Perfect Hedging Research Articles

Approximate utility

Approximating arbitrage or a perfect hedge in a limit implies approximation in utility (formally, expected utilities are continuous in L2), if and only if the utility function is bounded above and below by quadratics. We characterize when some special utility functions are continuous for all random consumptions with a common lower bound. Only linear, quadratic, and, in some cases, translated SAHARA utilities are continuous if there is no lower bound. We also characterize when a utility function defined on a convex subset can be extended to an L2-continuous nondecreasing and concave utility function on all of R.

Investment modeling between energy futures and responsible investment

This research examines the hedging and diversification ability of energy futures (crude oil, heating oil, natural gas, gasoline, carbon) concerning investment in four different segments of responsible investment. Wavelet coherence and DCC-GARCH are used to inspect the association and volatility transmission between them. Conditional correlation, optimum portfolio weights and hedge ratios are also calculated for real-time data and decomposed series to analyze the optimum portfolio structure. Our analysis reveals that energy futures are more efficient as a hedge to responsible investment during the short-run period. Natural gas is the perfect hedge against all the segments of responsible investment. Each segment of energy futures can hedge investments in sustainability stocks and green bonds. Carbon and Gasoline are not the perfect hedge for ESGL and GCEI but can be used as a cheap hedge. Our study will help responsible investors to hedge their portfolio risk using related assets, countering their familiarity bias.

Connectedness and portfolio hedging between NFTs segments, American stocks and cryptocurrencies Nexus

The paper examines the dynamic spillover and hedging effectiveness between five main segments of NFTs, which are Collectibles, Art, Game, Metaverse, and Utility, and the other asset classes namely Bitcoin and the American Stocks (S&P500). The study sample covers the period from April 27, 2018 to September 15, 2022. Using a Time-Varying connectedness approach through the TVP-VAR model and inspired by the Diebold and Yilmaz spillover index, the results show weak dynamic return spillovers between NFTs and the other assets, indicating that these new digital assets are still relatively decoupled from traditional asset and Bitcoin. We find also that Bitcoin is a major transmitter of spillover whereas Collectibles, Utility and S&P500 are net recipients of spillovers. Using the DCC-GARCH model, we extract the optimal weights, hedge ratios, and hedging effectiveness for the pairwise portfolios composed of S&P500/NFTs and Bitcoin/NFTs. The results indicate that investors and portfolio managers should consider adding NFTs in their portfolios of either S&P500 or Bitcoin to achieve diversification benefits. Finally, for Robustness Checks, we forecast the performance of the hedged versus the unhedged portfolios using the Long Short-Term Memory (LSTM) networks. Our findings confirm almost the results of the hedging effectiveness of NFTs and stem for the superiority of metaverse among these assets to serve as a perfect hedge.

Dynamic effect of Bitcoin, fintech and artificial intelligence stocks on eco-friendly assets, Islamic stocks and conventional financial markets: Another look using quantile-based approaches

Against the milieu of rapidly growing investment in technologically induced assets, this study examines the investment role of Bitcoin, fintech, and artificial intelligence (AI) stocks in relation to major environmentally friendly assets (green bonds, sustainable investments, and clean energy), Islamic stocks, and conventional financial markets using quantile-based approaches. To this end, we specifically examine the distributional and directional predictability between the returns of fintech, Bitcoin, and AI and various markets using the nonparametric causality-in-quantiles method and the cross-quantilogram correlation method respectively. We use daily data spanning March 9, 2018 to January 27, 2021. In terms of the distributional predictability of fintech, Bitcoin, and AI in relation to the traditional markets, Islamic stocks, clean energy stocks, and sustainable investments, we find strong evidence of causal asymmetry across quantiles and strong variations across markets. Likewise, findings in terms of directional predictability between the returns of fintech, Bitcoin, and AI and various markets infer that Islamic stocks act as a good hedge against Bitcoin. The S&P Treasury Bond and S&P Green Bond are also perfect hedges for fintech stocks, while S&P Global Clean Energy is a perfect hedge for AI stocks in terms of long-term dynamics.

Time-Frequency Connectedness between Shariah Indices in a Systemic Crisis Era

We examine the time- and frequency-domain spillover connectedness between regional and world Shariah indices. The spillover index approach is employed with data over the period from April 30, 2012, to May 9, 2022, for African, American, Asian, European, and world emerging and developed markets’ Shariah-based equity indices. The results indicate significant time- and frequency-dependent spillovers between Shariah indices. The world and developed markets’ Shariah indices transmit the greatest return spillover to their African and Asian counterparts, which act as net recipients of system spillovers. Our findings show that Asian Shariah assets are a perfect hedge against all relevant market shocks over the last decade. Our findings have implications for Shariah market regulators, investors, practitioners, and policymakers.

Cryptocurrencies versus environmentally sustainable assets: Does a perfect hedge exist?

