Setting up an algorithm for stock market trading strategies

The present article attempts to understand the relationship between foreign portfolio investment (FPI), domestic institutional investors (DIIs), and stock market returns in India using high frequency data. The study analyses the trading strategies of FPIs, DIIs and its impact on the stock market return. We found that the trading strategies of FIIs and DIIs differ in Indian stock market. While FIIs follow positive feedback trading strategy, DIIs pursue the strategy of negative feedback trading which was more pronounced during the crisis. Further, there is negative relationship between FPI flows and DII flows. The results indicate the importance of developing strong domestic institutional investors to counteract the destabilising nature FIIs, particularly during turbulent times.

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Artificial Intelligence Applied to Stock Market Trading: A Review

IEEE Access ◽

10.1109/access.2021.3058133 ◽

2021 ◽

Vol 9 ◽

pp. 30898-30917 ◽

Cited By ~ 1

Author(s):

Fernando G. D. C. Ferreira ◽

Amir H. Gandomi ◽

Rodrigo T. N. Cardoso

Keyword(s):

Artificial Intelligence ◽

Stock Market ◽

Stock Market Trading

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Can the FSCORE add value to anomaly-based portfolios? A reality check in the German stock market

Financial Markets and Portfolio Management ◽

10.1007/s11408-021-00400-9 ◽

2021 ◽

Author(s):

Eero J. Pätäri ◽

Timo H. Leivo ◽

Sheraz Ahmed

Keyword(s):

Stock Market ◽

Trading Strategies ◽

Added Value ◽

Financial Statement ◽

Research Setting ◽

Holding Period ◽

Reality Check ◽

German Stock ◽

Overall Performance ◽

German Stock Market

AbstractThis paper examines the added value of using financial statement information, particularly that of Piotroski’s (J Account Res 38:1, 2000. https://doi.org/10.2307/2672906) FSCORE, for equity portfolio selection in the German stock market in a realistic research setting in which the critique against the implementability of FSCORE-based trading strategies is taken into account. We show that the performance of annually rebalanced long-only portfolios formed on any of the examined 12 accounting-based primary criteria improves by including the FSCORE as a supplementary criterion. Our study is the first to show that although the FSCORE boost is strongest for the 1-year holding period length, it also holds, on average, for the 3-year holding period. The use of a 3-year updating frequency is particularly beneficial for the low-accrual portfolio that—when supplemented with the high-FSCORE threshold—generates the best overall performance among all 75 portfolios examined. Moreover, we show that a high FSCORE is also an efficient stand-alone criterion for long-only portfolio formation.

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Does the Croatian Stock Market Have Seasonal Affective Disorder?

Journal of Risk and Financial Management ◽

10.3390/jrfm14020089 ◽

2021 ◽

Vol 14 (2) ◽

pp. 89

Author(s):

Tihana Škrinjarić ◽

Branka Marasović ◽

Boško Šego

Keyword(s):

Stock Market ◽

Stock Returns ◽

Affective Disorder ◽

Seasonal Affective Disorder ◽

Stock Exchange ◽

Trading Strategies ◽

Future Research ◽

Winter Solstice ◽

Daily Data ◽

Depressive Episodes

This paper explores mood anomalies, specifically the seasonal affective disorder (SAD) effect on the Zagreb Stock Exchange (ZSE). SAD is defined as a syndrome of depressive episodes in human behavior due to the changing of the season. Thus, the motive of this research is to gain better insights into the investors’ sentiment regarding SAD effects. The purpose of the research is to observe how investors’ sentiment affects the return and risk series on ZSE and if this could be exploitable. Using daily data on stock market return CROBEX for the period January 2010—February 2021, SAD effects are tested to explore if seasonal changes affect the stock returns and risk. Besides the SAD variable in the model, some control variables are included as well: Monday, tax, and COVID-19 effect. The results indicate that SAD effects exist on ZSE, even with controlling for mentioned effects; and asymmetries around winter solstice exist. Implications of such findings can be found in simulating trading strategies, which could incorporate such information to gain profits. Limitations of the research focus on one market, observing static parameters of the estimated models, and observing simple trading strategies. Thus, future research should focus on international diversification possibilities, time-varying models, and fully exploring the exploitation possibilities of such findings.

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