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    <p align="left"><font face="Arial"><strong><small>About The Author:</small></strong></font></p>
      <p align="left"><font face="Arial"><!--webbot bot="HTMLMarkup" startspan --><A name=olsoinfo><!--webbot bot="HTMLMarkup" endspan --></font><font size="2">Joseph 
      P. Mathew is the President of Hybrid Energy Advisors, Inc.&nbsp; Hybrid Energy 
      Advisors, Inc., based in Houston, TX, </font><span lang="EN">
      <font size="2">provides independent business advisory services to the 
      natural gas industry and related markets.&nbsp; Their advisory services include 
      business development, risk management, asset and corporate valuation and 
      optimization analysis, corporate, project and public finance, general 
      industry research and analysis, and corporate credit risk analysis.</font></span></p>
      <p align="left"><font size="2">For more detail, please visit their website 
      at
      <a href="http://www.hybrid-advisors.com/" style="color: blue; text-decoration: underline; text-underline: single">
      www.hybrid-advisors.com</a> or contact Hybrid Energy Advisors, Inc. 
      directly by e-mail at
      <a href="mailto:[email protected]" style="color: blue; text-decoration: underline; text-underline: single">
      [email protected]</a> or call 713-666-9007.</font></p>
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      <font SIZE="6"><p><b><br>
    Gas Price Volitility:<br>
    Friend or Foe?<br>
    </b></font><b><i>Joseph P. Mathew<br>
    President<br>
    Hybrid Energy Advisors, Inc</i><span style="font-size: 12.0pt">.</span></b><strong><br>
    </strong><font face="Arial" size="2">(<em>originally published by PMA OnLine 
    Magazine: 2003/01</em>)</font></p>
    <p><font FACE="Palatino" SIZE="2">&nbsp;</p>
      </font>
      <p class="MsoNormal">One of the most prevalent subject matters in recent 
      gas market articles and headlines is volatility.&nbsp; Although the term is 
      widespread, the pure definition of volatility and its relevance to the 
      natural gas market is sometimes misunderstood.&nbsp; Volatility itself is not 
      the prime culprit which negatively affects the market, but it is the level 
      of volatility and its relation to the general trend, or �average price�, 
      of gas that a watchful eye must be kept.</p>
    <p class="MsoNormal" style="text-align:justify">If prices were low and 
    stable, perhaps the concept of volatility would not be as rampant an issue 
    in gauging the operations of a gas market participant, whether a net buyer 
    or a net seller.&nbsp; However, with the advent of deregulation, financial 
    contracts and new market entrants (such as traders, marketers and brokers) 
    from the early 1990�s to present, a much more dynamic market place has been 
    created.&nbsp; Combined with underlying market fundamentals that are causing 
    upward gas price pressure, volatility is something to be investigated.&nbsp;</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>What is Volatility?<br>
    </u></b>Volatility, in analytical terms, is also known as a numerical 
    variance, or more precisely, standard deviation from a �mean� or average 
    price trend.&nbsp; It says nothing about the direction of price movement.&nbsp; It can 
    be defined in terms of nominal integers to convey orders of magnitude from a 
    finite mean.&nbsp; However, volatility is typically expressed as a percentage.&nbsp; 
    Therefore, it is not calculated using nominal price data alone, but also the 
    changes in those prices from one estimation period to the next expressed in 
    percentage terms (periodic �<i>rates of return</i>�).&nbsp; In the gas market, 
    daily price settlements are best to use when calculating volatility, as each 
    day can count as one estimation period and each price will count as one 
    observation.&nbsp; Analytically, the greater frequency of observations utilized 
    in periodic calculations, the more accurate the measurement of volatility.&nbsp;</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Preliminary 
    Definitions<br>
    </u></b>In its most simple form, we can define rates of return as:&nbsp;</p>
    <p class="MsoNormal" style="text-align:justify"><b>i.) R = (P<sub>T</sub>-P<sub>t</sub>)/P<sub>t</sub></b>&nbsp;</p>
    <p class="MsoNormal" style="text-align:justify"><i>Where</i></p>
    <p class="MsoNormal" style="text-align:justify"><i>R: the periodic rate of 
    return<br>
    P<sub>T</sub>: the current price of an asset, time period T<br>
