The long and short of Quant Finance
Hey guys, this blog would provide a very basic understanding about quantitative finance with a special focus on stock market trends and statistical arbitrage.
Quantitative Finance is a field concerned with mathematical modelling of financial markets. It focuses on using mathematics, statistics and/or machine learning tools to develop models for pricing or predicting the state of the markets in the future. But how do you know whether the model you came up with would work in the future? Therefore, these models are always back-tested on historical data to check for performance and robustness before using them in the real world.
There are many asset classes which investors or traders use for the purpose of growing their wealth. One of the most basic amongst them is the stock market. A holder of a stock/share/equity represents ownership in a business. A number of businesses list their stocks in the ‘stock exchange’ where common people like us could buy them. This means suppose you buy a stock of ‘Maruti Suzuki India Ltd’, then you have (as meagre as it maybe) an ownership in the company. A stock market or an exchange is where buyers meet sellers, the same way as it happens in any other market. A buyer pays money to the seller to get a ‘share of ownership in a company’ in return. The buyer now can be called a ‘shareholder’ in the company.
“One of the funny things about the stock market is that every time one person buys, another sells, and both think they are astute”- William Feather
Each and everyday there are movements in the price of a stock and all market participants try to get the most of these price movements by predicting a trend and make money from that. There is almost always a risk that markets could enter in a direction opposite to the predicted trend. So, how do we protect ourselves from this?
The most well known solution to this is diversification of portfolio in various asset classes like stocks, bonds, commodities, real estate and money market instruments. There is another way to ‘hedge’ or reduce the risk of such market exposures. This is called ‘Statistical Arbitrage’(Stat-Arb). In Stat-Arb, you do not trade one or two stocks but an index of stocks(200, 500, 1000, 3000) with equal money allocated to buying(going long on) some stocks and selling(going short on) the rest at the same time such that your net exposure is zero. This is called being ‘long-short neutral’. But how does it helps in reducing risk?
Suppose there is a bearish(downward) sentiment in the market, this means most of the stock prices are going to fall as investors would change their asset allocation and pull money away from high risk equities to low-risk bonds, thus this further pushes the market down. As we are long-short neutral, we shall make our strategy such that we are short on those stocks whose returns we expect to be more negative and go long on the rest. Even though we are losing money on the stocks we bought, but we are still making more money from the stocks we sold. Thus being profitable even when everyone else might be losing money. A number of hedge funds globally like WorldQuant and TrexQuant have this business model of Statistical Arbitrage.
There is a concept widely known in the financial world called “The Efficient Market Hypothesis” which says that market instruments always trade at their correct price. But there is almost always an inefficiency in the market due to information asymmetry and sentiments coming into play. One such widely known inefficiency is called ‘mean-reversion’. Let us see this through an example. Suppose a stock XYZ is currently trading at Rs. 320 and you know from your analysis that it’s ‘correct price’ should be Rs. 300, you short-sell that stock. If someone is selling a stock, it’s supply is increasing in the market, so from basic logic of demand and supply, when supply increases, price decreases. Therefore, there will come a time when the stock reaches Rs. 300 or reverts back to it’s mean. But now, the market participants may think that this downward trend should continue further and the stock price decreases again and let’s say reaches it to Rs. 280. Now again, market participants would start buying this stock and this process would continue. This is an inherent inefficiency in the market and Statistical arbitragers take advantage of this inefficiency to make money.
Hope this was a good read and added to your understanding of quant finance. The upcoming blogs will deal with observing various market trends and converting them to statistical arbitrage models(alphas) and the what, why and how of alphas…
