Inside Information: To Trade or Not to Trade?

 

The recent raft of criminal charges brought by U.S. security regulators against consultants, investment managers, and other investment professionals, as well as the  long sentences imposed in high-profile cases brought by the Financial Service Authority in the United Kingdom, have again highlighted the continuing issue of insider trading. In the GCC, the regulation governing insider trading is in most cases light and in some markets non-existent. GCC exchanges are retail dominated with trading behaviour often either sentiment led or heavily influenced by market rumour generated from insider information. Trading on privileged information is commonplace  eroding market credibility . It is heartening to see that the Saudi CMA has started taking actions against insider trading by imposing finesbut they are still relatively small. As GCC markets continue to court institutional investors, against steep competition from other markets, the need to have firm policies to curb insider trading has become crucial. It is also an essential step in the development of the region’s stock markets.

 Following an earlier article in the Financial Times (FTfm supplement) Mr. Raghu Mandagolathur, President of CFA Kuwait and Michael G. McMillan, CFA Institute analyse the elements of insider trading to distinguish improper conduct from legitimate investment analysis.

 

What is inside information?

Generally, inside information, or material non-public information, is information not disseminated to the public that would likely affect the price of a security or that reasonable investors would want to know before making an investment decision. The materiality of information is a function of its substance and specificity, as well as the reliability of its source. Information that is ambiguous, has a tenuous effect on the price of a security, or originates from an unreliable source, is relatively less material.

What are some common examples of inside information?

The most common types of inside information concern intelligence about a company’s financial health or stability (earnings, revenues, bankruptcies, etc.); changes in a company’s structure arising from a merger, acquisition, or  joint venture; and a company’s new products , processes, licenses, patents, etc. 

What is wrong with trading on inside information?

Security market regulation is designed to promote the fairness, efficiency, and integrity of security markets. Trading—or inducing others to trade—on material non-public information erodes investor confidence in capital markets by supporting the idea that those with insider information and special access can take advantage of the investing public. 

Investors tend to avoid capital markets that are perceived to be “rigged,” thereby impairing liquidity and efficiency. As a result, most developed capital markets have enacted laws that prohibit trading on inside information.

Who might have access to inside information?

Anyone who has a direct or indirect relationship with a company may have special access to or become aware of information that is both material and non-public. Service providers (e.g., consultants, auditors, and investment bankers) may have access to material non-public information about both a company’s internal and financial activities. In addition, people who have no connection with a corporation may be given inside information either accidentally or purposefully by those who have a direct or indirect relationship.

Does relying on “industry experts” constitute insider trading?

There is nothing inherently wrong with hiring a company that arranges conversations between analysts or hedge fund managers and those who offer legitimate expertise to assist investors in making investment decisions. The information provided by experts can be part of the “mosaic” of information gathered by analysts or investment managers to assist them in the process of investment decision making. This type of information can include economic or industry forecasts.

Even if a piece of non-public immaterial information takes on significance when combined with primary research or other non-public immaterial information, the information may still be considered immaterial.  This concept is known at the mosaic theory. 

 How does one legitimately use “expert networks”?

In recent expert network cases, the misconduct alleged by U.S. prosecutors involved such material nonpublic information as detailed earnings, gross margins, and other confidential information leaked by insiders. 

Before hiring an expert network company, one would be wise to conduct due diligence to determine whether public company employees are engaged as consultants and whether the expert network company has in place sufficient policies and procedures to ensure that material nonpublic information is not being leaked or otherwise passed on to clients.

What are some precautions portfolio managers might take?

Before making an investment decision or recommendation, investment professionals should consider whether the information is widely known or available to the public. Has it been disclosed to only a select number of people?  

To evaluate whether information is material, consider whether the information would be likely to affect the price of a security if it were known or whether a reasonable investor would want to know the information before making an investment decision. The information’s substance, specificity, and reliability contribute to its materiality.

Consider the source of the information, as well. If the information has been provided by someone with either special access or a duty to keep the information confidential, it is likely to be reliable and thus inside information.    