    P<sub>t</sub>: the preceding price of an asset, from time period t</i></p>
    <p class="MsoNormal" style="text-align:justify">Gas prices exhibit what is 
    called lognormal behavior due to the simple fact that prices have no real 
    upside constraint, but the downside is constrained by zero, as market prices 
    can never go negative.&nbsp; Therefore, over a large sample space of prices, a 
    resulting random distribution (bell-shaped curve) will be skewed to the 
    positive around a sample mean (or �average�) price.&nbsp; This is the essence of 
    gas price lognormalcy.&nbsp; Although commodity prices, like stock prices, follow 
    a lognormal distribution over a given period of time, the <i>percentage 
    return</i> of such price movements <i>can</i> either be positive or 
    negative, approximating a more normal distribution.&nbsp;&nbsp;&nbsp; A log of the relative 
    prices (P<sub>T</sub>/P<sub>t </sub>is called the �price relative�)<b> </b>
    must be calculated to effect continuous compounding of returns in the 
    market.&nbsp; This is an important fact when calculating the price of options 
    (the right, but not obligation, to buy or sell an asset at a specific price 
    in some predetermined time period) on physical and financial gas contracts.</p>
    <p class="MsoNormal" style="text-align:justify">Similar to the simple rate 
    of return equation above, the lognormal expression of continuously 
    compounded returns on gas prices can be expressed as:</p>
    <p class="MsoNormal" style="text-align:justify"><b>ii.) X = ln(P<sub>T</sub>/P<sub>t</sub>)<br>
    <br>
    </b><i>Where </i></p>
    <p class="MsoNormal" style="text-align:justify"><i>X: the normal periodic 
    rate of return<br>
    P<sub>T</sub>: the current gas settlement price, time period T<br>
    P<sub>t</sub>: the preceding gas settlement price, from time period t</i></p>
    <p class="MsoNormal" style="text-align:justify">To calculate the mean rate 
    of return for the period being evaluated, the following formula can be 
    used:&nbsp;</p>
    <p class="MsoNormal" style="text-align:justify"><b>iii.) X� = &#8721;(X<sub>i</sub>)/n</b></p>
    <p class="MsoNormal" style="text-align:justify"><i>Where <br>
    <br>
    X�: the mean, or average, value of all return observations X<br>
    X<sub>i</sub>: one observation of periodic rate of return<br>
    n: the total number of observations<br>
    &#8721;: greek symbol for �the sum of�</i></p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Historic Volatility<br>
    </u></b>Given the continuously compounded return and the mean return 
    formulae for gas prices, volatility can now be addressed and defined.&nbsp; The 
    following formulae define variance and its relation to standard deviation 
    (which is synonymous with volatility) for an observed set of empirical price 
    data:</p>
    <p class="MsoNormal" style="text-align:justify">Variance:</p>
    <p class="MsoNormal" style="text-align:justify"><b>iv.) V = [&#8721;(X<sub>i</sub>-X<sub>�</sub>)<sup>2</sup>]/(n)</b></p>
    <p class="MsoNormal" style="text-align:justify"><i>Where <br>
    <br>
    V: the variance of prices observed<br>
    X<sub>i</sub>: one observation of periodic rate of return<br>
    X<sub>�</sub>: the mean, or average, value of all return observations X<br>
    n: the total number of observations<br>
    &#8721;: greek symbol for �the sum of�</i></p>
    <p class="MsoNormal" style="text-align:justify">Standard Deviation 
    (Volatility):</p>
    <p class="MsoNormal" style="text-align:justify"><b>v.) S = SQRT{[&#8721;(X<sub>i</sub>-X<sub>�</sub>)<sup>2</sup>]/(n)}<br>
    <br>
    </b><i>Where <br>
    <br>
    S: the standard deviation of prices observed (square root of the variance)<br>
    X<sub>i</sub>: one observation of periodic rate of return<br>
    X<sub>�</sub>: the mean, or average, value of all observations X<br>
    n: the total number of observations<br>
    &#8721;: greek symbol for �the sum of�</i></p>
    <p class="MsoNormal" style="text-align:justify">If the data being analyzed 
    is a large enough sample size as compared to the total data which describes 
    the primary variable, then no adjustment needs to be made to the above 
    volatility formula.&nbsp; However, the smaller the data sample size from the 
    entire amount available, an adjustment factor needs to be included (so as to 
    �standardize� the variance).&nbsp; Statistically speaking, this adjustment is 
    referred to as adding <i>one degree of freedom</i> to the sample.&nbsp; This can 
    be achieved by subtracting one from the total number of observations in the 
