arXiv daily: Mathematical Finance (q-fin.MF)

Authors:Michael Preisel

Abstract: Being a long-term investor has become an argument by itself to sustain larger allocations to risky assets, but - although intuitively appealing - it is rarely stated exactly why capital markets would provide a better opportunity set to investors with long investment horizons than to other investors. In this paper, it is shown that if in fact the equity risk-premium is slowly mean-reverting then an investor committing to a long-term deterministic investment strategy would realize a better risk-return trade-off in a mean-variance optimization than investors with shorter investment horizons. It is well known that the problem of mean-variance optimization cannot be solved by dynamic programming. Instead, the principle of Calculus of Variations is applied to derive an Euler-Lagrange equation characterizing the optimal investment strategy. It is a main result that the optimization problem is equivalent to a spectral problem by which explicit solutions to the optimal investment strategy can be derived for an equilibrium market of bonds and equity. In this setting, the paper contributes to portfolio choice in continuous time in the tradition of Markowitz.

Authors:Chonghu Guan, Zuo Quan Xu

Abstract: This paper is concerned with a long standing optimal dividend payout problem in insurance subject to the so-called ratcheting constraint, that is, the dividend payout rate shall be non-decreasing over time. The surplus process is modeled by a drifted Brownian motion process and the aim is to find the optimal dividend ratcheting strategy to maximize the expectation of the total discounted dividend payouts until the ruin time. Due to the path-dependent constraint, the standard control theory cannot be directly applied to tackle the problem. The related Hamilton-Jacobi-Bellman (HJB) equation is a new type of variational inequality. In the literature, it is only shown to have a viscosity solution, which is not strong enough to guarantee the existence of an optimal dividend ratcheting strategy. This paper proposes a novel partial differential equation method to study the HJB equation. We not only prove the the existence and uniqueness of the solution in some stronger functional space, but also prove the monotonicity, boundedness, and $C^{\infty}$-smoothness of the dividend ratcheting free boundary. Based on these results, we eventually derive an optimal dividend ratcheting strategy, and thus solve the open problem completely. Economically, we find that if the surplus volatility is above an explicit threshold, then one should pay dividends at the maximum rate, regardless the surplus level. Otherwise, by contrast, the optimal dividend ratcheting strategy relays on the surplus level and one should only ratchet up the dividend payout rate when the surplus level touches the dividend ratcheting free boundary.

Authors:Elisa Alòs, Eulalia Nualart, Makar Pravosud

Abstract: In this paper we study the short-time behavior of the at-the-money implied volatility for European and arithmetic Asian call options with fixed strike price. The asset price is assumed to follow the Bachelier model with a general stochastic volatility process. Using techniques of the Malliavin calculus such as the anticipating It\^o's formula we first compute the level of the implied volatility when the maturity converges to zero. Then, we find a short maturity asymptotic formula for the skew of the implied volatility that depends on the roughness of the volatility model. We apply our general results to the SABR and fractional Bergomi models, and provide some numerical simulations that confirm the accurateness of the asymptotic formula for the skew.

Authors:Benjamin Joseph, Gregoire Loeper, Jan Obloj

Abstract: We develop and implement a non-parametric method for joint exact calibration of a local volatility model and a correlated stochastic short rate model using semimartingale optimal transport. The method relies on the duality results established in Joseph, Loeper, and Obloj, 2023 and jointly calibrates the whole equity-rate dynamics. It uses an iterative approach which starts with a parametric model and tries to stay close to it, until a perfect calibration is obtained. We demonstrate the performance of our approach on market data using European SPX options and European cap interest rate options. Finally, we compare the joint calibration approach with the sequential calibration, in which the short rate model is calibrated first and frozen.

Authors:Yan Dolinsky, Or Zuk

Abstract: In this work we consider the exponential utility maximization problem in the framework of semistatic hedging.

