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Suppl. figure 2: PDX samples have different basal NR3C1 expression levels.

Purpose:KPT-8602 (Eltanexor) is a second-generation exportin-1 (XPO1) inhibitor with potent activity against acute lymphoblastic leukemia (ALL) in preclinical models and with minimal effects on normal cells. In this study, we evaluated whether KPT-8602 would synergize with dexamethasone, vincristine, or doxorubicin, three drugs currently used for the treatment of ALL.Experimental Design:First, we searched for the most synergistic combination of KPT-8602 with dexamethasone, vincristine, or doxorubicin in vitro in both B-ALL and T-ALL cell lines using proliferation and apoptosis as a readout. Next, we validated this synergistic effect by treatment of clinically relevant B- and T-ALL patient-derived xenograft models in vivo. Finally, we performed RNA-sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) to determine the mechanism of synergy.Results:KPT-8602 showed strong synergism with dexamethasone on human B-ALL and T-ALL cell lines as well as in vivo in three patient-derived ALL xenografts. Compared with single-drug treatment, the drug combination caused increased apoptosis and led to histone depletion. Mechanistically, integration of ChIP-seq and RNA-seq data revealed that addition of KPT-8602 to dexamethasone enhanced the activity of the glucocorticoid receptor (NR3C1) and led to increased inhibition of E2F-mediated transcription. We observed strong inhibition of E2F target genes related to cell cycle, DNA replication, and transcriptional regulation.Conclusions:Our preclinical study demonstrates that KPT-8602 enhances the effects of dexamethasone to inhibit B-ALL and T-ALL cells via NR3C1- and E2F-mediated transcriptional complexes, allowing to achieve increased dexamethasone effects for patients.

ChIP-seq data for NR3C1 bound genes

RNA-seq data

Suppl. figure 1: Doxorubicin and vincristine are not synergistic with KPT-8602 in diminishing proliferation of B-ALL and T-ALL

Suppl. figure 4: KPT-8602 single treatment or combined treatment with dexamethasone does not lead to nuclear accumulation of IKBα nor to effects on NFκB target genes

Suppl. figure 3: Dexamethasone and dexamethasone+KPT-8602 treatment induce NR3C1 binding and leads to differential gene expression of the bound genes in the SUP-T1 cell line

Not available.

The conditional covariance between the market return and its variance, which we refer to as the leverage effect, is positively related to the variance risk premium. It contains incremental information about the variance risk premium after controlling for other return moments and additional variables suggested by the literature as determinants of the variance risk premium. This empirical finding is supported by theory: the pricing of volatility risk is the economic channel behind the strong positive relation between the two variables. We use this relation to construct a time series of the variance risk premium dating back to 1926. (JEL G12, G13) Received February 7, 2020; editorial decision September 01, 2021.

The existing literature finds that information not captured by traditional term structure factors helps predict excess bond returns. When estimating no-arbitrage affine term structure models, aligning in-sample and out-of-sample objective functions results in term structure factors that capture information that remains hidden from existing approaches. Specifically, the estimates of the third term structure factor radically differ and are related to the fourth principal component, which helps forecast bond returns. The new objective function leads to substantial improvements in forecasting performance. It also results in higher model term premiums and lower expected future short rates. This paper was accepted by David Simchi-Levi, finance.

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of hematological cancers arising from the malignant transformation of mature T cells. In a cohort of 28 PTCL cases, we identified recurrent overexpression of MYCN, a member of the MYC family of oncogenic transcription factors. Approximately half of all PTCL cases was characterized by a MYC expression signature. Inducible expression of MYCN in lymphoid cells in a mouse model caused T-cell lymphoma that recapitulated human PTCL with an MYC expression signature. Integration of mouse and human expression data identified EZH2 as a key downstream target of MYCN. Remarkably, EZH2 was found to be an essential cofactor for the transcriptional activation of the MYCN-driven gene expression program, which was independent of methyltransferase activity but dependent on phosphorylation by CDK1. MYCN-driven T-cell lymphoma was sensitive to EZH2 degradation or CDK1 inhibition, which displayed synergy with US Food and Drug Administration-approved histone deacetylase (HDAC) inhibitors. ispartof: BLOOD vol:140 issue:23 pages:2463-2476 ispartof: location:United States status: published

Both large oil price increases and decreases are associated with deteriorating economic conditions. The projection of the state price density (SPD) onto oil returns estimated from oil futures and option prices displays a U-shaped pattern. Because investors assign high state prices to large negative and large positive oil returns, the U-shaped SPD may steepen in either tail when economic conditions deteriorate. The positive return region of the SPD is more closely related to economic conditions. The oil SPD contains information about economic conditions and future security returns that is distinct from the information in the stock index SPD.

