|
on Insurance Economics |
|
Issue of 2015‒08‒01
twenty-two papers chosen by Soumitra K. Mallick Indian Institute of Social Welfare and Business Management |
| By: | McBain, Florence |
| Keywords: | Health insurance, financial sustainability, water and sanitation, India, Health Economics and Policy, I13, |
| Date: | 2014–07 |
| URL: | http://d.repec.org/n?u=RePEc:ags:ubonwp:179200&r=ias |
| By: | Roy, Devesh; Munasib, Abdul; Guettabi, Mouhcine; Jordan, Jeffrey |
| Abstract: | Using Synthetic Control Method for comparative case studies, we estimate the causal impacts of the Massachusetts Health Care Reform (MHR) enacted in 2006 on the sources of insurance coverage. We find that MHR caused two main sources of expansions, viz., employer sponsored insurance (ESI) and Medicaid, with no evidence of crowding out. The expansion in ESI mirrors the economic cycles. The overall expansion in coverage of over half-a-million is distributed approximately 60:40 between ESI and Medicaid. Other sources of coverage such as direct purchase and Medicare, in a causal sense, were unaffected by MHR. |
| Keywords: | Massachusetts Health Reform, Insurance Mandate, Synthetic Control Method, Employer Provided Insurance, Medicaid, Medicare, Health Economics and Policy, Public Economics, I13, I18, R5, J38, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205581&r=ias |
| By: | Yu, Jialing |
| Keywords: | crop insurance, impact assessment, Corn Belt, Agricultural and Food Policy, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:206272&r=ias |
| By: | Luitel, Kishor P.; Hudson, Darren; Knight, Thomas O. |
| Abstract: | The 2014 Farm Bill adds the Stacked Income Protection Plan (STAX) and the Supplemental Coverage Option (SCO) to the suite of insurance choices for producers in 2015. Unlike other crops with the ARC and PLC programs, cotton only has access to crop insurance under the new Farm Bill. Therefore, the crop insurance choices that farmers make will constitute the only government safety net for farm income. The overall objective of this research is to understand the impact of the new crop insurance policy options for cotton on farmer decisions regarding risk management strategies. A mail survey was conducted in February 2015, at the time when farmers were making insurance purchase decisions. Our results suggest that cotton farmers are taking benefits of 2014 Farm Bill, which enables them to take separate dry land and irrigated insurance policies. |
| Keywords: | 2014 Farm Bill, SCO Endorsement, STAX, Cotton, Crop Insurance, Agribusiness, Agricultural and Food Policy, Institutional and Behavioral Economics, Risk and Uncertainty, D81, Q18, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205438&r=ias |
| By: | Sharma, Sankalp; Schoengold, Karina |
| Keywords: | Risk, risk preference, risk premium, insurance, pandel data methods., Production Economics, Risk and Uncertainty, D81, C23, C33, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205774&r=ias |
| By: | Adhikari, Shyam |
| Abstract: | The 2014 Farm bill included a new supplementary coverage option (SCO) to provide additional protection against shallow losses not covered by the individual crop plans. SCO indemnification triggers off of county yields or revenues whereas individual plans trigger off of the individual farmers’ yields or revenue. In this paper we examine the impact of supplementary coverage option on the optimum producer coverage level. Our findings indicate that the individual plan with SCO provides better protection but is distortionary to the current choice of coverage level. The new optimal coverage level choice is likely to differ and vary in counties depending upon the counties’ respective yield variability. |
| Keywords: | Crop insurance, supplemental coverage option, optimum coverage level, Crop Production/Industries, Risk and Uncertainty, G22, Q14, Q18, |
| Date: | 2015–05 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205053&r=ias |
| By: | Weber, Jeremy G.; Key, Nigel; O'Donoghue, Erik J. |
| Abstract: | Federally subsidized crop insurance has expanded in recent decades, with annual premium subsidies increasing from roughly $1 to $7 billion dollars between 2000 and 2013. The 2014 Farm Act further expanded crop insurance, making it the main conduit of financial support to farmers. Although designed for non-environmental goals, subsidized insurance may affect the use of land, fertilizer, and agrochemicals and therefore environmental externalities from agriculture such as nutrient and chemical runoff into lakes and streams. We use a newly constructed farm-level panel data set to examine farmer responses to changes in insurance coverage. Identification comes from an instrumental variable approach that exploits program limits on coverage, which constrained the response of some farmers to increasingly generous subsidies more than others. Our estimates indicate that expanded coverage had a small, if any, effect on farm decisions such as fertilizer and chemical use. |
