Relevant bibliographies by topics / Portfolio hedging

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Portfolio hedging'

Author: Grafiati
Published: 11 September 2021
Last updated: 12 February 2022

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Journal articles on the topic "Portfolio hedging"

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Jiménez-Gómez, Miguel, Natalia Acevedo-Prins, and Miguel David Rojas-López. "Simulation hedge investment portfolios through options portfolio." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (November 1, 2019): 843. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp843-847.

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<p>This paper presents two hedging strategies with financial options to mitigate the market risk associated with the future purchase of investment portfolios that exhibit the same behavior as Colombia's COLCAP stock index. The first strategy consists in the purchase of a Call plain vanilla option and the second strategy in the purchase of a Call option and the sale of a Call option. The second strategy corresponds to a portfolio of options called Bull Call Spread. To determine the benefits of hedging and the best strategy, the Geometric Brownian Motion and Monte Carlo simulation is used. The results show that the two hedging strategies manage to mitigate market risk and the best strategy is the first one despite the fact that the Bull Call Spread strategy is lower cost.</p>
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Meirelles, Sofia Kusiak, and Marcelo Fernandes. "Estratégias de Imunização de Carteiras de Renda Fixa no Brasil." Brazilian Review of Finance 16, no. 2 (July 11, 2018): 179. http://dx.doi.org/10.12660/rbfin.v16n2.2018.69279.

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This paper aims to statistically compare the performance of two hedging strategies for Brazilian fixed income portfolios, with discrete rebalancing. The first hedging strategy matches duration, and hence it considers only small parallel changes in the yield curve. The alternative methodology ponders level, curvature and convexity shifts through a factor model. We first estimate the yield curve using the polynomial model of Nelson & Siegel (1987) and Diebold & Li (2006) and then immunize the fixed income portfolio using Litterman & Scheinkman’s (1991) hedging procedure. The alternative strategy for portfolio immunization outperforms duration matching in the empirical exercise we contemplate. Additionally, we show that rebalancing the hedging portfolio every month is more efficient than at other frequencies.
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Machado-Santos, Carlos. "Portfolio insurance using traded options." Revista de Administração Contemporânea 5, no. 3 (December 2001): 187–214. http://dx.doi.org/10.1590/s1415-65552001000300010.

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Literature concerning the institutional use of options indicates that the main purpose of option trading is to provide investors with the opportunity to create return distributions previously unavailable, considering that options provide the means to manipulate portfolio returns. In such a context, this study intends to analyse the returns of insured portfolios generated by hedging strategies on underlying stock portfolios. Because dynamic hedging is too expensive, we have hedged the stock positions discretely, in a way that the positions were revised only when the daily hedge ratio has changed more than a specific amount. The results, provided by these hedging schemes, indicate that a small rise of the standard deviation seems to be largely compensated with the higher average returns. In fact, such strategies seem to be highly influenced by the price movements of underlying stocks, requiring more frequent (sparse) adjustments in periods of high (low) volatility. Thus, discrete hedging strategies seem more accurate and meaningful than the arbitrary regular intervals largely presented and discussed in literature.
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Engle, Robert F., Stefano Giglio, Bryan Kelly, Heebum Lee, and Johannes Stroebel. "Hedging Climate Change News." Review of Financial Studies 33, no. 3 (February 14, 2020): 1184–216. http://dx.doi.org/10.1093/rfs/hhz072.

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Abstract We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk exposures. We show that this approach yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample. We discuss multiple directions for future research on financial approaches to managing climate risk.
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Filipozzi, Fabio, and Kersti Harkmann. "Optimal currency hedge and the carry trade." Review of Accounting and Finance 19, no. 3 (August 24, 2020): 411–27. http://dx.doi.org/10.1108/raf-10-2018-0219.