We show that the prices of risk for factors that are nonlinear in the market return can be obtained using index option prices. The price of coskewness risk corresponds to the market variance risk premium, and the price of cokurtosis risk corresponds to the market skewness risk premium. Option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An analysis of factor models with coskewness risk indicates that the new estimates of the price of risk improve the models’ performance compared with regression-based estimates.

We introduce a top-down no-arbitrage model for pricing structured products. Losses are described by Cox processes whose intensities depend on economic variables. The model provides economic insight into the impact of structured products on financial institutions’ risk exposure and systemic risk. We estimate the model using CDO data and find that spreads decrease with higher interest rates and increase with volatility and leverage. Volatility is the primary determinant of variation in tranche spreads. Leverage and interest rates are more closely associated with rare credit events. Model-implied risk premiums and the probabilities of tranche losses increase substantially during the financial crisis.

We study energy futures option returns for crude oil, natural gas, heating oil, and gasoline. Average call and put returns are negative at short maturities, more so for OTM options, and increase with maturity. Put returns are less negative than call returns, but this is not the case for delta-hedged returns, indicating that the aggregate risk of the underlying energy futures is priced in the raw option returns. Moneyness patterns in raw and delta-hedged returns are similar to patterns for index option returns. Significant differences between the four commodities remain after removing the effect of the underlying futures returns, with natural gas as the main outlier. Variance risk premiums are negative and explain some maturity patterns in returns, but they cannot account for return differences across markets. Energy producers are net short the underlying through their option positions, and speculators net long. The larger the net long position of the speculators, the lower the returns on call options, which suggests that demand from speculators may affect option returns in energy markets.

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of non-Hodgkin lymphomas with poor prognosis. Up to 30% of PTCL lack distinctive features and are classified as PTCL, not otherwise specified (PTCL-NOS). To further improve our understanding of the genetic landscape and biology of PTCL-NOS, we perform RNA-sequencing of 18 cases and validate results in an independent cohort of 37 PTCL cases. We identify FYN-TRAF3IP2, KHDRBS1-LCK and SIN3A-FOXO1 as new in-frame fusion transcripts, with FYN-TRAF3IP2 as a recurrent fusion detected in 8 of 55 cases. Using ex vivo and in vivo experiments, we demonstrate that FYN-TRAF3IP2 and KHDRBS1-LCK activate signaling pathways downstream of the T cell receptor (TCR) complex and confer therapeutic vulnerability to clinically available drugs., Peripheral T cell lymphoma (PTCL) not otherwise specified (NOS) is a subgroup of PTCL, which has no distinctive features and is poorly characterized at the genetic level. Here, the authors identify two fusion transcripts that activate T cell receptor complex signalling and confer therapeutic vulnerability in PTCL-NOS.

ispartof: HEMASPHERE vol:5 issue:9 ispartof: location:United States status: published

