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Introduction to QuantLib Development - Intensive 3-day Training Course - September 10-12th, 2018 - Download Registration Form Here

 

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Quantitative Finance at arXiv wrote a new blog post titled The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts. (arXiv:1811.08604v1 [q-fin.ST])
We propose a multivariate elastic net regression forecast model for German quarter-hourly electricity spot markets. While the literature is diverse on day-ahead prediction approaches, both the intraday continuous and intraday call-auction prices have not been studied intensively with a clear focus on predictive power. Besides electricity price forecasting, we check for the impact of early day-ahead (DA) EXAA prices on intraday forecasts. Another novelty of this paper is the complementary discussion of economic benefits. A precise estimation is worthless if it cannot be utilized. We elaborate...
10 hours ago
Quantitative Finance at arXiv wrote a new blog post titled An Aspect of Optimal Regression Design for LSMC. (arXiv:1811.08509v1 [q-fin.CP])
Practitioners sometimes suggest to use a combination of Sobol sequences and orthonormal polynomials when applying an LSMC algorithm for evaluation of option prices or in the context of risk capital calculation under the Solvency II regime. In this paper, we give a theoretical justification why good implementations of an LSMC algorithm should indeed combine these two features in order to assure numerical stability. Moreover, an explicit bound for the number of outer scenarios necessary to guarantee a prescribed degree of numerical stability is derived. We embed our observations into a...
10 hours ago
Quantitative Finance at arXiv wrote a new blog post titled Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning. (arXiv:1811.08782v1 [q-fin.CP])
In this work we apply the Deep Galerkin Method (DGM) described in Sirignano and Spiliopoulos (2018) to solve a number of partial differential equations that arise in quantitative finance applications including option pricing, optimal execution, mean field games, etc. The main idea behind DGM is to represent the unknown function of interest using a deep neural network. A key feature of this approach is the fact that, unlike other commonly used numerical approaches such as finite difference methods, it is mesh-free. As such, it does not suffer (as much as other numerical methods) from the curse...
10 hours ago
Quantitative Finance at arXiv wrote a new blog post titled Entropy and Transfer Entropy: The Dow Jones and the build up to the 1997 Asian Crisis. (arXiv:1811.08773v1 [q-fin.ST])
Entropy measures in their various incarnations play an important role in the study of stochastic time series providing important insights into both the correlative and the causative structure of the stochastic relationships between the individual components of a system. Recent applications of entropic techniques and their linear progenitors such as Pearson correlations and Granger causality have have included both normal as well as critical periods in a system's dynamical evolution. Here I measure the entropy, Pearson correlation and transfer entropy of the intra-day price changes of the Dow...
10 hours ago
Quantitative Finance at arXiv wrote a new blog post titled Neural Network for CVA: Learning Future Values. (arXiv:1811.08726v1 [q-fin.CP])
A new challenge to quantitative finance after the recent financial crisis is the study of credit valuation adjustment (CVA), which requires modeling of the future values of a portfolio. In this paper, following recent work in [Weinan E(2017), Han(2017)], we apply deep learning to attack this problem. The future values are parameterized by neural networks, and the parameters are then determined through optimization. Two concrete products are studied: Bermudan swaption and Mark-to-Market cross-currency swap. We obtain their expected positive/negative exposures, and further study the resulting...
10 hours ago
Quantitative Finance at arXiv wrote a new blog post titled A sparse grid approach to balance sheet risk measurement. (arXiv:1811.08706v1 [q-fin.RM])
In this work, we present a numerical method based on a sparse grid approximation to compute the loss distribution of the balance sheet of a financial or an insurance company. We first describe, in a stylised way, the assets and liabilities dynamics that are used for the numerical estimation of the balance sheet distribution. For the pricing and hedging model, we chose a classical Black & Scholes model with a stochastic interest rate following a Hull & White model. The risk management model describing the evolution of the parameters of the pricing and hedging model is a Gaussian model....