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Purpose This paper aims to investigate the efficiency of different hedging strategies for an investor holding a portfolio of foreign currency bonds. Design/methodology/approach The simplest strategies of no hedge and fully hedged are compared with the more sophisticated strategies of the ordinary least squares (OLS) approach and the optimal hedge ratios found by the dynamic conditional correlation-generalised autoregressive conditional heteroskedasticity approach. Findings The sophisticated hedging strategies are found to be superior to the simple strategies because they lower the portfolio risk in domestic currency terms and improve the Sharpe ratios for multi-asset portfolios. The analyses also show that both the OLS and dynamic hedging strategies imply holding a limited carry position by being long in high-yielding currencies but short in low-yielding currencies. Originality/value The performance of multi-currency portfolios is examined using more realistic assumptions than in the previous literature, including a weekly frequency and a constraint of no short selling. Furthermore, carry trades are shown to be part of an optimal portfolio.
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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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Lee, Jae Ha, and Han Deog Hui. "Hedging Strategies with the KTB Futures." Journal of Derivatives and Quantitative Studies 10, no. 2 (November 30, 2002): 25–56. http://dx.doi.org/10.1108/jdqs-02-2002-b0002.

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This study explores hedging strategies that use the KTB futures to hedge the price risk of the KTB spot portfolio. The study establishes the price sensitivity, risk-minimization, bivariate GARCH (1,1) models as hedging models, and analyzes their hedging performances. The sample period covers from September 29, 1999 to September 18, 2001. Time-matched prices at 11:00 (11:30) of the KTB futures and spot were used in the analysis. The most important findings may be summarized as follows. First, while the average hedge ration of the price sensitivity model is close to one, both the risk-minimization and GARCH model exhibit hedge ratios that are substantially lower than one. Hedge ratios tend to be greater for daily data than for weekly data. Second, for the daily in-sample data, hedging effectiveness is the highest for the GARCH model with time-varying hedge ratios, but the risk-minimization model with constant hedge ratios is not far behind the GARCH model in its hedging performance. In the case of out-of-sample hedging effectiveness, the GARCH model is the best for the KTB spot portfolio, and the risk-minimization model is the best for the corporate bond portfolio. Third, for daily data, the in-sample hedge shows a better performance than the out-of-sample hedge, except for the risk-minimization hedge against the corporate bond portfolio. Fourth, for the weekly in-sample hedges, the price sensitivity model is the worst and the risk-minimization model is the best in hedging the KTB spot portfolio. While the GARCH model is the best against the KTB +corporate bond portfolio, the risk-minimization model is generally as good as the GARCH model. The risk-minimization model performs the best for the weekly out-of-sample data, and the out-of-sample hedges are better than the in-sample hedges. Fifth, while the hedging performance of the risk-minimization model with daily moving window seems somewhat superior to the traditional risk-minimization model when the trading volume increased one year after the inception of the KTB futures, on the average the traditional model is better than the moving-window model. For weekly data, the traditional model exhibits a better performance. Overall, in the Korean bond markets, investors are encouraged to use the simple risk-minimization model to hedge the price risk of the KTB spot and corporate bond portfolios.
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Bond, Michael T., and Jack H. Rubens. "Inflation Hedging Through International Equity Investment." Journal of Applied Business Research (JABR) 8, no. 2 (October 18, 2011): 107. http://dx.doi.org/10.19030/jabr.v8i2.6172.

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For years common stock were thought to be an effective inflation hedge. The dismal performance of domestic equities in the 1970s was, thus, completely unanticipated. A possible method for improving stock portfolio performance on a period-by-period basis vs. inflation would be the inclusion of foreign equities. Regression analysis of various foreign equity markets and internationally efficient portfolios vs. measures of actual, expected and unexpected inflation indicated that including non-US equities in portfolios did not protect investors from inflation on a period-by-period basis in the 1970-88 time period.
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HARYONO, NADIA ASANDIMITRA, and M. RIADHOS SOLICHIN. "Efektivitas Strategi Hedging Menggunakan Kontrak Indeks Lq45 Futures dalam Meminimalisasi Risiko Sistematis Portofolio." BISMA (Bisnis dan Manajemen) 2, no. 2 (June 6, 2018): 100. http://dx.doi.org/10.26740/bisma.v2n2.p100-106.

