Tag Archive | risk management

Is this £406m investment guru the mystery buyer of ‘stock market crash insurance’?

Interesting article out of the UK about what Ruffer who is one of Britain’s leading fund managers and oversees billions of pounds of savers’ cash and has a personal fortune of £406m.  He is reported to be ‘stockpiling’ insurance against a market collapse.

The investor who has been hedging using VIX Option contracts on the US market was unidentified until recently.  He had been dubbed  “50 cent”, after the well-known rapper and musician (and because the contracts are priced at 50 cents each) .  Was recentlly identified in Financial Times as Jonathan Ruffer who oversees the Ruffer investment house.     Read more at:  http://www.telegraph.co.uk/investing/shares/406m-investment-guru-mystery-buyer-stock-market-crash-insurance/

How will you keep your investments protected?

Earn higher returns by avoiding the downturns

Just look at how much per share one could save in this example with IBM below.  Stepping aside during a stock’s downturn can lead to higher returns overall for your investments especially when you consider that stocks on average will drop ~20% from their highs and market leaders can drop ~70% (per Investor Business Daily stats).     Buy & Hold philosophies have morphed to Buy & Protect as many studies have shown the increased value in skipping the downturns.   At SmartStops our goal is to help you protect your profits and minimize any losses.

IBM_SmartStops_Performance

MODERN PORTFOLIO THEORY IS HARMING YOUR PORTFOLIO

SmartStops comment:  an excellent article that every investor should read as MPT continues to be deeply entrenched in our systems.  Its shortcomings are proven.  The article concludes with:

The advice that most investment advisors give their clients – At its core, the message is usually something similar to this: “The markets are random and unpredictable, so the best way to invest is to properly diversify and wait for the averages to play out.”

However, what most investors seem to be unaware of is that this whole theory of random movement of market prices was proven false over 50 years ago by one of the most influential mathematicians of the 20th century, Benoit Mandelbrot. The random motion of market prices was a very nice theory, but it just doesn’t match what actually happens in the real world.

Some excerpts from JJ Abodeely, CFA’s article :   Modern Portfolio Theory Is Harming Your Portfolio

              1. MPT and the quantification of investing has further (mis)informed the debate by seeking a easy way to label and quantify “risk.” In 1952, Harry Markowitz chose variance or volatility of prices or returns to define risk. He did so because it was mathematically elegant and computationally simple. However, this idea has serious limitations (most of which Markowitz has since acknowledged).

              On the individual stock level, Vincent notes

Risk is often in the eye of the beholder. While “quants” (who rely heavily on MPT) might view a stock that has fallen in value by   50 percent over a short period of time as quite risky (i.e. it has a high beta), others might view the investment as extremely safe,   offering an almost guaranteed return. Perhaps the stock trades well below the cash on its books and the company is likely to         generate cash going forward. This latter group of investors might even view volatility as a positive; not something that they need to be paid more to accept. On the other hand, a stock that has climbed slowly and steadily for years and accordingly has a       relatively low beta might sell at an astronomical multiple to revenue or earnings. A risk-averse, beta-focused investor is happy to add the stock to his diversified portfolio, while demanding relatively small expected upside, because of the stock’s consistent track record and low volatility. But a fundamentally-inclined investor might consider the stock a high risk investment, even in a diversified portfolio, due to its valuation. There’s a tradeoff between risk and return, but volatility and return shouldn’t necessarily have this same relationship.

2.  After all, if you buy and hold the market you can earn the long-term returns right? Unfortunately, the answer to that is no. The long-term “average” returns are rarely available. In fact, depending on where you are standing, the returns are either much higher, or much lower. Consider this chart from Crestmont Research which shows that even for periods as long as 10 years, average rarely occurs:

10_yr_Rolling_Stock_Market_Return

3. Consider this chart which you’ve probably seen in one form or another. It shows expected risk and return of various mixes of asset classes and the typical approach to asset allocation which Modern Portfolio Theory has spawned:

Sample_Asset_Allocation_Risk_Expected_Returns

So what’s wrong with this picture? Lots of things.

