016/s0165-1889(97)00030-4.

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37

ZHANG, Long-bin, Chun-feng WANG, and Zhen-ming FANG. "Optimal Hedging Ratio Model with Skewness." Systems Engineering - Theory & Practice 29, no. 9 (September 2009): 1–6. http://dx.doi.org/10.1016/s1874-8651(10)60067-1.

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38

Schütz, Peter, and Sjur Westgaard. "Optimal hedging strategies for salmon producers." Journal of Commodity Markets 12 (December 2018): 60–70. http://dx.doi.org/10.1016/j.jcomm.2017.12.009.

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39

Draper, Andrew J., and Jay R. Lund. "Optimal Hedging and Carryover Storage Value." Journal of Water Resources Planning and Management 130, no. 1 (January 2004): 83–87. http://dx.doi.org/10.1061/(asce)0733-9496(2004)130:1(83).

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40

Wan, Wenhua, Jianshi Zhao, Jay R. Lund, Tongtiegang Zhao, Xiaohui Lei, and Hao Wang. "Optimal Hedging Rule for Reservoir Refill." Journal of Water Resources Planning and Management 142, no. 11 (November 2016): 04016051. http://dx.doi.org/10.1061/(asce)wr.1943-5452.0000692.

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41

Arshanapalli, Bala G., and Omprakash K. Gupta. "Optimal hedging under output price uncertainty." European Journal of Operational Research 95, no. 3 (December 1996): 522–36. http://dx.doi.org/10.1016/0377-2217(95)00306-1.

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42

Browning, Alexander P., Jesse A. Sharp, Tarunendu Mapder, Christopher M. Baker, Kevin Burrage, and Matthew J. Simpson. "Persistence as an Optimal Hedging Strategy." Biophysical Journal 120, no. 1 (January 2021): 133–42. http://dx.doi.org/10.1016/j.bpj.2020.11.2260.

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43

Guéant, Olivier. "Expected Shortfall and optimal hedging payoff." Comptes Rendus Mathematique 356, no. 4 (April 2018): 433–38. http://dx.doi.org/10.1016/j.crma.2018.03.010.

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44

ROUX, ALET. "PRICING AND HEDGING GAME OPTIONS IN CURRENCY MODELS WITH PROPORTIONAL TRANSACTION COSTS." International Journal of Theoretical and Applied Finance 19, no. 07 (November 2016): 1650043. http://dx.doi.org/10.1142/s0219024916500436.

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The pricing, hedging, optimal exercise and optimal cancellation of game or Israeli options are considered in a multi-currency model with proportional transaction costs. Efficient constructions for optimal hedging, cancellation and exercise strategies are presented, together with numerical examples, as well as probabilistic dual representations for the bid and ask price of a game option.

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45

Matsumoto, Koichi. "Mean–variance hedging with model risk." International Journal of Financial Engineering 04, no. 04 (December 2017): 1750042. http://dx.doi.org/10.1142/s2424786317500426.

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This paper studies a hedging problem of a derivative security in a one-period model when there is the model risk. The hedging error is measured by a quadratic criterion. The model risk means that the true model is uncertain and there are many candidates for the true model. The true model is assumed to be in a set of models. We study an optimal strategy which minimizes the worst-case hedging error over all models in the set. We show how to calculate an optimal strategy and the minimum hedging error effectively. Finally we give some numerical examples to demonstrate the usefulness of our method.

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46

Tetik, Metin, and Ercan Özen. "Time-Varying Structure of the Optimal Hedge Ratio for Emerging Markets." Scientific Annals of Economics and Business 69, no. 4 (December 19, 2022): 521–37. http://dx.doi.org/10.47743/saeb-2022-0030.

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Emerging markets are more exposed to risk than developed markets. Therefore, they require risk management using futures market instruments. This study aims to determine the hedging effectiveness of the spot index market risks in the stock index futures market in Brazil, Russia, India, South Africa, and Turkey. Measuring the hedging effectiveness level of futures markets is vital for these countries because investors must remain in the stock markets for the sustainability of the financial markets and economies. Weekly closing data for the period from January 2009 to October 2021 were analyzed via a dynamic method referred to as flexible least squares (FLS). Although the FLS results show that futures transactions provide high hedging effectiveness for all countries within the scope of this study, country-specific conditions may reduce the hedging effectiveness.

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47

Zhou, Rui, Johnny Siu-Hang Li, and Jeffrey Pai. "Hedging crop yield with exchange-traded weather derivatives." Agricultural Finance Review 76, no. 1 (May 3, 2016): 172–86. http://dx.doi.org/10.1108/afr-11-2015-0045.

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Purpose – The application of weather derivatives in hedging crop yield risk is gaining more interest. However, the further development of weather derivatives – particularly exchange-traded – in the agricultural sector has been impeded by concerns over their hedging performance. The purpose of this paper is to develop a new framework to derive the optimal hedging strategy and evaluate hedging effectiveness. Design/methodology/approach – This framework incorporates a stochastic temperature model, a crop yield model, a risk-neutral pricing method and a profit optimization procedure. Based on a large number of simulated scenarios, the authors study crop yield hedge for a future year. The authors allow the hedger to choose from different types of exchange-traded weather derivatives, and examine the impact of various factors on the optimal hedging strategy. Findings – The analysis shows that hedging objective, pricing method and geographical location of the hedged exposure all play important roles in choosing the best hedging strategy and assessing hedging effectiveness. Originality/value – This framework is forward-looking, because it focusses on the crop yield hedge for a future year rather than on the historical hedging effectiveness often studied in literature. It utilizes the most up-to-date information related to temperature and crop yield, and hence produces a hedging strategy which is more relevant to the year under consideration.

