Institutional Investor | 8 Mistakes Series – Final Installment Released Today

The last installment of the "8 Mistakes Money Managers Make" series on Institutional Investor (www.InstitutionalInvestor.com) was released today. The series has been highlighted in their weekly electronic newsletter and posted on their homepage. The articles focus on poor position sizing's effect on portfolio risk and return. The root cause being a basic misunderstanding of an asset's impact on the portfolio and how it should be used to determine position size.

A link to the entire series can be found here or by visiting www.InstitutionalInvestor.com and clicking on the "8 Mistakes Money Managers Make" link under the "Asset Management" section.

 

Institutional Investor Article Series: 8 Mistakes Money Managers Make

Institutional Investor (www.institutionalinvestor.com) will feature a daily article series I authored beginning today. The series, “The 8 Mistakes Money Managers Make,” was highlighted in their weekly electronic newsletter today and posted on their homepage. The articles focus on poor position sizing's effect on portfolio risk and return. The root cause being a basic misunderstanding of an asset’s impact on the portfolio and how it should be used to determine position size.

The initial article, “Mistake #1: Discounting the Downside” is located under the “Asset Management” portion of the website and can be found here. Be sure to visit www.InstitutionalInvestor.com tomorrow for the solution to Mistake #2: The Good Stock Paradox.

Fundamental vs. Traditional Risk Management

When people mention "Risk Management" in investing the traditional metrics of volatility, correlation, Value at Risk, Beta, Sharpe ratio, etc. come to mind. But for fundamental shops (stock pickers) it is difficult to utilize risk management statistics to manage a portfolio. In fact, at my old shop, we would fire up the risk management software on the 30th of every month so we could put the data in our investor letter and that was about it.

The reason is because good fundamental portfolio managers understand that risk is not volatility, it is loss potential. Loss potential is measured by their fundamental research and should be the primary risk constraint. This is a piece that I wrote a while back discussing some of the differences between fundamental and traditional risk management.

I think the concepts are more important today as the number of experts decrying the use of traditional risk metrics grows.

To Price Target or Not to Price Target…that is the question

The other day, I was doing what I spend much of my days doing – talking to a portfolio manager about Alpha Theory. He told me that Alpha Theory makes terrific sense for firms that calculate price targets, but that he didn’t believe in price targets. When I asked him why, he responded that there is a lot of instinct that price targets do not capture and it is his instinct that makes him successful. I explained that instinct and price targets are not mutually exclusive because price targets are estimates. Instead of estimating whether to buy or sell (pure instinct), you’re estimating reward and risk (price targets). To drive the point home, I asked him, “What are the 5 best ideas in your portfolio? Are they your 5 biggest positions?” He did not know. Is there any more proof needed?

Using price targets is not about being precise; it is about being directionally accurate. Price targets define why you are making the decisions you are making and do not require that you strip away the instinct that may be a primary component of your abilities. In fact, it is quite the opposite.  Because price targets are part science and part art, instinct plays a critical and indispensable role. This is especially true if you use probability weighted price targets because the art-to-science ratio is even higher. If you are already good at estimating price targets and probabilities, you will create a far superior portfolio if you discipline yourself to write them down. If you are not good at estimating price targets, well … you probably would not be successful anyway.

The only way to justifiably choose against the use of price targets is to take the position that instinctual decision making is not detrimentally affected by cognitive biases.  Before taking this position and relying solely on your instinct, however, it is an enlightening exercise to review a list of Cognitive Biases and consider whether any of them affect your decision making. Believers in the instinct assume (implicitly or explicitly) that instinct reflects logic. This assumption is compellingly supported by the studies of people like Gerd Gigerenzer, Daniel Goldstein, and Malcolm Gladwell.  Unfortunately, however, these studies become much less compelling when they are applied to investing. In this area, there is much more support for non-instinct based decision making. Behavioral Finance and Neuroeconomics research shows how logic based decision process is critical in achieving successful long-term results (see the work of, for example, Amos Tversky, Daniel Kahneman, Michael Mauboussin, Ron Howard, Jason Zweig, James Montier, and Matthew Lieberman).

