Transaction cost becomes significant when one holds many securities in a large portfolio where capital allocations are frequently rebalanced due to variations in non-stationary…
Abstract
Purpose
Transaction cost becomes significant when one holds many securities in a large portfolio where capital allocations are frequently rebalanced due to variations in non-stationary statistical characteristics of the asset returns. The purpose of this paper is to employ a sparsing method to sparse the eigenportfolios, so that the transaction cost can be reduced and without any loss of its performance.
Design/methodology/approach
In this paper, the authors have designed pdf-optimized mid-tread Lloyd-Max quantizers based on the distribution of each eigenportfolio, and then employed them to sparse the eigenportfolios, so those small size orders may usually be ignored (sparsed), as the result, the trading costs have been reduced.
Findings
The authors find that the sparsing technique addressed in this paper is methodic, easy to implement for large size portfolios and it offers significant reduction in transaction cost without any loss of performance.
Originality/value
In this paper, the authors investigated the performance the sparsed eigenportfolios of stock returns in S&P500 Index. It is shown that the sparsing method is simple to implement and it provides high levels of sparsity without causing PNL loss. Therefore, transaction cost of managing a large size portfolio is reduced by employing such an efficient sparsity method.
Details
Keywords
The purpose of this paper is to present an overview of the flash crash, and explain why and how it happened.
Abstract
Purpose
The purpose of this paper is to present an overview of the flash crash, and explain why and how it happened.
Design/methodology/approach
The author summarizes several studies suggesting various perspectives on the flash crash and its causes. Furthermore, the author highlights recently proposed and introduced improvements and regulations to reduce the risk of having similar market collapses in the future.
Findings
It is an overview paper that highlights the state of the art on the subject.
Research limitations/implications
Paper does not report any research findings of the author.
Practical implications
High-frequency trading (HFT) along with its pros and cons is the new normal for most of the current electronic trading activity in the markets. It is well recognized by the experts that HFT may have its important shortcomings whenever the rules and regulations are not up to date to match the technological progress offering faster computational and execution capabilities.
Social implications
HFT has created a societal discussion about its benefits and potential deficiencies as the common practice for trading due to potentially unequal access to market data by various categories of participants. Such arguments help the regulators to develop improvements to reduce the market risk and nurture more robust and fair markets for all.
Originality/value
The paper has a tutorial value and summarizes the current state of HFT. The readers of more interest are guided to the most relevant literature for further reading.
Details
Keywords
Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the…
Abstract
Purpose
Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the amount of deteriorate at any time, this paper aims to present a prognostics approach based on integrating optimize health indicator (OHI) and machine learning algorithm.
Design/methodology/approach
Proposed optimum prediction model would be used to evaluate the remaining useful life (RUL) of REBs. Initially, signal raw data are preprocessing through mother wavelet transform; after that, the primary fault features are extracted. Further, these features process to elevate the clarity of features using the random forest algorithm. Based on variable importance of features, the best representation of fault features is selected. Optimize the selected feature by adjusting weight vector using optimization techniques such as genetic algorithm (GA), sequential quadratic optimization (SQO) and multiobjective optimization (MOO). New OHIs are determined and apply to train the network. Finally, optimum predictive models are developed by integrating OHI and artificial neural network (ANN), K-mean clustering (KMC) (i.e. OHI–GA–ANN, OHI–SQO–ANN, OHI–MOO–ANN, OHI–GA–KMC, OHI–SQO–KMC and OHI–MOO–KMC).
Findings
Optimum prediction models performance are recorded and compared with the actual value. Finally, based on error term values best optimum prediction model is proposed for evaluation of RUL of REBs.
Originality/value
Proposed OHI–GA–KMC model is compared in terms of error values with previously published work. RUL predicted by OHI–GA–KMC model is smaller, giving the advantage of this method.
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Keywords
P. Gunasekar, S. Manigandan and Praveen Kumar T.R.
The rise in demand and high utilization of fuel causes severe environmental threat for the nations on the globe. Rapid burning potential of hydrogen produces enormous amount of…
Abstract
Purpose
The rise in demand and high utilization of fuel causes severe environmental threat for the nations on the globe. Rapid burning potential of hydrogen produces enormous amount of thrust, and it is mainly owing to wide flame range and less onset of ignition.
Design/methodology/approach
The significant contribution of hydrogen as fuel has been explored by several researchers around the globe recently to use in aviation sector owing to its eco-friendly nature. Hydrogen is a safe and clean fuel, and it can be generated from several sources. The effects of addition on hydrogen on gas turbine on combustion characteristics and emission concentration level on atmosphere have been reviewed in this paper.
Findings
Incorporation of hydrogen is effective reducing nitrous oxide emission, high calorific value and flame less combustion. Addition of hydrogen to higher proportions enhances the combustion performance, minimizing the setbacks of conventional fuel and meets the specified standards on emission.
Originality/value
From the literature review, the comparative study on hydrogen with other fuel is explained. This paper concludes that addition of hydrogen in fuel enhances the performance of combustion on gas turbine engine along with significant reduction in emission levels.