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In this paper, we study the pricing of contracts in fixed income markets under volatility uncertainty in the sense of Knightian uncertainty or model uncertainty. The starting point is an arbitrage-free bond market under volatility uncertainty. The uncertainty about the volatility is modeled by a G-Brownian motion, which drives the forward rate dynamics. The absence of arbitrage is ensured by a drift condition. Such a setting leads to a sublinear pricing measure for additional contracts, which yields either a single price or a range of prices and provides a connection to hedging prices. Similar to the forward measure approach, we define the forward sublinear expectation to simplify the pricing of cashflows. Under the forward sublinear expectation, we obtain a robust version of the expectations hypothesis, and we show how to price options on forward prices. In addition, we develop pricing methods for contracts consisting of a stream of cashflows, since the nonlinearity of the pricing measure implies that we cannot price a stream of cashflows by pricing each cashflow separately. With these tools, we derive robust pricing formulas for all major interest rate derivatives. The pricing formulas provide a link to the pricing formulas of traditional models without volatility uncertainty and show that volatility uncertainty naturally leads to unspanned stochastic volatility. [ABSTRACT FROM AUTHOR]

We analyze the problem of constructing multiple buy-and-hold mean-variance portfolios over increasing investment horizons in continuous-time arbitrage-free stochastic interest rate markets. The orthogonal approach to the one-period mean-variance optimization of Hansen and Richard (Econometrica 55(3):587–613, 1987) requires the replication of a risky payoff for each investment horizon. When many maturities are considered, a large number of payoffs must be replicated, with an impact on transaction costs. In this paper, we orthogonally decompose the whole processes defined by asset returns to obtain a mean-variance frontier generated by the same two securities across a multiplicity of horizons. Our risk-adjusted mean-variance frontier rests on the martingale property of the returns discounted by the log-optimal portfolio and features a horizon consistency property. The outcome is that the replication of a single risky payoff is required to implement such frontier at any investment horizon. As a result, when transaction costs are taken into account, our risk-adjusted mean-variance frontier may outperform the traditional mean-variance optimal strategies in terms of Sharpe ratio. Realistic numerical examples show the improvements of our approach in medium- or long-term cashflow management, when a sequence of target returns at increasing investment horizons is considered. [ABSTRACT FROM AUTHOR]

In this paper, in order to serve credit risk management, we introduce a pricing model for a vulnerable Bull Spread options in a Mixed Modified Fractional Hull-White-Vasicek stochastic volatility and stochastic interest rate model. We use Milstein scheme to find the sample paths of asset price and its volatility, and the sample paths of interest rates of asset price movement. We use the double Mellin transform to obtain an analytical vulnerable bull spread call option formula and an analytical vulnerable bull spread put option formula under fractional stochastic volatility and fractional stochastic interest rates. [ABSTRACT FROM AUTHOR]

The objective of this paper is to emphasize the differences between a call and a warrant as well as the different valuation methods of warrants which have been introduced in the financial literature. For the sake of simplicity and applicability, we only consider a debt-free equity-financed firm. More recently a formal distinction between structural and reduced form pricing models has been introduced. This distinction is important whether one wishes to price a new warrant issue or outstanding warrants. If we are interested in pricing a new issue of warrants, e.g. in the context of a management incentive package, one has to rely on a structural model. However most of practitioners use the simple Black-Scholes formula. In this context, we analyze the accuracy of the approximation of the "true" price of a warrant by the Black-Scholes formula. We show that in the current low interest rate environment, the quality of the approximation deteriorates and the sensitivity of this approximation to the volatility estimate increases. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has given rise to a spike in financial market volatility. In this paper, we attempt to assess the effects of financial & news-driven uncertainty shocks in growing Asian economies, using country-specific bond volatility shocks as a measure of local interest rate uncertainty. Also, we contrast the effects of local uncertainty with global stock market uncertainty. Using bond market data from nine Asian markets, we uncover a transmission mechanism of uncertainty shocks via the bond market. The mechanism works as a crowding-out effect due to government-led excessive market borrowing with supply-side consequences for the private sector, as opposed to economic policy or global stock market uncertainty which works more like a demand shock as in the literature. We conclude that countries with growing fiscal deficits that entail a larger government bond market or higher current account deficits, tend to experience an increase in the cost of borrowing due to this bond market volatility or interest rate uncertainty shocks. [ABSTRACT FROM AUTHOR]