Background T cell acute lymphoblastic leukemia (T-ALL) is a high-risk subtype that comprises 10–15% of childhood and 20–25% of adult ALL cases. Over 70% of T-ALL patients harbor activating mutations in the NOTCH1 signaling pathway and are predicted to be sensitive to gamma-secretase inhibitors. We have recently demonstrated that selective inhibition of PSEN1-containing gamma-secretase complexes can overcome the dose-limiting toxicity associated with broad gamma-secretase inhibitors. In this study, we developed combination treatment strategies with the PSEN1-selective gamma-secretase inhibitor MRK-560 and other targeted agents (kinase inhibitors ruxolitinib and imatinib; XPO-1 inhibitor KPT-8602/eltanexor) for the treatment of T-ALL. Methods We treated T-ALL cell lines in vitro and T-ALL patient-derived xenograft (PDX) models in vivo with MRK-560 alone or in combination with other targeted inhibitors (ruxolitinib, imatinib or KPT-8602/eltanexor). We determined effects on proliferation of the cell lines and leukemia development and survival in the PDX models. Results All NOTCH1-signaling-dependent T-ALL cell lines were sensitive to MRK-560 and its combination with ruxolitinib or imatinib in JAK1- or ABL1-dependent cell lines synergistically inhibited leukemia proliferation. We also observed strong synergy between MRK-560 and KPT-8602 (eltanexor) in all NOTCH1-dependent T-ALL cell lines. Such synergy was also observed in vivo in a variety of T-ALL PDX models with NOTCH1 or FBXW7 mutations. Combination treatment significantly reduced leukemic infiltration in vivo and resulted in a survival benefit when compared to single treatment groups. We did not observe weight loss or goblet cell hyperplasia in single drug or combination treated mice when compared to control. Conclusions These data demonstrate that the antileukemic effect of PSEN1-selective gamma-secretase inhibition can be synergistically enhanced by the addition of other targeted inhibitors. The combination of MRK-560 with KPT-8602 is a highly effective treatment combination, which circumvents the need for the identification of additional mutations and provides a clear survival benefit in vivo. These promising preclinical data warrant further development of combination treatment strategies for T-ALL based on PSEN1-selective gamma-secretase inhibition.

We develop a tractable dynamic model of an index option market maker with limited capital. We solve for the variance risk premium and option prices as a function of the asset dynamics and market maker option holdings and wealth. The market maker absorbs end users’ positive demand and requires a more negative variance risk premium when she incurs losses. We estimate the model using returns, options, and inventory and find that it performs well, especially during the financial crisis. The restrictions imposed by nested existing reduced-form stochastic-volatility models are strongly rejected in favor of the model with a market maker.

We analyze the relation between expected option returns and the volatility of the underlying securities. In the Black-Scholes-Merton and stochastic volatility models, the expected return from holding a call (put) option is a decreasing (increasing) function of the volatility of the underlying. These predictions are strongly supported by the data. In the cross-section of stock option returns, returns on call (put) option portfolios decrease (increase) with underlying stock volatility. This strong negative (positive) relation between call (put) option returns and volatility is not due to cross-sectional variation in expected stock returns. It holds in various option samples with different maturities and moneyness, and it is robust to alternative measures of underlying volatility and different weighting methods. Time-series evidence also supports the predictions from option pricing theory: Future returns on S&P 500 index call (put) options are negatively (positively) related to S&P 500 index volatility.

Building on theoretical asset pricing literature, we examine the role of market risk and the size, book‐to‐market (BTM), and volatility anomalies in the cross‐section of unlevered equity returns. Compared with levered (stock) returns, unlevered market beta plays a more important role in explaining the cross‐section of unlevered equity returns, even after controlling for size and BTM. The size effect is weakened, while the value premium and the volatility puzzle virtually disappear for unlevered returns. We show that leverage induces heteroskedasticity in returns. Unlevering returns removes this pattern, which is otherwise difficult to address by controlling for leverage in regressions.

Peripheral T cell lymphoma (PTCL) is a heterogeneous group of non-Hodgkin lymphomas with poor prognosis. Up to 30% of PTCL lack distinctive features and are classified as PTCL, not otherwise specified (PTCL-NOS). To further improve our understanding of the genetic landscape and biology of PTCL-NOS, we performed RNA-sequencing of 18 cases and validated results in an independent cohort of 37 PTCL cases. We identified FYN-TRAF3IP2, KHDRBS1-LCK and SIN3A-FOXO1 as new in-frame fusion transcripts, with FYN-TRAF3IP2 as a recurrent fusion detected in 8 of 55 cases. Using ex vivo and in vivo experiments, we demonstrate that FYN-TRAF3IP2 and KHDRBS1-LCK activate signaling pathways downstream of the T cell receptor (TCR) complex and confer therapeutic vulnerability to clinically available drugs.