New Year Resolutions 2011

More than 80% of UAE executives polled by Emirates24|7 hope to reduce debt next year

A quick survey of more than 50 of the UAE's senior executives conducted by Emirates24|7 reveals that while shedding weight remains a popular resolution for the New Year, shedding debt has overtaken it by a slight margin in 2011.
More than 80 per cent of the executives polled by this website mentioned saving more and/or reducing their overall exposure among their top 5 resolutions for the New Year, while losing weight was mentioned by 76 per cent of those polled.
"Smartly re-invest....reduce debts," is one of the top 5 resolutions of Shivam Goyal, Concept General Manager, Emax, Landmark Group, Dubai. On the other hand, MR Raghu, Senior Vice President-Research, Kuwait Financial Centre (Markaz), wants to "lose weight (21st year in the making)".
Then again, there are some like Vineet Kumar, Head of Leasing & Sales - Dubai, Asteco Property Management, all five of whose top 5 resolutions focus on finances. "[One,] Family involvement in budget preparation; [two] Minimum spend on credit cards; [three] Travel by low-cost airlines; [four] Liquidate any unwanted assets to settle any loan /debt; and [five] Enjoy with friends and family in house rather than spend on outdoor when possible," are his top resolutions for 2011.
Perhaps learning from what's going on in the global economy, a surprisingly large number (42 per cent) of respondents to the Emirates24|7 poll said they were planning to set up an 'emergency fund' to bank on in times of crisis (in the event of a loss of job or an unplanned major expense). "Keep a quarter of my earnings on the side every month - we're not out of the woods yet and who knows when one might need it," said an advertising executive who did not wish to be named.
However, risk-taking may be slowly but surely making a comeback. "Try and take some risks after being numbed for nearly three years," is the No 1 resolution of Markaz' Raghu, who also wants to "try and beat my mom in investment bets - she is still miles ahead with only a few investments, like land, gold, etc.," acknowledges the financial expert.
Imad Ghandour, the Chairman of Gulf Venture Capital Association (GVCA), has "steer away from politics" as one of his resolutions for 2011, and also wants to "see the light at the end of the tunnel" next year.
Panos Manolopoulos, Vice Chairman - Regions, Managing Partner Middle East at Stanton Chase International wants to "keep up the vision for growth" and bring "stability and maturity for businesses in UAE" while Landmark's Goyal hopes to "under promise and over deliver" as well as "think global, act local" in 2011.
Raghu, on the other hand, wants to "buy less of new gizmos, and use more of existing ones" while also hoping to "try and reduce the number of bank accounts as I finally realise that it is not proportional to the money you earn - people make a lot more money with a lot few bank accounts." Good thinking, Raghu!
While Al Maya Group's Kamal Vachani wants to "party hard", Goyal wants to "slog at work but never ignore family." GVCA's Ghandour wants to "cherish entrepreneurship" while Vachani wants to "smile and be more positive and outgoing" while also "be myself."
What's your New Year's Resolution for 2011? Let us know below. And here's wishing you and your loved ones a Happy and Prosperous New Year 2011.

Analyst Earnings Forecasts in Perspective

This article was originally published in Arab Times

GCC stock markets currently suffer from a lack of extensive analyst research. This is primarily due to the closed nature of many markets in the region. However, during the past few years, several of these markets have opened up spurring analysts interest, although by international standards this coverage still continues to be on the lower side.  With the research available,  only 18% of GCC listed stocks receive analysts coverage.  However measured in market capitalization terms, this accounts for only around 70%, indicating the concentrated nature of the GCC markets. Also, trading in GCC markets is currently dominated by retail investors, who do not demand analysts forecasts to base their trading decisions. In future the increased institutionalization of GCC markets will promote the need for more extensive analysts earnings forecasts. Following an earlier article in the Financial Times (FTfm supplement) Mr. Raghu Mandagolathur, President of CFA Kuwait and Stephen M. Horan discuss the usefulness of earnings forecasts in equity analysis. 

 

Q: Are analyst earnings forecasts important?

Analyst earnings forecasts are a quantifiable part of equity research and a reasonable proxy for the market’s expectations of those earnings.  Although some investors and fund managers emphasize them, many do not.  A quarter of analysts surveyed by CFA Institute rarely or never incorporates quarterly earnings into their analysis, choosing instead to focus on longer-term measures of performance. 

 

Q: Is a heavy emphasis justified?

 Earnings forecasts are only one factor in determining fundamental value.  Ultimately, a company’s value is the present value of its expected future cash flows over the long haul.  Reported earnings can be poor predictors of those future cash flows.  They can also be poor measures of historical cash flows, particularly over short time frames.

