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The Spanish Review of Financial Economics
Inicio The Spanish Review of Financial Economics Variance swaps and intertemporal asset pricing
Spanish Review of Financial Economics aims to publish theoretical and empirical papers across all the major fields of financial research. Topical areas of interest include, but are not limited to: accounting, asset management, asset pricing, banking and financial institutions, corporate finance, corporate governance, derivatives, financial econometrics, international finance, market microstructure, and risk management. The Journal's purpose is to improve communications between, and within, the academic research community and policymakers and operational decision makers at firms or financial institutions.
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Vol. 9. Issue 1.
Pages 20-30 (January - June 2011)
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Variance swap contracts and the variance risk premium
Data and descriptive statistics
A two-factor intertemporal asset pricing model
Asset pricing model performance
The non-linear version of the two-factor icapm
The linear version of the two-factor icapm
The linear version of the two-factor icapm with two regimes based on a market return threshold
DOI: 10.1016/j.srfe.2011.01.001
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Variance swaps and intertemporal asset pricing
Belén Nietoa, Alfonso Novalesb, Gonzalo Rubioc,
gonzalo.rubio@uch.ceu.es
a Universidad de Alicante, Alicante, Spain
b Universidad Complutense de Madrid, Madrid, Spain
c Universidad CEU Cardenal Herrera, Elche,Spain
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(Daily data update)
Table 1. Variance risk premia descriptive statistics.
Table 2. GMM estimation. 25 size/book-to-market portfolios and 17 industry portfolios. Monthly data, January 1996 to January 2007.
Table 3. Estimates and standard errors of intercepts and risk premia for the traditional Fama–MacBeth two-pass cross-sectional regressions, monthly data, January 1996 to January 2007.
Table 4. Estimates and standard errors of alphas and betas from a pooled OLS regression with two regimes based on a market return threshold, January 1996 to January 2007.
Table 5. Estimates and standard errors of intercepts and risk premia for the market threshold two-regimes Fama–MacBeth two-pass cross-sectional regressions, January 1996 to January 2007.
This paper proposes an ICAPM in which the risk premium embedded in variance swaps is the factor mimicking portfolio for hedging exposure to changes in future investment conditions. Recent empirical evidence shows that the fears by investors to deviations from Normality in the distribution of returns are able to explain time-varying financial and macroeconomic risks in addition to being a determinant of the variance risk premium. Moreover, variance swaps hedges unfavorable changes in the stochastic investment opportunity set, and is not a redundant asset because significantly expands the efficient mean-variance frontier. Thence, we should expect the variance swap risk premium to be priced in the market. We report relatively favorable evidence on the incremental pricing information associated with the variance risk premium, particularly at shorter horizons.
Variance risk premium
Intertemporal asset pricing
As shown by Carr and Wu (2009), Todorov (2010), and Egloff et al. (2010), the average variance risk premium is negative and sizeable for all available horizons. Since the payoff of a variance swap contract is the difference between the realized variance and the variance swap rate, the observed negative returns for long positions on variance swap contracts for all time horizons suggest that investors are willing to accept negative returns for insuring against future realized variance. Recently, Nieto et al. (2010) use the implications of an asset pricing model proposed by Chabi-Yo (2009) to find evidence that as it is the case with standard indicators of different types of macroeconomic and financial risks, the variance risk premium responds to changes in higher order moments of the conditional distribution of market returns.1 This common dependence suggests that the variance swap may offer hedging against a variety of risks and, consequently, the variance risk premium could be capturing the market willingness to pay for such a hedge.
A natural question then refers to whether the fluctuations in the variance risk premium may act as a sufficient statistic summarizing the information contained in a variety of macroeconomic and financial risk indicators which is relevant for asset valuation. In the continuous-time Intertemporal Asset Pricing Model (ICAPM hereafter) of Merton (1973), the value function depends not only on aggregate wealth, but also on the innovations to some state variables that describe the stochastic behavior of the investment opportunity set. These additional variables may hint at ways to design an appropriate hedge against unfavorable changes in the stochastic investment opportunities and the optimal portfolio should be made up by a combination of the market and the hedging portfolios. In this paper, we employ the payoff of the variance swap as the hedging variable for alternative investment horizons. Therefore, we take the ICAPM as the natural framework to investigate whether the variance risk premium may add information to the return on market wealth as an aggregate risk factor explaining the cross-section of expected returns.2
Specifically, the stochastic discount factor (SDF hereafter) is specified as a power function of the return on the market portfolio, expanded with an exponential function of the excess return of the variance swap contract as hedging variable. We perform several empirical tests of the model that suggest that the variance risk premium contains relevant information that helps pricing average stock returns. The measures of the global fit indicate that the model performs better when it includes the variance risk premium factor than when it only incorporates the market return portfolio. This evidence is generally observed for both the non-linear specification and the beta (linear) specification of the model. Specifically, the comparison between the one-factor model and the two-factor model at the one-month investment horizon reveals that the mean absolute pricing error decreases from 0.343 to 0.288 in the non-linear specification, and that the pseudo cross-sectional R-square used in the estimation increases from 0.278 to 0.412 in the beta specification. Moreover, we also show that, on average, test portfolio betas relative to the variance risk premium factor are strongly negative when we allow for regressions with two regimes based on a market return threshold. The relatively favorable evidence on the variance risk premium being a financial factor that is priced in the market is consistent with the result in Nieto et al. (2010), who show that the variance swap is not being spanned by a set of assets composed of government and corporate bonds and the stock market portfolio.3
The paper is organized as follows. Section 2 briefly describes the variance swap contract and defines the variance risk premium. Section 3 contains a description of the data. The two-factor asset pricing model is presented in Section 4, while Section 5 reports the results of the empirical tests. Section 6 concludes with a summary of our findings.
2Variance swap contracts and the variance risk premium
A variance swap is an over-the-counter financial instrument that pays the difference between a standard estimate of the realized variance of the return on a given asset (a stock market index in this case) and the fixed variance swap rate. More in detail, one leg of the variance swap pays an amount based upon the realized variance of the price changes of the underlying asset. Conventionally, these price changes will be daily log returns, based upon the most commonly used closing price. The other leg of the swap pays a fixed amount, the strike, quoted at the deal's inception. Thus the net payoff to the counterparties is the difference between these two values. It is settled in cash at the expiration of the deal, though some cash payments are likely to be made along the way by one or the other counterpart to maintain an agreed upon margin. The payoff of a variance swap issued at time t and maturing at time t+τ is therefore given by,
where Nvar denotes variance notional, also called variance units, RVt,t+τ is the annualized realized variance over the life of the contract, and SWt,t+τ is the delivery price quoted at time t for the variance of the asset between t and t+τ, also known as the variance swap rate. Hence, profits and losses from a variance swap depend directly on the difference between realized and implied variance.
Since variance swaps cost zero at entry, no arbitrage requires that the variance swap rate must be equal to the risk-neutral expected value of the realized variance. Therefore,
where EtQ(.) is the time-t conditional expectation operator under some risk-neutral measure Q. The variance risk premium at period t is then defined as,
where EtP(.) is the time-t conditional expectation operator under the physical probability measure P. If investors price variance risk, the variance swap rate will differ from the expected realized variance under P at the corresponding horizon, the difference being the variance risk premium.
3Data and descriptive statistics
