In the world of investing and corporate finance, the Efficient Market Hypothesis (EMH) casts a long shadow. EMH states that a sufficiently liquid market reflects the “correct” price at all times. Since efficient markets factor in all known and relevant information at all times, it is therefore practically futile to attempt to predict the future direction of market prices. In other words, a blindfolded monkey throwing darts at the Wall Street Journal has about the same chance as beating the market averages as any professional investor. At one extreme, the founder of Vanguard Investments Jack Bogle revolutionized the mutual fund industry around cheap indexing, which he posited as the solution to efficient markets. At the other, Warren Buffet’s seminal essay, The Super-Investors of Graham and Doddes-ville, defends the notion that right-headed investors can carve out a significant edge 1. In the middle, you have the greater majority of investors who will likely cede that both extremes contain some amount of the truth. Even 2013 Nobel Laureate Eugene Fama, of the University of Chicago Booth School of Business, who is credited with developing EMH, has stated that “[asset prices] are typically right and wrong about half the time” 2. Being able to determine when they are right and when they are wrong is the holy grail to traders and investors alike. In order to investigate how correctly assets prices reflect all known information, we must develop an intuition and methodology for estimating the fair value of an asset. As we will discuss, just because a methodology is descriptive does not mean it is predictive (i.e., correlation does not imply causation). Continue reading →
After recently having completed testing on a general method of discounted cash flow (DCF) analysis for estimating a broad basket of stocks’ intrinsic values, I became more concerned with “quality”. While DCFs remain the foundation of any sound business valuation, I discovered they are highly sensitive to the assumptions and data used. Slightly changing a minute detail can drastically influence the result causing an attractive investment to all of sudden seem not so attractive and vice versa. While relative valuation methods were a natural alternative (Wall Street’s preferred choice, in fact) to circumvent the sensitivity issues, I was inclined to believe that an ability to define robust ‘quality factors’ would complement the ideological purity of the discounted cash flow approach much better. The purpose of this discussion is to demonstrate that a good company can indeed also be a good investment. Continue reading →
Bloomberg Businessweek offers an alternative take on the analysis of cash flows, both from the business’ and the investor’s points of view. Their methodology of reporting statements of cash flows provides investors with a more natural way to analyze the ways in which cash flows from investors, into and out of business activities, and then hopefully back to investors. The result is a cash flow statement which, while not perfect, allows investors to more easily differentiate between cash flows from investors and back to investors.
On Monday, 23 September 2013, “Kingold Jewelry (NASDAQ:KGJI) was downgraded by analysts at Thomson Reuters/Verus from a buy rating to a hold rating”, according to Zolmax News. The shares closed at $1.73 on Thursday 26 September, up 25% on the day, and up 40.6% from Monday’s close of $1.23.
These kinds of anomalies are pretty rare; living proof of the fallacy of instantaneous market efficiency. But as a wise woman once said, contradictions do not truly exist; “Whenever you think you are facing a contradiction, check your premises. You will find that one of them is wrong” (AR).
A lone Chinese female investor, Xingmei Zhong, d.b.a. Full Alliance International Ltd., finalized its plan to buyout all outstanding shares of YONG for $6.69 per share in cash. The deal is expected to close at the end of the first fiscal quarter of 2014 (i.e., between October and January). The buyout price reflects a 40% premium to YONG’s market price ($4.79) as of the date of the announcement on 12-Oct-2012.
At $6.25 per share, the buyout represent a 7.04% premium to market price. Investor’s looking for a relatively low-risk return on investment can engage in a risk-arbitrage trade. Investors can buy YONG now and will likely realize the differential between market and buyout price within 3 to 6 months. At the present, one could realize a 29.18% annualized return if the deal executes in 3 months; 14.20% if the deal executes in 6 months.
I have had several people already say to me that I am giving away too much information about how to profit in the market. If they mean that I have not been concise enough, duly noted. I must work on expressing myself more clearly.
If, on the other hand, they mean that I am giving away too much intellectual property without payment, then my response is that I have said nothing new. If sharing out the truth made it any less potent, then no one acting on publicly held information could conceivably earn returns above the amount of assumed risk. This is not true for the following reasons: Continue reading →
In this post, I present a case that alpha can be gleaned from publicly available SEC Form 13-F data. Traditionally, pundits looked at commonalities in institutional top-holdings by dollar amount. Research suggests that these aggregated top holdings among many institutions can be indicative of their “best ideas” (1). That may be all good and well, but common sense indicates that the best leads should come from a good institution’s top holdings per unit of capacity. For my institution, I use RenTec because:
a.) they are quantitative and therefore it may be easier to find commonalities in their holdings; and,
b.) they have consistently delivered exceptional returns.
I believe that their “best ideas” should be those positions in which the position size is largest relative to capacity because a moderately-sized holding for a small float stock is much more indicative of expected risk-reward than a relatively much larger position in a relatively much larger float stock. Additionally, focusing on a single institution (rather than many) allows us to ask the all-important “why” by determining if there are any commonalities in their top holdings. Understanding the “why” might us allow us to move beyond “piggybacking” off of quarterly 13-F data, and understand what drives the decisions of the best in the industry. I argue that if we can deconstruct some of the decision-making criteria, we can use this for finding our own unique source of alpha.