To illustrate why price targets are critical, ask yourself this simple question, “Why did you buy this stock?” Your answer is probably some version of “I believe I can sell it for a higher price down the road.” If your decision is only about that one stock, that’s a great answer and you can responsibly stop the analysis right there. If, however, you have many stocks to choose from and you have capital that must be efficiently allocated between too much risk and too little return, then you have to consider each asset’s impact on the overall portfolio. To responsibly measure this impact, you must quantify the potential reward and its probability as well as the risk you are taking on and its probability, the combination of which is a risk-adjusted return. Instinct can, and perhaps, should be a primary component of these estimates, but it cannot responsibly stand alone.  Repeatable success requires disciplined price targets that explain the fitness of a decision within your portfolio.

Knowing the Financial Spread - Investor Lessons from WhatIfSports.com

“Once The Star-Spangled Banner began to play, I’d tell myself, “Here you go.  Start pulling away, start computerizing.  You must think clearly and remove yourself”...It was like watching a game through a window.” – Bill Walsh, Head Coach of San Francisco 49ers and creator of the West-Coast offense

A buddy of mine who knows how much I love sports analysis, sent me a website called WhatIfSports.com that runs mock simulations of games 10,000 times to create a projected outcome. Now I have no idea about the efficacy of WhatIfSports's Monte Carlo simulation, but I love this kind of stuff as anyone that has spoken to me about the chance of the Tarheels winning the National Championship in basketball can attest (we’ll save that diatribe for another blog). So, I decided to see what the best way to profit from this simulation, assuming it was accurate. I pulled up Vegas odds and Whatif’s NFL week 8 projections to see if I could find any inconsistencies and did a quick analysis: 

Based on this, Vegas was pretty much dead on, but not perfect. How would I profit from these mis-priced games? I would definitely bet the under on the Falcons/Saints, because Vegas has the game total at 54 and WhatIfSports has the total at 45.  I would also pick the Rams getting 9.5 points over the Lions, when WhatIfSports has the Rams winning outright. I may also pick the Broncos and 49ers, but I would not be as confident and would certainly place a smaller bet on those games. This got me thinking about how this analysis applies to investing.

If I am evaluating a basket of stocks for potential investment, the Vegas Odds are the current stock price because they indicate what I can “buy” the bet for today and the WhatIfSports analysis is my proprietary research. I want to find the assets with the biggest differentials, Falcons/Saints under and Rams and make big bets on them. If I find other stocks with a reasonable difference between the market price and my calculation of value then I will place a bet on them as well, but not to the same degree as the large spreads.

If I’m an investor, how can I determine which assets should go in my portfolio and how to size them without calculating the risk-adjusted return of every investment? I must measure the difference between the market price and what I think the value is to determine the attractiveness of the bet. This concept seems so straightforward, yet most investors are willing to allow their mental calculator to be the final arbiter of portfolio inclusion and position size. That’s just like looking down the list of Vegas Odds and saying, “hmmm, I know the Saints score a lot and 45 isn’t that high, I think I’ll take the over.” First off, our brains are not very well designed to make those kinds of decisions, just read any book on behavioral finance or neureconomics. Second, even if you are right in your assessment that it is a good bet, how do you know exactly how good it is. Is it pretty good, really good, or freakin’ fantastic? Those differences affect how the position should be sized.

No doubt, calculating risk-adjusted return is harder than not calculating risk-adjusted return. But honestly, there are millions/billions of dollars at stake. How do you know what to bet if you don’t know your own spread?

So, wish me luck this Sunday and GO RAMS!!!

Institutional Investor Magazine article: A Plea to Put Down the Mental Calculator

I recently wrote an article for Institutional Investor magazine (www.iimagazine.com) called "Capturing the Benefits of Risk-Adjusted Return." It was a plea to put down the mental calculator. You can read the article here.

