Relevant bibliographies by topics / Hedging Finance

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Hedging Finance'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Hedging Finance"

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Hamdi, Haykel, and Jihed Majdoub. "Risk-sharing finance governance: Islamic vs conventional indexes option pricing." Managerial Finance 44, no. 5 (May 14, 2018): 540–50. http://dx.doi.org/10.1108/mf-05-2017-0199.

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Purpose Risk governance has an important influence on the hedging performances in option pricing and portfolio hedging in both discrete and dynamic case for both conventional and Islamic indexes. The paper aims to discuss these issues. Design/methodology/approach This paper explores option pricing and portfolio hedging in a discrete and dynamic case with transaction costs. Monte Carlo simulations are applied to both conventional and Islamic indexes in US and UK markets. Simulations show that conventional and Islamic assets do not exhibit the same price and portfolio hedging strategy governance. Findings The authors conclude that Islamic assets show different option price and hedging strategy compared to their conventional counterpart. Originality/value The research question of this paper aims at filling the gap in the empirical literature by exploring option price and hedging structure for both conventional and Islamic indexes in US and UK stock markets.
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Stentoft, Lars. "Computational Finance." Journal of Risk and Financial Management 13, no. 7 (July 4, 2020): 145. http://dx.doi.org/10.3390/jrfm13070145.

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The field of computational finance is evolving ever faster. This book collects a number of novel contributions on the use of computational methods and techniques for modelling financial asset prices, returns, and volatility, and on the use of numerical methods for pricing, hedging, and risk management of financial instruments.
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Roig Hernando, Jaume. "Humanizing Finance by Hedging Property Values." Journal of Risk and Financial Management 9, no. 2 (June 10, 2016): 5. http://dx.doi.org/10.3390/jrfm9020005.

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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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Buehler, H., L. Gonon, J. Teichmann, and B. Wood. "Deep hedging." Quantitative Finance 19, no. 8 (February 21, 2019): 1271–91. http://dx.doi.org/10.1080/14697688.2019.1571683.

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Madan, Dilip B. "Adapted hedging." Annals of Finance 12, no. 3-4 (November 9, 2016): 305–34. http://dx.doi.org/10.1007/s10436-016-0282-8.

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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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Sun, Youfa, George Yuan, Shimin Guo, Jianguo Liu, and Steven Yuan. "Does model misspecification matter for hedging? A computational finance experiment based approach." International Journal of Financial Engineering 02, no. 03 (September 2015): 1550023. http://dx.doi.org/10.1142/s2424786315500231.

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To assess whether the model misspecification matters for hedging accuracy, we carefully select six increasingly complicated asset models, i.e., the Black–Scholes (BS) model, the Merton (M) model, the Heston (H) model, the Heston jump-diffusion (HJ) model, the double Heston (dbH) model and the double Heston jump-diffusion (dbHJ) model, and then impartially evaluate their performances in mitigating the risk of an option, under a controllable experimental market. In experiments, the ℙ measure asset paths are piecewisely simulated by a hybrid-model (including the Black–Scholes-type and the (double) Heston-type, with or without jump-diffusion term) with randomly given properly defined parameters. We access the hedging accuracy of six models within the operational dynamic hedging framework proposed by sun (2015), and apply the Fourier-COS-expansion method (i.e., the COS formula, Fang and Oosterlee (2008) to price options and to calculate the Greeks). Extensive numerical results indicate that the model misspecification shows no significant impact on hedging accuracy, but the market fit does matter critically for hedging.
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Korn, Olaf, and Marc Oliver Rieger. "Hedging with regret." Journal of Behavioral and Experimental Finance 22 (June 2019): 192–205. http://dx.doi.org/10.1016/j.jbef.2019.03.002.

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Bates, David S. "Hedging the smirk." Finance Research Letters 2, no. 4 (December 2005): 195–200. http://dx.doi.org/10.1016/j.frl.2005.08.004.

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Dissertations / Theses on the topic "Hedging Finance"

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Lindholm, Love. "Calibration and Hedging in Finance." Licentiate thesis, KTH, Numerisk analys, NA, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-156077.