In the wake of proliferation of cryptocurrencies and growing concerns regarding their environmental impact, we investigate the dynamic co-movement of digital assets and environmentally sustainable assets. We use daily data of five global indices from 01 March 2017 to 15 May 2022. The results suggest that environmentally sustainable indices and cryptocurrency indices demonstrate co-movements during pandemic. However, in the normal times, they mostly remain detached from each other. Therefore, it can be argued that both the asset classes can serve as hedge against each other. The findings carry important implications for the investment industry and regulators.

GENERALIZED FISHER HYPOTHESIS VALIDITY FOR CANADA, UK, AND SUISSE STOCK MARKETS: EVIDENCE FROM PANEL ARDL MODELS

In this paper we propose a decision support tool for the investor in terms of asset allocation. The key question is to know whether equities are perfect hedge against inflation if either we invest in only one market or if we go to all the considered markets. We chose three democratic countries having common monetary policy based on the Inflation rate stabilization targeting (including Canada, UK, and Suisse) over the period 1999M01-2018M04. We see how the stock return evolution is related to inflation rate Pre, during, and Post 2008 Global financial crisis (GFC). Then, some dynamic version of the Generalized Fisher hypothesis (GFH) models are explored by some univariate and panel autoregressive dynamic linear (ARDL) frameworks. We conclude that during crisis period, being on either Suisse or Canadian stock market, investors can have important abnormal gains. Then including the UK in a portfolio allows investors to limit losses caused by inflation in the UK stock market alone.

Generalized Fisher Hypothesis Validity for Canada, UK, and Suisse Stock Markets: Evidence from ARDL Models

In this paper we propose a decision support tool for the investor in terms of asset allocation. The key question is to know whether equities are perfect hedge against inflation. We chose three democratic countries having common monetary policy based on the Inflation rate stabilisation targeting (including Canada, UK, and Suisse) over the period 1999M01-2018M04. We see how the stock return evolution is related to inflation rate Pre, during, and Post 2008 Global financial crisis (GFC). Then, some dynamic version of the Generalized Fisher hypothesis (GFH) models is explored by some univariate autoregressive dynamic linear (ARDL) frameworks. We conclude that during crisis period, being on either Suisse or Canadian stock market, investors can have important abnormal gains. 

An integrated theory of dispatch and hedging in wholesale electric power markets

The literature on optimal dispatch of wholesale power systems implicitly assumes that market participants are risk-neutral. But, in practice, most wholesale electricity market participants behave as though they are risk averse, seeking to insulate themselves from the market risks they face. In this context, achieving the overall social-welfare maximum requires simultaneously finding both the optimal dispatch and optimal hedging arrangements. Assuming that market participants have mean–variance preferences, we show that the dispatch task can be separated from the hedging task. We show how market participants can achieve a perfect hedge by forming a portfolio of inter-temporal hedge contracts. Departing from the previous literature, we assume the system operator is risk averse. We show how the system operator can achieve a perfect hedge using a portfolio of inter-nodal hedging instruments which we refer to as generalised Financial Transmission Rights. The total risk experienced by market participants when optimally hedged is equal to the variation in the total surplus or total economic welfare. This approach therefore leads naturally to a form of merchant transmission investment where network upgrade decisions are carried out by a coalition of risk-bearers in the market. In addition, we propose a natural extension in which transmission network operators provide a form of insurance against network outages, and face the correct social incentive for avoiding network outages. This approach resolves a number of outstanding issues in the economic analysis of power markets.

Understanding the dual formulation for the hedging of path-dependent options with price impact

We consider a general path-dependent version of the hedging problem with price impact of Bouchard et al. (SIAM J. Control Optim. 57 (2019) 4125–4149), in which a dual formulation for the super-hedging price is obtained by means of PDE arguments, in a Markovian setting and under strong regularity conditions. Using only probabilistic arguments, we prove, in a path-dependent setting and under weak regularity conditions, that any solution to this dual problem actually allows one to construct explicitly a perfect hedging portfolio. From a pure probabilistic point of view, our approach also allows one to exhibit solutions to a specific class of second order forward backward stochastic differential equations, in the sense of Cheridito et al. (Comm. Pure Appl. Math. 60 (2007) 1081–1110). Existence of a solution to the dual optimal control problem is also addressed in particular settings. As a by-product of our arguments, we prove a version of Itô’s lemma for path-dependent functionals that are only C0,1 in the sense of Dupire.

IoT: For Maintaining a Health Care Record

In Arbitrage Theory, Hedging1 Strategy is an approach to eliminate the total risk, also known as Perfect hedge. Perfect Hedge will not be perfect solution to portfolio as they are exposed to market risk that can’t be controlled, therefore, financial firm and analysts opted for minimum loss strategy that is imperfectly hedged2 . A strategy where they hedge their share or portfolio in such a way that their client would suffer minimum loss instead of losing out on everything. The loss function will represent the performance of the market/ company. We will be looking at the market performance of COALINDIA3 of October 2021. A hedge that does not entirely eliminate market risk. Changes in the underlying position are not entirely reflected by changes in the hedge. This may be owing to timing issues or to the use of hedging instruments that are not entirely correlated to the underlying position.