This paper considers a capital-constrained online retailer (OR) selling products through an e-commerce platform (EP) who also offers financial services to retailers. During the selling season, the OR exerts an effort to promote market demand through activities like sales promotions, advertising and live-streaming selling events. To investigate the EP-based financing scheme, a game-theoretic model is developed where the EP functions as the leader determining the interest rate and platform usage fee rate, and the OR functions as the follower determining the order quantity and effort level. We explore the impacts of the OR's risk-aversion and find that when the OR is risk-averse (1) she sets a high effort level, and the EP sets a high usage fee rate; (2) a high risk-averse OR orders less products than low risk-averse OR. We design specific revenue-cost sharing contracts to coordinate the supply chain and demonstrate that the designed contracts are feasible. Moreover, we find that the OR consistently prefers EP financing compared to bank financing. [ABSTRACT FROM AUTHOR]

This paper studies the green new product development (GNPD) problem of a risk-averse capital constrained supply chain (SC). The SC is managed by an SME entrepreneur, seeking financial support from a multi-sided FinTech platform (MSP) to develop a portfolio of green and non-green products. The MSP offers the SC a combination of equity financing (EF) and debt financing (DF) facilities and must decide on the interest rate of its DF facility. Using a benchmark model, we first characterize the SC's production and the MSP's financing decisions under a deregulated scenario. Focusing on an alternative case with government intervention (i.e., hybrid environmental-green entrepreneurship policy), we next develop a three-level game theoretical model and sequentially characterize the decision-making behavior of government, MSP, and SC. The model outcomes are analyzed by considering the policy approach (i.e., economic influence vs. social welfare) and the platform's risk attitude. The results reveal that, when coupled with an appropriate government intervention policy, a regulated scenario leads to a better outcome, particularly when the MSP is risk-neutral and strikes a right balance between the EF and DF. The win–win situation may not be realized when the MSP is risk-averse and the host government is merely focused on its economic influence. To successfully promote sustainable supply chain finance (SSCF) through digital platforms, policy makers are urged to leverage their legislative power and prioritize green entrepreneurship and social welfare over their financial maximization agenda. [ABSTRACT FROM AUTHOR]

Green product development depends on the green innovation behavior of upstream and downstream companies in the supply chain. This paper focuses on a green supply chain consisting of a supplier and a manufacturer and considers two financing schemes wherein the manufacturer's operating capital and green innovation capital are both constrained: bank credit financing (BCF) and supplier green investment (SGI). We investigate the financing strategy of a manufacturer with different financing decision preferences and supply chain coordination contract designs. The results show that when the manufacturer's financing decision preference is low bankruptcy risk, it should choose BCF when the bank loan interest rate is lower than a threshold and SGI when the bank loan interest rate is higher than this threshold; when the manufacturer's financing decision preference is high R&D benefit, it should choose BCF when the initial capital is lower than another threshold and choose SGI when the initial capital is higher than this threshold. Then, we compare whether cost-sharing, quantity discount and revenue-sharing contracts can coordinate the supply chain, and discuss the selection strategies of supply chain members for coordination contracts. Research shows that revenue-sharing contracts fail to coordinate; however, when the cost-sharing ratio and quantity discount rate are appropriate, both cost-sharing and quantity discount contracts can achieve supply chain coordination. The lower the supplier's unit production cost, the stronger its motivation to accept a higher cost-sharing ratio and quantity discount rate. For the supplier, the key to choosing any coordination contract lies in the relative height of the cost-sharing ratio and quantity discount rate while the manufacturer should always choose a quantity discount contract when the quantity discount rate is high enough. [ABSTRACT FROM AUTHOR]

