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Algorithmic fundamental trading
Pižl, Vojtěch ; Krištoufek, Ladislav (advisor) ; Bubák, Vít (referee)
This thesis aims to apply methods of value investing into developing field of algorithmic trading. Firstly, we investigate the effect of several fundamental variables on stock returns using the fixed effects model and portfolio approach. The results confirm that size and book- to-market ratio explain some variation in stock returns that market alone do not capture. Moreover, we observe a significant positive effect of book-to-market ratio and negative effect of size on future stock returns. Secondly, we try to utilize those variables in a trading algorithm. Using the common performance evaluation tools we test several fundamentally based strategies and discover that investing into small stocks with high book-to-market ratio beats the market in the tested period between 2009 and 2015. Although we have to be careful with conclusions as our dataset has some limitations, we believe that there is a market anomaly in the testing period which may be caused by preference of technical strategies over value investing by market participants.
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Algorithmic fundamental trading
Pižl, Vojtěch ; Krištoufek, Ladislav (advisor) ; Bubák, Vít (referee)
This thesis aims to apply methods of value investing into developing field of algorithmic trading. Firstly, we investigate the effect of several fundamental variables on stock returns using the fixed effects model and portfolio approach. The results confirm that size and book- to-market ratio explain some variation in stock returns that market alone do not capture. Moreover, we observe a significant positive effect of book-to-market ratio and negative effect of size on future stock returns. Secondly, we try to utilize those variables in a trading algorithm. Using the common performance evaluation tools we test several fundamentally based strategies and discover that investing into small stocks with high book-to-market ratio beats the market in the tested period between 2009 and 2015. Although we have to be careful with conclusions as our dataset has some limitations, we believe that there is a market anomaly in the testing period which may be caused by preference of technical strategies over value investing by market participants.
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Stressed Value-at-Risk: Assessing extended Basel II regulation
Pižl, Vojtěch ; Šopov, Boril (advisor) ; Avdulaj, Krenar (referee)
This thesis investigates recently proposed enhancements to the Basel II market risk framework. The Basel Committee on Banking Supervision introduced a stressed Value-at-Risk, calculated from one year long period of financial stress, to be added to the current VaR as a reaction to the shortage in capital reserves of banks and thus their inability to cover extensive losses observed during the recent crisis. We present an empirical evidence that such an extension of the regulatory capital is not optimal. Firstly, supplementing an unconditional methods of VaR estimation, i.e. normal parametric VaR and historical simulation, by SVaR only lead to unnecessarily high capital requirements even in a low volatile periods whilst the same amount of capital during the crisis could be achieved using either the conditional GARCH VaR with student's-t innovations or the volatility weighted historical simulation. Moreover, we showed that all unconditional methods fail to capture volatility clusters such as the 2008 crisis.
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