In this paper we analyze variance swap contracts on the S&P 500 index. Daily variance swap rates on five different maturities from January 4, 1996 to January 31, 2007 are obtained from Bank of America. We get monthly data by using the quotes on the last day of each month. Our estimation of the realized variance employs intra-daily data observed at 30-min intervals, from 9 a.m. to 3 p.m., on the S&P 500 index returns provided by the Institute of Financial Markets. For each month in our sample, we compute the realized variance for each maturity τ of a variance swap contract (τ=1, 2, 3, 6, and 12 months) using quadratic changes on the value of the S&P 500 index, as given by
where Pt is the level of the index at time t, L is the number of 30-min intervals comprised in the interval (t, t+τ). We work with variance swap rates and realized variances in percent numbers.
For each month t and each maturity τ we compute the log variance risk premium as the logarithm of the ratio between realized variance and the swap rate,
which can be read as the excess rate of return of the variance swap contract. Clearly, VRPtt+τ is known only at time t+τ. Fig. 1 displays variance swap rates and realized variance for 1-, 3- and 6-month maturities. As expected, the swap rate is most often above the level of realized variance, especially for longer maturities. This evidence is similar to that shown by Carr and Wu (2009) for stock market indices and, to a lesser extent, for individual stocks.4 It is clear that investors are willing to accept a significantly negative return to long variance swaps on the S&P index in exchange for being hedged against future unexpected volatility shocks. Therefore, shorting variance swap contracts in the S&P index generates significantly positive average excess returns during our sample period, since the variance risk premium can be seen as the return on holding the variance swap contract.
Monthly variance swap rate and realized variance for different maturities. January 1996 to January 2007.
(0.5MB).
Panel A of Table 1 reports the variance risk premium descriptive statistics for alternative maturities. The variance risk premium is always negative on average, and it becomes more negative with maturity. Panel B of Table 1 reports the correlation coefficients between the variance risk premia at any two different maturities. Correlations between variance risk premia at adjacent maturities are high, debilitating for faraway maturities. The correlation matrix suggests the existence of at least two factors in the structure of variance risk premium.5
Variance risk premia descriptive statistics.
VRP1 VRP2 VRP3 VRP6 VRP12
Panel A: descriptive statistics
Mean −0.646 −0.635 −0.659 −0.694 −0.736
Median −0.697 −0.682 −0.719 −0.751 −0.734
Maximum 0.834 0.952 0.841 0.706 0.441
Minimum −1.556 −1.612 −1.631 −1.576 −1.600
Panel B: linear correlations
VRP1 1 0.793 0.659 0.402 0.224
VRP2 1 0.910 0.650 0.453
VRP3 1 0.798 0.574
VRP6 1 0.793
VRP12 1
VRP is the variance risk premium associated with the alternative horizons of the variance swap contract between 1 and 12 months. It is computed as the difference between the ex-post realized variance at the end of the swap contract and the observed variance swap rate.
Monthly data on value-weighted stock market portfolio returns (RW) and the risk-free rate (Rf) are taken from Kenneth French's web page. We also collect the excess returns of 25 size/book-to-market value-weighted portfolios and 17 industry value-weighted portfolios. We compute monthly series of cumulative returns corresponding to the five maturity intervals of the variance swap rates for the market return, the risk-free rate, and the 25 and 17 portfolio returns.
4A two-factor intertemporal asset pricing model
Evidence presented in Nieto et al. (2010) indicates that the variance risk premium is able to anticipate different kinds of risk embedded in traditional state variables, such as the stock market risk, risk of default, illiquidity risk or consumption and employment growth risk. On the other hand, previous empirical literature about the ICAPM shows that innovations to state variables that forecast future investment opportunities seem to be priced by investors.6 It may therefore be the case that the ICAPM holds as a two factor model with the excess return of the variance swap contract as the hedging factor. Bollerslev and Todorov (2010) show that, even though the equity market risk premium and the variance risk premium share similarities in the general dynamic dependencies in jump risk premia, they maintain important differences in the way how they capture the compensations for rare events (tail events).7 Their results imply that any satisfactory model explaining the cross-sectional variation of expected returns should be able to generate a large and time-varying compensation for fears of economic recessions. This is precisely the role that the variance risk premium may be playing in the ICAPM framework.
It is well known that, assuming no arbitrage opportunities, a positive SDF (mt) exists such that,
where Rj,t+1e is the excess return on asset j from t to t+1. The alternative asset pricing models are generated by specifying different SDFs; that is, assuming different preferences for investors or different stochastic processes for asset prices. For example, under the ICAPM, the SDF contains, in addition to the aggregate wealth return, variables that capture time variation in future investment opportunities. Although the model is generally accepted because evidence shows that state variables other than the market index are important for pricing stock returns, the debate about which state variables must enter in the SDF remains open. Therefore, a natural question to ask is whether the information embedded in fluctuations in the variance risk premium may act as a sufficient statistic summarizing relevant information for asset valuation.
To explore this possibility, we use five time horizons corresponding to the five maturities of the swap contracts and data sampled at monthly frequency, to estimate the following ICAPM specification
where RW,t+τ is the gross cumulative return on wealth between t and t+τ, VRPtt+τ is the variance risk premium, i.e., the log-difference between the variance swap rate at month t with maturity on t+τ and the realized variance of the market index between t and t+τ, as defined by expression (5), Rj,t+τe is the excess cumulative return between t and t+τ on asset j, and τ=1, 2, 3, 6 and 12 months.
This SDF specification is consistent with Brennan et al. (2004), and it ensures a positive SDF. These authors argue that if the interest rate and the maximal Sharpe ratio follow a joint Markov process, the investment opportunity set is fully described by their joint dynamics. Accordingly, they propose a three-factor intertemporal model in which the SDF is the product of an exponential function of the innovations of these two variables and a power function of the aggregate wealth return.8
The basic idea behind Eq. (7) relies on focusing on the two key risk premia in financial markets: (i) the equity risk premium for holding the market portfolio, and (ii) the variance risk premium for holding the variance of the market portfolio. It is clear that both risk premia should be correlated. Bollerslev and Todorov (2010) show that roughly 60% of the equity risk premium is due to fears of rare events, while half of the variance risk premium is also due to investor fears. Then, in the empirical estimation of Eq. (7), rather than using directly the variance risk premium, it may be advisable to employ the residuals of a linear projection of the variance risk premium on the market excess portfolio return. Our aim is therefore to test whether the variance risk premium has incremental explanatory power over and above the market portfolio return within an ICAPM framework.
5Asset pricing model performance5.1The non-linear version of the two-factor ICAPM
Panel A in Table 2 reports estimates of the coefficients of the iso-elastic SDF, obtained by applying first-stage GMM to Euler Eq. (7), which amounts to minimizing the Euclidean norm of the average vector of pricing errors.9 The test assets are the 25 Fama–French portfolios and 17 industry portfolios. Below each estimate, in parentheses, we report the standard errors that are computed taking into account the fact that pricing errors have different variances and nontrivial covariances. The J-test statistic for overidentifying restrictions, given by T times the sum of the squared pricing errors, T(g′g), is reported in the fourth column, with its p-value in parenthesis. The last column of the table (MAPE) is the mean absolute pricing error across portfolios. We estimate model (7) twice, with and without the exponential factor for the variance risk premium, and for the five time horizons available in our database. The sample frequency is always monthly, from January 2006 to January 2007, which permits the comparison between results across the different horizons and panels of Table 2.
GMM estimation. 25 size/book-to-market portfolios and 17 industry portfolios. Monthly data, January 1996 to January 2007.
Horizon Panel A: first step Panel B: Hansen–Jagannathan distance
γ c1 T(g′g) MAPE γ c1 TDist2 MAPE
1 month 3.57 (2.11) 0.0992 (0.092) 0.3425 2.07 (1.97) 64.895 (0.010) 0.4588
2.54 (2.15) 0.90 (0.65) 0.0758 (0.286) 0.2881 1.95 (1.98) 0.29 (0.43) 63.689 (0.018) 0.4389
2 months 5.78 (2.95) 0.1024 (0.008) 0.3480 3.02 (2.74) 92.063 (0) 0.4609
4.10 (2.97) 1.12 (0.67) 0.0893 (0.041) 0.3298 2.93 (2.74) 0.11 (0.44) 91.866 (0) 0.4595
3 months 8.37 (3.76) 0.1038 (0.000) 0.3514 4.27 (3.42) 105.805 (0) 0.4542
6.48 (3.87) 1.08 (0.84) 0.0948 (0.001) 0.3406 4.30 (3.41) −0.03 (0.39) 105.790 (0) 0.4542
6 months 16.76 (5.68) 0.1202 (0) 0.3903 8.19 (5.16) 118.208 (0) 0.4702
12.22 (5.63) 1.24 (0.54) 0.0960 (0) 0.3292 8.19 (5.13) 0.00 (0.31) 118.208 (0) 0.4702
12 months 25.31 (7.00) 0.1340 (0) 0.4261 12.53 (6.60) 121.344 (0) 0.4732
20.08 (6.92) 1.21 (0.41) 0.1048 (0) 0.3569 12.57 (6.59) −0.02 (0.26) 121.336 (0) 0.4745
