2019 IEEE 58th Conference on Decision and Control (CDC) 2019
DOI: 10.1109/cdc40024.2019.9029292
|View full text |Cite
|
Sign up to set email alerts
|

The Impact of Execution Delay on Kelly-Based Stock Trading: High-Frequency Versus Buy and Hold

Abstract: Stock trading based on Kelly's celebrated Expected Logarithmic Growth (ELG) criterion, a well-known prescription for optimal resource allocation, has received considerable attention in the literature. Using ELG as the performance metric, we compare the impact of trade execution delay on the relative performance of high-frequency trading versus buy and hold. While it is intuitively obvious and straightforward to prove that in the presence of sufficiently high transaction costs, buy and hold is the better strate… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
1
0
2

Year Published

2022
2022
2023
2023

Publication Types

Select...
3
1

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(3 citation statements)
references
References 18 publications
0
1
0
2
Order By: Relevance
“…Supervised learning methods are widely used in financial forecasting because of the high quality limit order book and market data, Researchers have formulated the price trend prediction problem as a regression task, and a set of classical machine learning algorithms are used for the regression tasks, such as linear regression [3], LASSO [4], elastic net [5], random forest [6], decision tree [7], support vector machine (SVM) [8] and LightGBM [9]. These non-linear algorithms usually outperform than linear models because they can learn the non-linear relationships between different features.…”
Section: A High-frequency Tradingmentioning
confidence: 99%
“…Supervised learning methods are widely used in financial forecasting because of the high quality limit order book and market data, Researchers have formulated the price trend prediction problem as a regression task, and a set of classical machine learning algorithms are used for the regression tasks, such as linear regression [3], LASSO [4], elastic net [5], random forest [6], decision tree [7], support vector machine (SVM) [8] and LightGBM [9]. These non-linear algorithms usually outperform than linear models because they can learn the non-linear relationships between different features.…”
Section: A High-frequency Tradingmentioning
confidence: 99%
“…Ini sejalan dengan pendapat Karpoff, pemegang saham perusahaan akan cenderung tidak menjual saham ketika memiliki informasi yang tidak dimiliki pasar. Selanjutnya menurut (Karpoff, 2016), kenaikan volume transaksi berkorelasi positif dengan "konten kejutan" informasi, efek selanjutnya dari konten kejut informasi berkorelasi positif dengan harga. Simulasi model menunjukkan bahwa hubungan antara informasi dan volume dipengaruhi oleh desain kelembagaan pasar.…”
Section: Literaturunclassified
“…Menggunakan ELG sebagai metrik kinerja dengan membandingkan dampak penundaan eksekusi perdagangan pada kinerja relatif perdagangan frekuensi tinggi versus beli dan tahan. Meskipun secara intuitif jelas dan langsung membuktikan bahwa dengan adanya biaya transaksi yang cukup tinggi, beli dan tahan adalah strategi yang lebih baik, atau tanpa biaya transaksi beli dan tahan masih bisa menjadi strategi yang lebih baik (Hsieh et al, 2019). Penelitian yang dilakukan Conrad et al , memeriksa hubungan antara penetapan frekuensi tinggi dan perilaku harga saham antara 2009 dan 2011 untuk seluruh sekuritas di AS.…”
Section: Literaturunclassified