We propose a novel factor model for option returns. Option exposures are estimated nonparametrically and factor risk premia can vary nonlinearly with states. The model is estimated using regressions, with minimal assumptions on factor and option return dynamics. Using index options, we characterize the conditional risk premia for the market return, market variance, and tail and intermediary risk factors. All average risk premia have the expected sign and meaningful magnitudes. Market and variance risk premia display pronounced time-variation, spike during crises, and always have the expected sign. Combined, market return and variance explain more than 90% of option return variation.

Purpose: KPT-8602 (Eltanexor) is a second-generation exportin-1 (XPO1) inhibitor with potent activity against acute lymphoblastic leukemia (ALL) in preclinical models and with minimal effects on normal cells. In this study, we evaluated whether KPT-8602 would synergize with dexamethasone, vincristine, or doxorubicin, three drugs currently used for the treatment of ALL. Experimental Design: First, we searched for the most synergistic combination of KPT-8602 with dexamethasone, vincristine, or doxorubicin in vitro in both B-ALL and T-ALL cell lines using proliferation and apoptosis as a readout. Next, we validated this synergistic effect by treatment of clinically relevant B- and T-ALL patient-derived xenograft models in vivo. Finally, we performed RNA-sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) to determine the mechanism of synergy. Results: KPT-8602 showed strong synergism with dexamethasone on human B-ALL and T-ALL cell lines as well as in vivo in three patient-derived ALL xenografts. Compared with single-drug treatment, the drug combination caused increased apoptosis and led to histone depletion. Mechanistically, integration of ChIP-seq and RNA-seq data revealed that addition of KPT-8602 to dexamethasone enhanced the activity of the glucocorticoid receptor (NR3C1) and led to increased inhibition of E2F-mediated transcription. We observed strong inhibition of E2F target genes related to cell cycle, DNA replication, and transcriptional regulation. Conclusions: Our preclinical study demonstrates that KPT-8602 enhances the effects of dexamethasone to inhibit B-ALL and T-ALL cells via NR3C1- and E2F-mediated transcriptional complexes, allowing to achieve increased dexamethasone effects for patients.

Consistent with models in which intermediaries absorb net demand pressure from end-users and respond by changing prices, net option demand is positively related to option prices in the market for VIX puts and VIX calls. These findings are consistent with existing results for S&P 500 index (SPX) options (Bollen and Whaley (2004)). They are very robust to variations in the empirical implementation. A joint analysis of net demand pressure in VIX and SPX option markets suggests that the VIX option markets are highly integrated with the SPX put market, but much less so with the market for SPX calls. The impact of net demand shocks on future prices is limited, but shocks to prices significantly affect future net demand.

Expected returns on market volatility, which can be obtained from VIX futures in closed form using standard models, predict subsequent multiperiod realized volatility returns. Multiperiod realized volatility returns are more negative following increases in volatility. Expected volatility returns are always negative. They also become more negative when volatility increases because of differences in mean reversion between the VIX and the risk-neutral VIX. Expected volatility returns negatively predict index returns, because realized volatility returns are negatively correlated with index returns. The results are robust to a wide range of variations in the empirical setup and the inclusion of existing predictors.

We propose no-arbitrage term structure models in which the volatility factors follow GARCH processes. The models’ tractability is similar to that of canonical affine term structure models, but they capture the conditional variances of yields much more accurately. We estimate a model with one volatility factor using Treasury yield data for 1971-2019. Relative to standard affine term structure models with stochastic volatility, the model improves the fit of yield volatility substantially, especially for long-maturity yields. This improvement does not come at the expense of a deterioration in yield fit. We conclude that the ability of no-arbitrage term structure models to extract and model conditional volatility critically depends on the specification of the volatility factors. Modeling volatility as a function of (lagged) squared innovations to factors improves on models where volatility is a linear function of the factors.

Equity options display a strong factor structure. The first principal components of the equity volatility levels, skews, and term structures explain a substantial fraction of the crosssectional variation. Furthermore, these principal components are highly correlated with the S&P 500 index option volatility, skew, and term structure, respectively. We develop an equity option valuation model that captures this factor structure. The model predicts that firms with higher market betas have higher implied volatilities, steeper moneyness slopes, and a term structure that covaries more with the market. The model provides a good fit, and the equity option data support the model's cross-sectional implications.