10 hours ago
Quantitative Finance at arXiv wrote a new blog post titled Fast mean-reversion asymptotics for large portfolios of stochastic volatility models. (arXiv:1811.08808v1 [math.PR])
We consider a large portfolio limit where the asset prices evolve according certain stochastic volatility models with default upon hitting a lower barrier. When the asset prices and the volatilities are correlated via systemic Brownian Motions, that limit exist and it is described by a SPDE on the positive half-space with Dirichlet boundary conditions which has been studied in \cite{HK17}. We study the convergence of the total mass of a solution to this stochastic initial-boundary value problem when the mean-reversion coefficients of the volatilities are multiples of a parameter that tends to...
10 hours ago
The Reformed Broker wrote a new blog post titled Clips From Today’s Halftime Report
 Stocks see some gains after sell-off from CNBC. Is PayPal a buy? Time to sell Cabot Oil? Those questions and more in #AskHalftime from CNBC. 5 stocks to watch in the trader blitz from CNBC. Goldman Sachs downgraded to equal-weight at Morgan Stanley from CNBC. Final trades: KKR, JPMorgan, Qualcomm, Ensco & Covanta from......
12 hours ago
The Practical Quant wrote a new blog post titled Building tools for enterprise data science
[A version of this post appears on the O'Reilly Radar.]The O'Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science.In this episode of the Data Show, I spoke with Vitaly Gordon, VP of data science and engineering at Salesforce. As the use of machine learning becomes more widespread, we need tools that will allow data scientists to scale so they can tackle many more problems and help many more people. We need automation tools for the many stages involved in data science, including data preparation, feature engineering, model selection and hyperparameter tuning,...
20 hours ago
The Reformed Broker wrote a new blog post titled Yards After Contact
Yards After Contact is the game right now. Be ready to play it. ...
20 hours ago
Quantitative Finance at arXiv wrote a new blog post titled Modeling aggressive market order placements with Hawkes factor models. (arXiv:1811.08076v1 [q-fin.TR])
Price changes are induced by aggressive market orders in stock market. We introduce a bivariate marked Hawkes process to model aggressive market order arrivals at the microstructural level. The order arrival intensity is marked by an exogenous part and two endogenous processes reflecting the self-excitation and cross-excitation respectively. We calibrate the model for an SSE stock. We find that the exponential kernel with a smooth cut-off (i.e. the subtraction of two exponentials) produces much better calibration than the monotonous exponential kernel (i.e. the sum of two exponentials). The...
yesterday
Quantitative Finance at arXiv wrote a new blog post titled Arbitrage Opportunities in CDS Term Structure: Theory and Implications for OTC Derivatives. (arXiv:1811.08038v1 [q-fin.PR])
Absence-of-Arbitrage (AoA) is the basic assumption underpinning derivatives pricing theory. As part of the OTC derivatives market, the CDS market not only provides a vehicle for participants to hedge and speculate on the default risks of corporate and sovereign entities, it also reveals important market-implied default-risk information concerning the counterparties with which financial institutions trade, and for which these financial institutions have to calculate various valuation adjustments (collectively referred to as XVA) as part of their pricing and risk management of OTC derivatives,...
yesterday
Quantitative Finance at arXiv wrote a new blog post titled Economics of disagreement -- financial intuition for the R\'enyi divergence. (arXiv:1811.08308v1 [q-fin.GN])
Lack of accurate intuition is often cited as a scientific challenge, especially when interpreting probabilistic and statistical research. A popular technique for developing statistical intuition involves imagining a game of chance with well-defined financial outcomes. In 1956 Kelly used this technique to propose an intuitive interpretation of relative entropy [1]. He considered a growth-optimizing investor in a game with mutually exclusive outcomes (a "horse race") and showed that the rate of return expected by such an investor is equal to the relative entropy which measures disagreement...