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This thesis treats aspects of two fundamental problems in applied financial mathematics: calibration of a given stochastic process to observed marketprices on financial instruments (which is the topic of the first paper) and strategies for hedging options in financial markets that are possibly incomplete (which is the topic of the second paper). Calibration in finance means choosing the parameters in a stochastic process so as to make the prices on financial instruments generated by the process replicate observed market prices. We deal with the so called local volatility model which is one of the most widely used models in option pricing across all asset classes. The calibration of a local volatility surface to option marketprices is an ill-posed inverse problem as a result of the relatively small number of observable market prices and the unsmooth nature of these prices in strike and maturity. We adopt the practice advanced by some authors to formulate this inverse problem as a least squares optimization under the constraint that option prices follow Dupire’s partial differential equation. We develop two algorithms for performing the optimization: one based on techniques from optimal control theory and another in which a numerical quasi-Newton algorithmis directly applied to the objective function. Regularization of the problem enters easily in both problem formulations. The methods are tested on three months of daily option market quotes on two major equity indices.The resulting local volatility surfaces from both methods yield excellent replications of the observed market prices. Hedging is the practice of offsetting the risk in a financial instrument by taking positions in one or several other tradable assets. Quadratic hedging is a well developed theory for hedging contingent claims in incomplete markets by minimizing the replication error in a suitable L2-norm. This theory, though, is not widely used among market practitioners and relatively few scientific papers evaluate how well quadratic hedging works on real marketdata. We construct a framework for comparing hedging strategies, and use it to empirically test the performance of quadratic hedging of European call options on the Euro Stoxx 50 index modeled with an affine stochastic volatility model with and without jumps. As comparison, we use hedging in the standard Black-Scholes model. We show that quadratic hedging strategies significantly outperform hedging in the Black-Scholes model for out of the money options and options near the money of short maturity when only spot is used in the hedge. When in addition another option is used for hedging, quadratic hedging outperforms Black-Scholes hedging also for medium dated options near the money.
Den här avhandlingen behandlar aspekter av två fundamentala problem i tillämpad finansiell matematik: kalibrering av en given stokastisk process till observerade marknadspriser på finansiella instrument (vilket är ämnet för den första artikeln) och strategier för hedging av optioner i finansiella marknader som är inkompletta (vilket är ämnet för den andra artikeln). Kalibrering i finans innebär att välja parametrarna i en stokastisk process så att de priser på finansiella instrument som processen genererar replikerar observerade marknadspriser. Vi behandlar den så kallade lokala volatilitets modellen som är en av de mest utbrett använda modellerna inom options prissättning för alla tillgångsklasser. Kalibrering av en lokal volatilitetsyta till marknadspriser på optioner är ett illa ställt inverst problem som en följd av att antalet observerbara marknadspriser är relativt litet och att priserna inte är släta i lösenpris och löptid. Liksom i vissa tidigare publikationer formulerar vi detta inversa problem som en minsta kvadratoptimering under bivillkoret att optionspriser följer Dupires partiella differentialekvation. Vi utvecklar två algoritmer för att utföra optimeringen: en baserad på tekniker från optimal kontrollteori och en annan där en numerisk kvasi-Newton metod direkt appliceras på målfunktionen. Regularisering av problemet kan enkelt införlivas i båda problemformuleringarna. Metoderna testas på tre månaders data med marknadspriser på optioner på två stora aktieindex. De resulterade lokala volatilitetsytorna från båda metoderna ger priser som överensstämmer mycket väl med observerade marknadspriser. Hedging inom finans innebär att uppväga risken i ett finansiellt instrument genom att ta positioner i en eller flera andra handlade tillgångar. Kvadratisk hedging är en väl utvecklad teori för hedging av betingade kontrakt i inkompletta marknader genom att minimera replikeringsfelet i en passande L2-norm. Denna teori används emellertid inte i någon högre utsträckning av marknadsaktörer och relativt få vetenskapliga artiklar utvärderar hur väl kvadratisk hedging fungerar på verklig marknadsdata. Vi utvecklar ett ramverk för att jämföra hedgingstrategier och använder det för att empiriskt pröva hur väl kvadratisk hedging fungerar för europeiska köpoptioner på aktieindexet Euro Stoxx 50 när det modelleras med en affin stokastisk volatilitetsmodell med och utan hopp. Som jämförelse använder vi hedging i Black-Scholes modell.Vi visar att kvadratiska hedgingstrategier är signifikant bättre än hedging i Black-Scholes modell för optioner utanför pengarna och optioner nära pengarna med kort löptid när endast spot används i hedgen. När en annan option används i hedgen utöver spot är kvadratiska hedgingstrategier bättre än hedging i Black-Scholes modell även för optioner nära pengarna medmedellång löptid.

