Big hitters wary of investing in agriculture

By Jürgen Siemer

Heavy hitters have lost appetite for investing in agriculture. As reported by The Financial Times on 27 January 2013, agriculture -- an industry worth an estimated tenth of total global economic output, with enough demand to drive a projected 70 per cent increase in production by 2050 -- has recently seen a turnaround with investors loosing appetite for entering the sector.

While still appealing to some investors, investing in agriculture has become more of a risky venture for those who take into account the fickle weather, political risk and quixotic governments, which can all have a negative impact on returns. According to the FT, since the beginning of the global financial crisis those factors have triggered a turnaround from earlier years when appetite for investing in agriculture was on the rise, with high-profile financial companies and big names in the investment world entering the sector.

“The last big industrialisation”

The FT quotes Richard Ferguson, director of agricultural consultant Masdar Farming, as saying that agriculture is “the last big industrialisation”. According to Ferguson, this is a process which will take between 20 and 30 years and will consist ofsmaller farms consolidating to form bigger corporate entities. Giving examples of this transformation of the global agricultural sector, Ferguson cited some of today’s big listed groups such asRussia’s Cherkizovo(LON:CHE) and UK-based Black Earth Farming (STO:BEF-SDB), which were formed on the basis of buying individual shares of blocks of land from hundreds of peasants.

Investors seek new routes to investing in agriculture

Analysts explain the decline of investment in agriculture with another factor of concern to prospective investors -- many view this sector as small-scale and localised, where single projects are risky. Based on this concern, new investment opportunities are being sought and investors are exploring ways of making farming more investable, such as by increasing scale or diversity to mitigate risk. An increasing number of investors are tapping agricultural growth via technology and equipment producers in the industry, buying shares in publically-traded companies such as German tractor maker John Deere (FRA:DEE) or Switzerland-based seed supplier Syngenta (VTX:SYNN).

Yet some analysts disagree

And while most estimates point toa trend of accelerating concerns over investing in agriculture and a decline in ventures in the sector, some analysts believe that agriculture is still an appealing and lucrative investment option.

About the author: Jürgen Siemer, senior analyst at Sustainable Asset Management, told the FT: “Prices for land are going up, so investment in agriculture and the value chain is becoming more attractive and there is much more profit to be made.” For more information on the topic visit click here. 

Pros and cons of economic value added

Effect of regulation on Economic Value Added

Image attribution: Mgmwki; CC BY-SA 3.0

Economic Value Added (EVA) is a term referring to financial gain in excess of profit expectations. In other words, EVA  measures the extra value profits yield for an organization after deducting cost of capital such as dividends to shareholders. Although EVA is an acronym used across multiple industries with different meanings, its significance in finance is specific. Moreover, the usage of EVA often refers to a proprietary version of the calculation claimed to have been created by the Business Advisory Firm Stern Stewart & Co in the late 1980s.

Uses

The EVA metric is primarily used as a business valuation tool. Some proponents of EVA such as P.C. Narayan of the Indian Institute of Management at Bangalore advocate EVA over other profitability metrics because it demonstrates potential future earnings. This according to Narayan, is because measurements such as Earnings Per Share (EPS) only provide a snapshot of how well a company has met stock-holder's past financial expectations and does not reflect potential for capital reinvestment.

Calculation

In terms of the Stern, Steward & Co. formula, EVA is the result of subtracting taxes and weighted average cost of debt and equity capital from net operating profit. This however, is not the only way to determine EVA because the cost of capital calculation varies between businesses. For example, the United States Postal Service version of EVA indexes its operating cost to inflation to more accurately reflect costs after rate increases. Other companies may not need to adjust costs to inflation based on corporate policies and accounting methods. The Stern Steward  & Co EVA formula is shown below:

EVA= (Net Operating Profit-Tax)-(Weighted Average Cost of Equity and Debt)

Advantages

The advantages of EVA are it supplements financial data from other methods of business assessment and valuation. Moreover, it reflects businesses' cost management and demonstrates availability working capital after its original opportunity cost has been deducted. Another benefit of EVA is it can be used as a managerial incentive that helps assure the continued performance of a business. It also evades problems associated with percentage calculations by using specific values according to Aswath Damodaran, a Finance Professor at the New York Stern School of Business.

Disadvantages

Economic value added cannot measure how well capital asset managers utilize retained earnings via project management and other business ventures. Moreover, capital asset managers may squander liquid reserves instead of effectively increasing the future return on capital by  reinvesting it with the aim of lowering operational costs via profitability instead of cost cutting. Economic value added also cannot valuate return on expenses such as research and development. Moreover, despite being an income statement operating expense, research and development actually has the potential to yield  future earnings not measured by EVA.