Here is an excerpt from the article:

Hedge funds throw away half of their potential returns by not explicitly calculating risk-adjusted return. After working for a fund and having numerous conversations with hedge and mutual fund managers over the past decade, it is obvious that an overwhelming majority of funds’ mistakes come from poor estimation of risk-reward. 

In fact, most funds have not explicitly defined an upside price target, downside risk target and conviction level for each investment in their portfolio. This is because most fund managers trust that they can manage the portfolio in their head. They analyze and discuss the upside, downside and conviction level for every investment so they assume these factors’ influence is carefully measured into every decision. But I would posit that there is a distinct difference between factoring in upside, downside and conviction level through mental calculation and measuring it with risk-adjusted return. 

Why would you trust your mental calculator for such an important decision? Could you imagine a bungee jumper that knows the height of a bridge, tension of the bungee cord and weight of the jumper but just estimates the correct length of the bungee cord? Absolutely not. For every jump, a calculation is performed to make sure that easily avoidable risk is eliminated.  Investors all too often skip the “bungee cord” calculation of risk-adjusted return and end up assuming undue risk. 

What is your investment’s Risk-Adjusted Return? The Alpha Theory Calculator will tell you.

Alpha Theory is exposing its pioneering Risk-Adjusted Return Calculator to the public at www.AlphaTheory.com/Calculator. This calculator lays the groundwork for every important portfolio decision an investment firm will make and calculates a first-ever Estimated Risk-Adjusted Return. Try it out by entering any stock, seeing its Estimated Risk-Adjusted Return, and then customizing your own Risk-Adjusted Return. Enjoy the calculator and please share it with others who may find it worthwhile.

 

The Risk-Adjusted Return calculation is the most effective way to measure investment quality. All research can be distilled down into the elements of potential profit, downside risk, and probability of each coming true. This holistic framework results in a quantitative measure that can be used to make the critical portfolio decisions of whether or not to make an investment, how to size the position, and when to trade. The use of Risk-Adjusted Return in portfolio construction reduces risk by decreasing position size when an asset has greater downside and increasing return by maximizing the portfolio’s overall Risk-Adjusted Return.

 

The Alpha Theory Risk-Adjusted Return (RAR) Calculator begins by giving you an Estimated Risk-Adjusted Return using market metrics. Enter one of your investments and see if the Estimated Risk-Adjusted Return is positive or negative. This Estimated RAR starts by deriving an Upside and Downside Price Target using an average 52-week high and low and 1-year annualized volatility implied high and low. Then, the Calculator derives probabilities by determining the Option-Market Implied Probability of the Upside and Downside targets being achieved. The Calculator then averages the Option Probabilities with Normal Distribution Implied Probabilities of Upside and Downside. The Alpha Theory Estimated RAR should be a part of every investment process.

 

The next step is to customize with your own research. Alpha Theory allows you to override the estimates with your own assumptions to truly appreciate the stock’s impact on your portfolio. Risk-Adjusted Return is the foundation of every investment decision and is imperative in ensuring that an asset’s position size is in-line with your fundamental research.

Why do you buy an asset?

"We construct portfolios the way theory says one should, which is different from the way many, if not most, construct their portfolios.  We do it on a risk-adjusted rate of return.” – Bill Miller, legendary investor

Why do you buy an asset? Because you believe that it is worth more than what you are paying for it.

Assume you can buy two different assets for $20 dollars. Stock #1 is worth $35 and Stock #2 is worth $30, which one would you buy more of?

Of course, Stock #1 with a value of $35, because it is worth more. Unfortunately in investing, assets have risk. So, unless there is a 100% probability of the stock going from $20 to $35, you have to compare its upside potential to its downside risk to better understand how much return you are being paid for the risk you are taking on.

Assume we calculate the downside using net cash per share. Stock #1 has more upside to $35 but only $5 in net cash per share ($15 of upside and $15 of downside) and Stock #2 has a lower upside of $30 but more net cash at $15 per share ($10 of upside and $5 of downside). Now, which one would you take a bigger position in?

