Viktor Manahov

A note on the relationship between market efficiency and adaptability - New evidence from artificial stock markets

We developed various artificial stock markets populated with different numbers of traders using a special adaptive form of the Strongly Typed Genetic Programming (STGP)-based learning algorithm. We then applied the STGP technique to historical data from three indices - the FTSE 100, S&P 500, and Russell 3000 - to investigate the formation of stock market dynamics and market efficiency. We used several econometric techniques to investigate the emergent properties of the stock markets. We have found that the introduction of increased heterogeneity and greater genetic diversity leads to higher market efficiency in terms of the Efficient Market Hypothesis (EMH), demonstrating that market efficiency does not necessarily correlate with rationality assumptions. We have also found that stock market dynamics and nonlinearity are better explained by the evolutionary process associated with the Adaptive Market Hypothesis (AMH), because different trader populations behave as an efficient adaptive system evolving over time. Hence, market efficiency exists simultaneously with the need for adaptive flexibility. Our empirical results, generated by a reduced number of boundedly rational traders in six of the stock markets, for each of the three financial instruments do not support the allocational efficiency of markets, indicating the possible need for governmental or regulatory intervention in stock markets in some circumstances.

The implications of high-frequency trading on market efficiency and price discovery

This study investigates the implications of high-frequency trading (HFT) on market efficiency and price discovery by using state-space models and real-life one-minute high-frequency data of the six most traded currency pairs worldwide – USD/EUR, USD/JPY, USD/GBP, USD/AUD, USD/CHF and USD/CAD. We found significant evidence that HFT enhances market efficiency and has a beneficial role in price discovery by trading in the direction of the permanent component of the state-space model and in the opposite direction of its transitory component.

Identification of house price bubbles using user cost in a state space model

This article studies how much variation in house prices results from nonfundamental factors. We propose a relative valuation approach to quantifying a bubble in housing by incorporating the housing User Cost into a state space model. We find that UK house prices were undervalued from January 1995 to May 2001 and subsequently moved into a bubble over the period to October 2012. Our results support the bounded rationality hypothesis in the long run. However, we also find that the irrational and the rational expectation hypotheses can coexist in the short run when explosive bubbles are driven by price dynamics.

Front‐Running Scalping Strategies and Market Manipulation: Why Does High‐Frequency Trading Need Stricter Regulation?

Regulators continue to debate whether high‐frequency trading (HFT) is beneficial to market quality. Using Strongly Typed Genetic Programming (STGP) trading algorithm, we develop several artificial stock markets populated with HFT scalpers and strategic informed traders. We simulate real‐life trading in the millisecond time frame by applying STGP to real‐time and historical data from Apple, Exxon Mobil, and Google. We observe that HFT scalpers front‐run the order flow, resulting in damage to market quality and long‐term investors. To mitigate these negative implications, we propose batch auctions every 30 milliseconds of trading.

Investigating the determinants of dividend policy in emerging markets using a combination of exploratory variables

The authors analyze the factors causing dividend policy by utilizing agency cost theory of dividend and transaction cost of dividend by using blue chips companies stock listed in the Indonesian Stock Exchange (IDX) from 2004-2013. They also examine the transaction costs of bid-offer spread and commission as the proxies with agency cost factors of insider ownership and shareholder dispersion. The authors observe that the independent variables affected the dividend policy simultaneously. In addition, they find that the bid-offer spread as a new proxy also had significant effects on the dividend policy.