The first is the inputs– namely expected returns and volatilities of various asset classes– most investment programs are built on logic like this:

  • Bonds will return 5% on average over the long-term but be between 0-10% in any given year
  • Stocks will return 10% on average over the long-term but be between -10% and +20% in any given year
  • Some might include other nuance regarding different types of bonds like High Yield or different types of stocks like Emerging Markets
  • Some might include different types of assets like real estate, commodities, or “alternatives”

The problem of course is this is an incomplete description of investment returns:

  • The math contends that returns are randomly and unpredictably distributed around the average
  • This “normal distribution” of returns contends that larger market movements outside of the ranges above will be relatively rare
  • “Average” returns ignore the role of valuation and the importance of when you start investing (buy) and when you finish (sell) even over multi-decade time horizons

The traditional approach to asset allocation is built on false axioms. The phenomenal secular bull market in stocks and bonds from 1982-1999 created the perfect conditions for the nearly religious acceptance of MPT. In a recent post, Expensive Markets Mean Low (or Negative) Prospective Returns, I made the case that valuation matters greatly and currently portend disappointing returns for both stocks and bonds. Traditional asset allocation has no way of dealing with this in a way that successfully protects portfolios from experiencing meaningful and unnecessary drawdowns.

Read JJ Abodeely, CFA’s article :   Modern Portfolio Theory Is Harming Your Portfolio in its entirety.

$1M more in your IRA by avoiding major losses

SmartStops Comment:   Modern Portfolio Theory  – continues to have holes poked in it.  Here’s a post by Hedgeable reiterating the importance of missing the worst times in the market.

From their post:  If you merely miss out on 75% of market losses during the two largest crashes of the past 25 years- the dot-com crash and the financial crisis crash- you will have $1 MILLION MORE IN THE AVERAGE IRA ACCOUNT!!!

Hedgeable_Portfolio_without_75_percent_Losses

BaseBall fans will like the rest of the post too.  Read Entire Post

 

Nowhere to Run: The Correlation Bubble

SmartStops Comment:: Indeed, Beta and correlation approaches are not enough to manage risk in today’s markets. However we have somewhere for you to run – to intelligent self-adjusting risk methodologies that the SmartStops optimization engine offers.

Originally published at Seeking Alpha: http://seekingalpha.com/article/815851-nowhere-to-run-the-correlation-bubble

Fundamental analysis of “buy and hold” companies is a quaint, Warren Buffetish notion that probably works in the long term. But as Keynes said, in the long term we’re all dead. The big risk in today’s über-correlated markets is systemic shock. One can practice due diligence on a company and buy at a reasonable valuation, but if global markets collapse the next day and don’t recover for years, one has paid a lot in opportunity cost. In other words, tail risk is not reflected in fundamental analysis.

Fundamental analysis is valuable so long as the basic fabric of capital markets remains intact. In an insane world (where U.S. Treasuries and German Bunds are considered “risk-free”, of infinite rehypothecation, where MF Global’s John Corzine walks off with $200M segregated assets, of the London Whale, LIBOR, Goldman’s muppets, regulatory capture of SEC and Fed, U.S. / China animosity and the dollar’s loss of world reserve status) it’s unlikely that business-as-usual will continue without a disruptive bout of creative destruction.

Precisely when and how it will occur is anyone’s guess, but, unfortunately, old school techniques like cross-asset class and regional diversification have lost their glimmer. Just as socioeconomic disparity is partitioning the globe into lords and serfs, so too has the market been divided into polarized castes of highly correlated risk-on assets and (scarce few) risk-off havens.

Position Sizing: Key to Maximizing Returns

In a time when market volatility and equity preservation is of utmost importance, determining the correct number of shares to buy, or “position sizing”, is key to maximizing returns and minimizing risk.

The common investor generally doesn’t spend much time thinking about how many shares to buy or how significant of a position to take.  Instead, most investors use a common methodology of trading the same number of shares each time, which usually translates to a specific dollar amount.  Other, more sophisticated investors, opt to allocate a certain percentage of their portfolio value to a specific position. Following this train of thought, a new position in a portfolio of $100,000 would transcribe either a $10,000, or 10%, investment or a usual position of 50 shares.

Although these methods may work for some, using the volatility of a specific portfolio is likely to be the most effective decision tool.  Measuring a portfolio’s overall volatility enables an investor to decide on what percentage of that portfolio he is willing to risk losing on the new position.  This methodology is better explained through the following example. Read More…

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