    sample.&nbsp; Thus, the sample formulae look like this:</p>
    <p class="MsoNormal" style="text-align:justify">Variance (Standardized):</p>
    <p class="MsoNormal" style="text-align:justify"><b>vi.) V = [&#8721;(X<sub>i</sub>-X<sub>�</sub>)<sup>2</sup>]/(n-1)</b></p>
    <p class="MsoNormal" style="text-align:justify">Standard Deviation 
    (Standardized):</p>
    <p class="MsoNormal" style="text-align:justify"><b>vii.) S = SQRT{[&#8721;(X<sub>i</sub>-X<sub>�</sub>)<sup>2</sup>]/(n-1)}</b></p>
    <p class="MsoNormal" style="text-align:justify">So far, the equations have 
    dealt with generic periodic volatility, but in the financial markets and in 
    calculating options, volatilities follow an annualized convention.&nbsp; To 
    adjust volatility from a specific period (i.e., a daily, weekly, monthly, 
    quarterly or semi-annually) to an annualized basis, the following formula 
    must be used:</p>
    <p class="MsoNormal" style="text-align:justify"><b>viii.) S<sub>A</sub> = S<sub>P</sub>*SQRT[# 
    periods in a year]*</b></p>
    <p class="MsoNormal" style="text-align:justify"><i>Where <br>
    <br>
    S<sub>A</sub>: annualized volatility<br>
    S<sub>P</sub>: periodic volatility (daily, weekly, monthly convention)<br>
    <span style="font-size:8.0pt">*Simple algebra will allow reverse conversion, 
    from annual volatility to periodic volatility</span></i></p>
    <p class="MsoNormal" style="text-align:justify">These standardized formulae 
    are most typically used in industry practice due to the fact that analysts 
    who calculate volatility utilize chosen periods, or samples, of data from an 
    entire historic data stream.&nbsp; The reason for this is that proper studies of 
    historic volatility must be evaluated concomitantly with the underlying 
    fundamentals observed in the market during that specific period of time. 
    &nbsp;Evaluating an average volatility over a prolonged period of time may prove 
    inaccurate when forecasting volatility under new economic circumstances.&nbsp; 
    Different periods of time have different underlying economic and fundamental 
    events that create unique periodic price movements. &nbsp;Examples of such 
    underlying fundamentals include changing regulations, storage, demand, 
    supply, transmission and weather.&nbsp; Other major economic factors such as 
    legislation, monetary and fiscal policy must be concurrently reviewed.</p>
    <p class="MsoNormal" style="text-align:justify">A plethora of analytical 
    techniques, such as single, multivariate and non-linear regression, can be 
    used to gauge the relationship between these underlying fundamentals and 
    their effect on then-prevalent prices as well as on future prices (and 
    resulting volatility).&nbsp; Forecast volatilities can either be estimated 
    through logical extrapolation of historical analysis (<i>�forward 
    volatilities�</i>) or can be calculated by deduction utilizing traded 
    options (<i>�implied volatilities�</i>).</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Implied and Forward 
    Volatility<br>
    </u></b>Traded gas option prices are published daily and calculated using 
    five primary parameters*:</p>
    <ul style="margin-top: 0in; margin-bottom: 0in" type="disc">
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Current Price of the underlying gas contract</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Exercise Price</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Interest Rate relative to maturity time remaining on the option</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">Time 
      to Maturity</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Volatility of the underlying asset</font></li>
    </ul>
    <p class="MsoNormal" style="text-align:justify"><i>
    <span style="font-size:8.0pt">*storage costs and convenience yield 
    associated with physical natural gas are ignored here for simplicity</span></i></p>
    <p class="MsoNormal" style="text-align:justify">These five parameters are 
    utilized in the Black-Scholes commodity option pricing formula.&nbsp; The first 
    four are observable, but the fifth, volatility, must be estimated.&nbsp; To 
    calculate the implied volatility of a gas contract, one can create a simple 
    equation using a published option price on that gas contract and the Black-Scholes 
    formula.</p>
    <p class="MsoNormal" style="text-align:justify">On the left-hand side of the 
    equation is the published option price. On the right-hand side of the 
    equation is the Black-Scholes formula. By plugging in the four known 