This paper examines the problem of hedging banks interest rate margins. We assume that the demand's deposits follow an exponential Lévy process with potential jumps. The forward market rates are assumed to follow the standard market model introduced by Brace et al. (Math Finance 7(2):127–155, 1997). As Adam et al. (Hedging interest rate margins on demand deposits, Université Paris 1 Panthéon-Sorbonne working paper, 2012), we consider that deposit rates depend linearly on market rates. Face to incompleteness, the liability manager must hedge both interest rate and demand deposit risks. For this purpose, we introduce various quadratic hedging criteria, allowing us to provide explicit hedging strategies that we further analyze. We illustrate in particular the impact of both the trends and the volatilities of interest rates and demand deposits. [ABSTRACT FROM AUTHOR]

The paper studies the term structure of interest rates imposed by equilibrium in a production economy consisting of participants with heterogeneous preferences with information costs and short selling constraints. Our model accounts explicitly and simultaneously for information costs and short sales in the pricing of assets in the economy. Consumption is continuous. The paper contains an exact solution to market equilibrium. It provides an explicit constructive solution for determining the state-price density process. Interest rates and their behaviors are a function of economic variables with information costs and short selling constraints. [ABSTRACT FROM AUTHOR]

In this paper, we examine the effect of relative/absolute firm efficiency on weighted average cost of capital (WACC). Using a sample of Korean listed firms, we find that WACC is negatively associated with relative firm efficiency (operational performance) suggesting that firms with higher (lower) relatively efficiency are expected to pay lower (higher) capital costs. When we repeat our analysis using absolute firm efficiency (ROA), we do not find a statistically significant relationship. Our results suggest relative efficiency which is estimated as output (sales) divided by the resources that are directly under the control of management is assessed by capital providers and impounded into a firm's capital costs. Absolute efficiency (ROA) which is estimated as sales divided by total assets is not. Our results suggest that simple accounting ratios used in the accounting literature are not considered as informative to explain borrowing costs compared to relative efficiency that captures managerial operational performance. [ABSTRACT FROM AUTHOR]

The development of the Internet and the emergence of social networks led people usually to give opinions and opinions about any product they have purchased. These comments and opinions may be viewed as positive or negative. So, it becomes a real challenge for any organization to manage these comments especially when they are regarded as negative news. Opinion mining is the discipline that is able to process these opinions. It is used as a decision-making tool to develop a strategy to reduce the number of negative comments or simply to compute general tendencies. In this paper, we study the case of opinions left by non-resident customers of a luxury hotel situated in a touristic country. Different tools and quantitative analysis, including codification, linear correlation as well as a multiple correspondence analysis, are implemented enabling to search for the reason of negative opinions. The main results indicated that negative ratings depend on negative perception of the service and/or the welcome and do not depend on journey type. Financial impact has been also studied. [ABSTRACT FROM AUTHOR]

This study addresses interest rate sensitivity of emerging market corporate debt. Previous research suggests that interest rate sensitivity of corporate bonds depends on residual maturity of issues, creditworthiness of issuers, embedded options and other idiosyncratic factors. However, the dependence of interest rate sensitivity on phases of the business cycle has not received an appropriate academic attention. This paper provides empirical evidence and theoretical interpretation of a dichotomy of interest rate sensitivity across the phases of the cycle, and sheds light on how credit spreads respond to interest rates. The historical span of the research covers the period of 2004–2016. The findings imply that hedging interest rate risk ought to be a dynamic process and take into consideration where the economy is positioned in the current business cycle. This research provides important insights on the nature of interest rate sensitivity, capable of enhancing financial stability and improving efficiency of financial system. [ABSTRACT FROM AUTHOR]