 Information such as accounting convention, industry trends, and management quality is critical to interpreting reported earnings figures and developing informed expectations of long-term cash flows.  The entire earnings report, formal filings, and independent information sources provide valuable information to update one’s long-term expectations. 

 Respected analysts use multiple metrics (such as cash flow, book value, and residual income) in addition to earnings to value companies. 
<!--[if !supportLineBreakNewLine]--> <!--[endif]-->

Q: How is the quality of an earnings forecast measured?

 Typically, the precision of an analyst’s earnings forecast is measured by the difference between the actual earnings per share reported by the company and the analyst’s estimate, called forecast error.  Accuracy is often measured by the absolute value of the forecast error such that forecasts that are 10 percent above or below actual earnings have the same level of accuracy. 

 But analysts are often charged with being overly optimistic in their forecasts.  This upward bias is sometimes measured by the raw forecast error or by the difference between an analyst’s forecast and the average forecast. 

 

Q: Are analyst forecasts actually biased?

Studies confirm the suspicion that earnings forecasts tend to be biased upward––that is, higher than actual earnings.  Annual and multi-year earnings forecasts tend to be more optimistic and less accurate than quarterly forecasts.  Optimism among analysts may have intensified over time as the proportion of upwardly biased quarterly forecasts has increased from less than half to more than three quarters over a 22-year period. 

 Some of the apparent trend toward optimism can be attributed to a growing inconsistency between forecasted and reported earnings.  Analysts tend to create pro forma earnings forecasts that exclude special charges.  Over time, these charges have become more frequent and more negative, making the analyst’s pro forma forecast appear optimistic compared with reported earnings. 

 

Q: Are some estimates better than others?

Conventional wisdom suggests that investment banking makes sell-side analysts more susceptible to misaligned incentives than buy-side analysts.  In a recent study published in the Financial Analysts Journal, researchers from Harvard Business School report that sell-side forecasts were actually less biased and more accurate than buy-side estimates issued by a top 10-rated money management firm––a result confirmed by other studies. 

 

In related research, analysts at the most prestigious banking firms provided less optimistic forecasts than their less prestigious peers. Moreover, retail brokers were more optimistic than institutional brokers. 

 

Q: What accounts for the difference?

  Institutional investors rank sell-side analysts in annual polls based in large part on the accuracy of their earnings forecasts.  Compensation is determined accordingly.  

 Buy-side analysts, in contrast, are typically not compensated based on their earnings forecasts.  In the Harvard study, they were evaluated based on internal rankings and market-adjusted returns. 

 

Q: Are there other indicators of forecast accuracy?

 Yes.  Analysts that cover fewer stocks and specialize in the company’s industry tend to produce more-accurate earnings forecasts than generalists.  Experience and resources also seem to play a role.  Forecasts from analysts with more experience and from larger firms tend to be more accurate.  Evidence also suggests that professional credentials improve accuracy. 

 

Q: Is it proper to focus on short-term earnings estimates?

 

The desire to hit quarterly or semi-annual earnings targets can prompt companies to use accruals opportunistically or classify expenses capriciously as special non-recurring items, such as restructuring charges.  In the extreme, company executives may knowingly misreport earnings.

A focus on short-term earnings to the exclusion of other factors can also lead to poor decisions by company executives on the quarterly treadmill.  In a survey of 400 executives, 80 percent reported that they would decrease discretionary spending on such areas as research and development, advertising, maintenance, and hiring to meet short-term earnings targets.  

 More than 50 percent of these executives said they would delay new projects, even if it meant sacrificing value creation to meet quarterly earnings expectations.  Focusing on earnings management not only detracts from long-term business management; it sends the wrong message to employees. 

 

The Pitfalls of Forecasting

This article was originally published in Arab Times

It’s that time of year again when market oracles debate what the coming year has in store. Economists and analysts are often criticised—with good reason—for inaccurate forecasting. In their defence, developing forecasts is difficult and riddled with challenges, especially in the GCC region, which is hostage to the volatile oil price. In addition many regional stock markets, are relatively new with little historical information available to perform rigorous statistical analysis. Economic data also comes with a time lag. This is further compounded as GCC stocks have only started receiving analyst’s coverage recently and therefore do not enjoy as much analyst’s attention as other emerging markets or developed markets. Following an earlier article in the Financial Times (FTfm supplement) Stephen Horan, CFA, and M.R. Raghu, president of CFA Kuwait discuss the role and challenges of forecasting in portfolio management.
<!--[if !supportLineBreakNewLine]--> <!--[endif]-->

 

What is the role of forecasting in portfolio management?