    parameters, the volatility parameter (the sole unknown parameter remaining) 
    can be solved for algebraically.&nbsp; Since the algebra involved in such a 
    complex equation can be both intimidating and exhausting, the best approach 
    would be to solve for this parameter iteratively on a computer spreadsheet 
    such that there exists equality between both sides of the equation.</p>
    <p class="MsoNormal" style="text-align:justify">Using a series of similar 
    options with successive maturities, a forward volatility curve can be 
    constructed.&nbsp; However, this term structure of volatility will only be as 
    protracted as option prices are liquidly traded.&nbsp; Therefore, most analysts 
    use a combination of implied and historic analysis to ascertain optimal 
    forward opinions on volatility.</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Applying the 
    Volatility Formula to Gas Prices<br>
    </u></b>In a market where sudden, massive price spikes or falls are 
    observed, periodic volatility may be high, as seen many times on sudden 
    changes in expectation, the release of fundamental data, observations of 
    unexpected weather patterns, short trading position covering and calendar 
    year �shoulder� months (winter-to-spring and summer-to-winter).&nbsp; This can 
    lead to critical demand-side price management using methods such as dollar 
    cost averaging or financial product risk management.&nbsp; Dollar cost averaging 
    is a simple method of hedging characterized by the buying or selling of 
    contracts spread over a predetermined period of time rather than entering a 
    contract for the full volume at one point in time.&nbsp; This method is intended 
    to �smooth� market-timing price risk.&nbsp; On the other hand, financial products 
    such as futures, forwards, swaps, options, or a �hybrid� of any can be 
    used.&nbsp; These types of products are also intended to protect net income, 
    mitigate cost oscillation and strengthen cash flows.&nbsp; From a supply-side 
    perspective, excessive volatility can wreak havoc in decisions regarding 
    construction of new gas exploration projects.&nbsp; Similar hedging mechanisms 
    can be utilized by suppliers to protect revenues, project returns and create 
    cash flow stability.</p>
    <p class="MsoNormal" style="text-align:justify">Despite the incidence of 
    volatility in the energy market, many buyers and sellers do not hedge price 
    risk.&nbsp; In the 5-year period of 1995-1999 with respect to Henry Hub physical 
    gas prices, one can see that volatility averaged around 60% using formula <b>
    vii</b>.&nbsp; This calculation utilized a mean gas price of approximately $2.10/mmbtu, 
    calculated using formula <b>iii</b>.&nbsp; If one were to compare this to another 
    5-year period of Henry Hub gas prices, for example 1992-1996, volatility is 
    around the same value.&nbsp; What this means is that over almost a decade, gas 
    price volatility was approximately 60% on an overall basis, whether looking 
    at the first 5 years, the latter 5 years, or the entire term.</p>
    <p class="MsoNormal" style="text-align:justify">This observation does not 
    hold true when �slicing the pie� further.&nbsp; For example, recent market 
    prices, from the years 2000-2002, portray periods of excessively high gas 
    price volatility. &nbsp;At times, monthly price volatility was exorbitantly high 
    (as much as 100% or more) when annualized using formula <b>viii.</b>&nbsp; This 
    compares to two other periods of time, the winter of 1996/1997 and winter of 
    1998/1999.&nbsp; What were the similarities?&nbsp; The analyzed answers are inadequate 
    gas production and ill-equipped gas storage capacity management relative to 
    sudden demand surges due to unpredicted weather patterns and plant outages.&nbsp; 
    These factors were significant independent variables which increased demand 
    and gas price volatility.&nbsp; These protracted periods of high volatility could 
    be a foreboding message of the times to come given long-term gas supply and 
    delivery ambiguity.</p>
    <p class="MsoNormal" style="text-align:justify">To evaluate the financial 
    impact of volatility on market participants, one must consider it in both a 
    high price environment and a low price environment.</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Observations in a Low 
    Price Market<br>
    </u></b>For the vast majority of the 1990�s, Henry Hub gas prices average 