| Keywords: | Agricultural Finance, Environmental Economics and Policy, Q15, Q18, Q12, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:204972&r=ias |
| By: | Tran, Anh N.; Motamed, Mesbah; Lee, Tani |
| Keywords: | crop insurance, abandoned acreage, actual production history, Agricultural and Food Policy, Crop Production/Industries, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205426&r=ias |
| By: | Ramsey, Ford; Goodwin, Barry |
| Abstract: | This paper considers exotic price coverage in crop insurance. The issue is similar to the pricing of options on extrema which are commonly called exotic options. Consideration is made of individual monthly average prices leading to a multivariate distribution with important dependencies. Additionally, the problem is approached in terms of the joint distribution of a maximum over an interval and the harvest time price. |
| Keywords: | crop insurance, exotic options, price coverage, Agricultural Finance, Research Methods/ Statistical Methods, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205208&r=ias |
| By: | Li, Yiting; Miranda, Mario J. |
| Abstract: | Conventional agricultural index insurance indemnifies based on the observed value of a specified variable, such as rainfall, that is correlated with agricultural production losses. Typically, indemnities are paid to the policyholder after the losses have been experienced. This paper explores alternate timing for index insurance payouts. In particular, we explore the potential benefits of what we call “mitigation index insurance” in which the payouts of the insurance contract arrive before losses are incurred, in time to be used to take measures to mitigate, that is, reduce, eventual losses. For mitigation insurance to be of value, two conditions must be met. First, there must be a strong objectively measurable signal that is highly correlated with losses, but which is realized before the losses are incurred. Second, the signal must be realized in time for loss mitigation measures to be cost effective. We can think of numerous examples, and mention three. First, the onset of extreme rainfalls and profound flooding in coastal equatorial areas can be anticipated months in advance based on low sea-surface temperature readings, the so called El Niño phenomenon. Skees et al., proposed an El Niño-Southern Oscillation (ENSO) business interruption insurance contract that would provide indemnities to rural communities in coastal Peru before the eventual onset of torrential rains and catastrophic flooding that typically accompany the most severe El Niño events. The indemnities would afford communities the opportunity to implement adaptation strategies to mitigate the serious losses and disruptions that are almost certain to follow (Skees and Murphy, 2009). A second example is slow-onset disasters such as severe droughts, which in developing countries often lead to widespread famine, but not immediately. Relief agencies whose mission is to provide humanitarian assistance to victims of famine face tough questions about when to act. International donor response to a humanitarian crisis is often slow and inadequate, with funding mobilized only after evidence of a widespread famine become apparent. Often, by the time that a famine is recognized to exist, large-scale loss of life is already inevitable. The loss of life is not due to lack of early warnings, but rather the ability of international donors to mobilize funds quickly. An insurance contract that indemnifies relief agencies when drought occurs, before the onset of widespread starvation, would provide ready funding that would allow relief agencies to begin relief efforts in a more timely way. Chantarat et al. (2007) proposed to use weather index insurance to improve drought response for famine prevention, which pays claims based on realizations of a weather index that forecasts the prevalence and severity of food insecurity conditions in the targeted areas. A third example is replanting guarantee insurance. Crop yields are especially sensitive to the weather conditions that exist during the critical agronomic phase of germination, which occurs shortly after planting. A poor smallholder who invests in high quality seeds can quickly find that poor rainfalls shortly after planting have substantially reduced the maximum attainable yield at harvest. Given that it is still early in the planting season, the farmer can typically replant. However, if the farmer is poor and credit-constrained, he may lack the financial means to purchase new seeds, given that he spent what little cash he had on his original bag of seeds. In 2014, in