How technical analysis of stock prices works

Image attribution: StocksDocs. CC BY S.A.-3.0

Technical analysis in stock trading refers to the evaluation of stock price changes over time. These changes are measured and plotted using formulas, charts and graphs and assessed in terms of patterns, and strength of stock price movement. A number of basic technical tools, and techniques are used to help technical analysts or chartists assess if specific indicators have occurred.

After a technical indicator has occurred, a confirmation of that indicator may follow using another technical analysis metric. Technical analysis is not an exact science, and generally shouldn't be considered as always being reliable. Rather basic technical analysis is sometimes used in stock trading to assist in substantiating or validating other methods of stock analysis.

• Moving averages

Moving averages are measured in days, usually up to 200. When longer-term moving averages have been moved through by stock prices, it sometimes indicates a significant price movement. Sometimes stock price support and resistance are formed near moving averages, and when these price levels are significantly broken it can mean a possible price momentum trend. In other words, moving averages are at times used as pivot points where a stock may have a pattern of rebounding upward or downward.  

• Candlestick charting

Candlestick charting is a form of technical analysis that began in East Asia. In this type of analysis price movements are represented by black or white candlesticks with lines at the top and bottom. Sometimes colors such as green or red replace the black and white in candlesticks. The color, length and positioning of these candles are placed on a chart and scaled in terms of time and stock price . The technical analysis of these charts will then interpret the candles based on past patterns of similar candle positioning.

• Oscillators

Oscillators are used to determine upper and lower limits of price movements. Examples of oscillators are the Relative Strength Index (RSI), and the Rate of Change (ROC) indicators. These basic stock technical analysis tools plot values on a scale between 0-100 using mathematical formulas. When certain value levels are reached, the oscillators are sometimes thought to show an increased probability of a price being close to a high or low.

• Trading levels

Trading levels constitute the amount of stock trading that takes place during a specific period of time and is another widely used basic aspect of technical analysis in stock trading. Trading levels are measured using volume and when it ncreases it can mean a growing momentum in the movement of a trend may be occurring or about to occur. Volume can also indicate overall market participation. For example, during holidays, volume can be quite low due to the absence of investing activity on those days in holiday when the stock market is open.

• Line graphs

Line graphs are also used in basic technical analysis of the stock market. When stock prices are plotted onto line graphs over time, the movement of that price can be analyzed for patterns in a similar way to candlestick charting. For example, a stock price line graph may create a pattern called 'head and shoulders', which literally takes the shape of a left and right shoulder with a head in the middle. If patterns like this become evident, stock prices sometimes follow similar movements to previous occurrences when a similar pattern was observed in that or other financial securities' line graphs.

Understanding High Beta Stocks

A high 'beta' stock has price movements similar to a larger group of stocks known as an index. The beta, also known as the 'beta coefficient', is a mathematical result calculated by recording changes in stock price over time and comparing those changes with changes a group of other stocks. For example, if XYZ has a beta value of 1 as measured against an index of stocks in the same industry, then XYZ has price movements similar to the average or weighted average of the larger group of stocks; this relationship is called correlation.

How beta is interpreted is also important as simply knowing a financial security has a high correlation with other securities only says that financial instrument performs in an average way in comparison to other financial instruments. For this reason understanding what high beta stocks are also involves interpretation of the beta value in each particular measurement.

• How a high beta stock is defined

To illustrate a high beta stock, suppose there is a company with an unknown historical price performance in relation to a broad based market index. That company has a 52 week price range of $10-$40 per share which in and of itself is an indication of past price volatility. However, if that volatility closely matches that of 100 other companies all in different sectors of the economy, then the probability increases the beta is indicating an overall market movement rather than a company specific matter.

Since beta values often range from -1 to +1 with +1 meaning high correlation, and the inverse for the negative, then a number close to +1 would be 'high beta'. I the company performs negatively when the overall market does well, then the chances the company has a specific problem increase and the beta has a lower value. Thus, beta should not only be understood as a variable in and of itself, but also in relation to other financial and economic situations.

• Why high beta stock assessments are useful

Beta values are used by investors, financial analysts, and other financial aficionados to better understand risk, potential and performance of financial instruments such as individual company stocks. For example, an analyst may want to compare the beta value of XYZ company in relation ABC Index with the beta of EFG company in terms of the same ABC Index.

