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The New Rules of Marketing and PR: How to Use Social Media, Online Video, Mobile Applications, Blogs, News Releases, and Viral Marketing to Reach Buyers Directly, 6th Edition

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When it comes to marketing, anything goes in the Digital Age, right? Well, not quite. While marketing and public relations tactics do seem to change overnight, every smart businessperson knows that it takes a lot more than the 'next big thing.'

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Key Account Management - Das Praxishandbuch B2B

Building Resilience to Global Risks: Challenges for African Central Banks

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BIS Papers No 93 by Benedicte Vibe Christensen and Christian Upper. The policy response of many African commodity exporting economies to the slump in commodity prices after mid-2014 has been markedly different from that of commodity exporters elsewhere. First, few African countries allowed their currency to depreciate as much as other EMEs, for instance in Latin America. Instead they resorted mainly to administrative controls, despite the high economic costs associated with such measures. Second, many African economies kept their policy rates very low despite...

Ethics in Social Networking and Business 1: Theory, Practice and Current Recommendations

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This book, the first of two volumes dedicated to ethics in social networking and business, presents the notions, theories and practical aspects related to ethics, morale and deontology in our society.

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CFTC Charges South Carolina Resident Thomas Lanzana, Florida Resident Nikolay Masanko, and Their Companies Blackbox Pulse, LLC and White Cloud Mountain, LLC with Fraud, Misappropriation, and Registration Violations

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The U.S. Commodity Futures Trading Commission (CFTC) filed a civil enforcement action against Defendants Thomas Lanzana (d/b/a Unique Forex) and his company Blackbox Pulse, LLC, and Nikolay Masanko and his company White Cloud Mountain, LLC, charging them with fraud in connection with soliciting customers for their foreign currency derivatives trading pools and other investments.


DGM: A deep learning algorithm for solving partial differential equations. (arXiv:1708.07469v1 [q-fin.MF])

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High-dimensional PDEs have been a longstanding computational challenge. We propose a deep learning algorithm similar in spirit to Galerkin methods, using a deep neural network instead of linear combinations of basis functions. The PDE is approximated with a deep neural network, which is trained on random batches of spatial points to satisfy the differential operator and boundary conditions. The algorithm is mesh-less, which is key since meshes become infeasible in higher dimensions. Instead of forming a mesh, sequences of spatial points are randomly sampled. We implement the approach for American options (a type of free-boundary PDE which is widely used in finance) in up to 100 dimensions. We call the algorithm a "Deep Galerkin Method (DGM)".

Second order approximations for limit order books. (arXiv:1708.07394v1 [q-fin.MF])

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In this paper we derive a second order approximation for an infinite dimensional limit order book model, in which the dynamics of the incoming order flow is allowed to depend on the current market price as well as on a volume indicator (e.g. the volume standing at the top of the book). We study the fluctuations of the price and volume process relative to their first order approximation given in ODE-PDE form under two different scaling regimes. In the first case we suppose that price changes are really rare, yielding a constant first order approximation for the price. This leads to a measure valued SDE driven by an infinite dimensional Brownian motion in the second order approximation of the volume process. In the second case we use a slower rescaling rate, which leads to a non-degenerate first order approximation and gives a PDE with random coefficients in the second order approximation for the volume process.

Optimal firm's policy under lead time-and price-dependent demand: interest of customers rejection policy. (arXiv:1708.07305v1 [q-fin.PR])

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Considering a lead-time-and price-sensitive demand, we investigate whether a client rejection policy, modeled as M/M/1/K system, can be more profitable than an all-client acceptance policy, modeled as M/M/1 system. We provide analytical insights for the cases with and without holding and penalty costs by comparing M/M/1/1 to M/M/1 models.


M&A Disputes: A Professional Guide to Accounting Arbitrations

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M&A Disputes takes you inside the dispute resolution process to help you put together the many "moving parts" necessary to obtain a successful outcome. With deep insight from experts in the field—including valuable advice from the arbitrator's perspective—this book guides you through the entire process to explore the variables at work. The high volume of M&A transactions makes post-closing

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JavaScript Is Eating The World

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#JavaScript Is Eating The World https://t.co/REU7XplJHV — moneyscience (@moneyscience) August 25, 2017

The Contractor's NEC3 ECC Handbook

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Addresses the daily challenges faced by contractors who use the NEC3 ECC with clear, practical and useable advice on how to solve them

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2017 International Valuation Handbook - Guide to Cost of Capital + Semiannual PDF Update (Set)

Promotion through Connections: Favors or Information?. (arXiv:1708.07723v1 [q-fin.EC])

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Connections appear to be helpful in many contexts such as obtaining a job, a promotion, a grant, a loan or publishing a paper. This may be due to favoritism or to information conveyed by connections. Attempts at identifying both effects have relied on measures of true quality, generally built from data collected long after promotion. This empirical strategy faces important limitations. Building on earlier work on discrimination, we propose a new method to identify favors and information from classical data collected at time of promotion. Under natural assumptions, we show that promotion decisions look more random for connected candidates, due to the information channel. We obtain new identification results and show how probit models with heteroscedasticity can be used to estimate the strength of the two effects. We apply our method to the data on academic promotions in Spain studied in Zinovyeva & Bagues (2015). We find evidence of both favors and information effects at work. Empirical results are consistent with evidence obtained from quality measures collected five years after promotion.

