Swing trading on biotech

A friend of mine introduced me to something called momentum trading (also called swing trading) today and it is a pretty interesting concept. So for a quick background, there are two types of trading: swing and trend. Trend is when you are hoping that a stock would go in one direction, either up or down, over a period of time. Swing is when you are hoping the stock will just oscillate in both directions and not really go anywhere. Hence, in bear and bull market extremes, it is wiser to use a trend strategy since the stocks will tend to follow a directional trend. The key challenge with swing trading is to accurately define the market when it is going “nowhere.” This is tough.

However, an industry that came to my mind immediately after hearing this was biotechnology. I have noticed that several biotech company stocks either oscillate continuously or stay near the baseline, going “nowhere.” The reason being that many biotech companies are in the clinical trials and research phase for 5-10 years before releasing their drug. That being said, I wonder if the swing trading approach would work more often than not for the biotech industry…

From basketball to random walk theory

I was watching the 76ers game the other day and heard something in the background commentary that caught my attention. Something along the lines of… the probability of an NBA player of making a shot does not depend on whether he made the shot before that. That claim basically said the “hot hand” was irrelevant when betting on whether a player would make their next shot. To me, that claim seemed like total crap. Apparently, upon researching this a little further after the game, I learned that there was a study done on the 76ers regarding this issue which concluded that there was no correlation between past shots’ influence on future shots.

I realized that this theory was also related to the random walk theory, originally proposed Burton Malkiel in 1973 to explain stock price fluctuation in financial markets. This really got me interested. I’m not going to go into much detail but basically what this theory suggested (based on a coin flipping experiment conducted by Malkiel) is that the fluctuation in stock prices are completely random due to the efficiency of the market.

Though some economists continue to believe in this theory to this day, I feel that there are three things fundamentally wrong with this claim:

1. Efficiency of market – there is a subtle claim in Malkiel’s theory which is that stock prices fluctuate randomly “due to the efficiency of the market.” But is the market completely efficient? I don’t believe so. You have government intervention bailing out the banks, time-lags, and significant human involvement (though many things are now becoming algorithmic driven), all three of which contribute to inefficiencies. Thus, Malkiel’s theory has some holes in its assumptions.
2. Market vs. Individual stocks – this is akin to the difference between the entire NBA vs. an individual player on the court. From what I understand, Malkiel’s theory applies to the NBA (the market), and so does the shot percentages research conducted with no correlation. But Statistics 101 says averaging data, and drawing more and more general correlations masks individualized data, which might give a whole new story. Perhaps random walk theory can suggest predicting market movement is impossible as it is random, but it cannot say predicting an individual stock’s movement is random. Similarly, the research on basketball shots combined data from the NBA and hence can apply to the NBA but not the Kobe Bryant’s or Michael Jordan’s of the world.
3. Present Day Wall Street – present day Wall Street makes the money on the individual stock, the individual player. And the trillions of dollars to be made in the financial industry clearly shed light on the fact that trades are not random. Otherwise, people would not be in this industry. There is clearly intelligence involved in using the large amounts of data, sorting out the relevant bits, and drawing conclusions – betting on IPOs, arbitrage trading, momentum trading are relevant examples. Though there is always an element of uncertainty and luck, it doesn’t govern the process but instead just plays a role.
   

The 76ers won that game 98-92.

Taking advantage of over-hyped IPOs

So I was reading about startup IPOs – when a company first offers company stock to the public – the other day. This process has some interesting points: first, I’ve noticed that many of these companies try to create massive amounts of hype prior to their IPO to attract many buyers, making the stock price increase rapidly in the initial phases. But when I looked at the data of many of the stock prices six months later, most of them decreased back down do an equilibrium point with market forces kicking in.

There are several reasons why this could have occurred: once the company declares itself public, it is mandated to share its future vision, finances, and all other sorts of data, making the company vulnerable to all types of financial calculations and estimates from traders globally. This naturally allows the market to dictate the price, rather than external influences that over-hype the stock initially. Another reason, which is less subtle, is that the management team, investors, and founders usually agree to a clause which prevents them from selling any of their equity for six months after the IPO. This prevents any startup founder or high stake holder to sell their entire stock, giving the company a horrible image in the market. But after six months, more often than not, several founders and high-stake holders invariably sell part of their stock, liquidating some of their assets, allowing them to gain more financial security. Since any stake-holder selling their stock after an IPO is a bad signal, the trend mentioned above may potentially help lower market estimates of the stock’s worth.

But now, the key question is: despite the above trends, why do buyers continue to purchase stock in the very beginning of the IPO, when the stock is severely over-hyped? Wouldn’t it be wiser to short sell the stock in the initial week and make money off the equilibration phase that takes place over the next few months? And THEN, if the company shows promise, buy the stock after the equilibration price is attained?

Would love to hear your thoughts.

Wall Street and MIT

One in every three people I meet at MIT are into finance in some way or the other. Some are in market research and investment banking and others are in sales and trading... seems like making big bucks on Wall Street is the central goal for many MIT undergrads. And working at JP Morgan, Goldman, and hedge funds seem like the "hot" things to do over the summer.

I come from a background of high-tech and am fascinated by next-generation web technologies, nanotechnology, AI, and the fusion of neuroscience and computers. Frankly, I have never really considered finance as potential career path. I did write some business plans and financial statements back in high school and also participated in virtual stock market games, but didn't seem to find enough time to devote to learning the ins and outs of the financial industry at that time.

Regardless of my background, however, I feel that I should make best use of this opportunity and culture and learn more about finance and how engineering can be applied to this industry. Who knows, I might get really into this stuff? And worst case, these concepts are essential to know anyways, no matter what industry I go into.