Tanzania, Acre Africa launched a mobile-enabled weather index insurance contract that is bundled by seed companies into the bags of seed they sell. The insurance product indemnifies the registered smallholder if a drought occurs during the first three weeks after planting, with the farmer receiving a mobile money transfer for the full cost of quality seed so they can replant within the same season. In this paper we systematically compare the costs and benefits of mitigation index insurance with those of conventional index insurance using a stylized three-period, discrete choice, stochastic dynamic optimization model. We assume that insurance is purchased in period 0; a signal correlated with losses in period 2 emerges in period 1, at which time mitigation measures may be taken; and losses, if any, are realized in period 2. We assess the relative values of mitigation index insurance and conventional index insurance by deriving the individuals expected ex-ante welfare under three insurance scenarios: a) the individual purchases no insurance; b) the individual purchases conventional index insurance, which indemnifies in period 2 based on an index observed in period 2; and c) the individual purchases mitigation index insurance, which indemnifies in period 1 based on an index observed in period 1. Our analysis indicates that mitigation insurance can reduce moral hazard by providing incentives to undertake mitigation that are absent with conventional index insurance. We also find that the value of mitigation insurance rises as the precision of the period 1 signal rises, the losses avoided through mitigation rise, the cost of mitigation rises, and the individual’s initial wealth falls. We then turn to a multi-period dynamic stochastic model with a more refined treatment of time and explore how the relative benefits of mitigation index insurance vary with the point in time at which the indemnities are paid. In general, we find that the relative benefits of mitigation index insurance depend on two dynamically countervailing factors. The closer one is to the realization of the loss event, the more accurately the signal predicts eventual loss; however, it is also the case that the loss reduction obtained from mitigation falls, or equivalently the cost of mitigation rises. Thus the trade-off is: the longer one waits to mitigate, the better informed one is about its benefits, but the less effective it becomes. Information and mitigation costs thus have profound implications for the optimal timing of insurance indemnities. Mitigation insurance appears to be most promising if there is signal that predicts eventual losses with high precision, in time for cost-effective mitigation measures to be taken. We also expect mitigation insurance to be most valuable when credit constraints prevent the agent from ceasing the opportunity to mitigate when it becomes clear that it is beneficial to do so, a common situation among the poor of the developing world. We are currently investigating the impacts of credit and savings on the value of mitigation insurance, with plans to report the results in the working paper we present at the AAEA Annual Conference. |
| Keywords: | Mitigation Index Insurance, Agricultural Finance, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205871&r=ias |
| By: | Hungerford, Ashley; O'Donoghue, Erik; Motamed, Mesbah |
| Abstract: | The 2014 Agricultural Act introduced several risk management programs for commodities. Price Loss Coverage (PLC) and Agricultural Risk Coverage (ARC) provide price and revenue protection, respectively, to eligible producers of covered commodities. Also in addition to existing federally-backed crop insurance policies, the Supplemental Coverage Option (SCO), a new program, provides subsidized add-on insurance coverage to producers of rice, cotton, corn, soybeans, sorghum, wheat, and spring barley. Through simulations of prices and yields, we examine the relationship between the support payments generated by these new programs and the magnitude of the risk reduction they produce, both under their current parameters as well as alternatives. The simulations also reveal the distribution of risk reduction among counties across the United States. |
| Keywords: | 2014 Agricultural Act, Yield Distribution, Copulas, Commodity Support, Agricultural Risk Coverage, Supplemental Coverage Option, Price Loss Coverage, Agricultural and Food Policy, Risk and Uncertainty, G32, Q18, Q14, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:204845&r=ias |
| By: | Botkins, Elizabeth Robison |