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AbstractInvestor can make hedging to the systematic risk or market risk by using LQ45 index futures contract whose value comparable to the share portfolio value they have. This research had the purpose to prove used the LQ45 index futures contract in minimize the portfolio systematic risk. In this research used LQ45 index as the proxy on the portfolio have been properly diversified. Data used in this research were LQ45 index daily value data and the daily closing price of LQ45 index futures with 2004-2005 research period. Testing was conducted by comparing the portfolio return hedged variance to the portfolio return unhedged variance. Calculation of hedging effectiveness used LQ45 index futures contract as much as -9%, negative hedging effectiveness calculation due to the portfolio return hedged variance larger than portfolio return unhedged variance or, in the other words the risk in the futures market was larger than the risk in the spot market. Thus, the LQ45 index futures contract was ineffective to use as the hedging strategy in minimize the portfolio systematic risk
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Novotný, Jan. "Portfolio Hedging and Earnings Management." Český finanční a účetní časopis 2014, no. 4 (December 1, 2014): 84–93. http://dx.doi.org/10.18267/j.cfuc.425.

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Dissertations / Theses on the topic "Portfolio hedging"

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Shin, On-Myung. "Portfolio Diversifikation und Hedging /." Lohmar [u. a.] : Eul-Verl, 2003. http://www.gbv.de/dms/zbw/362368791.pdf.

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Karlsson, Victor, Rikard Svensson, and Viktor Eklöf. "Contingent Hedging : Applying Financial Portfolio Theory on Product Portfolios." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-18602.

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In an ever-changing global environment, the ability to adapt to the current economic climate is essential for a company to prosper and survive. Numerous previous re- search state that better risk management and low overall risks will lead to a higher firm value. The purpose of this study is to examine if portfolio theory, made for fi- nancial portfolios, can be used to compose product portfolios in order to minimize risk and optimize returns. The term contingent hedge is defined as an optimal portfolio that can be identified today, that in the future will yield a stable stream of returns at a low level of risk. For companies that might engage in costly hedging activities on the futures market, the benefits of creat- ing a contingent hedge are several. These include creating an optimized portfolio that minimizes risk and avoid trading contracts on futures markets that would incur hefty transaction costs and risks. Using quantitative financial models, product portfolio compositions are generated and compared with the returns and risks profile of individual commodities, as well as the actual product portfolio compositions of publicly traded mining companies. Us- ing Modern Portfolio Theory an efficient frontier is generated, yielding two inde- pendent portfolios, the minimum risk portfolio and the tangency portfolio. The Black-Litterman model is also used to generate yet another portfolio using a Bayesian approach. The portfolios are generated by historic time-series data and compared with the actual future development of commodities; the portfolios are then analyzed and compared. The results indicate that the minimum risk portfolio provides a signif- icantly lower risk than the compositions of all mining companies in the study, as well as the risks of individual commodities. This in turn will lead to several benefits for company management and the firm’s shareholders that are discussed throughout the study. However, as for a return-optimizing portfolio, no significant results can be found. Furthermore, the analysis suggests a series of improvements that could potentially yield an even greater result. The recommendation is that mining companies can use the methods discussed throughout this study as a way to generate a costless contin- gent hedge, rather than engage in hedging activities on futures markets.
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Fu, Jun, and 付君. "Asset pricing, hedging and portfolio optimization." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48199345.

