政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/145793

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/145793

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政大機構典藏 > 商學院 > 風險管理與保險學系 > 學位論文 > Item 140.119/145793

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题名:	當沖交易之基本分析 The Fundamental Analysis of Day Trading
作者:	李彤 Lee, Tung
贡献者:	蔡政憲 Tsai, Cheng-Hsien 李彤 Lee, Tung
关键词:	當沖交易蒙地卡羅模擬投資策略 Day Trading Monte Carlo Simulation Investment Strategy
日期:	2023
上传时间:	2023-07-06 16:32:54 (UTC+8)
摘要:	本研究進行了深度探討與分析當沖交易的運作機制，主要以虛擬股市和交易投資者為研究基礎，並使用當沖投資方法與蒙地卡羅模擬進行實驗。分析了在各種不同條件和交易策略下的獲利可能性，並重點探討了勝率、交易費用、交易策略及標的波動性等因素對當沖交易的影響。研究結果顯示，交易成本對長期獲利可能性有顯著影響，以交易台灣加權指數為例，在無交易成本的情況下，投資者需達至少 44%的交易勝率才能實現長期獲利，若考慮交易成本，則需提高至73%。另外，即使勝率達 80%，部分投資者仍處於虧損狀態，顯示隨機性(運氣)亦是獲利的重要因素。同時揭示只有當交易成本降低至 0.08%，以勝率五成以上才可能使交易實現長期獲利。對於策略交易，發現停損並未對整體獲利產生顯著影響，而適當的槓桿交易則有助於提升獲利，當槓桿比例達 10 倍以上，則會開始傷害獲利機會。在個股交易上，選擇高波動的股票當沖能幫助獲利，另外研究當沖台積電，只需 55%勝率即有長期獲利機會。在實際應用上，投資者可以依據本研究的模型來設定自身的交易成本和選擇交易標的，並進一步計算出所需的邊際勝率。將過去的交易勝率紀錄與此邊際勝率進行比較，若無明顯優勢，則可能需要調整交易策略或是更換標的，但對於大部分的一般投資人來說，應避免繼續當沖交易。 This study delves deeply into and analyzes the operational mechanisms of intraday trading, mainly based on virtual stock markets and trading investors. It uses intraday investment methods and Monte Carlo simulations for the experiments. The analysis covers the potential profitability under various conditions and trading strategies, with a focus on factors such as win rate, transaction costs, trading strategies, and target volatility that affect intraday trading. The research results show that transaction costs have a significant impact on the potential for long-term profitability. Taking trading on the Taiwan Weighted Index as an example, in the absence of transaction costs, investors need to achieve at least a 44% win rate to realize long-term profitability. If transaction costs are considered, the rate needs to be increased to 73%. Furthermore, even with a win rate of 80%, some investors are still in a loss situation, showing that randomness (luck) is also an important factor in profitability. The study also reveals that only when transaction costs are reduced to 0.08% can trading achieve long-term profitability with a win rate of more than 50%. Regarding strategic trading, it was found that stop-loss does not significantly impact overall profitability, while appropriate leverage trading can help increase profits. However, when the leverage ratio exceeds 10 times, it begins to harm profit opportunities. In individual stock trading, choosing highly volatile stocks for intraday trading can help profitability. In addition, research on intraday trading in Taiwan Semiconductor Manufacturing Company shows that a win rate of 55% can potentially lead to long- term profitability. In terms of practical application, investors can set their own transaction costs and choose trading targets based on the model in this study, and further calculate the required marginal win rate. Comparing past trading win rates with this marginal win rate, if there is no obvious advantage, they may need to adjust their trading strategy or change their target. However, for most general investors, it is recommended to avoid continuing intraday trading.
參考文獻:	Anand, A., Chakravarty, S., & Martell, T. (2005). Empirical evidence on the evolution of liquidity: Choice of market versus limit orders by informed and uninformed traders. Journal of Financial Markets, 8(3), 288-308. Barber, B. M., Lee, Y. T., Liu, Y. J., & Odean, T. (2009). Just how much do individual investors lose by trading? Review of Financial Studies, 22(2), 609-632. Barber, Brad & Lee, Yong-Ill & Liu, Yu-Jane & Odean, Terrance. (2014). Do Day Traders Rationally Learn About Their Ability?. SSRN Electronic Journal. Barber, Brad & Lee, Yong-Ill & Liu, Yu-Jane & Odean, Terrance. (2014). Do Day Traders Rationally Learn About Their Ability?. SSRN Electronic Journal. Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307-343. Chakrabarty, S., Huang, L., & Jayaraman, N. (2013). The impact of short-selling restrictions on liquidity: Evidence from the London Stock Exchange. Journal of Banking & Finance, 37(10), 3787-3802. Dufresne, F., & Gerber, H. U. (1991). Risk theory for the compound Poisson process that is perturbed by diffusion. Insurance: Mathematics and Economics, 10, 51-59. Ibbotson, R. G., & Kaplan, P. D. (2000). Does asset allocation policy explain 40, 90, or 100 percent of performance? Financial Analysts Journal, 56(1), 26-33. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. Longstaff, F. A., & Schwartz, E. S. (2001). Valuing American options by simulation: A simple least-squares approach. The Review of Financial Studies, 14(1), 113-147. Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. Journal of Finance, 55(4), 1705-1765. Mandelbrot, B. (1963). The variation of certain speculative prices. The Journal of Business, 36(4), 394-419. Menkveld, A. J. (2013). High frequency trading and the new-market makers. Journal of Financial Markets. Paskov, S. H., & Traub, J. F. (1995). Faster valuation of financial derivatives. Journal of Portfolio Management, 35(3), 113-122. 彭聖傑，2022，「當沖比率、股價波動率、當沖損益及報酬率之分析」。私立東吳大學經濟學研究所碩士論文楊家維，2000，「技術分析用於當沖之有效性研究-台灣股市之實證分析」，國立臺北大學經濟學研究所碩士論文
描述:	碩士國立政治大學風險管理與保險學系 110358023
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0110358023
数据类型:	thesis
显示于类别:	[風險管理與保險學系] 學位論文

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