	Stock #1	Stock #2
Upside	$35	$30
Current Price	$20	$20
Downside	$5	$15
Upside / Downside	$15 Upside / -$15 Downside	$10 Upside / -$5 Downside

More than likely you would have a greater exposure to Stock #2 because it has a better risk-reward. But this still misses a critical component of the analysis, conviction level. What if I’m extremely confident, say 80%, in Stock #1 achieving $35. For Stock #2, it is a coin-flip whether it will reach $30 or fall to $15. If I multiply each stocks’ Upside times the Probability of Upside and add it to the Downside times the Probability of Downside, I get a Risk-Adjusted Value of $29 for Stock #1 and $22.50 for Stock #2. The Risk-Adjusted Value is truly representative of the full qualities of this asset and should be the basis from which portfolio level decisions are made.

	Stock #1	Stock #2
Upside	$35 * 80%	$30 * 50%
Current Price	$20	$20
Downside	$5 * 20%	$15 * 50%
Risk-Adjusted Value / Risk-Adjusted Return	$29.00 / 45%	$22.50 / 12.5%

If you were to invest in Stock #1 10 times, you would make $15 eight times and lose $15 twice for a total gain of $90. If you were to invest in Stock #2 10 times, you would win $10 five times and lose $5 five times for a total gain of $25. Now, which asset would receive greater exposure?

Every investment decision should be framed by Risk-Adjusted Return. This allows an investor to properly size positions and quickly adjust exposure as the underlying price of the asset changes and as new fundamental information is received. Although the concept seems simple, it is rarely implemented. To see how Alpha Theory puts this concept into practice, view our demo (www.AlphaTheory.com/demo).

Good Sight, Good Insight: Risk Management by Ed Seykota

I was discussing portfolio management strategy with a client who runs a long/short equity hedge fund. In his former life, he worked for a large Fund of Funds where he evaluated long/short equity mangers. In that role, he frequently referenced an article on Risk Management by Ed Seykota. He had increasingly become frustrated with traditional manager measurement techniques like VaR, Sharpe Ratio, alpha, etc. He found the article's concepts to be central to evaluating the portfolio management prowess of fund managers.

Fortunately for us, the tenets of Ed Seykota's article are embodied by the Alpha Theory Portfolio Management Platform:

1. Risk is the possibility of loss (not volatility).
2. Hunch-centric betting is certainly popular and likely accounts for an enormous proportion of actual real world betting.
3. Despite almost universal agreement that a system offers clear advantages over hunches, very few risk managers actually have a definition of their own risk management systems that is clear enough to allow a computer to back-test it.
4. To maximize returns, position sizing should be based on a measurement of potential profit, potential loss, and probability of each.
5. Kelly may be sub-optimal for portfolio management because of the diversification effect.
6. Diversification relies on the average security having a profitable expected value.
7. In times of stress, investors and managers access their primal gut feelings (when they should go back to discipline).
8. In actual practice, the most important psychological consideration is the ability to stick to the system. To achieve this, it is important (1) to fully understand the system rules, (2) to know how the system behaves and (3) to have clear and supportive agreements between all parties that support sticking to the system.
9. Profits and losses do not likely alternate with smooth regularity; they appear, typically, as winning and losing streaks. When the entire investor-manager team realizes this as natural, it is more likely to stay the course during drawdowns, and also to stay appropriately modest during winning streaks.

To see the full article, Risk Management by Ed Seykota. To view how Alpha Theory help create a investment process discipline, visit www.AlphaTheory.com.

Managing Portfolio Liquidity: Position Level Calculation

Liquidity is a critical, yet often overlooked, risk constraint.  The reason it is frequently ignored is because position size is throttled by heuristics and mental calculation instead of having a repeatable method to factor liquidity into how the fund sizes positions.  Alpha Theory has developed a simple calculation to help determine portfolio liquidity constraints.