Authors:Claude Martini, Arianna Mingone

Abstract: We observe that a European Call option with strike $L > K$ can be seen as a Call option with strike $L-K$ on a Call option with strike $K$. Under no arbitrage assumptions, this yields immediately that the prices of the two contracts are the same, in full generality. We study in detail the relative pricing function which gives the price of the Call on Call option as a function of its underlying Call option, and provide quasi-closed formula for those new pricing functions in the Carr-Pelts-Tehranchi family [Carr and Pelts, Duality, Deltas, and Derivatives Pricing, 2015] and [Tehranchi, A Black-Scholes inequality: applications and generalisations, Finance Stoch, 2020] that includes the Black-Scholes model as a particular case. We also study the properties of the function that maps the price normalized by the underlier, viewed as a function of the moneyness, to the normalized relative price, which allows us to produce several new closed formulas. In connection to the symmetry transformation of a smile, we build a lift of the relative pricing function in the case of an underlier that does not vanish. We finally provide some properties of the implied volatility smiles of Calls on Calls and lifted Calls on Calls in the Black-Scholes model.

Authors:Robert Denkert, Ulrich Horst

Abstract: We consider extended mean-field control problems with multi-dimensional singular controls. A key challenge when analysing singular controls are jump costs. When controls are one-dimensional, jump costs are most naturally computed by linear interpolation. When the controls are multi-dimensional the situation is more complex, especially when the model parameters depend on an additional mean-field interaction term, in which case one needs to "jointly" and "consistently" interpolate jumps both on a distributional and a pathwise level. This is achieved by introducing the novel concept of two-layer parametrisations of stochastic processes. Two-layer parametrisations allow us to equivalently rewrite rewards in terms of continuous functions of parametrisations of the control process and to derive an explicit representation of rewards in terms of minimal jump costs. From this we derive a DPP for extended mean-field control problems with multi-dimensional singular controls. Under the additional assumption that the value function is continuous we characterise the value function as the minimal super-solution to a certain quasi-variational inequality in the Wasserstein space.

Authors:Paul Krühner, Shijie Xu

Abstract: This paper is concerned with finite dimensional models for the entire term structure for energy futures. As soon as a finite dimensional set of possible yield curves is chosen, one likes to estimate the dynamic behaviour of the yield curve evolution from data. The estimated model should be free of arbitrage which is known to result in some drift condition. If the yield curve evolution is modelled by a diffusion, then this leaves the diffusion coefficient open for estimation. From a practical perspective, this requires that the chosen set of possible yield curves is compatible with any obtained diffusion coefficient. In this paper, we show that this compatibility enforces an affine geometry of the set of possible yield curves.

Authors:Ivan Guo, Shijia Jin, Kihun Nam

Abstract: We propose the macroscopic market making model \`a la Avellaneda-Stoikov, using continuous processes for orders instead of discrete point processes. The model intends to bridge a gap between market making and optimal execution problems, while shedding light on the influence of order flows on the strategy. We demonstrate our model through three problems. The study provides a comprehensive analysis from Markovian to non-Markovian noises and from linear to non-linear intensity functions, encompassing both bounded and unbounded coefficients. Mathematically, the contribution lies in the existence and uniqueness of the optimal control, guaranteed by the well-posedness of the Hamilton-Jacobi-Bellman equation or the (non-)Lipschitz forward-backward stochastic differential equation.

Authors:Peter Bank, Christian Bayer, Peter K. Friz, Luca Pelizzari

Abstract: In this work, we introduce a novel pricing methodology in general, possibly non-Markovian local stochastic volatility (LSV) models. We observe that by conditioning the LSV dynamics on the Brownian motion that drives the volatility, one obtains a time-inhomogeneous Markov process. Using tools from rough path theory, we describe how to precisely understand the conditional LSV dynamics and reveal their Markovian nature. The latter allows us to connect the conditional dynamics to so-called rough partial differential equations (RPDEs), through a Feynman-Kac type of formula. In terms of European pricing, conditional on realizations of one Brownian motion, we can compute conditional option prices by solving the corresponding linear RPDEs, and then average over all samples to find unconditional prices. Our approach depends only minimally on the specification of the volatility, making it applicable for a wide range of classical and rough LSV models, and it establishes a PDE pricing method for non-Markovian models. Finally, we present a first glimpse at numerical methods for RPDEs and apply them to price European options in several rough LSV models.