The Janus kinase 3 (JAK3) tyrosine kinase is mutated in 10% to 16% of T-cell acute lymphoblastic leukemia (T-ALL) cases. JAK3 mutants induce constitutive JAK/STAT signaling and cause leukemia when expressed in the bone marrow cells of mice. Surprisingly, we observed that one third of JAK3-mutant T-ALL cases harbor 2 JAK3 mutations, some of which are monoallelic and others that are biallelic. Our data suggest that wild-type JAK3 competes with mutant JAK3 (M511I) for binding to the common γ chain and thereby suppresses its oncogenic potential. We demonstrate that JAK3 (M511I) can increase its limited oncogenic potential through the acquisition of an additional mutation in the mutant JAK3 allele. These double JAK3 mutants show increased STAT5 activation and increased potential to transform primary mouse pro-T cells to interleukin-7-independent growth and were not affected by wild-type JAK3 expression. These data extend our insight into the oncogenic properties of JAK3 mutations and provide an explanation of why progression of JAK3-mutant T-ALL cases can be associated with the accumulation of additional JAK3 mutations.

We nest multiple volatility components, fat tails, and a U-shaped pricing kernel in a single option model and compare their contribution in describing returns and option data. All three features lead to statistically significant model improvements. A U-shaped pricing kernel is economically most important and improves option fit by 17%, on average, and more so for two-factor models. A second volatility component improves the option fit by 9%, on average. Fat tails improve option fit by just over 4%, on average, but more so when a U-shaped pricing kernel is applied. Overall, these three model features are complements rather than substitutes: the importance of one feature increases in conjunction with the others.

We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of firms. We also document important differences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 firms, we find that copula correlations are highly time-varying and persistent, and that they increase significantly in the financial crisis and have remained high since. Perhaps most importantly, tail dependence of CDS spreads increases even more than copula correlations during the crisis and remains high as well. The most important shocks to credit dependence occur in August of 2007 and in August of 2011, but interestingly these dates are not associated with significant changes to median credit spreads. The decrease in diversification potential caused by the increase in dependence and tail dependence is large. Finally, we find that the CDS volatility, correlation and tail dependence measures that we have constructed using the dynamic copula model are important determinants of credit spreads over time. Monday, May 5, 2014, 10:30-12:00 Room 125, Extranef building at the University of Lausanne Dynamic Dependence and Diversi…cation in Corporate Credit Peter Christo¤ersen Kris Jacobs University of Toronto, University of Houston CBS, and CREATES and Tilburg University Xisong Jin Hugues Langlois University of Luxembourg McGill University December 20, 2013 Abstract We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of …rms. We also document important di¤erences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 …rms, we …nd that copula correlations are highly time-varying and persistent, and that they increase signi…cantly in the …nancial crisis and have remained high since. Perhaps most importantly, tail dependence of CDS spreads increases even more than copula correlations during the crisis and remains high as well. The most important shocks to credit dependence occur in August of 2007 and in August of 2011, but interestingly these dates are not associated with signi…cant changes to median credit spreads. The decrease in diversi…cation potential caused by the increase in dependence and tail dependence is large. Finally, we …nd that the CDS volatility, correlation and tail dependence measures that we have constructed using the dynamic copula model are important determinants of credit spreads over time. JEL Classi…cation: G12 Keywords: credit risk; default risk; CDS; dynamic dependence; copula.We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of …rms. We also document important di¤erences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 …rms, we …nd that copula correlations are highly time-varying and persistent, and that they increase signi…cantly in the …nancial crisis and have remained high since. Perhaps most importantly, tail dependence of CDS spreads increases even more than copula correlations during the crisis and remains high as well. The most important shocks to credit dependence occur in August of 2007 and in August of 2011, but interestingly these dates are not associated with signi…cant changes to median credit spreads. The decrease in diversi…cation potential caused by the increase in dependence and tail dependence is large. Finally, we …nd that the CDS volatility, correlation and tail dependence measures that we have constructed using the dynamic copula model are important determinants of credit spreads over time. JEL Classi…cation: G12