We estimate the standard version and an intertemporal version of the CAPM using the variance risk premium as the hedging factor in the intertemporal specification. The vector of moment conditions is E[((RW,t+τ)−γ exp{c1VRPtt+τ})Rj,t+τe|It+τ−1]=0, where RW is the gross return on wealth, γ is the relative risk aversion coefficient, Rje is the excess return on portfolio j and VRP represents the variance risk premium, computed as the log difference between the realized variance at the end of the swap contract (t+τ) and the variance swap rate at the beginning of the contract (t). We use a linear projection to compute the component of the variance risk premium that is orthogonal to the market return. The estimation is made for different investment horizons (τ), from 1- to 12-months, using always monthly data. Results reported on Panel A refer to the first step GMM estimation while the estimates shown in Panel B have been obtained using the inverse of covariance matrix of the portfolio excess returns as weighting matrix. Columns 2, 3, 6, and 7 contain the estimated coefficients. Associated standard errors are shown below, in brackets. Column 4 provides the value of T times the sum of squared pricing errors. The p-value for the test of overidentifying conditions is shown in brackets, while in Panel B the specification test of the model is performed using the Hansen–Jagannathan distance (column 9). Finally, MAPE indicates the mean absolute pricing error across portfolios, in percentage terms.
When we use the identity matrix as the weighting matrix in Panel A, the results for the one-month horizon show that the J-test fails to reject both pricing specifications. Estimates of risk aversion look reasonable, between 2.5 and 3.6, although estimated standard errors are relatively large. The coefficient of the variance risk premium (c1) is positive, as expected, but it is also estimated with low precision.10 Apart from that, both the J-statistic and the MAPE become lower when adding the variance risk premium to the market factor, reflecting an improvement in the fit of the model. Hence, the variance risk premium, as the second factor in an ICAPM framework, seems to contain some relevant information for explaining the cross-section of average returns.
For all other horizons, the two pricing specifications are rejected by the J-test at the standard 5% significance level, although the enlarged specification at the 2-month horizon presents a p-value of 0.04. The risk aversion estimate increases with the horizon. The estimated coefficient for the variance risk premium is always positive, with a relatively low standard error for maturities of six and twelve months. The monthly average pricing errors of the CAPM and the two-factor model are higher than those obtained for the shortest horizon. The reduction in MAPE by introducing the VRP as the second factor for asset pricing is negligible at 2- and 3-month horizons, but it is around 16% at the 1-month horizon, and 18% at the 6- and 12-month horizons.
Panel B of Table 2 displays estimation results using the inverse of the matrix of second order moments of excess returns as weighting matrix. Therefore, the pricing specification tests are now based on the traditional HJ-distance.11 Neither one of the two alternative pricing specifications are rejected at the one-month horizon at the 1% significance level. On the contrary, both specifications are rejected at conventional significance levels for all other horizons. As before, the relative risk aversion coefficient increases with the horizon, but it is uniformly lower than in Panel A. The coefficient of the variance risk premium is smaller than in Panel A, close to zero except at the one-month horizon, and it is estimated with large standard errors. As a consequence, the contribution of the variance risk premium is now much smaller than when estimating with the identity matrix. Asset prices in our sample are much better fitted under the first-step GMM estimates. In fact, MAPE is lower for all horizons by at least 25%, relative to estimates obtained under the HJ-metric.
As an alternative way to compare the two model specifications, we now compute the time series for the SDFs obtained with the parameters estimated with an identity weighting matrix. To capture the strong cross-sectional and time-series variation of expected returns, we need a SDF with enough volatility. Moreover, its volatility should be high at the beginning of recessions and low when expansion periods begin. Fig. 2 shows the time-series of estimated SDFs for the two asset pricing models, for the one- and six-month horizons. At the shortest maturity, the SDF for the one-factor model becomes more volatile and with higher peaks in declining stock market periods once we add the variance risk premium as the second factor. This contribution of the variance risk premium is consistent with the relatively best results provided by the variance risk premium-based ICAPM relative to the one factor model in Table 2. At the six-month horizon, adding the variance risk premium again increases the volatility of the estimated SDF, relative to the one-factor model. This extensive representation of the SDF over the whole sample seems quite revealing of the difference between the two specifications. Furthermore, the reduction in MAPE indicates that the increased volatility in SDF actually helps pricing the portfolios in our sample.
Time series of estimated stochastic discount factors from GMM parameter estimates obtained using the identity matrix as weighting matrix. January 1996 to January 2007.
(0.46MB).
Independently of the non-concluding global evaluation of the model through the J-test, it is worthwhile to examine the model ability to explain portfolio prices in detail. We now describe which specific portfolios the model is more able to price correctly. Fig. 3 shows the average over time of the absolute pricing errors (APE) for each of the 42 original portfolios at the one- and six-month horizons, under the CAPM as well as under the ICAPM specification that incorporates the variance risk premium. When we add the variance risk premium to the one-factor model, the APE is reduced for most of the 42 portfolios considered. More specifically, the two-factor model reduces the APE for three out of the five extreme growth portfolios, FF31, FF41, and FF51 at both horizons. Interestingly, this is not the case for FF11, the portfolio of growth and small assets, whose performance shows a higher APE, or for the FF21 portfolio, whose pricing errors are essentially equal under the two specifications. It is also important to point out that the variance risk premium consistently helps pricing the extreme value Fama–French portfolios (FF15, FF25, FF35, and FF45).12 Finally, at the one-month horizon, the ICAPM achieves a better fit for portfolios FF12 throughout F15 (smallest assets) than the one-factor model. This evidence therefore suggests that the VRP factor contributes to an improvement in pricing extreme value, extreme growth and small-firm portfolios. Regarding industry portfolios, it turns out that adding the variance risk premium leads to a smaller APE for Mines, Oil, Machinery and Utilities at both horizons. Uncovering the characteristics of these sectors that provide a better fit in prices remains an interesting issue for further research.
Fama–French and industry portfolio absolute pricing errors from GMM parameter estimates obtained using the identity matrix as weighting matrix. January 1996 to January 2007.
5.2The linear version of the two-factor ICAPM
Estimating a tight theoretical model with a relatively short time series data can easily lead to a significant loss of efficiency in estimation that may condition the results of the tests for model adequacy. Despite the fact that the VRP seems to contain significant incremental information when pricing the cross-section of our test portfolios, especially at the shortest horizon, it should be recognized that the estimated coefficient of the VRP at this horizon is obtained with a large standard error. This consideration moves us to analyze in this section the pricing results obtained for the 25 Fama–French and the 17 industry portfolios under the linear beta representation of Eq. (7) for the one-month horizon. We therefore perform the well known Fama and MacBeth (1973) two-pass cross sectional analysis in which the monthly cross-sectional regressions are given by:
The results are presented in Table 3. Columns 1–3 report the risk premia estimates, together with the Fama–MacBeth and Shanken's (1992) standard errors. Columns 4 and 5 provide two pseudo-R2 statistics based on the residual sum of squares of the cross-sectional regressions. The coefficient associated with the variance risk premium beta turns out not to be statistically different from zero.13 But as in the non-linear model, it looks as if this could be more a consequence of estimating the risk premium for the variance swap payoff with low precision, since the incorporation of the variance risk premium as hedging factor leads to an increase in the cross-sectional overall goodness of fit from 0.237 to 0.358, or from 0.334 to 0.462, depending upon the statistical measure we may employ. The better fit of the linear model after incorporating the variance risk premium can be clearly appreciated in the two graphs of Fig. 4, that contain fitted expected returns versus average realized returns for the 42 portfolios for the CAPM and the ICAPM. The largest revisions occur for the FF25 portfolio, and for the Steel and Mine industry portfolios. The variance risk premium also improves average pricing for the small-value Fama–French portfolios, FF14 and FF15, which is consistent with the evidence reported on the GMM estimates.