| Abstract: | Abstract: Obesity and the negative health conditions related to it have been a growing public health concern over the last few decades. While there are many factors contributing to the rise of obesity, one that is often overlooked is the ex-ante moral hazard effect of health insurance. Ex-ante moral hazard occurs when an individual takes on more risk knowing they will not bear the full cost of the consequences. Simply having health insurance allows an individual to bear a smaller portion of the costs of obesity as an insurance company now bears a portion of the costs. While other studies have estimated the moral hazard impact of health insurance on obesity and other life-style related illnesses, this is the first paper to look at the impact of public verses private insurance. I use cross sectional data from the National Longitudinal Youth Survey 1997 from 2011 and employ an instrumental variable technique to address the endogeneity between insurance coverage and body mass index (BMI). The results show that private insurance is predicted to increase BMI by 3.5 kg/m2, while public insurance is predicted to increase BMI by 8 kg/m2. This result demonstrates that, not only is there a significant moral hazard problem, but it is also highly sensitive insurance type. This study can be used to help inform insurance policy design to minimize inefficiencies associated with moral hazard. |
| Keywords: | Health economics, moral hazard, obesity, Health Economics and Policy, Institutional and Behavioral Economics, Labor and Human Capital, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:206228&r=ias |
| By: | Ker, Alan. P; Tolhurst, Tor; Liu, Yong |
| Abstract: | The Agricultural Act of 2014 solidified insurance as the cornerstone of U.S. agricultural policy. The Congressional Budget Office (2014) estimates this Act will increase spending on agricultural insurance programs by $5.7 billion to a total of $89.8 billion over the next decade. In light of the sizable resources directed toward these programs, accurate rating of insurance contracts is of utmost importance to producers, private insurance companies, and the federal government. Unlike most forms of insurance -- where sufficient information exists to accurately estimate the probability and magnitude of losses (i.e. the underlying density) -- agricultural insurance is plagued by a paucity of spatially correlated data. A novel interpretation of Bayesian Model Averaging is used to estimate a set of possibly similar densities that offers greater efficiency if the set of densities are similar while seemingly not losing any if the set of densities are dissimilar. Simulations indicate finite sample performance -- in particular small sample performance -- is quite promising. The proposed approach does not require knowledge of the form or extent of any possible similarities, is relatively easy to implement, admits correlated data, and can be used with either parametric or nonparametric estimators. We use the proposed approach to estimate U.S. crop insurance premium rates for area-type programs and develop a test to evaluate its efficacy. An out-of-sample game between private insurance companies and the federal government highlights the policy implications for a variety of crop-state combinations. We repeat the empirical analyses under reduced sample sizes given: (i) new programs will dramatically expand area-type insurance to crops and states that have significantly less historical data; and (ii) changes in technology could render some historical loss data no longer representative. Consistent with the simulation results, the performance of the proposed approach with respect to rating area-type insurance -- in particular small sample performance -- remains quite promising. |
| Keywords: | rating crop insurance contracts, Bayesian model averaging, multiple density estimation, spatial correlation, small sample estimation, Agribusiness, Research Methods/ Statistical Methods, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205211&r=ias |
| By: | Ward, Patrick S.; Spielman, David J.; Ortega, David L.; Kumar, Neha; Minocha, Sumedha |
| Abstract: | Financial and technological innovations that mitigate weather-related production risks have the potential to greatly benefit farmers in many risk-prone. In this study we examine farmers’ preferences for two distinct tools that allow them to manage drought risk: weather index insurance and a recently released drought-tolerant rice variety. We illustrate how these tools can independently address drought risk and demonstrate the additional benefits gained by combining them into a complementary risk management product. Findings indicate that farmers are generally unwilling to adopt the drought-tolerant variety independent of insurance, largely due to a yield penalty under non-drought conditions. When bundled with insurance, however, farmers’ valuation of the variety increases. Farmers value insurance on its own, but even more so when bundled with the drought-tolerant variety. The results provide evidence that farmers value the complementarities inherent in a well-calibrated bundle of risk management tools. |
