Forecasting Financial Market Trading Behavior by Physical and Market Profiles

机译：预测物理和市场型材的金融市场交易行为

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This study applies the back-propagation neural network (BPNN) to compute stochastic (KD), moving average convergence- divergence (MACD), money flow index (MFI), value area rotation factor (VARF) and quantitative market profile data to extrapolate the Taiwan capitalization weighted stock index (TAIEX) futures market logic and knowledge rules. This study compares the experimental group and random trading. The experimental results show the proposed model obtains more profit than random trading. Therefore, integration of market profile and technical analysis can effectively improve forecasting performance and profitability.

机译：本研究将反向传播神经网络（BPNN）应用于计算随机（KD），移动平均会聚 - 发散（MACD），金钱流量指数（MFI），价值区域旋转因子（varf）和定量市场简档数据来推断台湾资本化加权股指（TAIEX）期货市场逻辑和知识规则。本研究比较了实验组和随机交易。实验结果表明，拟议的模型比随机交易获得更多的利润。因此，市场简介和技术分析的整合可以有效提高预测性能和盈利能力。

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《IEEE International Conference on Consumer Electronics - Taiwan》|2019年|710p|共2页
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作者
Chiu-Chin Chen; Chia-Chun Liao;
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中图分类 TM925-53;
关键词
backpropagation; economic forecasting; extrapolation; neural nets; profitability; stock markets;

机译：Backpropagation;经济预测;推断;神经网络;盈利能力;股票市场;

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2. Predict the Financial Markets Crises (Forecasting Models and Their Applicability in the Arab Financial Markets) [J] . Okocha R.C., Adedeji O.B. Journal of applied sciences research . 2011,第9期

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3. Forecasting Financial Markets Using High-Frequency Trading Data: Examination with Strongly Typed Genetic Programming [J] . Manahov Viktor, Zhang Hanxiong International Journal of Electronic Commerce . 2019,第1期

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4. Forecasting Financial Market Trading Behavior by Physical and Market Profiles [C] . Chiu-Chin Chen, Chia-Chun Liao IEEE International Conference on Consumer Electronics- Taiwan . 2019

机译：通过实物和市场概况预测金融市场交易行为
5. Volatility in the futures markets for financial and physical commodity assets: The impact of high frequency data on the distributional properties and forecasting of volatility, direction-of-change probability forecasting and asymmetric volatility effects. [D] . Georgiev, Georgi Y. 2007

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6. The Applicability of Self-Play Algorithms to Trading and Forecasting Financial Markets [O] . Jan-Alexander Posth, Piotr Kotlarz, Branka Hadji Misheva, 2021

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7. We develop a sequential trade model of Iceberg order execution in a limit order book. The Iceberg-trader has the freedom to expose his trading intentions or (partially) shield the true order size against other market participants. Order exposure can cause drastic market reactions (“market impact”) in the end leading to higher transaction costs. On the other hand the Iceberg trader faces a loss-in-priority when he hides his intentions, as most electronic limit order books penalize the usage of hidden liquidity. Thus the Iceberg-trader is faced with the problem to find the right trade-off. Our model provides optimal exposure strategies for Iceberg traders in limit order book markets. In particular, we provide a range of analytical statements that are in line with recent empirical findings on the determinants of trader’s exposure strategies. In this framework, we also study the market impact also market impact of limit orders. We provide optimal exposure profiles for a range of hightech stocks from the US SP500 and how they scale with the state-of-the-book. We finally test the Iceberg’s performance against the limit orders and find that Iceberg orders can significantly enhance trade performance by up to 60. [O] . Gökhan Cebiro˜glu, Ulrich Horst 100

机译：我们在限价订单簿中开发了冰山订单执行的顺序交易模型。 Iceberg-trader可以自由地揭露他的交易意图，或者（部分）屏蔽其他市场参与者的真实订单规模。订单暴露最终会导致市场反应激烈（“市场影响”），导致交易成本上升。另一方面，冰山交易员在隐藏他的意图时面临优先权损失，因为大多数电子限价订单都会惩罚隐藏流动性的使用。因此，冰山商人面临着找到正确权衡的问题。我们的模型为限额订单市场中的冰山交易者提供了最佳的风险敞口策略。特别是，我们提供了一系列分析性陈述，这些陈述与最近关于交易者暴露策略决定因素的实证研究结果一致。在此框架下，我们还研究了市场影响以及限价订单的市场影响。我们为来自美国标准普尔500指数的一系列高科技股票提供最佳曝光配置文件，以及它们如何随着本书的规模扩展。我们最终根据极限订单测试了冰山的表现，发现冰山订单可以显着提升贸易业绩高达60％。

Forecasting Financial Market Trading Behavior by Physical and Market Profiles

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