IEEE Journal of Selected Topics in Signal Processing

Issue 6 • Sept. 2016

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  • Frontcover

    Publication Year: 2016, Page(s): C1
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  • IEEE Journal of Selected Topics in Signal Processing publication information

    Publication Year: 2016, Page(s): C2
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  • [Blank page]

    Publication Year: 2016, Page(s): B976
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  • Table of Contents

    Publication Year: 2016, Page(s):977 - 978
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  • Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading

    Publication Year: 2016, Page(s):979 - 981
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  • Covariance Versus Precision Matrix Estimation for Efficient Asset Allocation

    Publication Year: 2016, Page(s):982 - 993
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (371 KB) | HTML iconHTML Multimedia Media

    Asset allocation constitutes one of the most crucial and most challenging tasks in financial engineering, which often requires the estimation of large covariance or precision matrices, from short time-span multivariate observations, a mandatory yet difficult step. The present contribution reviews and compares a large selection of estimators for covariance and precision matrices, organized into cla... View full abstract»

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  • Filtering of a Discrete-Time HMM-Driven Multivariate Ornstein-Uhlenbeck Model With Application to Forecasting Market Liquidity Regimes

    Publication Year: 2016, Page(s):994 - 1005
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2189 KB) | HTML iconHTML

    This paper investigates the modeling of risk due to market and funding liquidity by capturing the joint dynamics of three time series: the treasury-Eurodollar spread, the VIX, and a metric derived from the S&P 500 spread. We propose a two-regime mean-reverting model for explaining the behaviour of three time series, which mirror liquidity levels for financial markets. An expectation-maximisation a... View full abstract»

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  • Covariance Matrix Estimation for Interest-Rate Risk Modeling via Smooth and Monotone Regularization

    Publication Year: 2016, Page(s):1006 - 1014
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1025 KB) | HTML iconHTML

    Estimating covariance matrices in high-dimensional settings is a challenging problem central to modern finance. The sample covariance matrix is well-known to give poor estimates in high dimensions with insufficient samples, and may cause severe risk underestimates of optimized portfolios in the Markowitz framework. In order to provide useful estimates in this regime, a variety of improved covarian... View full abstract»

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  • Gaussian Process Regression Stochastic Volatility Model for Financial Time Series

    Publication Year: 2016, Page(s):1015 - 1028
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1777 KB) | HTML iconHTML

    Traditional economic models have rigid-form transition functions when modeling time-varying volatility of financial time series data and cannot capture other time-varying dynamics in the financial market. In this paper, combining the Gaussian process state-space model framework and the stochastic volatility (SV) model, we introduce a new Gaussian process regression stochastic volatility (GPRSV) mo... View full abstract»

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  • Data-Driven Stochastic Pricing and Application to Electricity Market

    Publication Year: 2016, Page(s):1029 - 1039
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (896 KB) | HTML iconHTML Multimedia Media

    This paper develops a novel approach to computation of the probability integrals encountered in derivative pricing using stochastic models estimated from historical data. First, nonparametric probability distribution models are built directly from the data as a solution of a convex optimization problem scalable to very big datasets. Second, these models are used for numerical calculus of probabili... View full abstract»

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  • Estimating Tipping Points in Feedback-Driven Financial Networks

    Publication Year: 2016, Page(s):1040 - 1052
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1536 KB) | HTML iconHTML

    Much research has been conducted arguing that tipping points at which complex systems experience phase transitions are difficult to identify. To test the existence of tipping points in financial markets, based on the alternating offer strategic model we propose a network of bargaining agents who mutually either cooperate or compete, where the feedback mechanism between trading and price dynamics i... View full abstract»

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  • Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer

    Publication Year: 2016, Page(s):1053 - 1060
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (392 KB) | HTML iconHTML

    We solve a multi-period portfolio optimization problem using D-Wave Systems' quantum annealer. We derive a formulation of the problem, discuss several possible integer encoding schemes, and present numerical examples that show high success rates. The formulation incorporates transaction costs (including permanent and temporary market impact), and, significantly, the solution does not require the i... View full abstract»

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  • Sequential Detection of Market Shocks With Risk-Averse CVaR Social Sensors

    Publication Year: 2016, Page(s):1061 - 1072
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (588 KB) | HTML iconHTML

    This paper considers a statistical signal processing problem involving agent-based models of financial markets, which at a microlevel are driven by socially aware and risk-averse agents. These agents trade (buy or sell) stocks at each trading instant by using the decisions of all previous agents (social learning) in addition to a private (noisy) signal they receive on the value of the stock. We ar... View full abstract»

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  • An Environment for Rapid Derivatives Design and Experimentation

    Publication Year: 2016, Page(s):1073 - 1082
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (714 KB) | HTML iconHTML

    In the highly competitive world of modern finance, new derivatives are continually required to take advantage of changes in financial markets, and to hedge businesses against new risks. The research described in this paper aims to accelerate the development and pricing of new derivatives in two different ways. First, new derivatives can be specified mathematically within a general framework, enabl... View full abstract»

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  • Mid-Price Prediction in a Limit Order Book

    Publication Year: 2016, Page(s):1083 - 1092
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (571 KB) | HTML iconHTML

    We propose several nonparametric predictors of the mid-price in a limit order book, based on different features constructed from the order book data observed contemporaneously. contemporaneously and in the recent past. We evaluate our predictors in the context of an order execution task by constructing order execution strategies that incorporate these predictors. In our evaluations, we use a large... View full abstract»

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  • Risk-Averse Multi-Armed Bandit Problems Under Mean-Variance Measure

    Publication Year: 2016, Page(s):1093 - 1111
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    The multi-armed bandit (MAB) problems have been studied mainly under the measure of expected total reward accrued over a horizon of length T . In this paper, we address the issue of risk in MAB problems and develop parallel results under the measure of mean-variance, a commonly adopted risk measure in economics and mathematical finance. We show that the model-specific regret and the model-independ... View full abstract»

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  • Financial Stress Through Complexity Science

    Publication Year: 2016, Page(s):1112 - 1126
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1726 KB) | HTML iconHTML

    Financial markets typically undergo periods of prosperity followed by periods of stagnation, and this undulation makes it challenging to maintain market efficiency. The efficient market hypothesis (EMH) states that there exist differences in structural complexity in security prices between regular and abnormal situations. Yet, despite a clear link between market acceleration (cf. recession in secu... View full abstract»

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  • IEEE Journal of Selected Topics in Signal Processing information for authors

    Publication Year: 2016, Page(s):1127 - 1128
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  • IEEE Signal Processing Society Information

    Publication Year: 2016, Page(s): C3
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  • [Blank page]

    Publication Year: 2016, Page(s): C4
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Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief

Shrikanth (Shri) S. Narayanan
Viterbi School of Engineering 
University of Southern California
Los Angeles, CA 90089 USA
shri@sipi.usc.edu