| Keywords: | Risk management, insurance, drought-tolerant rice, discrete choice experiments, Bangladesh, Demand and Price Analysis, Food Security and Poverty, Risk and Uncertainty, D12, Q12, Q14, Q16, Q54, |
| Date: | 2015–05 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:204882&r=ias |
| By: | Liu, Xianglin; Tang, Yingmei; Miranda, Mario J. |
| Abstract: | Although numerous index insurance pilot programs have been conducted in China, little is known about Chinese farmers’ willingness to pay for index insurance. By using a field survey of small farm households in China’s Heilongjiang Province, which suffered a large flood in the summer of 2013, this paper explores farmers’ willingness to pay (WTP) for a hypothetical rainfall index insurance product, with a special interest in whether farmers affected by the flood are willing to pay more than those where not. |
| Keywords: | index insurance, willingness-to-pay, natural experiment, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205374&r=ias |
| By: | Protopop, Iuliia; Schoengold, Karina; Walters, Cory G. |
| Keywords: | Demand and Price Analysis, Farm Management, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205785&r=ias |
| By: | Michler, Jeffrey D.; Viens, Frederi G.; Shively, Gerald E. |
| Abstract: | We investigate the sources of variance in crop output and measure their relative importance in the context of weather index insurance for smallholder farmers. We use parcel-level panel data from South Asia and a multilevel modeling approach to isolate the different sources of variance. We then measure how large a role weather plays in explaining variance in yields. Using Bayesian methods, we draw the underlying distribution of the random error term responsible for weather uncertainty, which is highly skewed and non-normal. We find that variance in weather accounts for a small but important fraction of total variance in crop output. We also derive pricing and payout schedules for actuarially fair weather index insurance. Our results shed light on the low uptake rates of index insurance in South Asia and provide direction for designing index insurance with less basis risk for farmers. |
| Keywords: | Weather Risk, Agricultural Production, Index Insurance, Bayesian Analysis, Multilevel Models, Rural South Asia, Environmental Economics and Policy, Food Security and Poverty, International Development, Production Economics, Research Methods/ Statistical Methods, Risk and Uncertainty, C11, D81, G22, O12, O13, Q16, Q12, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205297&r=ias |
| By: | Cooper, Joseph; Hungerford, Ashley; O'Donoghue, Erik |
| Abstract: | The 2014 Farm Act ends some long-standing and some more recent commodity support programs and introduces new programs that offer producers an array of choices which will determine the support they will receive over the 5-year life of the Act. Programs covering soybeans that are included in these new programs are the so-called “shallow loss” programs, including Agriculture Risk Coverage (ARC) and the Supplemental Coverage Option (SCO). The traditional “deep loss” Federal crop insurance program (e.g., Revenue Protection, or RP) – the largest commodity outlay over the last few years – continues. While current program parameters are set for the life of the 2014 Farm Act, in future farm legislation, the USDA’s expected budgetary allocations for shallow versus deep loss support could be adjusted by the “shallow loss” coverage rates in ARC and SCO, as well as by other policy parameters. Using regression analysis, we examine the ratio of expected net SCO and county-ARC payments to total net support benefits (shallow plus deep loss) as a function of variables that influence the size and distribution of these benefits, including key program policy parameters. For corn, winter wheat, and soybeans, we find the ratio to be approximately twice as sensitive to the deep loss coverage rate than to the shallow loss coverage rate. |
| Keywords: | supplemental coverage option, agricultural risk coverage, shallow loss, crop insurance, corn, winter wheat, soybeans, copula, Agricultural and Food Policy, Farm Management, Research Methods/ Statistical Methods, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205310&r=ias |
| By: | Awondo, Sebastain N.; Octavio, Ramirez; Colson, Gregory; Kostandini, Genti; Fonsah, Esendugue |