Bitcoin is emerging as a distinct asset class among investors given its seemingly detached price behavior relative to market and economic fundamentals. Its incomparably high returns in recent years has further fuelled intense interest and investment into Bitcoin and cryptocurrencies at large. This paper cautions that Bitcoin prices, despite their seemingly attractive independent behavior relative to economic variables, may still be exposed to the same types of market risks which afflict the performance of conventional financial assets. Using a Markov regime-switching model to distinguish between regimes of high and low Bitcoin price volatility, this paper shows that while returns on the aggregate market portfolio cannot explain Bitcoin returns, other asset pricing risk factors, such as interest rates and implied stock market and foreign exchange market volatilities, are important determinants of Bitcoin returns. Distinguishing between periods of high and low Bitcoin price volatility reveals heterogeneity in the explanatory power of market risk factors; in particular, Bitcoin returns are more difficult to explain during periods of high volatility relative to periods with low volatility. This finding can partially explain why extant studies, which neglect to distinguish between exchange rate regimes in Bitcoin, have difficulty linking Bitcoin prices to economic fundamentals. [ABSTRACT FROM AUTHOR]

An open question in interest rates derivative pricing is whether the price of the contracts should be computed by means of a multi-curve approach (different yield curves for discounting and forwarding) or by using a single curve (just one yield curve both for discounting and forwarding). The answer is of primary importance for financial markets as it allows to define a class of fair contracts. This paper calculates and compares the price of a simple swap within both multi-curve and single curve approaches and proposes a generalization of the lattice approach, which is usually used to approximate short interest rate models in the multi-curve framework. As an example, I show how to use the Black et al. (Financ Anal J 46(1):33–39, 1990) interest rate model on binomial lattice in multi-curve framework and calculate the price of the 2–8 period swaption with a single (LIBOR) curve and two-curve (OIS+LIBOR) approaches. Such technique can be used for pricing any interest rate based contract. [ABSTRACT FROM AUTHOR]

Bond immunization is an important topic in portfolio management. This paper presents a scenario based optimization framework for solving a cash flow matching problem. In this problem, the time horizon of the cash flow generated by the liability is longer than the maturities of the available bonds, and the interest rates are uncertain. Bond purchase decisions are made each period to generate cash flows to cover the obligations due in the future. We use buffered probability of exceedance (bPOE) and conditional value-at-risk (CVaR) to control for the risk of shortfalls. The initial cost of the hedging portfolio of bonds is minimized and optimal positions in bonds are calculated at all time periods. We also study the methodology when solving the optimization problem to minimize bPOE instead of CVaR, which has important practical relevance. The methodology we present in this paper is quite general and can be extended to other financial optimization problems. We use portfolio safeguard optimization package to solve the optimization problems. [ABSTRACT FROM AUTHOR]

Typically, implied volatilities for defaultable instruments are not available in the financial market since quotations related to options on defaultable bonds or on credit default swaps are usually not quoted by brokers. However, an estimate of their volatilities is needed for pricing purposes. In this paper, we provide a methodology to infer market implied volatilities for defaultable bonds using equity implied volatilities and CDS spreads quoted by the market in relation to a specific issuer. The theoretical framework we propose is based on the Merton's model under stochastic interest rates where the short rate is assumed to follow the Hull-White model. A numerical analysis is provided to illustrate the calibration process to be performed starting from financial market data. The market implied volatility calibrated according to the proposed methodology could be used to evaluate options where the underlying is a risky bond, i.e. callable bond or other types of credit-risk sensitive financial instruments. [ABSTRACT FROM AUTHOR]

This paper seeks to identify the macroeconomic and financial factors that drive credit spreads on bond indices in the US credit market. To overcome the idiosyncratic nature of credit spread data reflected in time varying volatility, skewness and thick tails, it proposes asymmetric GARCH models with alternative probability density functions. The results show that credit spread changes are mainly explained by the interest rate and interest rate volatility, the slope of the yield curve, stock market returns and volatility, the state of liquidity in the corporate bond market and, a heretofore overlooked variable, the foreign exchange rate. They also confirm that the asymmetric GARCH models and Student-t distributions are systematically superior to the conventional GARCH model and the normal distribution in in-sample and out-of-sample testing. [ABSTRACT FROM AUTHOR]