Authors:Christian Yeo

Abstract: Least Squares regression was first introduced for the pricing of American-style options, but it has since been expanded to include swing options pricing. The swing options price may be viewed as a solution to a Backward Dynamic Programming Principle, which involves a conditional expectation known as the continuation value. The approximation of the continuation value using least squares regression involves two levels of approximation. First, the continuation value is replaced by an orthogonal projection over a subspace spanned by a finite set of $m$ squared-integrable functions (regression functions) yielding a first approximation $V^m$ of the swing value function. In this paper, we prove that, with well-chosen regression functions, $V^m$ converges to the swing actual price $V$ as $m \to + \infty$. A similar result is proved when the regression functions are replaced by neural networks. For both methods (least squares or neural networks), we analyze the second level of approximation involving practical computation of the swing price using Monte Carlo simulations and yielding an approximation $V^{m, N}$ (where $N$ denotes the Monte Carlo sample size). Especially, we prove that $V^{m, N} \to V^m$ as $N \to + \infty$ for both methods and using Hilbert basis in the least squares regression. Besides, a convergence rate of order $\mathcal{O}\big(\frac{1}{\sqrt{N}} \big)$ is proved in the least squares case. Several convergence results in this paper are based on the continuity of the swing value function with respect to cumulative consumption, which is also proved in the paper and has not been yet explored in the literature before for the best of our knowledge.

Authors:Samuel Solgon Santos, Marlon Ruoso Moresco, Marcelo Brutti Righi, Eduardo de Oliveira Horta

Abstract: We present simple general conditions on the acceptance sets under which their induced monetary risk and deviation measures are comonotonic additive. We show that acceptance sets induce comonotonic additive risk measures if and only if the acceptance sets and their complements are stable under convex combinations of comonotonic random variables. A generalization of this result applies to risk measures that are additive for random variables with \textit{a priori} specified dependence structures, e.g., perfectly correlated, uncorrelated, or independent random variables.

Authors:Shuaijie Qian, Chen Yang

Abstract: This paper studies a finite-horizon portfolio selection problem with non-concave terminal utility and proportional transaction costs. The commonly used concavification principle for terminal value is no longer valid here, and we establish a proper theoretical characterization of this problem. We first give the asymptotic terminal behavior of the value function, which implies any transaction close to maturity only provides a marginal contribution to the utility. After that, the theoretical foundation is established in terms of a novel definition of the viscosity solution incorporating our asymptotic terminal condition. Via numerical analyses, we find that the introduction of transaction costs into non-concave utility maximization problems can prevent the portfolio from unbounded leverage and make a large short position in stock optimal despite a positive risk premium and symmetric transaction costs.

Authors:Hsin-Lun Li

Abstract: A money transfer involves a buyer and a seller. A buyer buys goods or services from a seller. The money the buyer decreases is the same as that the seller increases. At each time step, a pair of socially connected agents are selected and transact in agreed money. We evolve the Deffuant model to a money exchange system and study circumstances under which asymptotic stability holds, or equal wealth can be achieved.

Authors:Tongseok Lim

Abstract: The Black-Scholes-Merton model is a mathematical model for the dynamics of a financial market that includes derivative investment instruments, and its formula provides a theoretical price estimate of European-style options. The model's fundamental idea is to eliminate risk by hedging the option by purchasing and selling the underlying asset in a specific way, that is, to replicate the payoff of the option with a portfolio (which continuously trades the underlying) whose value at each time can be verified. One of the most crucial, yet restrictive, assumptions for this task is that the market follows a geometric Brownian motion, which has been relaxed and generalized in various ways. The concept of robust finance revolves around developing models that account for uncertainties and variations in financial markets. Martingale Optimal Transport, which is an adaptation of the Optimal Transport theory to the robust financial framework, is one of the most prominent directions. In this paper, we consider market models with arbitrarily many underlying assets whose values are observed over arbitrarily many time periods, and demonstrates the existence of a portfolio sub- or super-hedging a general path-dependent derivative security in terms of trading European options and underlyings, as well as the portfolio replicating the derivative payoff when the market model yields the extremal price of the derivative given marginal distributions of the underlyings. In mathematical terms, this paper resolves the question of dual attainment for the multi-period vectorial martingale optimal transport problem.