QC 20141121

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Nance, Deana R. (Deana Reneé). "The Determinants of Off-Balance-Sheet Hedging in the Value-Maximizing Firm: an Empirical Analysis." Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc331494/.

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The observed use (and indeed tremendous growth in volume) of forward contracts, futures, options, and swaps as hedges against interest rate risk, foreign exchange risk, and commodity price risk indicates that hedging does add value to the firm. The purpose this research was to empirically examine the value of off-balance-sheet hedging. The benefits of off-balance-sheet hedging were found to accrue from reducing (1) taxes, (2) expected financial distress costs, and (3) agency costs. Taxes. Hedging reduces the firm's tax liability by reducing the variability in taxable income. The value of hedging to the firm is a positive function of the convexity of the tax function and the variability of taxable income. Expected Financial Distress Costs. The value of hedging is a positive function of the degree to which hedging reduces the probability of financial distress and the costs of financial distress. Agency Cost. Due to the fact that bondholders and some managers hold fixed claims while shareholders hold variable claims, shareholders desire more risky projects than do bondholders or managers. Hedging reduces this conflict by allowing shareholders to undertake higher risk projects while protecting the holders of fixed claims. Firms can achieve the same benefits of hedging by using alternative strategies. Among the various alternatives to hedging are modifying the firm's capital structure, purchasing insurance, and modifying dividend policy. The amount of off-balance-sheet hedging activity undertaken by a specific firm is therefore a function of the value of hedging to the firm and the degree to which the firm has used alternatives to hedging. Using a regression analysis, this paper provides empirical evidence on the preceding relations. This study provides (1) the first empirical evidence into the reasons for a value-maximizing firm using off-balance-sheet hedging instruments, and (2) empirical insights into the way in which the firm's hedging decision interrelates with the capital structure, dividend, and insurance decisions.
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Yick, Ho-yin. "Theories on derivative hedging." Click to view the E-thesis via HKUTO, 2004. http://sunzi.lib.hku.hk/hkuto/record/B30703530.

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Ogg, Richard. "Hedging volatility: different perspectives compared." Master's thesis, Faculty of Commerce, 2020. http://hdl.handle.net/11427/32900.

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The accuracy of the Black and Scholes (1973) delta and vega neutral portfolio for a vanilla option was compared to a benchmark set by the Heston (1993) model in a stochastic volatility environment. The Black-Scholes portfolio was implemented using a fixed volatility and by implying volatility from the market. Additionally, a portfolio based on the Dupire (1994) local volatility model was also compared. It was found that a portfolio consisting of two short maturity options with matching maturities was best hedged by the Black-Scholes model when using implied volatility. This result was not maintained when the two options had mismatching maturities as the proportional differences in the vegas no longer cancelled. Further examination was completed on the type of financial instruments used to hedge volatility, comparing portfolios that consisted of an additional option and a variance swap to offset any vega. It was found that both hedged the option well, with similar accuracies.
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Yick, Ho-yin, and 易浩然. "Theories on derivative hedging." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30703530.

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Haria, Krisan. "New developments in hedging in finance and insurance." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.441279.

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Ziervogel, Graham. "Hedging performance of interest-rate models." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/20482.

