Trading profitability from learning and adaptation on the Tokyo Stock Exchange
Trading profitability from learning and adaptation on the Tokyo Stock Exchange
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通过学习和适应东京证券交易所的交易盈利能力
DOI：
10.1080/14697688.2015.1091941
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发表时间：
2016
影响因子：
1.3
通讯作者：
Ryuichi Yamamoto
中科院分区：
文献类型：
--
作者：
Yuri Sasaki;Yushi Yoshida;Yuri Sasaki Yushi Yoshida;佐々木百合;Yuri Sasaki;Yuri Sasaki;Yuri Sasaki;Yuri Sasaki;Yuri Sasaki;Yuri Sasaki;Yuri Sasaki;吉田裕司;Yuri Sasaki;吉田裕司;佐々木百合・吉田裕司;吉田裕司;吉田裕司;佐々木百合・吉田裕司;Ryuichi Yamamoto;Ryuichi Yamamoto
本文提出了未经检验的技术交易规则，即过滤规则、移动平均规则和交易区间突破规则之间的动态切换策略。动态切换策略是基于符合短视效用最大化概念的离散选择理论制定的。我们使用的是2005年9月1日至2007年8月31日在日经225指数上市的个股的交易数据。在我们的样本期内，我们证明了转换策略产生正收益，其表现优于买入并持有和非转换策略。我们还证明了在不同学习视界的情况下，股票投资者的行为异质性源于不同学习视界程度的不同策略的共存。我们的研究结果支持了几个基于主体的理论模型的研究假设和结果，这些模型成功地复制了金融市场的经验特征，如收益分布的肥尾和波动性聚类。然而，考虑到数据窥探偏差的影响，优越的性能就消失了。
This study proposes unexamined technical trading rules, which are dynamically switching strategies among filter, moving average and trading-range breakout rules. The dynamically switching strategy is formulated based on a discrete choice theory consistent with the concept of myopic utility maximization. We utilize the transaction data of the individual stocks listed on the Nikkei 225 from September 1, 2005 to August 31, 2007. We demonstrate that switching strategies produce positive returns and their performance is better than those from the buy-and-hold and non-switching strategies over our sample periods. We also demonstrate equivalent performance for switching with different learning horizons, implying that behavioural heterogeneity of stock investors arises from the coexistence of different strategies with varying degrees of learning horizons. Our result supports several research assumptions and results on agent-based theoretical models that successfully replicate empirical features in financial markets, such as fat tails of return distributions and volatility clustering. However, upon considering the effects of data-snooping bias superior performance disappears.