    approximately $2.10/mmbtu.&nbsp; During this time, annualized volatility averaged 
    approximately 60%.&nbsp; Numerically, it can be suggested that with 68% 
    confidence, gas prices were expected to be within $0.84/mmbtu and $3.36/mmbtu 
    and with 95% confidence, gas prices were expected to be between $0.00/mmbtu 
    (gas prices can never be negative, thus lognormal) and $4.62/mmbtu.&nbsp; The 
    two-way finite difference from the mean (the absolute volatility) is $1.26/mmbtu, 
    in terms of order of magnitude.</p>
    <p class="MsoNormal" style="text-align:justify">&nbsp;</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Observations in a High 
    Price Market<br>
    </u></b>During the 2000�s, gas prices have averaged approximately $4.50/mmbtu.&nbsp; 
    Eliminating the largest spikes in prices, volatility exhibited its 10-year 
    historic characteristic and averaged 60%.&nbsp; It can be suggested that with 68% 
    confidence, gas prices were expected to be within $1.80/mmbtu and $7.20/mmbtu 
    and with 95% confidence, gas prices were expected to be between $0.00/mmbtu 
    and $9.90/mmbtu.&nbsp; The two-way finite difference from the mean (the absolute 
    volatility) is $2.70/mmbtu, in terms of order of magnitude.</p>
    <p class="MsoNormal" style="text-align:justify">From looking at both 
    low-price and high-price scenarios, it is clear that general levels in price 
    play a significant factor in the actual dollar amount at risk when 
    considering an equal volatility percentage measurement.&nbsp; Thus, it is not the 
    volatility figure itself that is provocative.&nbsp; Rather it is the gross dollar 
    effect of a similar volatility measurement in either price environment that 
    may result in vastly different economic outcomes on a market participant�s 
    financial position and decision-making process.</p>
    <p class="MsoNormal" style="text-align:justify">This observation shows that 
    natural gas supply must be abundant and fluid enough to reduce the general 
    level of prices in order to minimize the effect of absolute volatility on 
    the cost structure of a buyer and the revenue structure of the seller.&nbsp; 
    Therefore, abundant gas supply, optimal storage management and 
    transportation/pipeline efficiencies can not only play a key role in 
    minimizing general price levels, but also in reducing absolute volatility.</p>
    <p class="MsoNormal" style="text-align:justify"><b><u>Observations in the 
    Current Gas Market<br>
    </u></b>Given the proportionately small amount of storage to provide price 
    buffers, increasing fundamental demand, unpredictable weather patterns, 
    demand-driven transportation capacity constraints and the higher 
    unpredictability and marginal cost of procuring reliable natural gas supply, 
    the United States is feeling greater upward gas price pressure.</p>
    <p class="MsoNormal" style="text-align:justify">This year, the Energy 
    Information Administration (EIA) anticipated medium-term gas prices to range 
    from $3.25/mmbtu to $3.50/mmbtu and long-term gas prices to be close to 
    $4.00/mmbtu.&nbsp; In analytically forecasting natural gas prices (and other 
    price curves, for that matter), one can assume that the gas price itself is 
    a �dependent� variable (dependent on the underlying fundamentals that drive 
    the price) and the underlying fundamentals are the �independent� variables 
    (that influence the dependent variable).</p>
    <p class="MsoNormal" style="text-align:justify">In the spring of 2002, 
    Hybrid Energy Advisors, Inc. (HEAI), using such analytic techniques, 
    predicted Henry Hub financial gas prices, the dependent variable, to hold 
    between $3.35 and $4.10 through the winter months of 2002/2003 (within a 90% 
    confidence interval). They also estimate ten-year price forecasts of 
    $2.25-$2.80/mmbtu during the summer months and $3.70-$4.25/mmbtu during the 
    winter months (also within a 90% confidence interval). These estimates 
    utilize stochastic price forecasting methods with the aforementioned natural 
    gas fundamentals serving as the independent variables.&nbsp; HEAI believes that 
    ten-year city gate prices of gas on the West Coast and Midwest United States 
    will trade approximately equivalent (�flat�) to Henry Hub prices. Similarly, 
    they expect upper East Coast prices to trade at an approximate 45-65 basis 
    point (cents/mmbtu) premium to Henry Hub prices.</p>
    <p class="MsoNormal" style="text-align:justify">New sources of gas and its 
    optimal dissemination into the market can be used to mute this upward price 
