Complementary cumulative distribution (Survival Function) function of Kolmogorov distribution. exceptions when an error occurs. Prereq: 15.012 G (Spring; first half of term)4-0-2 units. Multiplying this by 1.23|$\%$| implies an impact of CDS introduction on the corporate-debt-to-GDP ratio in our sample of 3.14|$\%$|. C_2^H,0) + \left( 1 - \phi \right)(N - q\lambda C_2^L ) \right] &\mbox{if } F > \tilde{F}_C^L \\ Prereq: Permission of instructor G (Fall, IAP, Summer; second half of term)Units arranged [P/D/F]Can be repeated for credit. \(d(g^{-1})/d\eta = d\mu/d\eta\). \end{align}$$. Bessel function of the second kind of real order and complex argument. \theta \left(1 - \phi \right)\left(N - q\lambda C_2^L \right) + \left( 1 - \theta \right)\left[\phi {\it max}(\gamma N - q\lambda In this synthetic sample, there is no correlation between the treatment and the observed covariates. (1989) Introduces doctoral students to the field and explores where their research interests fit within the broader field. 24 Based on the point estimate of the effect of CDS introduction on the leverage ratio of 1.23|$\%$|, one can perform a back-of-the-envelope calculation to judge the implied effect of CDS introduction on aggregate corporate financing in our sample. 6 Beyond the empty creditor problem in Bolton and Oehmke (2011), the existence of CDSs may affect the financing structure of firms by influencing the monitoring intensity of lenders (Morrison 2005) and by affecting investors incentives to hold synthetic debt rather than primary debt, particularly during economic expansions (Oehmke and Zawadowski 2016; Campello and Matta 2013). Underscores sales force management within the context of go-to-market strategy; however, does not address selling per se. The effect of credit default swaps on credit risk, Credit default swaps, exacting creditors and corporate liquidity management, Noble default-swap verdict in play as test of ISDA system, Inverse probability weighted M-estimators for sample selection, attrition, and stratification. Gauss hypergeometric function 2F1(a, b; c; z). The mean speed , most probable speed v p, and root-mean-square speed can be obtained from properties of the Maxwell distribution.. Primarily for doctoral students. Subject meets with 14.260Prereq: 14.01 U (Spring)4-0-8 units. Primary focus is on microeconomics. Student teams work with a provider, supplier or healthcare-related startup organization on an applied project. Students are required to summarize their work in the context of understanding organization, leadership, teamwork, and task management, in conjunction with 15.317. Prereq: 15.401, 15.414, or 15.415 G (Fall)2-0-4 units. Each case has a full width at half-maximum of very nearly 3.6. Cumulative distribution function of the non-central F distribution. Prereq: None U (Fall, Spring)3-0-9 unitsCredit cannot also be received for 15.516. Presents the modern methods of product development using a systematic innovation approach. Introduces the energy system in terms of sources and uses, market characteristics, and key metrics. Set how special-function errors are handled. \theta \left({1 - \phi } \right)\left( {F - q\lambda C_2^L } \right) + \left( {1 - \theta } \right)\left[ {\phi {\it max}(\gamma N - q\lambda C_2^H,0) + \left( {1 - \phi } \right)(S - q\lambda C_2^L )} \right] &\mbox{if } F \in (F_C^L,\tilde{F}_C^L]\\[6pt] Prereq: Permission of instructor G (Fall, Spring)3-0-3 units. Provides integrated approach to analyze the economy, geopolitics, and geo-economy of China through action learning. Restricted to Sloan Fellow MBAs. Studies effects of digitization and technology on business strategy and organizational structure. ellip_harm(h2,k2,n,p,s[,signm,signn]), Ellipsoidal harmonic normalization constants gamma^p_n. Units assigned to MBA students upon completion of the Sloan Intensive Period(SIP) elective requirement. Observations are weighted using overlap weights (Li, Morgan, and Zaslavsky 2018). Extensive reading and discussion of research literature explores the application of these theories to business issues with relevant guest speakers. Tools covered include monadic pricing surveys, empirical price elasticity calculations, and conjoint. Same subject as EC.731[J], MAS.665[J]Prereq: Permission of instructor G (Fall)3-0-9 units. Applies finance science and financial engineering tools and theory to asset management, lifecycle investing, and retirement finance. variance proportional to mean as in the quasi-binomial model, note If |$F > F_C^H $|, strategic default would always arise even in the up-up state in our binomial path, and the maximum pledgeable cash flow degenerates to |$\phi q\lambda C_2^H + (1 - \phi )q\lambda C_2^L $|, which is less than the funding the firm would have achieved at |$F = F_C^H $| in Equation (1). Opportunities resulting from demand growth, supply challenges, environmental constraints, security of supply, technology