- Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator and . . .
This paper aims to investigate a simple and general trading model We focused on estimating overbought and oversold stock market indices and translating them into real-world investments We tested and presented simulated trades on tracking indices and the ETFs that use them as benchmarks and have the largest AUM
- Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator and . . .
We tested two ETFs, SPY (S P 500) and EWY (MSCI Korea), from 2010 to 2022 Over the 12-year study period, our model showed it can outperform the benchmark index, having a high hit ratio of over 80%, a maximum drawdown in the low single digits, and a trading frequency of 1 5 trades per year
- Financial Engineering Lab. - KAIST
Woo Chang Kim, Do Gyun Kwon, Yongjae Lee, Jang Ho Kim, and Changle Lin (2019) "Personalized goal-based investment via multi-stage stochastic goal programming," Quantitative Finance, 1-12 [full paper]
- Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator and . . .
We tested two ETFs, SPY (S P 500) and EWY (MSCI Korea), from 2010 to 2022 Over the 12-year study period, our model showed it can outperform the benchmark index, having a high hit ratio of over 80%, a maximum drawdown in the low single digits, and a trading frequency of 1 5 trades per year
- Quantum Finance Forecast System with Quantum Anharmonic Oscillator . . .
In this paper, the author proposed an innovative Quantum Finance Schrödinger Equation (QFSE) for the modeling of the quantum dynamics of worldwide financial markets using Quantum Anharmonic Oscillatory Model (QAOH)
- A Quantum Oscillator Model of Stock Markets - SAGE Journals
This paper has presented a quantum oscillator model which captures key empirically-observed features of stock markets, using a minimal set of assumptions and parameters
- Modeling stock return distributions with a quantum harmonic oscillator
In this paper, we use the term "quantum" to indicate the mathematical description of stock prices, rather than the real quantum nature Our model outperforms the traditional models, such as the GBM and the Heston model, in fitting the empirical distribution of FTSE All Share Index returns
- Algorithm-Based Low-Frequency Trading Using a Stochastic Oscillator . . .
The primary research problem addressed in this study is whether incorporating volume-based stochastic indicators, such as the Williams %R and stochastic oscillator, enhances the accuracy of identifying oversold conditions and improves the effectiveness of market timing strategies
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