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Starting from the most famous Black-Scholes model for the underlying asset price, there has been a large variety of extensions made in recent decades. One main strand is about the models which allow a jump component in the asset price. The first topic of this thesis is about the study of jump risk premium by an equilibrium approach. Different from others, this work provides a more general result by modeling the underlying asset price as the ordinary exponential of a L?vy process. For any given asset price process, the equity premium, pricing kernel and an equilibrium option pricing formula can be derived. Moreover, some empirical evidence such as the negative variance risk premium, implied volatility smirk, and negative skewness risk premium can be well explained by using the relation between the physical and risk-neutral distributions for the jump component. Another strand of the extensions of the Black-Scholes model is about the models which can incorporate stochastic volatility in the asset price. The second topic of this thesis is about the replication of exponential variance, where the key risks are the ones induced by the stochastic volatility and moreover it can be correlated with the returns of the asset, referred to as leverage effect. A time-changed L?vy process is used to incorporate jumps, stochastic volatility and leverage effect all together. The exponential variance can be robustly replicated by European portfolios, without any specification of a model for the stochastic volatility. Beyond the above asset pricing and hedging, portfolio optimization is also discussed. Based on the Merton (1969, 1971)'s reduced portfolio optimization and the delta hedging problem, a portfolio of an option, the underlying stock and a risk-free bond can be optimized in discrete time and its optimal solution can be shown to be a mixture of the Merton's result and the delta hedging strategy. The main approach is the elasticity approach, which has initially been proposed in continuous time. In addition to the above optimization problem in discrete time, the same topic but in a continuous-time regime-switching market is also presented. The use of regime-switching makes our market incomplete, and makes it difficult to use some approaches which are applicable in complete market. To overcome this challenge, two methods are provided. The first method is that we simply do not price the regime-switching risk when obtaining the risk-neutral probability. Then by the idea of elasticity, the utility maximization problem can be formulated as a stochastic control problem with only a single control variable, and explicit solutions can be obtained. The second method is to introduce a functional operator to general value functions of stochastic control problem in such a way that the optimal value function in our setting can be given by the limit of a sequence of value functions defined by iterating the operator. Hence the original problem can be deduced to an auxiliary optimization problem, which can be solved as if we were in a single-regime market, which is complete.
published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
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Suppakitjarak, Nathridee. "International portfolio diversification and hedging exchange rate risk." Thesis, University of Birmingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.668332.

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Polat, Onur. "Dynamic Complex Hedging And Portfolio Optimization In Additive Markets." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12610441/index.pdf.

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In this study, the geometric Additive market models are considered. In general, these market models are incomplete, that means: the perfect replication of derivatives, in the usual sense, is not possible. In this study, it is shown that the market can be completed by new artificial assets which are called &ldquo
power-jump assets&rdquo
based on the power-jump processes of the underlying Additive process. Then, the hedging portfolio for claims whose payoff function depends on the prices of the stock and the power-jump assets at maturity is derived. In addition to the previous completion strategy, it is also shown that, using a static hedging formula, the market can also be completed by considering portfolios with a continuum of call options with different strikes and the same maturity. What is more, the portfolio optimization problem is considered in the enlarged market. The optimization problem consists of choosing an optimal portfolio in such a way that the largest expected utility of the terminal wealth is obtained. For particular choices of the equivalent martingale measure, it is shown that the optimal portfolio consists only of bonds and stocks.
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Bär, Tobias. "Predicting and hedging credit portfolio risk with macroeconomic factors /." Hamburg : Kovac, 2002. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=009735176&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Mironenko, Georgy. "Problem of hedging of a portfolio with a unique rebalancing moment." Thesis, Högskolan i Halmstad, Tillämpad matematik och fysik (MPE-lab), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-17357.

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The paper deals with the problem of finding an optimal one-time rebalancing strategy for the Bachelier model, and makes some remarks for the similar problem within Black-Scholes model. The problem is studied on finite time interval under mean-square criterion of optimality. The methods of the paper are based on the results for optimal stopping problem and standard mean-square criterion. The solution of the problem, considered in the paper, let us interpret how and - that is more important for us -when investor should rebalance the portfolio, if he wants to hedge it in the best way.
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Shi, Yuan, and 石园. "A portfolio approach to procurement planning and risk hedging under uncertainty." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44905051.

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Bouveret, Géraldine. "A contribution in hedging and portfolio optimisation under weak stochastic target constraints." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/33726.