Authors:Fausto Di Biase, Stefano Di Rocco, Alessandra Ortolano, Maurizio Parton

Abstract: The Consumer Financial Protection Bureau defines the notion of payoff amount as the amount that has to be payed at a particular time in order to completely pay off the debt, in case the lender intends to pay off the loan early, way before the last installment is due (CFPB 2020). This amount is well-understood for loans at compound interest, but much less so when simple interest is used. Recently, Aretusi and Mari (2018) have proposed a formula for the payoff amount for loans at simple interest. We assume that the payoff amounts are established contractually at time zero, whence the requirement that no arbitrage may arise this way The first goal of this paper is to study this new formula and derive it within a model of a loan market in which loans are bought and sold at simple interest, interest rates change over time, and no arbitrage opportunities exist. The second goal is to show that this formula exhibits a behaviour rather different from the one which occurs when compound interest is used. Indeed, we show that, if the installments are constant and if the interest rate is greater than a critical value (which depends on the number of installments), then the sequence of the payoff amounts is increasing before a certain critical time, and will start decreasing only thereafter. We also show that the critical value is decreasing as a function of the number of installments. For two installments, the critical value is equal to the golden section. The third goal is to introduce a more efficient polynomial notation, which encodes a basic tenet of the subject: Each amount of money is embedded in a time position (to wit: The time when it is due). The model of a loan market we propose is naturally linked to this new notation.

Authors:Damir Filipovic

Abstract: Discount is the difference between the face value of a bond and its present value. I propose an arbitrage-free dynamic framework for discount models, which provides an alternative to the Heath--Jarrow--Morton framework for forward rates. I derive general consistency conditions for factor models, and discuss affine term structure models in particular. There are several open problems, and I outline possible directions for further research.

Authors:Xin Hai, Kihun Nam

Abstract: We refer to recent inference methodology and formulate a framework for solving the distributionally robust optimization problem, where the true probability measure is inside a Wasserstein ball around the empirical measure and the radius of the Wasserstein ball is determined by the empirical data. We transform the robust optimization into a non-robust optimization with a penalty term and provide the selection of the Wasserstein ambiguity set's size. Moreover, we apply this framework to the robust mean-CVaR optimization problem and the numerical experiments of the US stock market show impressive results compared to other popular strategies.

Authors:E. Alòs, F. Rolloos, K. Shiraya

Abstract: In the short time to maturity limit it is proved that for the conditionally lognormal SABR model the zero vanna implied volatility is a lower bound for the volatility swap strike. The result is valid for all values of the correlation parameter and is a sharper lower bound than the at-the-money implied volatility for correlation less than or equal to zero.

Authors:David Criens, Mikhail Urusov

Abstract: Consider a single asset financial market whose discounted asset price process is a stochastic integral with respect to a continuous regular strong Markov semimartingale (a so-called general diffusion semimartingale) that is parameterized by a scale function and a speed measure. In a previous paper, we established a characterization of the no free lunch with vanishing risk (NFLVR) condition for a canonical framework of such a financial market in terms of the scale function and the speed measure. Ioannis Karatzas (personal communication) asked us whether it is also possible to prove a characterization for the weaker no unbounded profit with bounded risk (NUPBR) condition, which is the main question we treat in this paper. Here, we do not restrict our attention to canonical frameworks but we allow a general setup with a general filtration that preserves the strong Markov property. Our main results are precise characterizations of NUPBR and NFLVR which only depend on the scale function and the speed measure. In particular, we prove that NUPBR forces the scale function to be continuously differentiable with absolutely continuous derivative. The latter extends our previous result, that, in the canonical framework, NFLVR implies such a property, in two directions (a weaker no-arbitrage notion and a more general framework). We also make the surprising observation that NUPBR and NFLVR are equivalent whenever finite boundary points are accessible for the driving diffusion.

Authors:Francesca Biagini, Alessandro Doldi, Jean-Pierre Fouque, Marco Frittelli, Thilo Meyer-Brandis

Abstract: We introduce the notions of Collective Arbitrage and of Collective Super-replication in a setting where agents are investing in their markets and are allowed to cooperate through exchanges. We accordingly establish versions of the fundamental theorem of asset pricing and of the pricing-hedging duality. Examples show the advantage of our approach.

Authors:Christian Laudagé, Florian Aichinger, Sascha Desmettre

Abstract: Increased insecurities on the energy markets have caused massive fluctuations of the electricity spot price within the past two years. In this work, we investigate the fit of a classical 3-factor model with a Gaussian base signal as well as one positive and one negative jump signal in this new market environment. We also study the influence of adding a second Gaussian base signal to the model. For the calibration of our model we use a Markov Chain Monte Carlo algorithm based on the so-called Gibbs sampling. The resulting 4-factor model is than compared to the 3-factor model in different time periods of particular interest and evaluated using posterior predictive checking. Additionally, we derive closed-form solutions for the price of futures contracts in our 4-factor spot price model. We find that the 4-factor model outperforms the 3-factor model in times of non-crises. In times of crises, the second Gaussian base signal does not lead to a better the fit of the model. To the best of our knowledge, this is the first study regarding stochastic electricity spot price models in this new market environment. Hence, it serves as a solid base for future research.