A STOCHASTIC OIL PRICE MODEL FOR OPTIMAL HEDGING AND RISK MANAGEMENT

In this paper, we develop a stochastic model for future monthly spot prices of the most important crude oils and refined products. The model is easy to calibrate to both historical data and views of a user even in the presence of negative prices which have been observed recently. This makes it particularly useful for risk management and design of optimal hedging strategies in incomplete market situations where perfect hedging may be impossible or prohibitively expensive to implement. We illustrate the model with optimization of hedging strategies for refinery margins in illiquid markets using a portfolio of 12 most liquid derivative contracts with 12 maturities traded on New York Mercantile Exchange (NYMEX) and Intercontinental Exchange (ICE).

Quantile hedging in a defaultable market with life insurance applications

The paper is devoted to quantile hedging in a market with defaultable securities. Both perfect and quantile hedging strategies are given for a European call option on a vulnerable equity. Application of quantile methodology to pricing the equity-linked life insurance contracts is demonstrated. A numerical example is provided to illustrate the effect of a default on the option price, on the probability of successful hedging, and on the insurance-related variables.

Variance and Interest Rate Risk in Unit-Linked Insurance Policies

One of the risks derived from selling long-term policies that any insurance company has arises from interest rates. In this paper, we consider a general class of stochastic volatility models written in forward variance form. We also deal with stochastic interest rates to obtain the risk-free price for unit-linked life insurance contracts, as well as providing a perfect hedging strategy by completing the market. We conclude with a simulation experiment, where we price unit-linked policies using Norwegian mortality rates. In addition, we compare prices for the classical Black-Scholes model against the Heston stochastic volatility model with a Vasicek interest rate model.

Option Market Making with Inventory Risk: The Effect on Information Diffusion

This paper develops a model to study how option market makers' inventory and capital influence the relative informativeness of the option and stock markets. The model suggests that the option market maker's capital defines a lower bound for the option market informativeness. In addition, when perfect hedging is impossible, a larger inventory of sold (bought) options diminishes the informativeness of changes in the option's ask (bid) quote and increases the informativeness of changes in the option's bid (ask) quote. Finally, the model implies that noisy information is more likely to enter through the option market than the stock market. My empirical analysis provides stylized facts consistent with the model's key implications.

Optimal Hedging in Incomplete Markets

ABSTRACT We consider the problem of optimal hedging in an incomplete market with an established pricing kernel. In such a market, prices are uniquely determined, but perfect hedges are usually not available. We work in the rather general setting of a Lévy-Ito market, where assets are driven jointly by an n-dimensional Brownian motion and an independent Poisson random measure on an n-dimensional state space. Given a position in need of hedging and the instruments available as hedges, we demonstrate the existence of an optimal hedge portfolio, where optimality is defined by use of a least expected squared error criterion over a specified time frame, and where the numeraire with respect to which the hedge is optimized is taken to be the benchmark process associated with the designated pricing kernel.

Exchange Rate Exposure and Optimal Hedging Strategies when Interest Rates are Stochastic: a Simulation-Based Approach

In this paper i analyze the problem faced by an investor expecting to receive a cash flow in a foreign currency. The investor is assumed to be exposed to long-term exchange rate risk, having no access to long-term forward contracts to hedge perfectly. Under non stochastic interest rates the investor is able to hedge perfectly using short-term forward contracts, but perfect hedging is not possible when we consider interest rates to be stochastic. I present here a simulation-based methodology to obtain optimal hedging under stochastic interest rates (i.e. when perfect hedging can not be reached). Then, i explore how we quality of the hedging to be reached depends on some key factors such as the volatility of the exchange rate, the volatility of the interest rates, and the degree of correlation among the stochastic variables considered.

Optimal Hedging Under Fast-Varying Stochastic Volatility

In a market with a rough or Markovian mean-reverting stochastic volatility there is no perfect hedge. Here it is shown how various delta-type hedging strategies perform and can be evaluated in such...

Perfect hedging in rough Heston models

Rough volatility models are known to reproduce the behavior of historical volatility data while at the same time fitting the volatility surface remarkably well, with very few parameters. However, managing the risks of derivatives under rough volatility can be intricate since the dynamics involve fractional Brownian motion. We show in this paper that surprisingly enough, explicit hedging strategies can be obtained in the case of rough Heston models. The replicating portfolios contain the underlying asset and the forward variance curve, and lead to perfect hedging (at least theoretically). From a probabilistic point of view, our study enables us to disentangle the infinite-dimensional Markovian structure associated to rough volatility models.

Valuing bets and hedges: Implications for the construct of risk preference

AbstractRisk attitudes implied by valuations of risk-increasing assets depart markedly from those implied by valuations of risk-reducing assets. For instance, many are unwilling to pay the expected value for a risky asset or for its perfect hedge. Although nearly every theory of risk preference (and logic) demands a negative correlation between valuations of bets and hedges, we observe positive correlations. This inconsistency is difficult to expunge.