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Despite these changes, traders still face the same challenges as before. They seek to minimize the total cost of trading including commissions, bid/ask spreads, and market impact. New technologies allow traders to implement traditional strategies more effectively. For example, dark pools and indications of interest are just an updated form of tactics that NYSE floor traders used search for counterparties while minimizing the exposure of their clients’ trading interest to prevent front running.
Virtually every measurable dimension of U.S. equity market quality has improved. Execution speeds and retail commission have fallen. Bid-ask spreads have fallen and remain low, although they spiked upward along with volatility during the recent financial crisis. Market depth has increased. Studies of institutional transactions costs find U.S. costs among the lowest in the world. Unlike during the Crash of 1987, the U.S. equity market mechanism handled the increase in trading volume and volatility without disruption. However, our markets lack a market-wide risk management system that would deal with computer generated chaos in real time, and our regulators should address this.
“Make or take” pricing, the charging of access fees to market orders that “take” liquidity and paying rebates to limit orders that “make” liquidity, causes distortions that should be corrected. Such charges are not reflected in the quotations used for the measurement of best execution. Direct access by non-brokers to trading platforms requires appropriate risk management. Front running orders in correlated securities should be banned.
movements with sufficient confidence. The "Eficient Market Hypothesis" provides theoretical grounds for the belief that the best strategy is the "buyand-hold" passive investment strategy, since no excess return can be obtained consistently by predicting and timing the market
Technical trading rules are extensively used by foreign exchange (forex) traders. Despite the essential need to the forex diversification, it is not addressed by academic researches to generate forex portfolio trading systems based on technical indices. This paper aims to develop an interpretable and accurate Takagi-Sugeno-Kang (TSK) system for forex portfolio trading. The system uses technical indices of the forex rates and delivers the preferred portfolio composition among multiple foreign currencies. The proposed model considers the transaction cost and trading risk, which are the two important factors in the high frequency trading strategies. The proposed model was implemented to develop a trading system for portfolio trading among the five of the most traded currencies in the Tehran forex market. Four experiments were designed to examine the performance of the proposed model in different market trends, in terms of the portfolio return and risk adjusted return.According to the experimental results, the proposed model is able to extract profitable portfolio trading systems in this market, especially when the market is in the downward trend.
Most technical analysis tools focus traditionally on the simple and exponential moving average technique. This study looks at the performance of an optimized fractal adaptive moving average strategy over different frequency intervals, where the Euro/US Dollar currency pair is analyzed due to the increased correlation between the Euro Index and EUR/USD, and the Dollar Index and EUR/USD over the last year compared to the last 15 years. The optimized strategy is evaluated against a buy-and-hold strategy over the 2000- 2015 period, using annualized returns, annualized risk and Sharpe performance measure. Due to the existence of different number of long and short trades in every trading scenario, this paper proposes the use of a new measure called the Sharpe/Total trades ratio which takes into account the number of trades when evaluating the different trading strategies. Findings strongly support the use of the adaptive fractal moving average model over the naïve buy-and-hold strategy where the former yielded higher annualized returns, lower annualized risk, a higher Sharpe value, although it was subject to more trades than the buy-and-hold strategy. The best market timing strategy occurred when using 131 daily fractal data with a Sharpe/Total trades ratio of 0.31%.