Authors:Svetlozar Rachev, Nancy Asare Nyarko, Blessing Omotade, Peter Yegon

Abstract: Environmental, Social, and Governance (ESG) finance is a cornerstone of modern finance and investment, as it changes the classical return-risk view of investment by incorporating an additional dimension of investment performance: the ESG score of the investment. We define the ESG price process and integrate it into an extension of Bachelier's market model in both discrete and continuous time, enabling option pricing valuation.

Authors:Vincent Lemaire, Gilles Pagès, Christian Yeo

Abstract: We propose two parametric approaches to price swing contracts with firm constraints. Our objective is to create approximations for the optimal control, which represents the amounts of energy purchased throughout the contract. The first approach involves explicitly defining a parametric function to model the optimal control, and the parameters using stochastic gradient descent-based algorithms. The second approach builds on the first one, replacing the parameters with neural networks. Our numerical experiments demonstrate that by using Langevin-based algorithms, both parameterizations provide, in a short computation time, better prices compared to state-of-the-art methods (like the one given by Longstaff and Schwartz).

Authors:Ofelia Bonesini, Giorgia Callegaro, Martino Grasselli, Gilles Pagès

Abstract: We propose a new theoretical framework that exploits convolution kernels to transform a Volterra path-dependent (non-Markovian) stochastic process into a standard (Markovian) diffusion process. This transformation is achieved by embedding a Markovian "memory process" within the dynamics of the non-Markovian process. We discuss existence and path-wise regularity of solutions for the stochastic Volterra equations introduced and we provide a financial application to volatility modeling. We also propose a numerical scheme for simulating the processes. The numerical scheme exhibits a strong convergence rate of 1/2, which is independent of the roughness parameter of the volatility process. This is a significant improvement compared to Euler schemes used in similar models.

Authors:Yan Dolinsky, Or Zuk

Abstract: The aim of this short note is to present a solution to the discrete time exponential utility maximization problem in a case where the underlying asset has a multivariate normal distribution. In addition to the usual setting considered in Mathematical Finance, we also consider an investor who is informed about the risky asset's price changes with a delay. Our method of solution is based on the theory developed in [4] and guessing the optimal portfolio.

Authors:Alexander Gairat, Vadim Shcherbakov

Abstract: This paper concerns a local volatility model in which volatility takes two possible values, and the specific value depends on whether the underlying price is above or below a given threshold value. The model is known, and a number of results have been obtained for it. In particular, explicit pricing formulas for European options have been recently obtained and applied to establish a power law behaviour of the implied volatility skew in the case when the threshold is taken at the money. These results have been obtained by techniques based on the Laplace transform. The purpose of the present paper is to demonstrate how to obtain the same results by another method. This alternative approach is based on the natural relationship of the model with Skew Brownian motion and consists in the systematic use of the joint distribution of this stochastic process and some of its functionals.

Authors:Felix Fießinger, Mitja Stadje

Abstract: Focusing on gains instead of terminal wealth, we consider an asset allocation problem to maximize time-consistently a mean-risk reward function with a general risk measure which is i) law-invariant, ii) cash- or shift-invariant, and iii) positively homogeneous, and possibly plugged into a general function. We model the market via a generalized version of the multi-dimensional Black-Scholes model using $\alpha$-stable L\'evy processes and give supplementary results for the classical Black-Scholes model. The optimal solution to this problem is a Nash subgame equilibrium given by the solution of an extended Hamilton-Jacobi-Bellman equation. Moreover, we show that the optimal solution is deterministic and unique under appropriate assumptions.