breakthroughs, and regulation are analyzed from the perspectives of both established players and entrepreneurs. Explores a wide range of strategic problems, focusing particularly on the sources of competitive advantage and the interaction between industry structure and organizational capabilities. Our final sample consists of an unbalanced panel of more than 56,000 firms across 51 countries over the period 20012015. The sample consists of an unbalanced panel of more than 56,000 nonfinancial firms across 51 countries over the period 20012015. For example, the logit function is the canonical link function for logistic regression and allows transformations between probabilities and log-odds. Prereq: None. This approach specifies a grid of possible parameters that determine the empirical distribution of the confounder in order to capture the characteristics of potential confounders that could drive the estimated treatment effect to zero. Addresses law-sensitive issues arising in the overlapping contexts of complex deals and financial services and products. logical function. 1998; Djankov, McLiesh, and Shleifer 2007; Djankov, Hart, et al. Limited to 60. To focus our identification on the introduction of CDSs, we do not include in our main results any firm-year observations of CDS firms after the introduction of CDSs. Provides the tools to better understand an individual's unique way of leading, i.e., one's leadership signature. Introspective course that helps students understand and develop their unique way of leading, i.e., their leadership signature. Restricted to first-year Sloan master's students. Same subject as 14.441[J]Prereq: None G (Spring)3-0-9 units. Priority to Sloan Fellows MBAs. Natural logarithm of absolute value of beta function. Considers key strategic concepts and ideas useful for managers and entrepreneurs, especially the distinction between a product versus a platform strategy as well as product versus a service strategy. Applications to a variety of business decisions that arise in different industries, both within and outside the firm. Presents material through a combination of cases, lectures, and a group project. Prereq: 6.041B, 15.0791, or permission of instructor U (Spring)4-0-5 unitsCredit cannot also be received for 15.734, 15.761. Compute nt zeros of Bessel derivative Y1'(z), and value at each zero. Get the current way of handling special-function errors. \theta F + \left( {1 - \theta } \right)\left[\phi {\it max}(\gamma N,q\lambda C_2^H ) + \left( {1 - \phi } \right)S \right] & \mbox{if }F \le \tilde{F}_C^L \\\theta \left[\phi F + \left( 1 - \phi \right)S \right] +\left(1 - \theta \right)& \\ Restricted to Sloan Fellow MBAs. Topics include basic financial analysis for the life-sciences professional; risks and returns in the biopharma industries; the mechanics of biotech startup financing; capital budgeting for biopharma companies; and applications of financial engineering in modern healthcare investment strategies and institutions. Executives then discuss what they did, or are doing, and reflect on their own journeys as enterprise-level leaders. Taught through the lens of US policy decision-making; also covers international dimensions. Focuses on the emerging legal framework of cutting-edge digital technologies, including AI/machine learning, big data and analytics, blockchain, the internet, and social media. Project-based subject, in which teams of students from MIT and Harvard work with startups on problems of strategic importance to the venture. Specifically, our results indicate that while the introduction of CDS contracts is associated with higher leverage, this effect is significantly larger when the legal environment provides creditors with greater certainty about their ability to use their (stronger) creditor rights (high |$\gamma $|, proxied by creditors ability to restrict entry into reorganization); with weaker ability to enforce contracts (low |$\lambda $|, proxied by weak property rights); with higher priority in the event of liquidation (high |$S$|, proxied by the payment of liquidation proceeds to secured creditors first); and with weaker initial bargaining power relative to shareholders (low |$q$|, proxied by the extent to which the firm is closely held). Successful entrepreneurs, including VCs and social impact founder-builders, are recruited to develop brief descriptions of major issues to overcome. Builds upon and integrates material from core topics, such as economics and organizational processes. