You are missing trading opportunities:
- Free trading apps
- Over 8,000 signals for copying
- Economic news for exploring financial markets
Registration
Log in
You agree to website policy and terms of use
If you do not have an account, please register
Any differences between Algorithmic trading and Algo Trading?
Do you know the name of a regulated broker that provide algo trading?
IB agents stay far from me! Please dont suggest any scam broker. Or I will report you!
Is there any real trader to help on this?
We investigate an alternative relative accuracy measure which avoids this bias: the log of the accuracy ratio: log (prediction/actual).
Relative accuracy is particularly relevant if the scatter in the data grows as the value of the variable grows (heteroscedasticity). We demonstrate using simulations that for heteroscedastic data (modelled by a multiplicative error factor) the proposed metric is far superior to MAPE for model selection.
Another use for accuracy measures is in fitting parameters to prediction models. Minimum MAPE models do not predict a simple statistic and so theoretical analysis is limited. We prove that when the proposed metric is used instead, the resulting least squares regression model predicts the geometric mean. This important property allows its theoretical properties to be understood.
Fuzzy logic, originally introduced by Lofti Zadeh in the 1960's, resembles human reasoning in its use of approximate, vague, noisy or imprecise data/information and uncertainty to generate decisions. According to Sriram (2005), fuzzy theory was designed with a specific purpose of mathematically representing vagueness and provides formalized procedures for tackling the impreciseness inherent in many variables in a multitude of problems. Crises, bubbles, fiscal politics etc. makes investing difficult in financial markets. These issues haphazardly raise and cause irregular characteristics which also raise risk. On the other hand, traders and market participants try to reduce risk and increase returns. We try to make dependable suggestion tool which contains a few technical indicators using fuzzy logic modeling. In financial markets technical analysis is commonly used to provide trading decisions. Technical analysis presumes that there are trends and patterns in financial assets’ movements. In this study, BIST-30 and Islamic (Participation) Index data is used between March 2012 and November of 2014 taken from Borsa Istanbul. The aim of the study is to create a new technical analysis indicator using fuzzy logic method which could be an alternative to popular indicators used by traders. BUY and SELL signals given by indicators’ after closing prices are assumed to be applied in the next day opening prices when calculating the indicators’ performance. The performance of the indicator for BIST-30 and Islamic index is measured by modified sharpe ratio and compared to widely used indices like MACD, MA, RSI and OBV. The Sharpe ratio is used to calculate risk adjusted return. It shows the rate of return as opposed to risk. The asset which has the higher Sharpe Ratio is considered to yield better return for the same amount of risk.
Many technical indicators have been selected as input variables in order to develop an automated trading system that determines buying and selling trading decision using optimal trading rules within the futures market. However, optimal technical trading rules alone may not be sufficient for real-world application given the endlessly changing futures market. In this study, a rule change trading system (RCTS) that consists of numerous trading rules generated using rough set analysis is developed in order to cover diverse market conditions. To change the trading rules, a rule change mechanism based on previous trading results is proposed. Simultaneously, a genetic algorithm is employed with the objective function of maximizing the payoff ratio to determine the thresholds of market timing for both buying and selling in the futures market. An empirical study of the proposed system was conducted in the Korea Composite Stock Price Index 200 (KOSPI 200) futures market. The proposed trading system yields profitable results as compared to both the buy-and-hold strategy, and a system not utilizing a genetic algorithm for maximizing the payoff ratio.