Estimates and standard errors of intercepts and risk premia for the traditional Fama–MacBeth two-pass cross-sectional regressions, monthly data, January 1996 to January 2007.
λˆ0 λˆm λˆvrp Statistic 1 Statistic 2
FM estimate 0.00445 0.00218 0.237 0.334
FM St. error (0.00475) (0.00647)
SH St. error [0.00475] [0.00682]
FM estimate 0.00444 0.00169 −0.08337 0.358 0.462
FM St. error (0.00467) (0.00628) (0.08017)
SH St. error [0.00467] [0.00673] [0.08670]
This table presents the Fama–MacBeth two-step cross-sectional estimation results for the one-factor (CAPM) and two-factor (ICAPM) capital asset pricing models using the variance risk premium as the hedging factor:
Rjte=λ0+λmβjmt+λvrpβjvrpt+ujt.
The test assets are the returns on the 25 FF portfolios plus 17 industry portfolios in excess of the T-bill rate. We report risk premium parameter estimates (λˆ), standard errors under the Fama–MacBeth (FM) methodology in parenthesis, and the Shanken (SH) errors-in-variable-robust standard errors in brackets. The overall goodness of model fit is measured by the two following statistics:
Statistic 1:∑t=1T(TSSt−RSSt)∑t=1TTSSt;Statistic 2:1T∑t=1T1−RSStTSSt.
TSS and RSS denote the Total Sum of Squares and the Residual Sum of Squares, respectively.
Fitted expected returns vs. average realized returns. January 1996 to January 2007. This figure shows realized returns on the horizontal axis and fitted expected returns on the vertical axis for 25 size and book-to-market sorted portfolios and 17 industry portfolios. For each portfolio, the realized average return is the time-series average of the portfolio return, while the fitted expected return is the fitted value for the expected return from the corresponding model.
5.3The linear version of the two-factor ICAPM with two regimes based on a market return threshold
As suggested by our proposed SDF, stock returns should react very differently to the variance risk premium depending upon the state of the economy. In fact, as we already pointed out, the variance risk premium has very distinct compensation behavior for negative tail events. The previous non-significant cross-sectional results ignore the possibility of different conditional sensitivities of stock returns to the variance swap payoffs on "bad" versus "good" scenarios. We now want to analyze whether the actual information content of the variance risk premium occurs mainly during recessions.
In order to investigate this issue, we allow for market and variance risk premium betas to change over time as a function of the market state. We define factor regression regimes as a function of a given level of market returns, and estimate such threshold simultaneously with the betas for the market and the variance risk premium in each regime. In each regime we use the pooled data for the 42 portfolios for the corresponding periods. This is a Threshold Regression Model, which we estimate under the assumption of a Normal error term. The maximum likelihood estimate is the threshold level for which the least squares estimates of the regressions for the good and bad regimes lead to the lowest aggregate residual sum of squares:
where u is the market return threshold, and βm1, βvrp1, and βm2, βvrp2 are the market and variance risk premium betas for the regimes above and below the threshold, respectively.
The maximum likelihood estimate of the market return threshold is −7.20%. This is an extreme return that splits the sample into "good/regular" regime for the 95% of the sample, and a "very low/very bad" regime that includes 5% of the sample. Given this partition, the results for the two-regime betas are reported in Table 4. The difference on the overall variance risk premium betas between both regimes are striking. The variance risk premium beta is highly significant and equal to −0.067. Since the variance risk premium is negative for most periods, long positions on variance swaps have positive payoffs only in those states in which the realized volatility is high enough to compensate the fears embedded in the risk neutral expectation of volatility. Moreover, it is also well known that volatility increases in periods of extremely low returns. This explains the large negative and highly significant variance risk premium beta in bad states. On the other hand, the variance risk premium beta for periods with positive or relatively small negative returns becomes practically zero. Even more illustrative is the evidence contained in Fig. 5 in which we present the variance risk premium betas for both regimes for each portfolio separately. For most portfolios, the variance risk premium betas become negative and large in bad states. However, they are practically zero in good and regular states. Interestingly, the extreme small-growth portfolios and construction have positive variance risk premium betas in bad states. This implies that the variance swap does not play its hedging role relative to these portfolios. It should be recalled that our sample period coincides with the boom in the real estate industry.
Estimates and standard errors of alphas and betas from a pooled OLS regression with two regimes based on a market return threshold, January 1996 to January 2007.
Extremely low market return Regular market return
αˆ βˆm βˆvrp αˆ βˆm βˆvrp
Estimates 0.0093 1.0523 −0.0677 0.0022 0.8814 −0.0007
St. errors 0.0161 0.1467 0.0073 0.0011 0.0162 0.0015
This table reports the overall market beta and the variance risk premium beta from a pooled OLS time-series regression under a two-regime specification defined by a given market return. The market return threshold is simultaneously estimated with the two regressions. The test assets are the 25 FF portfolios and 17 industry portfolios, with the returns in excess of the T-bill rate. The maximum likelihood estimate is the threshold level for which the least square estimates of the regressions for the good and bad regimes lead to the lowest aggregate residual sum of squares:
Min{u,α,βm,βvrp}∑j=142∑t=1T1(u)(Rjte−α1(u)−βm1(u)Rmte−βvrp1(u)VRPtt+1)2+∑j=142∑t=1T2(u)(Rjte−α2(u)−βm2(u)Rmte−βvrp2(u)VRPtt+1)2
where u is the market return threshold, and βm1, βvrp1, and βm2, βvrp2 are the market and the variance risk premium betas for the regime with the market return above and below the threshold, respectively.
Variance risk premium betas across 25 Fama–French and 17 industry portfolios from a pooled OLS regression with two regimes based on a market return threshold. January 1996 to January 2007.
Given this evidence, we now run the Fama–MacBeth two-pass cross sectional regressions using for the market return and the variance risk premium the appropriate betas for the market state in each period:
where βjmt+/− and βjvrpt+/− denote the betas in the appropriate "good" or "bad" states. As before, Fig. 6 shows a clear improvement in fit when we include the two-regime variance risk premium betas relative to the CAPM. More precisely, Table 5 reports the risk premia coefficients from the cross-sectional regression of expression (10). The compensation for the variance risk premium beta becomes much more negative than in Table 3 moving from −0.083 to −0.265 with a clear increase in precision. Moreover, the two measures of goodness of fit employed in the paper increase from 0.188 to 0.274 and from 0.278 to 0.412 when we add to the cross-sectional regression the variance risk premium betas conditional on the market threshold.
Fitted expected returns vs. average realized returns from cross-sectional regressions under two-regime betas based on a market return threshold. January 1996 to January 2007. This figure shows realized returns on the horizontal axis and fitted expected returns on the vertical axis for 25 size and book-to-market sorted portfolios and 17 industry portfolios. For each portfolio, the realized average return is the time-series average of the portfolio return, while the fitted expected return is the fitted value for the expected return from the corresponding model.
Estimates and standard errors of intercepts and risk premia for the market threshold two-regimes Fama–MacBeth two-pass cross-sectional regressions, January 1996 to January 2007.
Rjte=λ0+λmβjmt+/−+λvrpβjvrpt+/−+ujt,
where βjmt+/− and βjvrpt+/− denote the betas in the corresponding states.
The test assets are the 25 FF portfolios and 17 industry portfolios, with returns in excess of the T-bill rate. We report risk premia parameter estimates (λˆ), standard errors under the Fama–MacBeth (FM) methodology in parenthesis, and the Shanken (SH) errors-in-variable-robust standard errors in brackets. The overall goodness of model fit is measured by two statistics:
To summarize our findings, Fig. 7 contains the monthly differences between the adjusted R2 statistic from each Fama–MacBeth cross-sectional regressions with and without the variance risk beta as an explanatory variable. Independently of using a market threshold in the estimation of betas, we find an increase in the explanatory power of the two-factor ICAPM relative to the one-factor CAPM model in all months of our sample. We may therefore conclude that the variance risk premium contains incremental information for asset pricing over and above the market portfolio.
Differences between adjusted R2 from monthly cross-sectional regressions under rolling OLS and two-regime beta estimates. January 1996 to January 2007.
6Conclusions
Recent available evidence show that the excess return on the variance swap contract hedges equity market risks, interest rate and business cycle risks. This evidence motivates the consideration of a two-factor ICAPM with the variance risk premium playing the role of a hedging portfolio. The question is whether the variance risk premium acts as a sufficient statistic summarizing the information contained in a variety of risk indicators that might be potentially relevant for asset valuation.