Authors:Kamil Fortuna, Janusz Szwabiński

Abstract: Systemic risk is a rapidly developing area of research. Classical financial models often do not adequately reflect the phenomena of bubbles, crises, and transitions between them during credit cycles. To study very improbable events, systemic risk methodologies utilise advanced mathematical and computational tools, such as complex systems, chaos theory, and Monte Carlo simulations. In this paper, a relatively simple mathematical formalism is applied to provide a unified framework for modeling credit cycles and systemic risk assessment. The proposed model is analyzed in detail to assess whether it can reflect very different states of the economy. Basing on those results, measures of systemic risk are constructed to provide information regarding the stability of the system. The formalism is then applied to describe the full credit cycle with the explanation of causal relationships between the phases expressed in terms of parameters derived from real-world quantities. The framework can be naturally interpreted and understood with respect to different economic situations and easily incorporated into the analysis and decision-making process based on classical models, significantly enhancing their quality and flexibility.

Authors:Matteo Gardini, Edoardo Santilli

Abstract: In this article we discuss the application of the Heat-Jarrow-Morton framework Heath et al. [26] to energy markets. The goal of the article is to give a detailed overview of the topic, focusing on practical aspects rather than on theory, which has been widely studied in literature. This work aims to be a guide for practitioners and for all those who deal with the practical issues of this approach to energy market. In particular, we focus on the markets' structure, model calibration by dimension reduction with Principal Component Analysis (PCA), Monte Carlo simulations and derivatives pricing. As application, we focus on European power and gas markets: we calibrate the model on historical futures quotations, we perform futures and spot simulations and we analyze the results.

Authors:David García-Lorite, Raul Merino

Abstract: In this paper, we develop a novel method based on Malliavin calculus to find an approximation for the convexity adjustment for various classical interest rate products. Malliavin calculus provides a simple way to get a template for the convexity adjustment. We find the approximation for Futures, OIS Futures, FRAs, and CMSs under a general family of the one-factor Cheyette model. We have also seen the excellent quality of the numerical accuracy of the formulas obtained.

Authors:Alan Guo

Abstract: We develop a formalism for reasoning about trading on decentralized exchanges on blockchains and a formulation of a particular form of maximal extractable value (MEV) that represents the total arbitrage opportunity extractable from on-chain liquidity. We use this formalism to prove that for blockchains with deterministic block times whose liquidity pools satisfy some natural properties that are satisfied by pools in practice, this form of MEV is invariant under changes to the ordering mechanism of the blockchain and distribution of block times. We do this by characterizing the MEV as the profit of a particularly simple arbitrage strategy when left uncontested. These results can inform design of blockchain protocols by ruling out designs aiming to increase trading opportunity by changing the ordering mechanism or shortening block times.

Authors:Zhuo Jin, Zuo Quan Xu, Bin Zou

Abstract: We study an optimal reinsurance problem under a diffusion risk model for an insurer who aims to minimize the probability of lifetime ruin. To rule out moral hazard issues, we only consider moral-hazard-free reinsurance contracts by imposing the incentive compatibility constraint on indemnity functions. The reinsurance premium is calculated under an extended distortion premium principle, in which the distortion function is not necessarily concave. We first show that an optimal reinsurance contract always exists and then derive two sufficient and necessary conditions to characterize it. Due to the presence of the incentive compatibility constraint and the nonconcavity of the distortion, the optimal contract is obtained as a solution to a double obstacle problem. At last, we apply the general result to study three examples and obtain the optimal contract in (semi)closed form.

Authors:Yunhong Li, Zuo Quan Xu, Xun Yu Zhou

Abstract: We study a continuous-time expected utility maximization problem in which the investor at maturity receives the value of a contingent claim in addition to the investment payoff from the financial market. The investor knows nothing about the claim other than its probability distribution, hence an ``intractable claim''. In view of the lack of necessary information about the claim, we consider a robust formulation to maximize her utility in the worst scenario. We apply the quantile formulation to solve the problem, expressing the quantile function of the optimal terminal investment income as the solution of certain variational inequalities of ordinary differential equations. In the case of an exponential utility, the problem reduces to a (non-robust) rank--dependent utility maximization with probability distortion whose solution is available in the literature.

Authors:Masaaki Fujii, Masashi Sekine

Abstract: In this paper, we study a problem of equilibrium price formation among many investors with exponential utility. The investors are heterogeneous in their initial wealth, risk-averseness parameter, as well as stochastic liability at the terminal time. We characterize the equilibrium risk-premium process of the risky stocks in terms of the solution to a novel mean-field backward stochastic differential equation (BSDE), whose driver has quadratic growth both in the stochastic integrands and in their conditional expectations. We prove the existence of a solution to the mean-field BSDE under several conditions and show that the resultant risk-premium process actually clears the market in the large population limit.