| Abstract: | We investigate how self-protection from the adoption of Improved Maize Varieties (IMV) and off-farm income affects risk premiums for smallholder maize producers in Uganda. To unbundle these effects, we specify the cost of risk to explicitly capture four risk components - mean, variance, skewness and kurtosis. Using unique plot-level panel data for Uganda, we estimate and test moments of a flexible production function based on an expanded form of the Johnson SU family distribution and proceed to simulate the degree of responsiveness of risk premiums and welfare estimates to marginal changes in the share of land under IMV and off-farm income. Scenarios of joint adoption of IMV accompanied with low and high application of inorganic fertilizer, and the effect of off-farm income when there is high and low supply of farm labor are examined. Results show that the use of IMV and off-farm income substantially reduces risk premiums and the individual effect is much higher under low fertilizer application and high supply of farm labor, respectively. Thus implying that self-protection is likely to reduce the propensity for index insurance especially if its design fails to consider the reduction in downside risk. |
| Keywords: | Self-protection Improved maize varieties Off-farm Income Insurance, Agricultural and Food Policy, International Development, Risk and Uncertainty, O12, O15, O33, C16, Q12, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:206226&r=ias |
| By: | Atreya, Ajita; Michael-Kerjan, Erwann; Czajkowski, Jeffrey |
| Abstract: | The NFIP’s Community Rating System (CRS) adopted in the early 1990s is an incentive program that recognizes, encourages, and rewards – by the use of flood insurance premium reductions – community and state activities that go beyond the minimum NFIP requirements. With an access to the entire dataset of the CRS from FEMA, over a period of 15 years (1998-2012) we perform longitudinal analysis of active CRS communities and answer the questions such as: How does the distribution of communities look like across all CRS activities? Do the communities improve their CRS classes over time? How long does it take for CRS communities to move up in class? What’s the tenure in the CRS? Do many communities drop their participation after just a few years in a similar way that many residents drop their flood insurance coverage after just three of four years (Michel-Kerjan et al, 2012)? Overall we find that the CRS program works well. It keeps attracting more communities every year, the tenure is very high with 99% of participation communities remaining in the program from year to year. The distribution of scores across all communities has also improved overtime; the average number of activities communities are involved in increase 20% between 1998 and 2012 (from 10 to 12, out of 18 possible ones). There are positive moves within activities as well. |
| Keywords: | NFIP, Insurance, CRS, Environmental Economics and Policy, Institutional and Behavioral Economics, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205592&r=ias |
| By: | Romero-Aguilar, Randall S.; Miranda, Mario J. |
| Abstract: | We model a regional grain reserve as a game of two countries that agree to pool together a fraction of their grain to cope with production risk, but that can also repudiate their obligations at any moment. The reserve can be operated as a “credit union” or an “insurance union”. We find that although risk sharing is more effective when production shocks are negatively correlated, the regional reserve is more sustainable when the correlation is positive. We also find that an “insurance” game can be more sustainable than a “credit” game. |
| Keywords: | multilateral reserve, grain, food crisis, default, game theory, Agricultural and Food Policy, Food Security and Poverty, International Development, International Relations/Trade, Risk and Uncertainty, |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea15:205773&r=ias |
| By: | Tetsuji Okazaki (Faculty of Economics, The University of Tokyo) |
| Abstract: | This paper presents a new approximation formula for pricing discretely monitored average options and spread options in a local-stochastic volatility (LSV) model with jumps. Particularly, our model includes local-volatility functions and jump components in both the underlying asset price and its volatility processes. To the best of our knowledge, the proposed approximation is the rst one which achieves analytic approximations for the average and spread option prices in this environment. In numerical experiments, by employing several models we provide approximate prices for average and calendar spread options on the WTI futures based on the parameters through calibration to the listed (plain-vanilla) futures option prices, and compare those with the CME settlement prices, which conrms the validity of the method. Moreover, we show the LSV with jumps model is able to replicate consistently and precisely listed futures option, calendar spread option and average option prices with common parameters. -- |
| Date: | 2015–07 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2015cf981&r=ias |