Specification tests based on GMM estimates using the identity matrix as metric do not reject the model at one- and two-month horizons at conventional significance level, although the opposite is obtained at the remaining horizons. The time-varying behavior of the estimated SDF under the two-factor model presents a relatively more volatile behavior than the simple one-factor model, and pricing errors on individual portfolios are generally lower when the variance risk premium is incorporated into the model. More specifically, and relative to the one-factor model, the variance risk premium seems to explain small and value stocks, as well as Mines, Steel, Oil, Machinery, and Utilities. This is reflected in a reduction in global measures of fit between 16 and 18% for 1-, 6- and 12-month horizons, even though the reduced size of pricing errors does not seem to be small enough to not reject the model at these longer horizons according to the standard test for over-identification constraints. The linearized version of the model supports these results by providing a clearly improved fit to observed returns for the 25 Fama–French portfolios and the 17 industry portfolios, always at the one-month horizon.
Although it is standard practice, considering time-invariant parameter values for the full sample period might be too strong an assumption to make the model compatible with the data. When we include a recession threshold in the estimation of the variance risk premium betas in the linearized version of the model, we obtain that the compensation to the variance risk premium beta in asset pricing is limited to recession periods. Hence, the role of the variance risk premium as a pricing factor seems to concentrate on periods of significant market downturns. The cross-sectional overall measures of fit for the two-factor ICAPM relative to the one-factor CAPM specification increase independently of using conditional bad state betas or constant betas. The increase in monthly adjusted R2 in the cross sectional regression from adding the variance risk premium beta is often sizeable. Overall, our results suggest that the premium in variance swaps contains relevant information for asset pricing, possibly because summarizes information contained in a variety of macroeconomic and financial risk indicators. Analyzing the distinct gains in fitting prices of the different portfolios remains as an interesting issue for further research.
The authors acknowledge financial support from Ministerio de Ciencia e Innovación through grants ECO2008-02599/ECON (Belén Nieto), ECO2008-03058/ECON (Gonzalo Rubio), and SEJ2006-14354 (Alfonso Novales). Alfonso Novales and Gonzalo Rubio also acknowledge financial support from Generalitat Valenciana grant PROMETEO/2008/106 and from Programa Copernicus CEU-UCH/Banco de Santander. The authors thank seminar participants at the 33rd Meeting of the European Accounting Association, the 8th INFINITI Conference on International Finance, and XVII Foro de Finanzas, IESE, and especially Enrique Sentana, for constructive comments.
Let Rte be the N×1 vector of excess return of the N assets at time t and mt(θ) be one out of the two specifications of the SDFs described in Section 4, where θ is the vector of the preference parameters for each particular specification. We define an N×1 vector of moment conditions containing the pricing errors generated by the model at time t,
and the corresponding sample averages,
Then GMM estimator minimizes the following quadratic form
where WT is a weighting N×N matrix.
For estimation, we could use the optimal weighting matrix in Hansen (1982), ST−1, where
Instead of that, we employ a pre-specified weighting matrix which is either the identity matrix (for the results of Panel A of Table 2) or the matrix of the second moments of excess returns (for the results of Panel B of Table 2).
The asymptotic variance–covariance matrix of the GMM estimates is given by
where DT is a matrix of partial derivatives defined by
Then, the standard errors of the estimated coefficients θˆ are computed from the estimated variance:
where DˆT and SˆT are obtained replacing θ by θˆ in DT and ST, respectively.
The evaluation of the model performance is carried out by testing the null hypothesis:
with Dist=g(θ)′Wg(θ) where, as mentioned above, the weighting matrix, W, is either the identity matrix or the second moment matrix of excess returns.
If the weighting matrix is optimal, T[Dist(θˆ)]2 is asymptotically distributed as a Chi-square with N−P−1 degrees of freedom, where P is the number of parameters. However, for any other weighting matrix (including the identity matrix), the distribution of the test statistic is unknown. Jagannathan and Wang (1996) show that, in this case, T[Dist(θˆ)]2 is asymptotically distributed as a weighted sum of N−P−1 independent Chi-square random variables with one degree of freedom. That is
where λi, for i=1, 2,…,N−P−1, are the positive eigenvalues of the following matrix:
in which X1/2 means the upper-triangular matrix from the Choleski decomposition of X, and IN is a N-dimensional identity matrix.
Therefore, in order to test the different models we estimate, we proceed in the following way. First, we estimate the matrix A by
and compute its nonzero N−P−1 eigenvalues. Second, we generate {vhi}, h=1, 2,…,100, i=1, 2,…,N+1−P, independent random draws from a χ2(1) distribution. For each h, uh=∑i=1N−P−1λivhi is computed. Then we compute the number of cases for which uh>T[Dist(θˆ)]2. Let p denote the percentage of this number. We repeat this procedure 1000 times. Finally, the p-value for the specification test of the model is the average of the p values for the 1000 replications.
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L. Hansen, R. Jagannathan.
Assessing specification errors in stochastic discount factors models.
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[Hansen, 1982]
L. Hansen.
Large sample properties of Generalized Method of Moments Estimators.
Econometrica, 50 (1982), pp. 1029-1054
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Nieto, B., Novales, A., Rubio, G., 2010. Why do variance swaps exist? Working Paper, University CEU Cardenal Herrera.
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EU tobacco products directive would have 'serious consequences for jobs, the economy and tax revenues'
The review of the EU's tobacco products directive must strike a balance between economy, health and jobs, writes José Isaías Rodríguez García-Caro.
By José Isaías Rodríguez García-Caro
The tobacco sector, employing almost 1.5 million people in the EU, promotes rural and economic development and is one of the few major export sectors to still maintain a positive balance, both at European level and in many member states.
The changes proposed would have serious consequences for jobs, the economy and tax revenues, thereby breaching other fundamental EU objectives, such as full employment and a return to growth.
"The proposal to include health warnings covering 75 per cent of the front and rear of the cigarette pack, together with the new text covering 50 per cent... is not... based on scientific evidence"
It is of course crucial that health takes priority over all economic considerations, though scepticism remains on how effectively the proposed measures would help the gradual process of giving up smoking.
The proposal to include health warnings covering 75 per cent of the front and rear of the cigarette pack, together with the new text covering 50 per cent of the sides, is not, however, based on scientific evidence.
This change in packaging may threaten jobs in the packaging industry, which remains a sector of great economic importance in several European countries, and would undermine the legitimate intellectual and industrial rights of manufacturers to use their registered trademarks.
Moreover, allowing differentiation only on the basis of price would reduce the attractiveness of producing high quality tobacco in the EU, since all products would end up almost the same.
Standardising format and taste could lead to an increase in tobacco smuggling, satisfying public demand through unregulated channels. Member state tax authorities already lose €10bn in tobacco tax receipts every year.
In addition, the absence of any quality control of such products would severely compromise consumer safety.
20 Dec Health
The revolution in HIV demands an EU response, explains Frédérique Ries
by Frédérique Ries MEP
Read the most recent articles written by José Isaías Rodríguez García-Caro - EU must recognise dangers of 'overregulation' on tobacco
Strengthening responsible use of antibiotics in animal health
01 Dec by Roxane Feller
Why the world needs an International Pandemic Agreement
26 Nov by Anna Maria Zakowicz
A harmonised EU approach to the off-label use of medicines?
19 Nov by MEP Cyrus Engerer & Frédéric Destrebecq
The obscure UN conflab that seeks to cut off the world from vaping and harm reduction
12 Nov by Yaël Ossowski
AHF Europe's Zoya Shabarova reflects on the lessons learned fighting the AIDS/HIV pandemic and how these can be applied to a future international pandemic agreement
by Zoya Shabarova
13 Dec Tech & Research
This week in the European Parliament
The last European Parliament plenary session of the year has traditionally often focused on Human Rights, as Parliament's spokesperson Jaume Duch reminded the press at Friday's pre-session briefing
European Parliament's Special Cancer Committee adopts final report
BECA Committee MEPs look to strengthen EU's role in fighting cancer and drive move towards a European Health Union
MEPs hear from cities and regions on how well COVID recovery instruments are being utilised
Mayors praise speed and flexibility of handling by Member States, though France criticised for delays in making funding available

