How To Catch A Falling Knife (Stock That Is Rapidly Falling)

Investors are always advised that they should never try to catch a falling knife. Tanay Loya and Yogesh Supekar explain why catching a falling knife deftly can be highly profitable.

What is “Catching of Falling Knife?”

A security which shows a steep decline with virtually no counter movement on its way down is called a 'falling knife'. There could be many reasons which lead to this phenomenon. The earnings report could be one of the reasons as companies that report earnings are subject to volatile swings. If the earnings are lower than expected, then the stock might turn into a falling knife. Economic reports also influence the prices of shares, which could sharply fall in response to negative reports. The stocks could be falling at an accelerated rate right before a bankruptcy or after a horrible earnings report. Some falling knives can be an effect of technical breakdown rather than fundamental factors. Sectoral or legal issues, investors' sentiments or some other negative triggers could result in a decline in stock prices.

Investors are well aware of the clichéd advice: “Never catch the falling knife”. But in spite of this well-known phrase in the stock market, we find that several investors never give up on catching the falling knife. In other words, investors keep on hunting for stocks that have witnessed a drastic fall in their prices, thinking that these stocks will eventually rise and deliver superior returns.

Why do investors attempt to catch the falling knife and is it worth it? But how does one go about this whole business of catching the falling knife and is there any strategy that can be adopted to clinically perform the act, resulting in superior returns? We will explore these common issues faced by the investors in this article.

Why do investors catch a falling knife? It is a well-established fact that equity markets are fundamentally unpredictable. In spite of this overwhelming historical evidence, we find that investors attempt to predict prices, both in the near term as well as in the long term.