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This dissertation is a hedging back-study which assesses the effectiveness of interest- rate modelling and the hedging of interest-rate derivatives. Caps that trade in the Johannesburg swap market are hedged using two short-rate models, namely the Hull and White (1990) one-factor model and the subsequent Hull and White (1994) two-factor extension. This is achieved by using the equivalent Gaussian additive-factor models (G1++ and G2++) outlined by Brigo and Mercurio (2007). The hedges are constructed using different combinations of theoretical zero-coupon bonds. A flexible factor hedging method is proposed by the author and the bucket hedging technique detailed by Driessen, Klaasen and Melenberg (2003) is tested. The results obtained support the claims made by Gupta and Subrahmanyam (2005), Fan, Gupta and Ritchken (2007) and others in the literature that multi-factor models outperform one-factor models in hedging interest-rate derivatives. It is also shown that the choice of hedge instruments can significantly influence hedge performance. Notably, a larger set of hedge instruments and the use of hedge instruments with the same maturity as the derivative improve hedging accuracy. However, no evidence to support the finding of Driessen et al. (2003) that a larger set of hedge instruments can remove the need for a multi-factor model is found.
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Kauppila, M. (Mikko). "Hedge fund tail risk:performance and hedging mechanisms." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201412042095.

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The goal of this master’s thesis is to understand the performance implications of hedge fund’s tail risk, and the mechanisms of how some funds achieve lower tail risk. The current evidence on the performance implications is mixed, with most empirical hedge fund studies suggesting higher returns to higher risk. This is not obvious since the goal of skillful hedge fund managers is to deliver positive risk-adjusted returns, and indeed a few studies do report higher returns to lower risk. The issue is further complicated by the evidence of asset-level low-risk anomalies, which could create a low-skill alternative for managers to achieving higher returns with lower risk. Using a consolidation of commercial hedge fund databases, we decompose hedge fund tail risk, conditional on market distress, into two components: Systematic Conditional Tail Risk (SCTR) arising predictably via equity market exposure, and Idiosyncratic Conditional Tail Risk (ICTR) arising from unpredictable, proprietary alpha investment technology. First, using a subset of large, 13F-HR matched hedge funds from March 2000 to June 2013, we show that especially low-ICTR hedge funds deliver superior future risk-adjusted returns. In contrast to existing hedge fund literature our results support the broader view in asset-pricing literature that low risk is associated with higher risk-adjusted returns. The results are robust to the inclusion of additional risk factors, including a low-risk factor, suggesting that the better performance could be due to skillful hedging rather than harvesting of low-risk anomalies. This skill hypothesis is further supported by the finding that low-risk funds charge higher incentive fees, consistent with economic theory. To further resolve the puzzle of whether low-risk funds outperform high-risk funds, using a large set of funds from January 1994 to June 2013, we run a comprehensive “horse race” between our risk measures and a replication of a large array of existing risk measures. Our results show that for many existing risk measures, the purported risk premium largely diminishes when controlling fund size, suggesting that existing results may be somewhat driven by the inclusion of smaller funds. Our measures SCTR and ICTR consistently show low-risk funds outperforming high-risk funds. Second, using 13F-HR option holdings data from March 1999 to June 2013, we investigate the underlying hedging mechanism implemented by low tail risk hedge funds. We demonstrate that low-SCTR funds allocate a high fraction of their wealth — consistently over time — to protective option strategies, while low-ICTR funds use costly protective strategies only during the financial crisis. Funds with low ICTR also employ more stock, but not index, options, which fits the idiosyncratic nature of the measure. After the financial crisis, volatility-linked Exchange Traded Products (ETPs) have emerged as a potential alternative to hedging tail risk. We show that, from April 2009 to June 2013, the use of such volatility-linked ETPs is associated with lower SCTR but not ICTR, consistent with the option result, and indeed suggesting a complementary hedging mechanism.
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Zheng, Wendong. "Hedging and pricing of constant maturity swap derivatives /." View abstract or full-text, 2009. http://library.ust.hk/cgi/db/thesis.pl?MATH%202009%20ZHENG.

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Mavuso, Melusi Manqoba. "Mean-variance hedging in an illiquid market." Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/15595.