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details. Standard errors are clustered at the firm level and are reported in parentheses. Incorporates practical applications from several industries including finance, insurance, biotechnology, pharmaceuticals, and government policy. Primarily for doctoral students. Restricted to Tata Fellows. Applies advanced entrepreneurial techniques to build and iterate a venture in a time-compressed manner. The use of CBPS involves fitting the propensity-score model subject to the constraint of matching (potentially multiple) moments of the covariate distribution. Introduces concepts of corporate financial accounting and reporting of information widely used in making investment decisions, corporate and managerial performance assessment, and valuation of firms. This fact is known as the 68-95-99.7 (empirical) rule, or the 3-sigma rule.. More precisely, the probability that a normal deviate lies in the range between and Compute derivatives of Bessel functions of the second kind. The first term applies the derivative of the inverse link function to every linear predictor in the model, and the second term is the covariate matrix from our data! Required subject spanning the Sloan Fellows summer term. Prereq: 15.809, 15.814, or permission of instructor G (Fall) HASS-SCredit cannot also be received for 14.444[J], 15.038[J]. Not offered regularly; consult department3-3-3 units. Subject meets with 21A.129Prereq: None Acad Year 2022-2023: U (Spring) Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details. Prereq: 15.280, 15.284, or permission of instructor G (Spring; first half of term)3-0-3 unitsCredit cannot also be received for 15.287, 15.721. Note that it reduces their payoff only in the |$H$| state at time 2, in which the continuation value of the firm turns out to be high (i.e., sufficient to pay off creditors), and there is some probability |$\varepsilon $| that creditors cannot trigger CDS payments. model. Prereq: None G (Fall, Spring; second half of term)3-0-3 units. Prereq: Permission of instructor G (Fall) Subject meets with 15.4331Prereq: 15.401, 15.414, or 15.415 G (Fall)3-0-6 units. No prior knowledge of law expected. No listeners. Meets with 15.394 when offered concurrently. log(ij)=0+1newprocessij+2time_devij+3temp_devij+4supplier_Cij+5supplier_Bij+bi, defectsij j ( j = 1, 2, , 5) i ( i = 1, 2, , 20) , supplier_Cij supplier_Bij C B j i , bi ~ N(0,b2) i , 'defects ~ 1 + newprocess + time_dev + temp_dev + supplier + (1|factory)', fitglme 'Distribution' 'Poisson' fitglme , mfr newprocesstime_devtemp_dev supplier , Model information (100) ( 6 20) (1) Poisson Log Laplace , Model fit statistics (AIC) (BIC) (LogLikelihood) (Deviance) , Fixed effects coefficients fitglme 95% 1 1 (Name) 2 (Estimate) 3 (SE) 4 (tStat) 0 t 5 (DF) 6 (pValue) t p 2 (Lower Upper) 95% , Random effects covariance parameters ( factory ) (20) std fitglme 0.31381 () 1 , fitglme covarianceParameters , fitglme GLME , , fixedEffects t 0 p , randomEffects GLME EBP () CMSEP () t 0 p , covarianceParameters GLME , designMatrix GLME , , anova F () 0 anova , coefCI GLME fitglme 95% coefCI , coefTest , GLME , fitted , predict , refit GLME , residuals , plotResiduals , MATLAB Web MATLAB . Despite its name, the first explicit analysis of the properties of the Cauchy distribution was published by the French Same subject as 6.7220[J]Prereq: 18.06 and (18.100A, 18.100B, or 18.100Q) G (Spring)4-0-8 units, Same subject as 6.7700[J]Prereq: Calculus II (GIR) G (Fall)4-0-8 units, T. Broderick, D. Gamarnik, Y. Polyanskiy, J. N. Tsitsiklis, Prereq: Calculus I (GIR) and permission of instructor G (Summer; first half of term)1-0-2 units. Uses statistics software R, Python, and MATLAB. Foundational, applied course providing instruction in the tools and techniques of corporate financial management from the perspective of the CFO. Students work in multi-disciplinary teams (combining MFin, MBA, and Sloan Fellows) to analyze and problem-solve, culminating in reports which teams present in a group setting for evaluation and feedback. In-depth analysis of the structure of the private equity industry. Students practice experiential interviewing and discuss how to use metaphor analysis, observation, the voice of the customer, and other methods to uncover customer needs. Intended for students interested in building a life science company or working in the sector as a manager, consultant, analyst, or investor. Two central themes: How to think systematically and strategically about aspects of managing the organization's human assets, and what really needs to be done to implement these policies and to achieve competitive advantage. Lectures are combined with cases, guest speakers, and brainstorming sessions where students work in teams to apply concepts to real-world problems. The name comes from the fact that the logit function, defined as logit(p) = log(p / (1 p)), is the inverse of the logistic function. Clarifies the interactions among competition, patterns of technological and market change, and the development of internal firm capabilities. Not offered regularly; consult department3-0-3 units. The problems will vary with the organization in question, as will the skills and capabilities students draw on to appropriately address them. Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details. Prereq: 15.342 Acad Year 2022-2023: G (Spring) Expectations and evaluation criteria differ for students taking graduate version; consult syllabus or instructor for specific details. Covers complex valuations, modelling of capital structure decisions, financial restructuring, analysis and modelling of merger transactions, and real options. Meets with 15.025 when offered concurrently. Focuses on identifying core leadership strengths and weaknesses, immunity to change, and developing one's leadership signature. For creditor rights, we use an aggregate index (Creditor Rights) as well as its four subindexes, namely, restrictions on a firm entering reorganization without creditors consent (Restrictions on Entry); no automatic stay or asset freeze (No Automatic Stay); restriction on managements administration of a firms assets pending resolution of the reorganization (Management Does Not Stay); and payment of secured creditors first out of any liquidation proceeds (Secured Creditors First). Application required; consult instructor. Preparation for an organizational change project. Meets with 15.2191[J] when offered concurrently. Provides students opportunities to meet senior executives of private and public institutions, and discuss key management issues from the perspective of top management. Coreq: 15.915 G (Spring; second half of term)3-0-3 units. Focuses on developing the skills and tools needed to successfully apply systems thinking and simulation modeling in diverse real-world settings, including growth strategy, management of technology, operations, public policy, product development, supply chains, forecasting, project management, process improvement, service operations, and platform-based businesses, among others. Teams gather evidence that permits a fact-based iteration across multiple application domains, markets, functionalities, technologies, and products, leading to a recommendation that maps a space of opportunity and includes actionable next steps to evolve the market and technology. Prereq: None. Prereq: 15.900 or permission of instructor G (Fall; first half of term) Students examine particular applications to deepen their understanding of topical issues. Covers monetary policy, bank regulation and crisis management, drawing on the experience of the Federal Reserve, the ECB and other central banks in advanced and emerging market economies. Develops writing, speaking, teamwork, interpersonal, social media, and cross-cultural communication skills necessary for management professionals. Calculate non-centrality parameter for non-central t distribution. Preference to Sloan Master of Business Analytics students. History. Same subject as 2.351[J]Prereq: Permission of instructor G (Fall, Spring)3-0-3 units. We use Closely Held Shares, the fraction of equity ownership held by controlling shareholders, obtained from Worldscope, as our proxy for concentration of shareholder ownership. - \left( {1 - \theta } \right)q\left[ {\phi C_2^H 1_{\gamma N > q\lambda C_2^H } + \left( {1 - \phi } \right)C_2^L } \right] & \mbox{if }F \le F_C^L \\- \theta \left( {1 - \phi } \right)qC_2^L - \left( {1 - \theta } \right)q\left[ {\phi C_2^H 1_{\gamma N > q\lambda C_2^H } + \left( {1 - \phi } \right)C_2^L } \right] & \mbox{if }F > F_C^L \\ However, as Figure 1 shows, while the overlap weighting procedure does not consider moments beyond the mean, the empirical density functions match relatively well even for covariates with the largest deviations in densityand markedly better than in the unweighted sample. Introduction to behavioral economics for future managers, analysts, consultants or advisors to private and public enterprises. Our overlap weighting approach, in contrast, uses the resultant propensities as balancing weights. Presents examples of successful applications in credit ratings, fraud detection, marketing, customer relationship management, investments, and synthetic clinical trials. \theta \left[ \phi F + \left( 1 - \phi \right)N \right] + \left(1- \theta \right) & \\ Also covers design of experiments, missing data imputations, mixture of Gaussian models, exact bootstrap, and sparse matrix estimation, including principal component analysis, factor analysis, inverse co-variance matrix estimation, and matrix completion. - \theta \left( {1 - \phi } \right)\lambda C_2^L - \left( {1 - \theta } \right)\lambda \left[ {\phi C_2^H 1_{\gamma N > q\lambda C_2^H } + \left( {1 - \phi } \right)C_2^L } \right] &\mbox{if }F > F_C^L \\ Among firms and non-CDS firms, those with a Lab component that skills Predicted probability of treatment will be down-weighted to account for the noncentral F-distribution projects include valuation of an panel Real situations and hypothetical examples we source the LLSV variable Restrictions on entry reorganization! `` dual-track '' approach to the unexpected with confidence and agility the swap. 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