This allows the analyst to not only determine which company has most closely conformed with average price movements, but which company is more volatile and hence riskier. Beta values can be used in different ways for different assessments; they can be used when planning an investment strategy, in retirement planning, in forecasting performance and more.

• Other uses of for high beta stock values

High beta stocks may be further analyzed using the same high beta variable discussed above. This is because the beta coefficient is also used in other financial formulas and is a resulting variable of regression analysis. In other words, the beta coefficient is both a variable and an outcome depending on the financial measurement involved. Since regression analysis measures relationships between financial variables it logically follows that the beta coefficient would be a result of that technique.

In the case of the Capital Asset Pricing Model (CAPM), pricing of an asset is determined in part by measuring volatility. Beta is a variable that measures volatility in terms of comparative price movement, and is consequently widely known to be used in CAPM. A high beta stock might cause a stock measured with CAPM to be worth more if the index against which the stock is being measured is performing well, and vice versa if the situation is otherwise.

Summary:

A high beta stock is one with a value closer to +1 or higher. This value measures comparative change over time and is a historical value. Since beta is historical, it doesn't necessarily predict future price movements with great accuracy. Nevertheless, knowing the beta of a stock can be helpful when making financial decisions, especially when understood in the context in which the value is used.

A high beta stock isn't necessarily a good thing as the beta may reflect a tendency to perform on average. However, in some cases a high beta may be good, such as when one sector of the economy is performing better than other sectors and the beta for a particular stock with stocks in that sector is high.

The Top Morningstar Rated Funds

The top rated Morningstar funds are divided into categories including dividend, value, growth, large-capitalization, mid-capitalization and small-capitalization. Additionally, within these groups, Morningstar rates fund by classes; for example ABC Fund Class A and ABC Fund Class B. As of the date this article was produced, Morningstar’s top rated funds included 1) AIM Diversified Dividend Fund, 2) Allianz NFJ Small Cap Value Fund, 3) American Century Equity Fund, 4) American Century Mid Cap Fund, and 5) the American Century Small Cap Mutual Fund. Morningstar rates each of the funds within this category to come up with the highest rated funds. 

Before delving into the top rated Morningstar funds it is a good idea to understand what Morningstar is and why their ratings are considered by some to be useful assessments of mutual funds. Morningstar describes itself as an investment research firm that has been around since the 1980’s before mutual funds became the massive industry they are today. Over time the Morningstar product line, reputation and analysis grew with the market making it a leading investment information firms. Having said that, and without further ado, more about the top rated Morningstar funds as of the date of this article are as follows:

Top Morningstar rated funds by category:

1. AIM Diversified Dividend Instl  (DDFIX)
 High minimum investment, average risk and return institutional fund as per Morningstar.com. The fund is in the 10th percentile for the 3 years beginning in 2006.

2. Allianz NFJ Small Cap Value A  (PCVAX)
 A closed fund as of 12/16/09 with billions in assets, above average returns and low risk. 10 year investor percentile rank of 22 within the category as per Morningstar.com.

3. American Century Equity Income Instl  (ACIIX)
High minimum investment institutional fund i.e. for financial institutions to invest in.  26th percentile investor return ranking for 10 years with 7.08% investor return.

4. American Century Mid Cap Value Adv  (ACLAX)
A no load fund with high turnover and assets in the millions. This fund was incepted in 2006 and has a 52nd percentile investor return rank in 12/09.  Considered by Morningstar to have high returns for low risk as per Morningstar’s 11/30/09 data.

5. American Century Small Cap Value Instl  (ACVIX)
An institutional fund that has opened and closed to investors more than once. The fund has a high 10 year return and rating with below average risk according to Morningstar.

Rating methodology

It is important to note these ratings were compiled in December of 2009,  are based on data from the previous month, and do not necessarily rank high in dollar weighted returns. In such cases, evaluating the top rated Morningstar funds over a multi year period and in terms of investor returns may be more revealing and of additional use to investors. 

Moreover, the criteria by which mutual funds can be evaluated vary allowing investors to independently rank funds with Morningstar’s investor tools. Morningstar itself uses  1) a star rating system, 2) year to date return and 3) expense ratio when listing top rated funds.   The star rating itself is divided into further criteria that include variables such as risk.

The rating methodology used for the above funds does not necessarily include the same criteria an investor would look for. For this reason additional fund comparison tools are provided by Morningstar to arrive at top rated Morningstar funds for themselves and their specifications. For example,  the 1st ranked fund above does not rank in the highest in the 1,3 or 5 year percentile rankings. 

