By Puneet Tewani
Artificial Intelligence can help you make decisions more objectively as it is based on numerous data points. AI is evolving at a very fast pace and is being used in every field. AI mimics the human brain, we have been using it ourselves from ages, when we track the prices of stock and try to remember them we are creating memory which creates patterns. AI can do the same task efficiently and can include more data point.
AI systems work by crunching through data, trying to find patterns and correlations, and teaching themselves how to approximate future outcomes by formulating algorithms that use the patterns and correlations found in the data. This process of the AI program going through data and trying to learn from it and find insights is known as Machine Learning and the data that is fed into the program is called training data.
Some commonly used machine learning models are Linear Regression, Decision Trees, Random Forest, Logistic Regression, K-nearest neighbours (KNN), etc. The best type of ML model is known as Deep Learning (DL). DL models are inspired by how our very own human brains work and are structured. Just like brains have billions of neurons and neurons themselves are connected to each other and these connections are called synapses—there are trillions of them in the brain! But sometimes to get a reasonably good DL model, the amount of training data that is needed is so huge that it's called Big Data.
Usually, any data, whose size is above or equal to 1TB is considered Big data. If you can combine DL models with Big data, you can make fantastic AI systems.
Now the question, what can AI do for you? If you are a trader who trades in small timeframes, then you can use AI to make a better selection of which stocks to trade and you can even let the AI optimize your strategy, stop-loss, position-sizing, etc. AI systems can be capable of optimizing and adjusting the strategy and other variables involved in real-time to give your trades the best chance to be profitable.
You can use AI systems that can analyze the sentiment of the market towards stock or a sector by letting AI using NLP(Natural Language Processing) can parse through newspaper articles, tweets, social media posts and feeds. By analyzing the sentiment you can estimate whether the market is bullish or bearish on a stock.AI can also help in order book analysis, it can go browse through no of buyers/sellers active in the market and hence, give us an idea about the market direction.
Some, AI algorithms are been used by HFT firms for stop-loss hunting. AI can solve a trader's never-ending search for an edge in the markets.
If you are a long-term investor, then AI can help you decide which kind of long-term investing is most favourable in the current market regime. A value investor may not make money in the market for some time and the same goes for growth or dividend or any type of long-term investing style. Depending upon the economy, what market is focusing on and market sentiment, some investing styles do better than others, but only for a while, and AI can help shift seamlessly to any style to maximize gains.
Another problem of portfolio making and asset allocation can also benefit from the use of AI. It can optimize and allocate resources in real-time by analyzing thousands of inputs in real-time. AI can help choose the winners and cutoff the losers before much loss is sustained since machines are not prone to the same cognitive biases that humans are.
There are pros and cons to everything, AI is no exception. AI models are very vulnerable to over-fitting especially DL models. Meaning, they get so customed to the training data that can make inaccurate decisions whenever new data that wasn't in the training is given input to the model. So you need to be very cautious while training the model.
Sometimes it difficult to understand what rules have the system taught itself and it often takes a lot of time to train and test the model before deploying depending upon the size of the training data. The accuracy and the quality of outputs given by the AI model are highly dependent on the quality of the training data. So getting good quality data is key.
Compared to traditional methods, AI-based trading gave some striking differences, such as cost and maintenance, speed, and emotion. In traditional methods, humans can make quick decisions and have control over the running strategy. AI also has some significant capabilities when it comes to speed and short-term plans. Traditional trading takes much time to collect data and make strategies by analyzing it, which is time-consuming.
The AI trading arrangement is expensive to build, and once it is created, it can explore the vast amount of data and generate better outcomes, which can make it highly profitable. Computers can crunch almost countless data points in minutes. It means they can also detect historical and replicating patterns for smart trading that are often hidden from human investors. AI can assess hundreds and thousands of stocks in flashes. Humans are not capable of processing that amount of data or seeing these patterns at the same rate as technology.
Now more than ever both technology and information have never been so accessible and democratized. A few popular languages can be spotted in AI like java, python, R, and c++. Especially in python many libraries like Scikit-learn, Keras, PyTorch, and Tensorflow, provide you with various standard off-the-shelf pre-built models for quick and easy implementation.
More than often these pre-built models give about similar accuracy when compared to custom or models that have been fine-tuned. Anyone with a little knowledge and some hands-on practice can build good models with the help of these libraries. So, what am trying to get to here is, opportunities are merely beginning in this symphony of finance and AI and one could grab this opportunity and with effort and hard work, one can expect their p & l statements to become greener.
(The author is CEO, Fox Trading Solutions)Disclaimer: The views and investment tips expressed by experts on Moneycontrol.com are their own and not those of the website or its management. Moneycontrol.com advises users to check with certified experts before taking any investment decisions.