Algo Trading For Retail Inverstors

Algo trading is a buzz word in the stock trading world. Here, I would like to explain about fundamentals and execution of Algo Trading for Retails Investors.

Retail investors are the investors who are individuals and investing by their own styles and nothing to constrain them.

Retail investors define the sentiment of the market. Success rate of retail investors is very low due to their lack of knowledge about financial markets and it’s tactics. It is strongly recommended to take minimum two year training in qualified institutions prior to starting trading. Many stock exchanges require a higher minimum trading amount and certification for a retail trader to be more profitable. Most success rate analysis reports are saying only 6% success rate for retail investors and few others reporting 15 to 24%.

To understand algo trading, first we have to know pattern trading. Pattern trading means if some conditions exist, that may be price, volume, or some events when we will start trade. After reaching stop loss or gain, we will stop or exit from trade. We can create a lot of trading patterns. For this kind of pattern trading we can use trading indicators i.e. RSI, MACD and MA. We can do a computer program for these patterns. We can run this computer program on the brokers platform. Most brokers give the algo trading provisions and they will give documents and samples to perform an algo trade in the stock broker's platform.

Due to the computer execution of the trades, trade will be executed with great accuracy so traders can get better prices in the algo trading.

Algo can handle a variety of trades. We can choose depending upon our risk/profit margins.

Arbitrage trading is the low risk and low profit trading and algo can handle it accurately. Beginners in algo traders can start from arbitrage trading.

Fundamental trading by algo is suitable for all traders. It will give better results than manual trading.

Hedge trading by algo is suitable for high liquidity retail investors.

Algo is the only platform for High Frequency Tradings (HFT). HFT requires complex mathematical models to perform trading.

We will see simple Crossover Strategy for algo trading

We will take two moving averages: long term (100 days) and short term (50 days). When the 50 days moving average is higher than the 100 days moving average, algo (a piece of program in a stock broker’s trading platform) will buy the stock. When the 100 day moving average is higher than 50 days moving average, algo will sell the stock.

This is piece of python code for the above said Crossover Strategy algorithm

for i in range(len(crossovers['sma_50'])):

    if crossovers['sma_50'][i] > crossovers['sma_100'][i]:        

        crossovers['signal'][i] = 'buy'

    else:

        crossovers['signal'][i] = 'sell'

In the above code ,'crossovers' is a list variable. After crossover (i.e. either of conditions will become true) the values of 50 days moving average are stored in 'crossovers[sma_50]' and 100 days moving average are stored in 'crossovers[sma_100]'. As per our algorithm after every crossover, algo will decide whether to buy or sell. If 50 days SMA value is greater than 100 days SMA value which will buy the stocks. Again if 100 days SMA value is greater than 50 days SMA which will sell the stocks.

The above python code is a part of algorithm code. As per our trading platform documentation, we will upload this code into the trading system which will automatically trade. This kind of trading by piece of trading code or computer program without any human interaction is called algo trading.