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This thesis aims at investigating hedging and portfolio optimisation problems under weak stochastic target constraints. Our first contribution consists in the representation of the hedging price of some contingent claims under both probabilistic and expected shortfall ("weak") constraints holding on a set of dates. We consider a Markovian and complete market framework and favour a dual approach. This work is an extension to Föllmer and Leukert (1999,2000). We then extend the previous results to the case where the wealth process diffusion is semi-linear in the control/strategy variable. The previous convex duality machinery does not apply anymore and we rely on PDE arguments. Bouchard, Elie and Touzi (2009) already proved the PDE characterisation of such price functions but a comparison result, necessary to build a convergent numerical scheme, is still missing in the literature. We will prove that such a result actually holds. The main difficulty arises from the discontinuity of the operators involved in the PDE characterisation of the price function. An application to the quantile hedging of Bermudan options is provided. Our third contribution relies on the PDE characterisation of the problem of portfolio optimisation under a European quantile hedging constraint. We extend the results of Bouchard, Elie and Imbert (2010) to the case where the constraint holds in a weaker sense. The study is based on a reformulation of the initial constraint into an obstacle and almost-sure stochastic target one. This reduction is done by the introduction of an additional controlled state variable coming from the diffusion of the probability of reaching the target (see Bouchard, Elie and Touzi (2009)) and by means of the Geometric Dynamic Programming principle of Soner and Touzi (2002). However this additional controlled state variable raises non-trivial boundary conditions that have to be characterised. We also have to handle the discontinuity of the operators involved in the characterisation.
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Moumouni, Zoulkiflou. "Modeling and hedging strategies for agricultural commodities." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTD047/document.

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Sur les marchés agricoles, les producteurs encourent les risques de prix et de production ainsi que d'autres types de risques liés aux aléas de production. Ces risques impactent l'activité du producteur et pourraient diminuer ses revenus. La mondialisation des marchés, en particulier ceux des matières premières agricoles, permet de développer une stratégie de couverture en utilisant des instruments comme les contrats à terme. Cependant, la situation selon laquelle une position basée seulement sur un contrat futures devrait couvrir tous les risques, entraîne un marché incomplet. Le producteur en recherche de meilleure stratégie de couverture pour ajouter un contrat d'assurance ou d'option pour garantir davantage ses revenus, surtout lorsque les rendements des cultures prévus diminuent. Nous étudions, ici les stratégies de couverture dans le cadre statique, ainsi que dans le cadre de temps continu. Avant, nous analysons le comportement des prix des matières premières agricoles en utilisant diverses approches statistiques afin de suggérer la modélisation des prix adéquate aux données. La stratégie de couverture statique comprend également le processus de retournement de positions qui pourrait entraîner d'autres risques supplémentaires en raison de l'écart entre les nouveaux contrats à terme et des contrats à terme à proximité ainsi que la couverture inter-culture. Nous proposons une stratégie de couverture qui combine des contrats futures et d'assurance. Comme la prise de décisions dans le cadre statique ne tient pas compte des mouvements quotidiens de prix le long de l'horizon de couverture, la stratégie de couverture optimale en temps continu combine des positions en contrat à terme et options tout en prenant en compte les sauts et la saisonnalité dans la dynamique des prix
In agricultural markets, producers incur price and production risks as well as other risks related to production contingencies. These risks impact the producer activity and could decrease his income. The globalization of markets, particularly those of agricultural commodities, provides hedging instruments including futures contracts which will serve to develop a hedging strategy. However, the situation whereby a single futures contract-based positions could offset many risks leads to incomplete market. Especially, an producer looking for better hedging strategy could also include insurance, option contract or mutual funds to further guarantee his income, specially when crop yields are lower than expected.vspace{0.25cm}We investigate the hedging strategies in static framework as well as in continuous time framework. Prior, we analyze the behavior of agricultural prices using various statistical approaches and suggest appropriate price modeling for data at hands. The static hedging strategy also accounts for rollover process which gives raise to additional risks due to spread between new futures and nearby futures and inter-crop hedging. We particularly address hedging strategy that combines futures and insurance contracts. Since decisions making in static framework does not include price changes along the hedging horizon, optimal hedging strategy in continuous time framework will take into account jumps and seasonality by combining futures and option contracts
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Books on the topic "Portfolio hedging"

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Campbell, John Y. Global currency hedging. Cambridge, Mass: National Bureau of Economic Research, 2007.

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Adler, Michael. Hedging with futures in an intertemporal portfolio complex. Brussels: European Institute For Advanced Studies in Management, 1987.