redpajama_set_name: RedPajamaCommonCrawl


Many of us are used to suffering through the seasons in our homes – bundling up in blankets and slippers when it's freezing outside, and running the fan and sleeping with open windows at night during the hot summers.
We chalk it up to something we just need to deal with as part of the changing seasons, but the reality is – we don't.
More often than not, the problem isn't the outdoor temperatures at all, but the way our homes are working (or in these cases – not working) for us.
Adam Duke, 24, and Jacob Smith, 23, are the founders of Go Green Energy Consulting (www.gogreenec.com) – a company dedicated to improving the comfort factor in clients' homes by scientifically pinpointing the ways homes are losing energy, and developing smart, customized solutions using sustainable and locally made materials.
According to Duke, homeowners often waste thousands of dollars trying to fix their heating and cooling problems by replacing their windows, bulking up their insulation or even purchasing larger furnaces, but often a unique combination of issues are the culprit – each home requiring a comprehensive assessment and not just the quick fixes that contractors may make.
The team at Go Green conducts home audits that determine why clients' homes are not comfortable (extremely cold rooms, incredibly hot second stories, drafty areas, etc.) and, in the process, why their utility bills are so high. They utilize innovative technology, including infra-red cameras, specialized blowers and smoke sticks to assess the home, and leave no nook and cranny un-inspected. After the audit, a Go Green consultant sits down with the homeowner to explain the findings, and offer customized solutions.
A by-product of Go Green's work is that less fossil fuel needs to be burned while heating or cooling a home, which helps protects the environment. Homeowners have found that they save as much as $1200 a year on their energy bills, and can feel good about using less energy and reduce their carbon footprint.
Additionally, many energy companies are currently offering rebates on audits.


Drillers throughout the years have been frustrated with the inability of tricone roller bits to efficiently handle geothermal drilling in the harder rock formations. Today, with advances in drilling technology and methodology, drillers are turning to DTH hammers and bits in order to complete their challenging projects. Many drillers have found that increased performance and total lower cost of drilling provided by DTH products have been instrumental in their continued success.
One such drilling company that has realized the significant benefits of DTH drilling is Evans Energy Development. Evans is a drilling outfit 21 years of experience in the energy industry and has vast experience with drilling in all types of environments. Having to deal with diverse conditions, the company is always looking for products and methods that can help them complete their projects more quickly and easily. Recently, Evans utilized Numa's new Patriot® 60 down hole hammer on a geothermal project in eastern Kansas. The Patriot® 60 hammer allowed them to complete the job in less time and at a much lower cost than if they had used a tricone method.
Evans was supplied with their Numa Patriot™ 60 hammer by Numa distributor NDS Drilling Supply located in Elko, Minnesota. Since the drill crew was new to the DTH drilling method, Numa's regional manager, Kathy Wagoner, went to the job site to provide training. Kathy's presence allowed the drillers to ask questions and learn how to maximize the efficiencies of the DTH hammer and bits. The training proved to be invaluable with the tremendous performance Evans was able to yield from the new products.
The project involved the drilling of geothermal boreholes to be used for a newly built Church ministry retreat camp for Stonecroft Ministries. The vertical heat loop will supply heating and hot water for the camp, which includes a 10,000 sq ft (112 sq m) office and a two-story dorm with 41 apartments totaling 60,000 sq ft (672 sq m). Forty (40) holes were required for this project in ground conditions that consisted of clay, limestone and shale. Holes were drilled to a depth of 350 feet (107 m) by a 2001 Gefco Speedstar 30K rig with 1000 CFM / 350 PSI (472 l/24 Bar) onboard compressor.
Geothermal is an emerging energy source that provides advanced, energy-efficient heating and cooling systems that can provide savings up to 60% over conventional heating and cooling systems. It is environmentally friendly as it generates zero hazardous emissions. This helps to minimize many common problems such as acid rain, air pollution and the destruction of the ozone layer that are typically found in fossil fuel systems. The US Environmental Protection Agency (EPA) has endorsed this system as a viable alternative for heating and cooling homes and businesses. There is even legislation being reviewed that, if passed, will require geothermal heat loops in all government financed building projects.
There are many different types of geothermal energy systems available today and one of the most widely used is the closed loop system. The closed loop system harnesses both the energy sources inside the earth and solar heat radiating down from the sun. These forces combine to provide a fairly constant temperature of 50° F (10° C) in the outer layer of the earth that is used in these revolutionary energy systems. A geothermal heat loop system consists of series of pipes, a heat exchanger and ductwork that goes into the structure being heated and cooled. During the winter months, heat from the earth is collected in the exchanger and distributed into the structure. In the summer, the heat is absorbed from the air and the water source carries the heat back to the earth in order to cool. The system is also very beneficial for heating water.
The Numa Patriot® 60 hammer has a wealth of features including an impressive penetration rate which easily outperforms competitor hammers. The ultimate goal of the hammer is to provide the drilling industry with a complete combination of speed and long life. A compact design provides for the transfer of drilling energy to the bit quickly and efficiently. Due to this innovation, drillers realize faster drilling speeds and the completion of more holes in less time.
The Patriot® 60, with only 8 major parts, is a simplified geothermal drilling hammer design that was accomplished by eliminating several internal components. Less overall parts makes the Patriot® 60 easier to maintain than competitor hammers, which means more time can be spent drilling. Numa engineers also designed the hammer to attach the feed tube directly to the backhead of the hammer to provide outstanding alignment of all hammer parts. This enhancement results in longer hammer life and improved overall hammer performance.
Another key feature of the Patriot® 60 is the ability to handle difficult back pressure drilling conditions. When faced with high heads of water, The Patriot® will continue to drill where other hammers will quit. It is not uncommon for the Patriot® to continue drilling flawlessly against 100 gallons (380 l) or more of water in the hole.
From the outset of this project, the increase in drilling speed over previously used methods was obvious as the crew had to alter their typical procedures. The crew now spent much of their time changing connections due to the speed of the Patriot® hammer. The Patriot® 60 drilled at 130 to 140 feet (40 – 43 m) per hour and was able to complete an average of 1000 feet (305 m) per day which was the equivalent of 2 – 3 holes. This virtually tripled their production previously realized with the tricone method where it would take up to three days to complete the same amount of holes now done in one.
The Patriot® DTH method definitely has made an impression on Evans Energy in the manner of improved performance and saved cost. The remarkable increase in production has allowed the company to complete more holes in less time which resulted in a much lower cost per foot. Furthermore, the DTH method has reduced equipment requirements. On this project alone, Evans was able to reduce cost by 33% by using the Numa DTH method. So no matter what your drilling need, you can count on the Patriot's overall combination of speed and performance to provide you with successful results. Contact Numa today at 800-356-NUMA or 860-923-9551 to get a head start on drilling with the best hammer in the business – The Numa Patriot® 60.


Looking for Pizza Delivery in Calgary Manchester Industrial? Not everybody knows or has the time to prepare tasty food.
Yes, we're located near Calgary Manchester Industrial and are delighted to take your online order.


text:
Paninsky District  () is an administrative and municipal district (raion), one of the thirty-two in Voronezh Oblast, Russia. It is located in the north of the oblast. The area of the district is . Its administrative center is the urban locality (a work settlement) of Panino. Population:  The population of Panino accounts for 24.7% of the district's total population.