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Consider a market consisting of two correlated assets: one liquidly traded asset and one illiquid asset that can only be traded at time 0. For a European derivative written on the illiquid asset, we find a hedging strategy consisting of a constant (time 0) holding in the illiquid asset and dynamic trading strategies in the liquid asset and a riskless bank account that minimizes the expected square replication error at maturity. This mean-variance optimal strategy is first found when the liquidly traded asset is a local martingale under the real world probability measure through an application of the Kunita-Watanabe projection onto the space of attainable claims. The result is then extended to the case where the liquidly traded asset is a continuous square integrable semimartingale, and we again use the Kunita-Watanabe decomposition, now under the variance optimal martingale measure, to find the mean-variance optimal strategy in feedback form. In an example, we consider the case where the two assets are driven by correlated Brownian motions and the derivative is a call option on the illiquid asset. We use this example to compare the terminal hedging profit and loss of the optimal strategy to a corresponding strategy that does not use the static hedge in the illiquid asset and conclude that the use of the static hedge reduces the expected square replication error significantly (by up to 90% in some cases). We also give closed form expressions for the expected square replication error in terms of integrals of well-known special functions.
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Books on the topic "Hedging Finance"

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Rheinländer, Thorsten. Hedging derivatives. New Jersey: World Scientific, 2011.

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Haughey, Brian J. Hedging Irish Options. Dublin: University College Dublin, 1990.

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Miller, Sennholz Lyn, and Helstrom Carl O, eds. Options hedging handbook. Cedar Falls, IA: Center for Futures Education, 1985.

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Eades, Simon. Options, hedging & arbitrage. London: McGraw-Hill, 1992.

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Reichling, Peter. Hedging mit Warenterminkontrakten. Bern: P. Haupt, 1991.

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Miron, Paul. Pricing and hedging swaps. London: Euromoney Books, 1991.

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Rozanov, Andrew, and Ryan McRandal. Tail risk hedging. London: Risk Books, 2014.

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Merrick, John J. Hedging with mispriced futures. [Philadelphia]: Federal Reserve Bank of Philadelphia, 1987.

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Langowski, Larry. Hedging mortgage servicing rights. Chicago: Market and Product Development, Chicago Board of Trade, 1999.

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Orol, Ronald D. Extreme value hedging: How activist hedge fund managers are taking on the world. Hoboken, N.J: Wiley, 2008.

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Book chapters on the topic "Hedging Finance"

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Connor, Gregory. "Hedging." In Finance, 164–71. London: Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-20213-3_18.

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Eberlein, Ernst, and Jan Kallsen. "Mean-Variance Hedging." In Springer Finance, 595–615. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26106-1_12.

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Newbery, David M. "Futures Markets, Hedging and Speculation." In Finance, 145–52. London: Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-20213-3_15.

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Hatherley, Anthony. "Hedging Asymmetric Dependence." In Asymmetric Dependence in Finance, 110–32. Chichester, UK: John Wiley & Sons Ltd, 2018. http://dx.doi.org/10.1002/9781119288992.ch5.

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Härri, Matthias. "Electricity Trading with Derivative Instruments: Speculation, Hedging, or Speculative Hedging?" In Finance in Crises, 159–75. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-48071-3_11.

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Davis, Mark H. A., Walter Schachermayer, and Robert G. Tompkins. "Installment Options and Static Hedging." In Mathematical Finance, 130–39. Basel: Birkhäuser Basel, 2001. http://dx.doi.org/10.1007/978-3-0348-8291-0_12.

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Willsher, Richard. "Currency Risk and Hedging Techniques." In Export Finance, 139–42. London: Palgrave Macmillan UK, 1995. http://dx.doi.org/10.1007/978-1-349-13980-4_16.

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Lee, Raymond S. T. "Quantum Trading and Hedging Strategy." In Quantum Finance, 119–58. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9796-8_6.

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Vasigh, Bijan, and Zane C. Rowe. "Airline fuel hedging practice." In Foundations of Airline Finance, 473–515. Third edition. | Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429429293-11.