We specify and estimate no-arbitrage models for sovereign CDS contracts by assuming that the country’s default intensity depends on observable economic and …nancial indicators. We estimate these models using a sample of twenty-eight countries, three CDS maturities, and over a decade of daily data. The models provide a good …t. The impact of the economic and …nancial variables on spreads is consistent with economic intuition. Spreads increase as a function of stock market and exchange rate volatility, but decrease as a function of interest rates and stock market returns. The magnitudes of these impacts vary substantially across countries and over time. Estimated risk premiums are also highly time-varying and peak during the 2008 …nancial crisis for nearly all countries. For European countries, the risk premiums are also high during the Eurozone debt crisis. In periods of market stress and high CDS spreads, the increase in market risk premiums is even larger than the increase in default probabilities. The cross-sectional variation in risk premiums across countries is high, also in non-crisis periods.

Peter Christoffersen passed away on June 22, 2018 at an early age. He was one of the most prolific and gifted researchers in the area of derivatives, combining a very strong theoretical background with an appreciation for the practical details of real world markets. He will be sorely missed. This memorial article provides a few general comments about his work and offers reminiscences about Peter as a researcher, a teacher, and a mentor from three of his coauthors and former students.

The polycomb repressive complex 2, with core components EZH2, SUZ12, and EED, is responsible for writing histone 3 lysine 27 trimethylation histone marks associated with gene repression. Analysis of sequence data from 419 T-cell acute lymphoblastic leukemia (T-ALL) cases demonstrated a significant association between SUZ12 and JAK3 mutations. Here we show that CRISPR/Cas9-mediated inactivation of Suz12 cooperates with mutant JAK3 to drive T-cell transformation and T-ALL development. Gene expression profiling integrated with ChIP-seq and ATAC-seq data established that inactivation of Suz12 led to increased PI3K/mammalian target of rapamycin (mTOR), vascular endothelial growth factor (VEGF), and WNT signaling. Moreover, a drug screen revealed that JAK3/Suz12 mutant leukemia cells were more sensitive to histone deacetylase (HDAC)6 inhibition than JAK3 mutant leukemia cells. Among the broad genome and gene expression changes observed on Suz12 inactivation, our integrated analysis identified the PI3K/mTOR, VEGF/VEGF receptor, and HDAC6/HSP90 pathways as specific vulnerabilities in T-ALL cells with combined JAK3 and SUZ12 mutations. ispartof: BLOOD vol:134 issue:16 pages:1323-1336 ispartof: location:United States status: published

A tremendous amount of theoretical and empirical research has been devoted to modeling the dynamics of stock returns and applying this knowledge to valuing equity derivatives. The statistical evidence indicates that the returns process exhibits time-varying diffusive volatility and stochastic jumps in returns, and probably in volatility as well. Moreover, the parameters governing this process appear to drift over time. Yet prices for crude oil and other commodities have not been explored nearly as much, although they are volatile, crucially important to the real economy, and have actively traded futures and options. In this article, the authors go a long way toward correcting this lacuna for derivatives based on crude oil. Their approach is at the current frontier for research on equity derivatives, or indeed beyond it since they allow the jump intensity to vary stochastically over time. Their large sample of daily data spans nearly 25 years of crude oil futures and options, including multiple maturities and degrees of moneyness on each date. Bringing information from both the futures and options markets into the estimation allows much greater statistical power and, more importantly, enforces consistency in the modeling of both derivatives and their underlying. This is a significant advance in our understanding of the price dynamics of the most important commodity, and the futures and option contracts that are based on it.

The computational cost of estimating option valuation models is very high, due to model complexity and the abundance of available option data. We propose an approach that addresses these computational constraints by filtering the state variables using particle weights based on model-implied spot volatilities rather than model prices. We show that this approach is reliable. We illustrate our method by estimating the workhorse stochastic volatility and double-jump models using a big option data set. We obtain more precise estimates of variance risk premia and more plausible implied preference parameters, and we show that for these models moneyness and especially maturity restrictions may result in identification problems. The composition of the option sample affects parameter inference and the relative importance of options and returns in joint estimation.