References

Notes

Sources

Districts of Voronezh Oblast

redpajama_set_name: RedPajamaWikipedia


Unity is a center of light for the world. We are dedicated to letting this light shine so brightly that people become more aware of their spiritual nature and express it in their daily lives, including our employees.
Work and life balance is important to us—most departments have four-day workweeks. We like to have fun. We do this through our employee appreciation events, holiday gatherings, sports team days, fun contests, and much more. Unity also supports the local community. We take part in parades and charitable-giving opportunities.


Description: The J24 is a four-person keelboat, meaning it has a fixed keel.
David lives in Toronto, and is therefore very excited to be competing in front of a home crowd at the Toronto 2015 Pan Am Games. He and his J24 crew sailed to first overall in the Pan Am Trials, giving them a hard-earned Team Canada berth. In 1989, David received an HBS in the Ivey School of Business at the University of Western Ontario. He now works in commercial real estate, and is the proud father of three children. David still has the ability to squeeze as much sailing as he can into his evenings and weekends.
1. If you could sail with anyone, dead or alive, who would it be?
Paul Elvstrom "You haven't won the race if in winning the race you have lost the respect of your competitors."
2. What does the average day in the life of David include?
Early workout, commercial real estate during the week days, sailing in the evenings and weekends, snowboarding in the winter. Engaged on a daily basis with Habitat for Humanity of Greater Toronto. Enjoy evenings with Christianne and our 3 boys 7, 12, 14.
3. What has been your greatest challenge so far in life, and how did you overcome it?
Starting my own business in 2001. Overcame the challenge with hard work, trusted relationships and always being a man of character.
4. If you could have one superpower, what would it be?
Flying. From a bird's eye view I could see where all the puffs are on the water, could travel anywhere on a whim.
5. What would be your ultimate achievement in life, and/or in sport?
My relationship with my youngest son, Jack. I walk him to school every day and pick him up most days; I take him to hockey and coach his soccer team. I am a proud Dad.
6. Do you have any routines and/or superstitions that are considered before you race?
7. What do you believe is the key to success?
Hard work, trusted relationships, integrity and understanding the importance of your character.
8. What is the strangest thing you have seen happen during a race?
We were over early at the start of a race in a 50 boat fleet, the wind shifted 35 degrees to the right and we banged the right corner of the second upwind leg and managed to pass all 50 boats by the finish line.
9. Who is your role model, and/or where do you draw your inspiration from?
Gerald Knowlton. He inspired me to get into commericial real estate out of business school in 1989. He encouraged me to travel, have a balanced life and work smart at a young age. In June of this year I am dedicating a Habitat for Humanity home in his name here in Toronto.


It is more than a decade since the Investments and Securities Act[i] was enacted but the controversy surrounding the parallel jurisdiction of the High Court of a State and the Investments and Securities Tribunal (IST) in respect of civil matters arising from the operation and application of the ISA appears far from settled. As a result, many legal practitioners, renowned academics and even the courts of law have expressed different opinions on this issue.
Perhaps this conundrum stems from the fact that jurisdiction is the life wire of a court and the blood that gives life to any action before a court; and accordingly no court can adjudicate over a matter when it does not have jurisdiction.[ii] More so, the relevance of the State High Court and the IST to our legal system cannot be overstated, as such necessitating a clear-cut distinction between the jurisdiction and roles of both courts.
Irrespective of the trifling dissimilarities with regards to the qualification of the jurisdiction of the High Court of a State by the superior courts, it is however crystal clear that the Court has astronomical jurisdiction birthed from the CFRN, 1999 with respect to civil and criminal proceedings in Nigeria.
There is established a body to be known as the Investment and Securities Tribunal to exercise the jurisdiction, powers and authority conferred on it by or under this Act.
The Tribunal shall have exclusive jurisdiction on matters specified in this Act.
The clear interpretation of the act of the National Assembly in 1999 when it created the Investments and Securities Tribunal as a specialist Court simply means that the exclusive jurisdiction of the Federal High Court would no longer extend to matters affecting the operations of the capitals and securities market, but remain limited to matters that may arise from the provisions of BOFIA and CAMA and I so hold.
The aforestated dictum of the Court seems to suggest that because the National Assembly via an Act created a specialist court with exclusive jurisdiction, then all other courts of law including those seemingly given unlimited powers by the CFRN, 1999 in respect of civil and criminal matters will have their jurisdiction adjusted to conform to the ISA.
The connotations of the decision in the Weathzone case to the extent that the IST's jurisdiction overrides the jurisdiction of a court created by the CFRN, 1999 in the event that the express jurisdiction of the latter as provided for in the Constitution conflicts with the jurisdiction of the IST as set down in the ISA cannot be correct with due respect.
If any other law is inconsistent with the provisions of the constitution, this constitution shall prevail, and that other law shall to the extent of the inconsistency be void.
Therefore, nothing that exists outside the CFRN, 1999 can purport to divest the State High Court of its jurisdiction as expressly provide for in the Constitution.
The jurisdiction of the High Court of the Federal Capital Territory Abuja is set out in section 257(1) of the Constitution of the Federal Republic of Nigeria, 1999 (as amended). It provides as follow. "Subject to the provision of section 251 and any other provision of this Constitution and in addition to such other jurisdiction as may be conferred upon it by law, the High Court of the Federal Capital Territory, Abuja shall have jurisdiction to hear and determine civil proceedings in which the existence or extent of a legal right, power, duty, liability, privilege, interest, obligation or claim is in issue…" Thus the High Court of the Federal Capita Territory, Abuja, is a court of unlimited jurisdiction subject to any limitation imposed upon it by section 251 of the Constitution or any other provision thereof… It cannot be taken away by section 284(1) of the Investments and Securities Act, 2007, which is inferior to the Constitution of Nigeria, 1999.
The State High Court equally has jurisdiction to entertain any dispute covered by or arising under the Investment and Securities Act including a dispute between a capital market operator and its client like the dispute in the present case, by virtue of the unlimited jurisdiction of the State High Court to hear and determine any civil or criminal proceeding vested on it by Section 236(1) of the 1979 Constitution of Nigeria, applicable when the cause of action arose and Section 272 of the 1999 Constitution of Nigeria, applicable when the suit was filed and up to date.
As it is, the State High Court and the Investment and Securities Tribunal have concurrent jurisdiction to entertain cases involving disputes covered by or arising from the Investment and Securities Act.
It is true that the IST has jurisdiction to entertain all civil matters that may arise from the operation and application of ISA but the preponderance of authorities suggest strongly that its jurisdiction, though labelled "exclusive" cannot in anyway divest the perceived unlimited jurisdiction of the High Court of a State to also entertain all matters that may arise from the application of the ISA.
Without any doubt, both the IST and the State High Courts have equal and concurrent jurisdiction with respect to the ISA and all the relevant portions of the ISA that exist to divest all courts of the jurisdiction to entertain matters that arise from the operation of the ISA cannot apply to the High Court of a State as the latter's jurisdiction is deeply rooted in the Constitution. It goes without saying that where there are conflicts between the provisions of the ISA and the Constitution, all those conflicts or inconsistencies must be resolved against the ISA.
[i] Investments and Securities Act, 2007 (Hereafter, ISA).
[ii] See Dangana v. Usman (2013) 6 NWLR (Pt. 1349) 50.
[iii] Cap. C23, Laws of the Federation of Nigeria, 2004 (Hereafter, CFRN, 1999).
[iv] See section 257(1) CFRN, 1999 (as amended) for the equivalent provision as it relates to the High Court of the Federal Capital Territory. See also Mailantarki V. Tongo & Ors (2017) LPELR-42467 (SC).
[v] (2008) 10 NWLR (Pt. 1095) 293.
[viii] (2008) 7 NWLR (Pt. 1086) 421.
[ix] (2008) All FWLR (Pt. 398) 235.
[x] See SEC v. Kasunmu (2009) 10 NWLR (Pt. 1150) 509.
[xi] See generally section 6(1)-(5) CFRN, 1999 (as amended).
[xiii] (2012) 10 NWLR (Pt. 1307) 115 @ 161.
[xiv] See generally, section 312 of the ISA, 2007.
[xv] (2009) 13 NWLR (Pt. 1157) 226.
[xvi] The decisions in Ngige & Anor v. INEC & Ors (2014) LPELR-25413 (CA); Obayuwana v. Governor, Bendel State & Anor (1982) LPELR-2160 (SC); N.U.E.E. v. B.P.E. (2010) All FWLR (Pt.525) 201; and National Union of Electricity Employees & Anor v. Bureau of Public Enterprises (2010) LPELR-1966 (SC) also epitomize this axiomatic principle of law.
[xvii] (2015) LPELR-24495 (CA) per Ekanem, J.C.A., (Pp.20-22, paras. G-A).
[xviii] (2015) LPELR-24486 (CA) per Agim J.C.A., (Pp. 25-33, paras.A-A).
[xix] Investments and Securities Act, No. 45, 1999. This Act was repealed by the ISA, 2007. See section 314(1) of the ISA, 2007.