Formulating capital market expectations is the foundation of any sensible asset allocation strategy. We often equate forecasting with predicting future returns on asset classes, sectors, and individual securities. Importantly, however, portfolio management also requires managers to have a view on future volatility and correlations.

Moreover, we often think of forecasts in annual terms, especially at this time of year. Developing capital market expectations, however, is done in the context of the investor’s time horizon. In most situations, this requirement implies forecasting well beyond one year. Some of the challenges in making forecasts concern choosing relevant forecasting methods, properly interpreting historical data, overcoming behavioural biases, and managing the impact of forecast errors.

 

What are some common forecasting methods?

Ideal forecasting methods vary by asset class, but most forecasts have some connection with the past, to which analysts make a series of adjustments. A long historical sample period has the advantage of more statistical robustness but also runs the risk of introducing obsolete or irrelevant data. Statistical techniques allow analysts to place more weight on recent observations, de-emphasise or overemphasise extreme events, and capture the tendency of volatility to cluster over time.

Other forecasting techniques include adding appropriate risk premiums to the current risk-free rate, imputing the expected return implied by a discounted cash flow model or a portfolio optimisation model, and deriving financial market estimates from macroeconomic forecasts.

 

What are some data-related challenges in developing forecasts?

The timeliness and reliability of historical data are often questionable. For example, the International Monetary Fund sometimes reports macroeconomic data for developing countries with a lag of two years or more. Documents recently released by WikiLeaks reinforced the belief that some Chinese economic data may be “man-made.”

Hedge fund returns are notoriously plagued by survivorship bias, which is the inflation of average returns caused by the exclusion of failed funds from databases. Returns on real estate investments suffer from infrequent market valuations, which may not affect long-run return forecasts but which substantially reduces volatility estimates.

What are some of the behavioural challenges?

As human beings, we are vulnerable to several psychological traps when making predictions. We tend to think that the future will look like the recent past and naively extrapolate our most recent experiences into the future or over-emphasise experiences that have left a strong impression. We also tend to anchor our forecasts to our first impressions, over-emphasise low-probability events, and place greater weight on information that confirms rather than contradicts our pre-existing beliefs.

Most people are generally comfortable running with the herd. In making earnings projections, equity analysts (particularly those with little experience) often develop forecasts that are “in line” with other analysts’ forecasts. Finally, we tend to emphasise anecdotes and subjective personal experience over objective empirical data.

 

What are the implications of incorrect forecasts?

The impact of forecasting errors on portfolio construction depends on several factors. For example, if two asset classes have similar expected returns and variances, small changes in the inputs will lead to relatively large changes in optimisers’ outputs because the two asset classes are otherwise so similar. Optimizers will significantly over-allocate to those assets with either overestimated returns or underestimated variances. 

Do these differences lead to large performance differences?

Interestingly, these types of misallocations have a relatively modest effect on the portfolio's exposure to loss because the two asset classes are such close substitutes. Forecasting errors among dissimilar assets have an even smaller effect on asset allocation, which highlights the need to carefully define distinct assets in an asset allocation framework. Errors in estimating correlations have even less impact than errors in estimating expected returns.

 

What are the implications for portfolio management?

Although developing accurate forecasts is difficult work, we should not abandon the practice because it promotes insight and discipline. Furthermore, modest errors yield only modest differences in a portfolio optimisation context.

That said, analysts and portfolio managers are well-advised to avoid placing undue confidence in their forecasts and the models that use them. Most models assume that the expected returns, volatilities, correlations, and other inputs are known with certainty. In fact, they are only estimates of true values, and most traditional models do not fully incorporate this forecasting uncertainty. Therefore, be cautious and perhaps make conservative adjustments when interpreting a model’s outputs. 