In other words, the aforementioned mutual funds are not measured using a percent rank methodology which measures fund return against similar mutual funds. The Morningstar tools allow an investor to weight criteria according to importance to them to arrive at ’fund scores’. In other words, this allows investors to customize their investments search by their investment goals, and criteria and not Morningstar’s.

Source: http://www.morningstar.com

Originally written 12/17/2009

Finance Professionals Assess Hybrid Portfolio Theory (HPT)

Hybrid Portfolio Theory (HPT) is a model of financial management intended for use in client portfolio asset allocations and investment decision making by investment managers.

The term Hybrid Portfolio Theory (HPT) has multiple meanings ranging from diversified asset allocation with risk and reward optimization in mind to investment selection based on algorithms and quantified investment data. This article will outline and assess hybrid portfolio theory in terms of its meaning, benefits, disadvantages and validity.

What Hybrid-Portfolio Theory is

In simple terms, hybrid means the conversion of two financial methods; portfolio means the distribution of assets via investment and/or asset allocation, and theory means, a tested but not absolutely proven financial hypothesis. Thus, HPT is essentially an investment management optimization theory. Below are two examples of HPT, both of which are quite differentiated from one another.

1. Hybrid Portfolio Theory using algorithmic data compression:

The application of Hybrid Portfolio Theory ideally produces financial consistency and returns with higher returns on investment with less risk making it an investment selection model. An example of Hybrid Portfolio Theory is described by Paul Bao and Hakman Wong uses several key components including the following:

• Fuzzification: Data classification
• Compression techniques: Simplification of information
• Genetic algorithm: Analysis of changing data for use in a formula

Since 'fuzzification', 'data compression' and 'algorithms' can vary, so can a Hybrid Portfolio Theory. In other words, HPT can be viewed in terms of 1) data in, 2) data processed, and 3) data out. All three steps in the HPT model can vary making the actual data, its processing and outcome important to the validity of the model.

2. Hybrid portfolio using non-sequential data analysis:

This second model of Hybrid Portfolio Theory is more static and presumes conditions don't change, but rather follow general principles that are consistent enough to be incorporated into the theory. This particular version of Hybrid Portfolio Theory is attributed to Jeff Joseph of Prescient Advisors and makes use of a split portfolio technique. The two portfolios combine low risk and average return in the majority of the split portfolio and high return with optimized risk in the minority portion.

Essentially, this theory goes without saying, but does provide financial planners with a method by which to allocate assets. The question with this HPT is which particular investments provide the portfolio with its intended results, i.e. one can easily state the conditions by which an objective can be achieved without actually defining how those conditions can be met.

Benefits of Hybrid-Portfolio Theory

The benefits of Hybrid-Portfolio Theory are unique to the actual performance of the application of the theory. In other words, both the above theories must be demonstrated to work to be considered beneficial to an investor or investment manager. Until that is done, the HPT theory is just another theory that sounds interesting, but may not actually be any better than simpler quantitative techniques of investment analysis combined with intuitive insight, existing knowledge and traditional analysis.

The benefits of traditional analysis techniques such a technical analysis and fundamental analysis is that they are time tested to be accurate within a certain range. The goal of new models and theories such as Hybrid Portfolio Theory is to improve upon the accuracy of the predictive capacity of existing investment analytics, investment management models and financial planning policies.

Disadvantages of Hybrid-Portfolio Theory

The Hybrid Portfolio Theory put forth in the second example above is a reaction to what it refers to as "black swan" market conditions. In this reaction, the call for lower risk investment techniques is emphasized in order to reduce the probability of highly volatile asset value swings. Essentially the 'theory' states by aggressively reducing risk while simultaneously increasing return an investment portfolio can achieve an 'asymmetrical' return i.e. a ROI that is not symmetrical with risk.

The disadvantages of both the above techniques are 1) opportunity cost, 2) validity verification, 3) fiscal and temporal cost. In other words, the theory needs to be proven, and the theory needs to be proven as being better than other investments in terms of both risk and return. Additionally, especially in the case of the first HPT example, the quantitative and information technology consulting and upfront costs for such a model, especially in the case of asset managers, may be high, making the necessity of value for the premium to be worthwhile.

Validity of Hybrid-Portfolio Theory

"In theory", there's nothing invalid with the assertions made by either Jeff Joseph's, Paul Bao and Hakman Wong's HPT. However, financial models are not financial theories, and financial hypotheses are not financial models. On first impression, it seems as though HPT may encompass a little of all three of these terms of validity potentially giving it more credibility than might be justified.