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Stojanovic, Srdjan. Neutral and Indifference Portfolio Pricing, Hedging and Investing. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-0-387-71418-9.

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Park, Hun Y. Hedging in the portfolio theory framework: A note. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1987.

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1971-, Ferbert Wayne, ed. Buy and hedge: The 5 iron rules for investing over the long term. Upper Saddle River, N.J: FT Press, 2012.

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Greer, Robert J. The Handbook of Inflation Hedging Investments. New York: McGraw-Hill, 2006.

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Bychuk, Oleg V. Hedging market exposures: Identifying and managing market risks. Hoboken, N.J: Wiley, 2011.

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Keith, Schap, ed. Hedging financial instruments: A guide to basis trading for traders, investors, and portfolio managers. Chicago, Ill: Probus, 1988.

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Merrick, John J. Portfolio insurance with stock index futures. [Philadelphia]: Federal Reserve Bank of Philadelphia, 1987.

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N, Chorafas Dimitris. Derivative financial instruments: Bonds, swaps, options, hedging, and portfolio management. New York: McGraw-Hill, 2008.

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Book chapters on the topic "Portfolio hedging"

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Stojanovic, Srdjan. "Hedging." In Neutral and Indifference Portfolio Pricing, Hedging and Investing, 149–61. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-71418-9_5.

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Hult, Henrik, Filip Lindskog, Ola Hammarlid, and Carl Johan Rehn. "Quadratic Hedging Principles." In Risk and Portfolio Analysis, 39–83. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4103-8_3.

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Hünseler, Michael. "CDS: Hedging of Issuer and Counterparty Risks." In Credit Portfolio Management, 165–206. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9780230391505_7.

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van Deventer, Donald R. "Credit Derivatives and Hedging Credit Risk." In Advanced Bond Portfolio Management, 373–88. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119201151.ch15.

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Stojanovic, Srdjan. "Investment Portfolio Optimization." In Neutral and Indifference Portfolio Pricing, Hedging and Investing, 39–91. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-71418-9_3.

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Chevallier, Julien. "Risk-Hedging Strategies and Portfolio Management." In Econometric Analysis of Carbon Markets, 147–79. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2412-9_5.

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Martellini, Lionel, Philippe Priaulet, Frank J. Fabozzi, and Michael Luo. "Hedging Interest Rate Risk with Term Structure Factor Models." In Advanced Bond Portfolio Management, 267–89. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119201151.ch11.

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Alexander, Carol. "Hedging the Risk of an Energy Futures Portfolio." In Risk Management in Commodity Markets, 117–27. Chichester, West Sussex, UK: John Wiley & Sons, Ltd., 2012. http://dx.doi.org/10.1002/9781118467381.ch9.

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Stojanovic, Srdjan. "Background Material." In Neutral and Indifference Portfolio Pricing, Hedging and Investing, 1–18. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-71418-9_1.

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Stojanovic, Srdjan. "Simple Economies: Complete and Incomplete Markets." In Neutral and Indifference Portfolio Pricing, Hedging and Investing, 19–38. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-71418-9_2.

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Conference papers on the topic "Portfolio hedging"

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Thanekar, Gananjay Sandeep, and Zaheed Shamsuddin Shaikh. "Hedging The Portfolio Using Options Strategies." In 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2021. http://dx.doi.org/10.1109/icaccs51430.2021.9441986.

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Florianová, Hana. "THE PORTFOLIO SELECTION FOR A HEDGING STRATEGY." In 7th Economics & Finance Conference, Tel Aviv. International Institute of Social and Economic Sciences, 2017. http://dx.doi.org/10.20472/efc.2017.007.001.

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Liu, Yanwu, and Zhongzhen Zhang. "Mean-Absolute Deviation Optimization Model for Hedging Portfolio Selection Problems." In 2009 ETP International Conference on Future Computer and Communication (FCC). IEEE, 2009. http://dx.doi.org/10.1109/fcc.2009.51.

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Yuan, Jun. "Hedging Security Portfolio with Random Parameters in Stochastic Linear Quadratic Framework." In 2010 International Conference on Management and Service Science (MASS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icmss.2010.5577936.