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Bielecki, Tomasz R., and Stéphane Crépey. "Dynamic Hedging of Counterparty Exposure." In Inspired by Finance, 47–71. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02069-3_3.

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Conference papers on the topic "Hedging Finance"

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Kurmanova, L. "Hedging Market Risks." In International Conference on Finance, Entrepreneurship and Technologies in Digital Economy. European Publisher, 2021. http://dx.doi.org/10.15405/epsbs.2021.03.28.

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Gao, Kang, Stephen Weston, Perukrishnen Vytelingum, Namid Stillman, Wayne Luk, and Ce Guo. "Deeper Hedging: A New Agent-based Model for Effective Deep Hedging." In ICAIF '23: 4th ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3604237.3626913.

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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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Costa, O. L. V., A. C. Maiali, and A. de C. Pinto. "Mean-variance hedging strategies in discrete time and continuous state space." In COMPUTATIONAL FINANCE 2006. Southampton, UK: WIT Press, 2006. http://dx.doi.org/10.2495/cf060111.

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Fukasawa, Masaaki. "Conservative Delta Hedging under Transaction Costs." In Proceedings of the International Workshop on Finance 2011. WORLD SCIENTIFIC, 2012. http://dx.doi.org/10.1142/9789814407335_0004.

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Daluiso, Roberto, Marco Pinciroli, Michele Trapletti, and Edoardo Vittori. "CVA Hedging with Reinforcement Learning." In ICAIF '23: 4th ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3604237.3626852.

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Murray, Phillip, Ben Wood, Hans Buehler, Magnus Wiese, and Mikko Pakkanen. "Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions." In ICAIF '22: 3rd ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3533271.3561731.

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Tong, Anh, Thanh Nguyen-Tang, Dongeun Lee, Toan M. Tran, and Jaesik Choi. "SigFormer: Signature Transformers for Deep Hedging." In ICAIF '23: 4th ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3604237.3626841.

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Grépat, J. "On the Limit Behavior of Option Hedging Sets under Transaction Costs." In International Workshop on Finance 2012. WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814571647_0004.

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Vittori, Edoardo, Michele Trapletti, and Marcello Restelli. "Option hedging with risk averse reinforcement learning." In ICAIF '20: ACM International Conference on AI in Finance. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3383455.3422532.

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Reports on the topic "Hedging Finance"

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Arif, Muhammad, Muhammad Abubakr Naeem, Saqib Farid, Rabindra Nepal, and Tooraj Jamasb. Diversifier or More? Hedge and Safe Haven Properties of Green Bonds During COVID-19. Copenhagen School of Energy Infrastructure, 2021. http://dx.doi.org/10.22439/csei.pb.010.

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The COVID-19 pandemic represents a global case of the fragility of the financial markets and vulnerability of natural disasters and exceptional risks. Against the backdrop of the COVID-19 pandemic, this study explores the ‘hedging’ and ‘safe-haven’ potential of green bonds for conventional equity, fixed income, commodity, and forex investments. Our results show that the green bond index could serve as a diversifier asset for medium- and long-term equity investors. It can also serve as a hedging and safe haven instrument for currency and commodity investments. This study is the first to provide evidence on the hedging and safe-haven potential of green bonds during the COVID-19 pandemic. Our findings imply that green bonds could play a constructive role in global financial recovery efforts without compromising the low-carbon transition targets as they can also be a source of finance for green energy.
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León, John Jairo, Leandro Gaston Andrian, and Jorge Mondragón. Optimal Commodity Price Hedging. Banco Interamericano de Desarrollo, December 2022. http://dx.doi.org/10.18235/0004649.

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The dependence of many countries in the region on oil exports makes them vulnerable to oil price volatility. In particular, the sharp declines observed between 2014 and 2016 show how public finances weakened with significant debt increases in these countries. A strategy to mitigate the effect of sharp falls in oil prices would allow oil exporting countries to suffer a smaller impact on their public finances. This paper shows that using put options to insure against oil price hikes lowers public debt and fiscal deficits.
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