As with any hypothesis, model or theory, until the data is demonstrated to be both statistically significant, and quantitatively proven, it is nothing more than financial idealism packaged within fiscal lingo. This is not to say Hybrid Portfolio Theory doesn't work, but it is to say, HPT must first be demonstrated to work, and the burden of proof is on the proponents of the theory.

Sources:
1. http://tinyurl.com/4tv62e2
2. http://tinyurl.com/4ftwbr2
3. http://tinyurl.com/lrxfgn
4. http://www.badros.com/greg/papers/badros-dcc94.pdf

What is the beta coefficient of a stock?

The beta coefficient, also represented by the Greek letter Beta, or the English letter B, is a measure of risk most notably in regard to an equities traded in markets such as stocks. The beta determines price movement relationships alongside broader market indicators such as an index or group of stocks.

The closer the beta value is to the integer 1, the more probable that stock is to move in tandem with broader market movements such as the index. It is important to note, the beta coefficient is calculated using historical prices and should not be interpreted to indicate an exact measurement of future price movements.

Key attributes of the beta coefficient

The beta coefficient has several functions and attributes that make it a unique and important financial equation. The beta is considered a standard statistic in financial analysis and is used in a number of other more complex formulas. A few of the specific features of the beta are listed below:

• Establishes numerical relationships between stock prices and markets over time
• Is an accurate measure of historical price volatility
• Beta is also used in the Capital asset pricing model (CAPM)
• Can be calculated quickly and easily in a number of ways
• Assists in determining price risk
• Calculated using percentage rates of return for 2 or more points in time.

How to calculate the beta coefficient

There are several ways to obtain a beta value including the Microsoft excel statistical tool, a financial calculator, an online financial analysis website or manually using a formula. It can be helpful to understand the math behind a beta in understanding what the beta is. One simple method to calculate the beta is the rise over run method (Brigham and Houston p.277) This method simply takes two historical percentage price points and subtracts them and then divides the difference between corresponding percentage price points in the index.

Beta=Rise over Run=Change in Y (Stock price)/Change in X (Index value)

For example, when company Y had a rate of return of 7% dollars, the index had a return of 5%, and when the index had a return of 2% , company Y had a return of 4%. Using the rise over run equation, the change in company Y (also plotted on the Y axis of a graph) is 3% and the change in the rate of return of the index is 2%.

The change in Y divided by the change in X is equal to 1.5 which is the beta. Since a beta of 1 represents an exact historical price correlation, values higher than 1 are less correlated i.e. numerically related than betas of 1. The further a beta gets from the value 1, the less likely the stock being measured will move with the index if the historical relationship remains constant.

Advantages and disadvantages of the beta coefficient

The beta value is a useful tool to measure price relationships under various market conditions. For example, if there is a recession, a stock with a historical beta of 1 is statistically more probable to also decline in price than a stock with a beta of 2. This is because the stock with a beta of 2 does not necessarily follow market trends. There are several advantages to using beta, most importantly its ability to determine price stability over time. It can also be calculated using many points in time thereby augmenting its statistical validity.

On the other hand, the beta coefficient does have a few disadvantages. Since the calculation is limited i.e. only uses two variables as changed over time, it does not take into account other variables such as inflationary pressures, capital liquidity, financial ratios etc. Such being the case, the beta is restricted to being a potential indicator of price movement in relation to a broader index. Additionally, since market and company conditions can change over time, the beta will not take into account these future changes.

Summary

The beta coefficient is a mathematical value that represents risk of a financial instrument over time in relation to a market. The beta can be easily calculated or obtained and is a standard financial value used in financial analysis. The beta coefficient is a statistical tool based on historical trends and price movements and is therefore not an exact indicator of future price relationships. Rather, the beta coefficient is a useful estimator for determining future price relationships and risk of a particular company or stock.

The beta can be determined under various market conditions to enhance risk and return predictions for a particular asset and/or equity product and can also be calculated using an adjustable range of percentage returns over time. Since the beta value is limited by its variables, it is narrow in its predictive ability. However, the beta coefficient is also an important variable in other financial equations such as the capital asset pricing model (CAPM) and in regression analysis.

Sources:

1. Calculating Beta using excel: http://faculty.babson.edu/academic/Beta/CalculateBeta.htm
2. Eugene F. Brigham, and Joel F. Houston. Fundamentals of Financial Management 9th Ed. South-Western, 1999.p277-281.
3. Howard Bryan Bonham CPA, The complete Investment and Finance Dictionary. Avon Media Corporation, 2001.p.62
4. Zvi Bodei, Alex Kane and Alan J.Marcus. 'Investments' Mcraw-Hill Irwin. New York, 2002. P. 265-271