Despite powerful advances in interest rate curve modeling for data-rich countries in the last 30 years, comparatively little attention has been paid to the key practical problem of estimation of the term structure of interest rates for emerging markets. This may be partly due to limited data availability. However, emerging bond markets are becoming increasingly important and liquid. It is, therefore, important to be understand whether conclusions drawn from developed countries carry over to emerging markets. We estimate model parameters of fully flexible Nelson-Siegel-Svensson term structures model which has become one of the most popular term structure model among academics, practitioners, and central bankers. We investigate four sets of bond data: U.S. Treasuries, and three major emerging market government bond data-sets (Brazil, Mexico and Turkey). By including both the very dense U.S. data and the comparatively sparse emerging market data, we ensure that are results are not specific to a particular data-set. We find that gradient and direct search methods perform poorly in estimating term structures of interest rates, while global optimization methods, particularly the hybrid particle swarm optimization introduced in this paper, do well. Our results are consistent across four countries, both in- and out-of-sample, and for perturbations in prices and starting values. For academics and practitioners interested in optimization methods, this study provides clear evidence of the practical importance of choice of optimization method and validates a method that works well for the NSS model. [ABSTRACT FROM AUTHOR]

This paper analyses the interaction of monetary and fiscal policies in a dynamic stochastic general equilibrium model of a monetary union where conventional monetary policy is restricted by the binding zero lower bound constraint. We use the OccBin toolkit to analyze the performance of optimally set monetary and fiscal policies and compare outcomes with simple rules for government spending or the interest rate. Government spending are set independently from each other. We make several findings. First, fiscal policy plays an active role in stabilizing the economy under the binding zero lower bound constraint. Second, properly designed fiscal policy can even shorten the duration of the binding constraint. Third, coordination of policies is not always preferable. [ABSTRACT FROM AUTHOR]

We consider a compound Poisson surplus process perturbed by diffusion with debit interest. When the surplus is below zero or the company is on deficit, the company is allowed to borrow money at a debit interest rate to continue its business as long as its debt is at a reasonable level. When the surplus of a company is below a certain critical level, the company is no longer profitable, we say that absolute ruin occurs at this situation. In this risk model, absolute ruin may be caused by a claim or by oscillation. Thus, the absolute ruin probability in the model is decomposed as the sum of two absolute ruin probabilities, where one is the probability that absolute ruin is caused by a claim and the other is the probability that absolute ruin is caused by oscillation. In this paper, we first give the integro-differential equations satisfied by the absolute ruin probabilities and then derive the defective renewal equations for the absolute ruin probabilities. Using these defective renewal equations, we derive the asymptotical forms of the absolute ruin probabilities when the distributions of claim sizes are heavy-tailed and light-tailed. Finally, we derive explicit expressions for the absolute ruin probabilities when claim sizes are exponentially distributed. [ABSTRACT FROM AUTHOR]

Many financial optimization problems involve future values of security prices, interest rates and exchange rates which are not known in advance, but can only be forecast or estimated. Several methodologies have therefore been proposed to handle the uncertainty in financial optimization problems. One such methodology is Robust Statistics, which addresses the problem of making estimates of the uncertain parameters that are insensitive to small variations. A different way to achieve robustness is provided by Robust Optimization, which looks for solutions that will achieve good objective function values for the realization of the uncertain parameters in given uncertainty sets. Robust Optimization thus offers a vehicle to incorporate an estimation of uncertain parameters into the decision making process. This is true, for example, in portfolio asset allocation. Starting with the robust counterparts of the classical mean-variance and minimum-variance portfolio optimization problems, in this paper we review several mathematical models, and related algorithmic approaches, that have recently been proposed to address uncertainty in portfolio asset allocation, focusing on Robust Optimization methodology. We also give an overview of some of the computational results that have been obtained with the described approaches. In addition we analyze the relationship between the concepts of robustness and convex risk measures. [ABSTRACT FROM AUTHOR]