Dynamic trading under integer constraints. (arXiv:1708.07661v1 [q-fin.MF])

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In this paper we investigate discrete time trading under integer constraints, that is, we assume that the offered goods or shares are traded in integer quantities instead of the usual real quantity assumption. For finite probability spaces and rational asset prices this has little effect on the core of the theory of no-arbitrage pricing. For price processes not restricted to the rational numbers, a novel theory of integer arbitrage free pricing and hedging emerges. We establish an FTAP, involving a set of absolutely continuous martingale measures satisfying an additional property. The set of prices of a contingent claim is no longer an interval, but is either empty or dense in an interval. We also discuss superhedging with integral portfolios.

Trends and Risk Premia: Update and Additional Plots. (arXiv:1708.07637v1 [q-fin.PM])

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Recently, our group has published two papers that have received some attention in the finance community. One is about the profitability of trend following strategies over 200 years, the second is about the correlation between the profitability of "Risk Premia" and their skewness. In this short note, we present two additional plots that fully corroborate our findings on new data.


Feedback effect between Volatility of capital flows and financial stability: evidence from Democratic Republic of Congo. (arXiv:1708.07636v1 [q-fin.CP])

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Financial system being the place of metting capital flows (equality between saving and investment), a volatility of capital flows can destroy the robustness and good working of financial system, it means subvert financial stability. The same a weak financial system, few regulated and bad manage can exacerbate volatility of capital flows and finely undermine financial stability. The present study provides evidence on feedback effect between volatility of capital flows and financial stability in Democratic republic of Congo (DRC), and estimate the contributions of macroeconomic and macroprudential policies in the attenuation volatility of capital flows effects on financial stability and in the prevention of instability financial. Assessment dynamic regression model a la Feldstein-Horioka we showed that financial system is widely supplied and financed by internationals capital flows. This implicate Congolese economy is financially mobile, that can be dangerous for financial stability. The study dynamic econometric of financial system's absolute size, we stipulate financial system has a systemic weight on real economy. Hence a shock of financial system could have devastating effects on Congolese economy. We estimate a vector autoregressive (VAR) model for prove the bilateral causality and impacts of macroeconomic and macroprudential policies. With regard to results, it proved on the one there is a feedback effect between volatility of capital flows and financial stability, on the other hand macroeconomic and macroprudential policies can't attenuate volatility of capital flows and prevent instability financial. It prove macroprudential approach is given a better result than monetary policy. The implementation of framework macroprudential by Central Bank of Congo will be beneficial in the realization of financial stability and attenuation volatility of capital flows.Keywords: Volatility of capital flows, financial stability, macroeconomic and macroprudential policies

Semiparametric GARCH via Bayesian model averaging. (arXiv:1708.07587v1 [stat.ME])

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As the dynamic structure of the financial markets is subject to dramatic changes, a model capable of providing consistently accurate volatility estimates must not make strong assumptions on how prices change over time. Most volatility models impose a particular parametric functional form that relates an observed price change to a volatility forecast (news impact function). We propose a new class of functional coefficient semiparametric volatility models where the news impact function is allowed to be any smooth function, and study its ability to estimate volatilities compared to the well known parametric proposals, in both a simulation study and an empirical study with real financial data. We estimate the news impact function using a Bayesian model averaging approach, implemented via a carefully developed Markov chain Monte Carlo (MCMC) sampling algorithm. Using simulations we show that our flexible semiparametric model is able to learn the shape of the news impact function from the observed data. When applied to real financial time series, our new model suggests that the news impact functions are significantly different in shapes for different asset types, but are similar for the assets of the same type.

Haircutting Non-cash Collateral. (arXiv:1708.07585v1 [q-fin.PR])

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Haircutting non-cash collateral has become a key element of the post-crisis reform of the shadow banking system and OTC derivatives markets. This article develops a parametric haircut model by expanding haircut definitions beyond the traditional value-at-risk measure and employing a double-exponential jump-diffusion model for collateral market risk. Haircuts are solved to target credit risk measurements, including probability of default, expected loss or unexpected loss criteria. Comparing to data-driven approach typically run on proxy data series, the model enables sensitivity analysis and stress test, captures market liquidity risk, allows idiosyncratic risk adjustments, and incorporates relevant market information. Computational results for main equities, securitization, and corporate bonds show potential for uses in collateral agreements, e.g. CSAs, and for regulatory capital calculations.

Active Preference Learning for Personalized Portfolio Construction. (arXiv:1708.07567v1 [cs.CE])

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In financial asset management, choosing a portfolio requires balancing returns, risk, exposure, liquidity, volatility and other factors. These concerns are difficult to compare explicitly, with many asset managers using an intuitive or implicit sense of their interaction. We propose a mechanism for learning someone's sense of distinctness between portfolios with the goal of being able to identify portfolios which are predicted to perform well but are distinct from the perspective of the user. This identification occurs, e.g., in the context of Bayesian optimization of a backtested performance metric. Numerical experiments are presented which show the impact of personal beliefs in informing the development of a diverse and high-performing portfolio.

The Keynesian Model in the General Theory: A Tutorial. (arXiv:1708.07509v1 [q-fin.EC])

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This small overview of the General Theory is the kind of summary I would have liked to have read, before embarking in a comprehensive study of the General Theory at the time I was a student. As shown here, the main ideas are quite simple and easy to visualize. Unfortunately, numerous introductions to Keynesian theory are not actually based on Keynes opus magnum, but in obscure neoclassical reinterpretations. This is completely pointless since Keynes' book is so readable.





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