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48

Broll, Udo, Andreas Förster, and Kit Pong Wong. "FARMER’S INCOME RISK AND RISK MANAGEMENT BY CROSS-HEDGING: A NOTE." JOURNAL OF DEVELOPMENT ECONOMICS AND FINANCE 3, no. 2 (2022): 323–29. http://dx.doi.org/10.47509/jdef.2022.v03i02.04.

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The purpose of this study is to provide theoretical insights into the optimal hedging strategies in farmers contracts usage. We study the hedging decisions of a risk-averse farmer. The farmer faces multiple sources of price uncertainty. Cross-hedging is plausible in that one of these two commodities has a futures market. We show that the farmer’s optimal futures market position is a fullhedge, an over-hedge, or an under-hedge, depending on whether the two random prices are strongly positively correlated, uncorrelated, or negatively correlated, respectively.

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49

Xu, Bin, Ping-An Zhong, Qiyou Huang, Jianqun Wang, Zhongbo Yu, and Jianyun Zhang. "Optimal Hedging Rules for Water Supply Reservoir Operations under Forecast Uncertainty and Conditional Value-at-Risk Criterion." Water 9, no. 8 (July 30, 2017): 568. http://dx.doi.org/10.3390/w9080568.

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Hedging rules for water supply reservoir operations provide guidelines for balancing the consequences of competing water allocations. When inflow forecast uncertainty is addressed, hedging acts as insurances for offsetting the negative influence of water shortage in the future, especially when drought is anticipated. This study used a risk-averse criterion, the conditional value-at-risk (CVaR), rather than the expected value (EV) criterion, to rationalize water delivery for overcoming the shortcomings of risk-neutral hedging rules in minimizing water shortage impacts in unfavorable realizations, in which actual inflow is less than anticipated. A two-period hedging model with the objective of maximizing the CVaR of total benefits from water delivery and water storage is established, and the optimal hedging rules using first-order optimality condition are analytically derived. Differences in hedging rules under the two criteria are highlighted by theoretical analysis and numerical experiments. The methods are applied to guide the operations of a water supply reservoir, and results show that: (1) the hedging rules under the EV criterion are special cases under the CVaR criterion; (2) water delivery in the current period would be greatly curtailed under the high influence of forecast uncertainty or the significant risk-averse attitude of decision makers; (3) hedging to maximize the CVaR of total benefit is at the cost of reducing the EV of total benefit; and (4) in real-time operations, compared with the hedging policies under the EV criterion, the hedging policies under the CVaR criterion would be more effective when applied to dry and extremely dry hydrological conditions, especially when inflow is overestimated. These implications provide new insights into rationing water supply and risk aversion.

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50

Tayebiyan, Aida, Thamer Ahmad Mohammad, Nadhir Al-Ansari, and Mohammad Malakootian. "Comparison of Optimal Hedging Policies for Hydropower Reservoir System Operation." Water 11, no. 1 (January 10, 2019): 121. http://dx.doi.org/10.3390/w11010121.

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Reservoir operation rules play an important role in regions economic development. Meanwhile, hedging policies are mostly applied for municipal, industrial, and irrigation water supplies from reservoirs and it is less used for reservoir operation for hydropower generation. The concept of hedging and rationing factors can be used to maintain the water in a reservoir for the sake of increasing water storage and water head for future use. However, water storage and head are the key factors in operation of reservoir systems for hydropower generation. This study investigates the applicability of seven competing hedging policies including four customary forms of hedging (1PHP, 2PHP, 3PHP, DHP) and three new forms of hedging rules (SOPHP, BSOPHP, SHPHP) for reservoir operation for hydropower generation. The models were constructed in MATLAB R2011b based on the characteristics of the Batang Padang hydropower reservoir system, Malaysia. In order to maximize the output of power generation in operational periods (2003–2009), three optimization algorithms namely particle swarm optimization (PSO), genetic algorithm (GA), and hybrid PSO-GA were linked to one of the constructed model (1PHP as a test) to find the most effective algorithm. Since the results demonstrated the superiority of the hybrid PSO-GA algorithm compared to either PSO or GA, the hybrid PSO-GA were linked to each constructed model in order to find the optimal decision variables of each model. The proposed methodology was validated using monthly data from 2010–2012. The results showed that there are no significant difference between the output of monthly mean power generation during 2003–2009 and 2010–2012.The results declared that by applying the proposed policies, the output of power generation could increase by 13% with respect to the historical management. Moreover, the discrepancies between mean power generations from highest to lowest months were reduced from 49 MW to 26 MW, which is almost half. This means that hedging policies could efficiently distribute the water-supply and power-supply in the operational period and increase the stability of the system. Among the studied hedging policies, SHPHP is the most convenient policy for hydropower reservoir operation and gave the best result.

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Journal articles on the topic 'Optimal Hedging'

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