I have written book reviews in the past in bits and pieces. However, it has been a long time wish to make a comprehensive list of the best investing books that I have read. Such a list goes beyond the typical finance focus and takes a multidisciplinary approach, which is something investment legend Charlie Munger had been advocating for. Hence, in this long (really really long!) piece, not only you will find the usual topics such as valuation and accounting, but also life advice, culture, philosophy etc. The list is however only limited to books that I have personally read and so don’t be disappointed if one of your favorites did not make it. I know that some great books are missing and once I have read those I will include them also.
Originally posted at Developing Insights Blog. The Developing Insights Blog (DI) is dedicated to emerging and frontier markets, which collectively will account for the majority of world output by 2020.
In Frontier and Emerging markets the cost of not understanding the big picture can be very painful. Countries with weak institutions, frequently coupled with very narrow export bases, can change quite rapidly on both the upside and the downside. This creates the potential for big losses in USD terms as well as numerous missed investment opportunities.
Graham and Dodd-style investing is predicated on the notion that value is recognized over the long term. As Benjamin Graham famously asserted, “in the short run, the market is a voting machine but in the long run, it is a weighing machine.” Implicit in that formulation are many developed market assumptions about political stability, exchange rate volatility, peaceful power transitions and a meaningful degree of economic policy consensus. Often, in a developing market context, those factors simply can’t be held constant. The ability to pursue a purist bottom-up strategy, devoid of political economy considerations and the macroeconomic fallout from poor policy, is severely constrained. If all risk is simply the variability of future outcomes then these additional “macro” considerations necessarily widen the band of potential returns for individual companies.
My last blog post focused on some tips on forecasting which were fairly qualitative . I thought that it would be great to follow up by discussing a few technical mistakes done during company valuation. While trying to forecast company performance and valuing companies, we often fall victim of what I would refer to as the ‘routine trap’. That happens when we apply certain methods without understanding the logic behind those assumptions even though situations and circumstances could be very different and require changes in methods. Thus we end up with inconsistent company valuation. Let me go a bit deeper into few common areas of mistakes. Be warned that this will be a fairly long post.
The best book I read in 2015 was probably Superforecasting. It is about a project created by IARPA (Intelligence Advanced Research Projects Activity) to find phenomenal forecasters. Through a competition they identified a team of superforecasters who predicted extremely complicated events with great success. On closer look the author also found out that these people have some common characteristics.
I don’t want to recreate the wheel and make another review of this fantastic book. In fact I would highly recommend people to read the book. There are also some great podcasts that came out recently featuring the author Philip Tetlock. I would recommend the one by Econtalk and another by Freakonomics.
Unknown to many of us, we are actually continuously forecasting in everyday decisions. For example, deciding to use a certain route to go to work to avoid traffic involves forecasting.When we delay buying something in anticipation that price can come down soon, we are making a forecast. People in my profession pretty much earn their bread and butter by trying to make ‘educated’ guesses about the future. Our predictions fail often as much as we get them right. But as two highly respected seniors in this field told me, the difference between a great investment manager and a not so great one can just be a few % of right calls.
Assessing the performance of an employee is not the most difficult job (caveats exist!!!) in the world despite the subjective judgments involved. Nevertheless, I find that in Bangladesh (and possibly the world) top management and HR often fails in awarding the good performers and penalizing the bad ones. Rather, either nepotism wins or employees are promoted by ‘socialism’ which usually means that age determines position and rank.
When we extend the challenge to analyzing companies, it becomes slightly more difficult. However, it’s still quite doable by using a number or relative (benchmarking against key competitors) and absolute (Total shareholder returns, RoIC, Profit growth etc) metrics.
The toughest of these all is assessing the performance of a government in my view. The challenges actually start from the very basic level as we are still not sure if GDP growth is the single best indicator of economic progress. On top of that consider that, calculation methodologies and data collection ability also differs greatly between countries. Morten Jerven has done some great work on GDP calculation of African economies that highlights this challenge.
Thanks to Linkedin, I got to know that the Asif Khan Blog has just passed two years. It has been a rewarding two years. Writing these posts helped me clear up my own concepts. Additionally seeing people from all around the world read and subscribe to the blog gives me extra confidence.
One of the goals for 2016 that I have is to write better quality and more well researched posts. This will make the posts longer (which is against the conventional wisdom cited by social media experts) but for the type of content I write, they are ideal. On the flip side, as work and other activities take away more and more time the number of posts will surely come down.
As a new years gift to readers I bring link to a talk show “Weathtrack” which I recently stumbled upon. It was love at first sight (or in my case love at first listen as I use my podcast app to listen to these episodes). Here are two great episodes that I listened to recently. Coincidentally both the guests have worked in the First Eagle Fund.
I was reading Aswath Damodaran’s blog and much to my surprise found a series of posts on country risk. A lot of the material he talks about overlaps with my last post on currency risk and risk free rate. I did not however find confirmation of what I suggested for currencies which are ‘highly’ overvalued (my suggestion for a global investor was to adjust the fair value estimates, for assumption of a large currency depreciation which is not captured by the risk free rate).
Nevertheless, I think all 4 blog posts are relevant readings for equity investors. Here they are.
- Groundhog day in Greece, Hijinks in Brazil and Market Chaos in China: Pictures of Global Risk – Part I
- Valuing Country Risk: Pictures of Global Risk – Part II
- Pricing Country Risk: Pictures of Global Risk – Part III
- Decoding Currency Risk: Pictures of Global Risk – Part IV
While the posts become quite technical and makes it clear to the reader that a lot of what we do is subjective one key advice from Damodaran is very important. That is consistency in our cash flow assumptions and discount rate assumptions. If our discount rate implies inflation rate of 5% and cash flow assumes inflation rate of 2% we have a mismatch and our valuation could well undervalue the company. The reverse can also happen where we are using a high terminal growth rate number and a low discount rate.
The risk free rate is one of the basic inputs used for company valuation. I have done a bit of thinking on the risk free rate because it poses a number of practical challenges faced by analysts.
For example, when risk free rates are extremely high or extremely low (e.g. government bond yields are fairly low across South Asia at the moment) do we take the current yield or a historical average? If we take an average will it be a 3 year or a 5 year average? In fairly volatile times, the answers to these questions can have pretty large implication for stock valuation.
In the first 6 months of the year I read about 33 books (for full disclosure note that a good number were fiction which can be finished in one day). I will probably give the complete list of books I read in 2015 towards the end of the year. After a break of a few months I am back to reading again. As I mentioned before I usually read multiple books at the same time.
Microfinance is not innovative. Many will be understandably aghast at such a statement. The origins of microfinance is of a hapless yet determined economist, Muhammad Yunus, attempting to sell the novel idea that the poor can be creditworthy, a notion that was shunned by virtually all the banks existent in the late 1970s. Banks could not imagine loaning to those without collateral. It was simply too big a risk. This is precisely what is not innovative about microfinance. It was just another example of a loan to a customer. It is not like a bond, which is also a loan, as bonds are transferable securities; nor is it like a derivative, whose value depends on another financial asset.
Instead, what makes microfinance unique, though not innovative, is its success depends on monitoring and mentoring. Without observation or the support required to set up small enterprises, the likelihood is that the poor, in general, would fail to pay back their loans. This is not an indictment on the poor, far from it. Rather it is to say that the presence of an overseer and an enabler can lead to ideal outcomes.Hardly a novel insight, it is not only a characteristic of microfinance; we see the importance of mentors in other industries, particularly venture capital and private equity industries.