    pressure. &nbsp;Close analysis must be performed as to where this physical gas 
    comes from, what it will cost, what market prices will support expected 
    project returns and when it will be available to the market. &nbsp;Some sources 
    of new gas, each with its own unique cost structure, are projected to be 
    from:</p>
    <ul style="margin-top: 0in; margin-bottom: 0in" type="disc">
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">The 
      United States Gulf Coast (offshore, deeper wells)</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">The 
      Western Canadian Sedimentary Basin</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Eastern Canada</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">The 
      MacKenzie Delta in Northwest Canada (Yukon Territory)</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Alaska</font></li>
      <li class="MsoNormal" style="text-align: justify"><font face="Arial">
      Liquified Natural Gas (LNG)</font></li>
    </ul>
    <p class="MsoNormal" style="text-align:justify"><b><u>Conclusion<br>
    </u></b>When calculating volatility, one must do an �apples-to-apples� 
    comparison.&nbsp; That is, the analytical techniques used to calculate volatility 
    and create opinions about current and future volatility must be considered 
    in conjunction with the underlying fundamentals that were prevalent during 
    the estimation periods.&nbsp; Also, any new information regarding changes in 
    fundamentals must be incorporated in volatility assessments.</p>
    <p class="MsoNormal" style="text-align:justify">As the market currently 
    heads into a higher price environment, awareness of volatility should 
    increase due to its greater absolute effect on financial position, given a 
    similar volatility measurement in a lower price environment as seen in the 
    1990�s.</p>
    <p class="MsoNormal" style="text-align:justify">Volatility is healthy for 
    the market as long as it is not exorbitant.&nbsp; The potential for volatility is 
    a primary reason traders look to enter any market.&nbsp; There is compelling 
    empirical evidence by Fama, French and Roll that a market with trading 
    creates greater volatility than a market without trading even while 
    considering the discovery of new information regarding underlying 
    fundamentals.&nbsp; However, traders, marketers and brokers in the gas markets 
    play a critical role in creating competition, market price transparency, 
    liquidity and overall strength.&nbsp; Thus, contrary to popular current belief, 
    it would be a loss to the gas markets (and thus power markets) in the long 
    run if the merchant energy trading business disappeared.</p>
    <p class="MsoNormal" style="text-align:justify">A more prudent focus would 
    be that on increased gas supply, demand-side management, alternative fuel 
    potential, optimal storage management and efficient transportation 
    networks.&nbsp; &nbsp;This would lead to a lower gas price environment and reduced 
    overall volatility, which bodes well for the residential, commercial, 
    industrial and power generation markets.&nbsp; A joint focus on improving 
    fundamentals with proper hedging techniques allows buyers and sellers to 
    prosper in a market with inherent volatility and healthy trading.</p>
    <hr color="#FFFF00">
    <blockquote>
      <p align="left"><font face="Arial"><!--webbot bot="HTMLMarkup" startspan --><A name=olsoinfo><!--webbot bot="HTMLMarkup" endspan --></font>Joseph 
      P. Mathew is the President of Hybrid Energy Advisors, Inc.&nbsp; Hybrid Energy 
      Advisors, Inc., based in Houston, TX, <span lang="EN">provides independent 
      business advisory services to the natural gas industry and related 
      markets.&nbsp; Their advisory services include business development, risk 
      management, asset and corporate valuation and optimization analysis, 
      corporate, project and public finance, general industry research and 
      analysis, and corporate credit risk analysis.</span></p>
      <p align="left">For more detail, please visit their website at
      <a href="http://www.hybrid-advisors.com/" style="color: blue; text-decoration: underline; text-underline: single">
      www.hybrid-advisors.com</a> or contact Hybrid Energy Advisors, Inc. 
      directly by e-mail at
      <a href="mailto:[email protected]" style="color: blue; text-decoration: underline; text-underline: single">
      [email protected]</a> or call 713-666-9007.</p>
    </blockquote>
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