The New “Ab”normal: Measuring Volatility is Risky Business

Market pundits suggest we are entering into an era of the “new normal” characterized by low returns and high volatility on risky assets.  Following an earlier article in the Financial Times (FTfm supplement) Stephen Horan, head of professional education content and private wealth management at CFA Institute  and Raghu Mandagolathur of CFA Kuwait, the national Kuwait society, discuss how the financial crisis has encouraged new thinking about what it means for markets to be abnormal and how to measure it.  The GCC stock markets measure very high in terms of volatility, even higher than emerging markets. The high volatility contributes to excessive speculation which reduces market efficiency. The issue is exacerbated by index concentration with few large cap stocks dominating the index. While decline in volatility happens over a long period of time when markets become more efficient, investors would do well to understand its source and take measures to manage it.
<!--[if !supportLineBreakNewLine]-->
<!--[endif]-->Why is it important to measure market volatility?

Volatility has implications for the future market behavior.  Research shows that abnormally large price movements (whether positive or negative) tend to be followed by relatively high returns.  Investors gain confidence as markets gradually resolve uncertainty instigated by the initial price shock. 

 Moreover, price shocks portend continued high volatility in the near term.  In other words, volatility tends to cluster through time.  So, even if an investor is unable to anticipate the onset of increased market volatility, they can expect it to continue for a while once it begins. 

How do portfolio managers typically measure market volatility?

Investors often think of market volatility in terms of the standard deviation of historical returns, which measures how variable returns have been over some time period.   Options markets provide an opportunity to get a forward-looking glimpse of volatility because the market price of calls and puts is directly related to the standard deviation of returns expected to prevail over the life of the option. However, GCC region is yet to have the benefits of a fully fledged derivatives market. Kuwait has a limited options market with only call options being allowed to be written...

Returns that are one standard deviation away from average are more typical than returns three standard deviations away from average.  Whether based on historical experience or implied by option prices, an asset’s standard deviation provides a benchmark for normal, or typical, variation relative to itself.

Are we in an abnormally volatile era?

The EURO STOXX 50 Volatility index, which measures the forward-looking standard deviation implied by prices of EURO STOXX 50 index options, has been close to its 52-week low, suggesting that market participants anticipate relative tranquility in the near term.   Based on this measure, one might say we are in an era of abnormally low volatility.  All else equal, markets respond negatively when implied volatility increases.

Are there other ways to measure market volatility?

One could think about the variability of returns among individual stocks in an index rather than the variability of broad market index relative to itself.  The more disperse the returns among a group of securities, the greater the opportunity for profitable security selection within that group.  This volatility across securities tends to spike in times of crisis, suggesting that returns from active management can be most pronounced during these times.

In a more eclectic vein, market volatility can be measured using linguistics to quantify the volume, tenor, and variability of sentiment of newswire stories.  This non-traditional, forward-looking approach can be helpful when forward-looking implied volatilities from option contracts are unavailable. 

Finally, volatility can be measured in terms of how asset classes typically behave in relation to one another, sometimes called market turbulence.

What do you mean by “turbulence”?

For example, in relatively tranquil markets, returns on corporate bonds and large company stocks are normally fairly independent of each other.  In turbulent markets, the returns of these asset classes may tend to move together. 

Even if return variability of corporate bonds or large company stocks is not particularly abnormal based on their individual behavior, the market can be turbulent based on the uncharacteristically high correlation between the two asset classes.  Mark Kritzman, CFA, and Yuanzhen Li propose a method measuring turbulence that incorporates unusual correlations in a recent Financial Analysts Journal article.

Are you simply describing the notion that correlations increase in times of crisis?

The concept has broader applicability.  In some cases, correlations decrease in turbulent markets.  For example, returns on high-yield corporate bonds and high-quality government bonds tend to be highly correlated in normal markets when returns on fixed income instruments are dominated by interest rate movements. 

In times of stress, changes in the risk premium dominate price changes, driving down returns on high-yield bonds and pushing up returns on high-quality government bonds in a flight to safety.  The main point is that turbulence is defined as much by abnormal correlation of returns as it is by abnormal volatility.

How might portfolio managers integrate different notion of volatility into practice?

First, portfolio managers can use the variability of returns across different securities to judge the profit potential of active management in a particular asset class and adjust their active or passive strategy weights accordingly. 

Portfolio managers might also spend extra time conducting scenario analyses based on experiences in market crises and focusing on variables that have been historically unstable.  Finally, they can incorporate covariances and other parameters derived from turbulent market periods rather than normally tranquil markets to construct portfolios.