yesterday
Quantitative Finance at arXiv wrote a new blog post titled An updated review of (sub-)optimal diversification models. (arXiv:1811.08255v1 [q-fin.PM])
In the past decade many researchers have proposed new optimal portfolio selection strategies to show that sophisticated diversification can outperform the na\"ive 1/N strategy in out-of-sample benchmarks. Providing an updated review of these models since DeMiguel et al. (2009b), I test sixteen strategies across six empirical datasets to see if indeed progress has been made. However, I find that none of the recently suggested strategies consistently outperforms the 1/N or minimum-variance approach in terms of Sharpe ratio, certainty-equivalent return or turnover. This suggests that...
yesterday
Quantitative Finance at arXiv wrote a new blog post titled A possible alternative evaluation method for the non-use and nonmarket values of ecosystem services. (arXiv:1811.08376v1 [econ.GN])
Monetization of the non-use and nonmarket values of ecosystem services is important especially in the areas of environmental cost-benefit analysis, management and environmental impact assessment. However, the reliability of valuation estimations has been criticized due to the biases that associated with methods like the popular contingent valuation method (CVM). In order to provide alternative valuation results for comparison purpose, we proposed the possibility of using a method that incorporates fact-based costs and contingent preferences for evaluating non-use and nonmarket values, which...
yesterday
Quantitative Finance at arXiv wrote a new blog post titled An analysis of cryptocurrencies conditional cross correlations. (arXiv:1811.08365v1 [q-fin.ST])
This letter explores the behavior of conditional correlations among main cryptocurrencies, using a generalized DCC class model. From a portfolio management point of view, asset correlation is a key metric in order to construct efficient portfolios. We found that correlations including Monero are more stable in time than other correlation pairs.
yesterday
Complexity Digest wrote a new blog post titled The spread of low-credibility content by social bots
Online misinformation is a threat to a well-informed electorate and undermines democracy. Here, the authors analyse the spread of articles on Twitter, find that bots play a major role in the spread of low-credibility content and suggest control measures for limiting the spread of misinformation.   The spread of low-credibility content by social botsChengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kai-Cheng Yang, Alessandro Flammini & Filippo Menczer Nature Communications volume 9, Article number: 4787 (2018) Source: www.nature.com
yesterday
Complexity Digest wrote a new blog post titled Fractional Dynamics of Individuals in Complex Networks
The relation between the behavior of a single element and the global dynamics of its host network is an open problem in the science of complex networks. We demonstrate that for a dynamic network that belongs to the Ising universality class, this problem can be approached analytically through a subordination procedure. The analysis leads to a linear fractional differential equation of motion for the average trajectory of the individual, whose analytic solution for the probability of changing states is a Mittag-Leffler function. Consequently, the analysis provides a linear description of the...
2 days ago
Complexity Digest wrote a new blog post titled Information Dynamics in Urban Crime
Information production in both space and time has been highlighted as one of the elements that shapes the footprint of complexity in natural and socio-technical systems. However, information production in urban crime has barely been studied. This work copes with this problem by using multifractal analysis to characterize the spatial information scaling in urban crime reports and nonlinear processing tools to study the temporal behavior of this scaling. Our results suggest that information scaling in urban crime exhibits dynamics that evolve in low-dimensional chaotic attractors, and this can...
2 days ago
Quantitative Finance at arXiv wrote a new blog post titled A Big data analytical framework for portfolio optimization. (arXiv:1811.07188v1 [q-fin.GN])
With the advent of Web 2.0, various types of data are being produced every day. This has led to the revolution of big data. Huge amount of structured and unstructured data are produced in financial markets. Processing these data could help an investor to make an informed investment decision. In this paper, a framework has been developed to incorporate both structured and unstructured data for portfolio optimization. Portfolio optimization consists of three processes: Asset selection, Asset weighting and Asset management. This framework proposes to achieve the first two processes using a...
2 days ago