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    Elad L. Roisman has been sworn into office as an SEC Commissioner by SEC Chairman Jay Clayton.read more...

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    Elad L. Roisman has been sworn into office as an SEC Commissioner by SEC Chairman Jay Clayton.read more...

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    A number of major cryptocurrency firms are forming the Blockchain Association to lobby Washington, D.C. lawmakers on regulations in the space.

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    The cryptocurrency bear market of 2018 has unsurprisingly affected crypto startups looking to raise funds via initial coin offerings (ICO), with two research papers noting a disappointing performance for the novel fundraising method this year.read more...

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    FINRA announced today that it filed a complaint against Timothy Tilton Ayre of Agawam, Massachusetts, charging him with securities fraud and the unlawful distribution of an unregistered cryptocurrency security called HempCoin. This case represents FINRA’s first disciplinary action involving cryptocurrencies.read more...

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    The least squares Monte Carlo algorithm has become popular for solving portfolio optimization problems. A simple approach is to approximate the value functions on a discrete grid of portfolio weights, then use control regression to generalize the discrete estimates. However, the classical global control regression can be expensive and inaccurate. To overcome this difficulty, we introduce a local control regression technique, combined with adaptive grids. We show that choosing a coarse grid for local regression can produce sufficiently accurate results.

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    For option pricing models and heavy-tailed distributions, this study proposes a continuous-time stochastic volatility model based on an arithmetic Brownian motion: a one-parameter extension of the normal stochastic alpha-beta-rho (SABR) model. Using two generalized Bougerol's identities in the literature, the study shows that our model has a closed-form Monte-Carlo simulation scheme and that the transition probability for one special case follows Johnson's $S_U$ distribution---a popular heavy-tailed distribution originally proposed without stochastic process. It is argued that the $S_U$ distribution serves as an analytically superior alternative to the normal SABR model because the two distributions are empirically similar.

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    Remittances mean an important connection between people working abroad and their home countries. This paper considers them as a measure of preferences revealed by workers, underlying a ranking of countries around the world. We use the World Bank bilateral remittances data between 2010 and 2015 to compare European countries. The database contains international salaries and interpersonal transfers. The suggested least squares method makes the ranking invariant to country sizes and satisfies the property of bridge country independence. Our ranking reveals a crucial aspect of quality of life and may become an alternative to various composite indices.

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    Deregulation of energy markets in the 90s boosted the interest in energy derivatives. Over the last two decades, more and more complex financial instruments were developed. Pricing exotic derivatives often involves Monte Carlo simulations, which rely on stochastic processes to model the underlyings. It is thus critical to choose appropriate models and precisely calibrate them, so that they reflect the market scenario. Several models have been proposed in the literature, from the simple Geometric Brownian motion to more complex mean-reverting, multi-factor models. To enable their calibration against listed vanilla options, it is required to compute the variance of their states. This paper presents a simple and general method to compute the covariance matrix of the state though a matrix Lyapunov differential equation, and discusses its numerical and analytical solutions. In terms of computational speed, the latter is found to be 30 to 40 times faster. The availability of an analytical solution paves the way to an efficient market calibration of model parameters. As case studies, EEX German electricity and TTF Dutch gas markets were considered. Two different single-factor models and a two-factor one were calibrated against market prices: out-of-sample validation showed that a two-factor model outperforms the other two approaches.

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    These are the lecture notes for the summer course given for 2018 Mathematical Finance Summer School at Shandong Unversity. It contains a brief introduction to the Kyle model and the related topics in filtering, enlargement of filtrations and Markov bridges.

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    It has been widely observed that capitalization-weighted indexes can be beaten by surprisingly simple, systematic investment strategies. Indeed, in the U.S. stock market, equal-weighted portfolios, random-weighted portfolios, and other naive, non- optimized portfolios tend to outperform a capitalization-weighted index over the long term. This outperformance is generally attributed to beneficial factor exposures. Here, we provide a deeper, more general explanation of this phenomenon by decomposing portfolio log-returns into an average growth and an excess growth component. Using a rank-based empirical study we argue that the excess growth component plays the major role in explaining the outperformance of naive portfolios. In particular, individual stock growth rates are not as critical as is traditionally assumed.

older | 1 | .... | 165 | 166 | (Page 167)