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Huang, Xin, and Duan Li. "A Two-level Reinforcement Learning Algorithm for Ambiguous Mean-variance Portfolio Selection Problem." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/624.

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Traditional modeling on the mean-variance portfolio selection often assumes a full knowledge on statistics of assets' returns. It is, however, not always the case in real financial markets. This paper deals with an ambiguous mean-variance portfolio selection problem with a mixture model on the returns of risky assets, where the proportions of different component distributions are assumed to be unknown to the investor, but being constants (in any time instant). Taking into consideration the updates of proportions from future observations is essential to find an optimal policy with active learning feature, but makes the problem intractable when we adopt the classical methods. Using reinforcement learning, we derive an investment policy with a learning feature in a two-level framework. In the lower level, the time-decomposed approach (dynamic programming) is adopted to solve a family of scenario subcases where in each case the series of component distributions along multiple time periods is specified. At the upper level, a scenario-decomposed approach (progressive hedging algorithm) is applied in order to iteratively aggregate the scenario solutions from the lower layer based on the current knowledge on proportions, and this two-level solution framework is repeated in a manner of rolling horizon. We carry out experimental studies to illustrate the execution of our policy scheme.
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Wei, Jie, and Liyan Han. "Delta-neutral dynamic hedging of the HS300 stock index futures and option portfolio — The evidence from simulation." In EM). IEEE, 2009. http://dx.doi.org/10.1109/icieem.2009.5344336.

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Bielecki, Tomasz R., Areski Cousin, Stéphane Crépey, and Alexander Herbertsson. "A Bottom-Up Dynamic Model of Portfolio Credit Risk. Part II: Common-Shock Interpretation, Calibration and Hedging Issues." In International Workshop on Finance 2012. WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814571647_0003.

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Sebastian, Steffen, and Halil Memis. "Currency Hedging for International Real Estate Portfolios." In 26th Annual European Real Estate Society Conference. European Real Estate Society, 2019. http://dx.doi.org/10.15396/eres2019_166.

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Goldberg, Richard, James Read, Art Altman, and Remi Audouin. "Delta Hedging Energy Portfolios: an Exploratory Study." In 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07). IEEE, 2007. http://dx.doi.org/10.1109/hicss.2007.167.

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Xin, Ye, Zhang Lu, and Liu Ming-ming. "The performance of conditional hedging RMB for international portfolios." In 2010 International Conference on Management Science and Engineering (ICMSE). IEEE, 2010. http://dx.doi.org/10.1109/icmse.2010.5719951.

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Reports on the topic "Portfolio hedging"

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Rincón-Torres, Andrey Duván, Kimberly Rojas-Silva, and Juan Manuel Julio-Román. The Interdependence of FX and Treasury Bonds Markets: The Case of Colombia. Banco de la República, September 2021. http://dx.doi.org/10.32468/be.1171.

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We study the interdependence of FX and Treasury Bonds (TES) markets in Colombia. To do this, we estimate a heteroskedasticity identified VAR model on the returns of the COP/USD exchange rate (TRM) and bond prices, as well as event-analysis models for return volatilities, number of quotes, quote volume, and bid/ask spreads. The data under analysis consists of 5-minute intraday bid/ask US dollar prices and bond quotes, for an assortment of bond species. For these species we also have the number of bid/ask quotes as well as their volume. We found, also, that the exchange rate conveys information to the TES market, but the opposite does not completely hold: A one percent COP depreciation leads to a persistent reduction of TES prices between 0.05% and 0.22%. However, a 1% TES price increase has a very small effect and not entirely significant on the exchange rate, i.e. a COP appreciation between 0.001% and 0.009%. Furthermore, TRM return volatility increases do not affect bond return volatility but its liquidity, i.e. the bid/ask quote number and volume. These results are coherent with the fact that the FX market more efficiently reflects the effect of shocks than the TES market, which may be due to its low liquidity and concentration on a specific habitat. These results have implications for the design of financial stability policies as well as for private portfolio design, rebalancing and hedging.
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