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@article{ART003029572},
author={Sunghyuck Hong},
title={Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2023},
volume={9},
number={6},
pages={57-62},
doi={10.20465/KIOTS.2023.9.6.057}

TY - JOUR
AU - Sunghyuck Hong
TI - Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy
JO - Journal of Internet of Things and Convergence
PY - 2023
VL - 9
IS - 6
PB - The Korea Internet of Things Society
SP - 57
EP - 62
SN - 2466-0078
AB - This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.
KW - volatility breakout strategy;auto trading;AI prediction;stock prediction
DO - 10.20465/KIOTS.2023.9.6.057
ER -

Sunghyuck Hong. (2023). Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy. Journal of Internet of Things and Convergence, 9(6), 57-62.

Sunghyuck Hong. 2023, "Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy", Journal of Internet of Things and Convergence, vol.9, no.6 pp.57-62. Available from: doi:10.20465/KIOTS.2023.9.6.057

Sunghyuck Hong "Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy" Journal of Internet of Things and Convergence 9.6 pp.57-62 (2023) : 57.

Sunghyuck Hong. Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy. 2023; 9(6), 57-62. Available from: doi:10.20465/KIOTS.2023.9.6.057

Sunghyuck Hong. "Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy" Journal of Internet of Things and Convergence 9, no.6 (2023) : 57-62.doi: 10.20465/KIOTS.2023.9.6.057

Sunghyuck Hong. Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy. Journal of Internet of Things and Convergence, 9(6), 57-62. doi: 10.20465/KIOTS.2023.9.6.057

Sunghyuck Hong. Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy. Journal of Internet of Things and Convergence. 2023; 9(6) 57-62. doi: 10.20465/KIOTS.2023.9.6.057

Sunghyuck Hong. Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy. 2023; 9(6), 57-62. Available from: doi:10.20465/KIOTS.2023.9.6.057

Sunghyuck Hong. "Comparative Study of Automatic Trading and Buy-and-Hold in the S&P 500 Index Using a Volatility Breakout Strategy" Journal of Internet of Things and Convergence 9, no.6 (2023) : 57-62.doi: 10.20465/KIOTS.2023.9.6.057