Opioid use has been shown to contribute to depression as prolonged use can produce neurological changes as we established in an earlier blog about opioid use and brain damage. Most anti-depressants are called selective serotonin re-uptake inhibitors (SSRI's). SSRI's ease depression by increasing levels of serotonin in the brain. Serotonin is one of the chemical messengers (neurotransmitters) that carry signals between brain cells. SSRI's block the re absorption of serotonin in the brain, making more serotonin available.
Visit Dr. Browne at her clinic in Harmony, NC!
There is no question that anti-depressants can save lives of those who have suicidal tendency. However, it tends to be prescribed over long period's of time instead of an acute stop-gap for a crisis. In my opinion, those recovering from opioid dependency should not rely on mood altering substances as this is not a true recovery. Instead, look to natural modalities that will lead to wellness and balance. After all, recent studies have demonstrated that acupuncture can have a profound effect on depression and repair the brain. In this way, one can lead a full and abundant life coping with all of the natural up-and-downs that that come with our existence on Earth.


Will Interest Rates Or Home Prices Make A Difference?
One of our clients, a first time homebuyer, asked us the other day whether they should wait for home prices to drop more before buying a home. They were also concerned about interest rates rising and rightly so. Our answer to them was twofold (don't you just love literary elegance?) and we thought we would pass this on to you as well.
seeing for the last several months in Salt Lake. Now this means not only a higher payment on a loan, but can also mean that your buying power is diminished (you can't qualify for as much to purchase a home).
Although prices in Salt Lake City and the surrounding areas may continue to drop slightly during theremainder of the year, the consensus is that our market has basically bottomed out, especially in the first time home buyer price range of under $250,000. Our market has not suffered the free fall associated with California, Las Vegas, and Arizona, and so has stabilized more quickly.
With the incentives offered by the govt in the form of the $8000 first time homebuyers tax credit, the $6500 credit extended tax credit for existing homeowners, grant money, and Utah Housing financing buying a home in Salt Lake holds it's attraction. Now, this post was written back during the good old days when these were all in place, but since you missed 'em, we will just tell you that Mortgage Interest is Still Tax deductible, which can turn a 2,000 refund into a $4,000 refund with that deduction, which means you can adjust your take home pay to cover part of your payment. Whoo Hoo!
To illustrate how interest rates more so than a drop in price will affect you in buying a home, we turned to our trusty lender, Lance Sorenson, to provide some valuable information for you.
As you can see, interest rates will make more of a difference than a decline in price, so keep that in mind as you make your decision to buy a home.
It could save you lots of money (and I don't know about you, but I would rather have that extra 100 bucks in My pocket, not the banks).
If you have any questions, be sure to give us a call or shoot us an email!


text:
Regent's Park College is a small, dynamic community at the heart of the City and University of Oxford, specialising in the Arts and Humanities. Our award-winning tutors and pioneering academic minds make Regent's a fantastic place to study and live, where every student can thrive.
How to apply to study at Regent's Park College
Undergraduate Graduate Ministerial Formation Visiting Students
Our mission is to be an exceptional place of learning, where members of a diverse and inclusive community can achieve great things together.
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Regent's Park College welcomes its new Principal
The Fellows and Governing Body are delighted to we...
Congratulations to Andrzej Karpinski
Enormous congratulations to Andrzej Karpinski, a f...
Dr William H. Brackney
With sadness we announce the loss of long-time fri...
Oxford applicants – could Regent's Park College be the place for you?
Regent's Park College is committed to attracting...
We are very sad to announce that Emmanuelle, the College's much loved tortoise, has died
After struggling over the past year from multiple ...
Celebrating a fantastic set of results
Enormous congratulations to all of this year's f...
Giving thanks for the life of HM Queen Elizabeth II
The community of Regent's Park College, Oxford j...
Regent's staff and students win University awards
Award ceremonies are back in full swing at Oxford,...


text:
Cicutoxina é o principal componente do veneno colinérgico chamado cicuta. O elemento químico é sólido com a fórmula C17H22O2. A substância é encontrada em várias plantas, principalmente nas espécies apiáceas do gênero Cicuta. Essas plantas são tem como habitat terrenos pantanosos da América do Norte e Europa, todas contem cicutoxina. São facilmente confundidas com plantas com raízes comestíveis como a pastinaga, a cenoura selvagem e o ginseng.

Toxicocinética

Quando a cicutoxina é isolada forma um óleo amarelado. Na planta o composto é estável, mas quando exposto ao ar, luz ou calor torna-se castanho conforme a cicutoxina é desfeita. Pode ser absorvido pela pele, inalada ou ingerida.

Toxicodinâmica
Provoca morte diretamente do sistema nervoso central. É um antagonista potente e não competitivo dos receptores de ácido gama-aminobutírico A (GABAa). É capaz de bloquear os canais de potássio dos linfócitos T. Nos seres humanos, a cicutoxina produz sintomas de náusea, vômito e dor abdominal, tipicamente nos primeiros 15-60 minutos de ingestão. Em poucas horas (dose-dependente) causa tremores, convulsões, arritmia, hipertensão e insuficiência respiratória.  A Dose letal (LD50) é de 2.8 mg/kg.

Tratamento
Os tratamentos mais utilizados são a administração de carvão ativado em menos de uma hora depois da ingestão para reduzir a quantidade de veneno absorvido no sistema, manutenção das vias aéreas abertas para evitar asfixia, reidratação para prevenir a desidratação pelo vômito e administração de diazepam para prevenir convulsões.

História
Foi muito usada durante a história, desde tempos ancestrais, em assassinatos e suicídios. O caso mais famosos é o do filósofo Sócrates, acusado de corromper jovens com suas ideias revolucionarias.

Bibliografia

Ligações externas

Neurotoxinas
Alcinos
Alquenos
Álcoois
Moduladores alostéricos negativos ao receptor GABAA
Antimuscarínicos
Convulsivantes
Bloqueadores dos canais de potássio


Flutist Anthony Trionfo will be the sixth concert in Saint Vincent College's 46thConcert Series season at 7 p.m. Saturday, March 17, in the Robert S. Carey Student Center Performing Arts Center on the campus of Saint Vincent College. A free reception will follow the concert.
Praised for his "spellbinding" performances with "authoritative intellect" by the Santa Barbara Voice after his performance of the Jolivet Concerto with the Music Academy of the West Festival Orchestra, Trionfo will make his recital debuts this spring on the Young Concert Artists Series at the Kennedy Center as well as in New York City's Merkin Concert Hall, premiering a new work by YCA Composer-in-Residence Katherine Balch.
In the 2017-18 season he appears in recital and conducts educational and community outreach at Chamber on the Mountain, Iowa State University, Southern Adventist University, Saint Vincent College, the Levine School of Music, the Lied Center of Kansas and the Port Washington Library. He performs Bach's Brandenburg Concerto No. 5 with Vadim Gluzman and the ProMusica Chamber Orchestra, and appears with Jupiter Chamber Players. He has performed concertos with the Interlochen Symphony Orchestra, the Colburn Symphony Orchestra, Mr. Obama's "President's Own" Marine Band and the Las Vegas Philharmonic.
Recipient of the Jack Kent Cooke Young Artist Award in 2012, Trionfo appeared on From the Top as a Featured Alumni Performer. In 2013, he was a first prize winner of the Alexander and Buono International Flute Competition and a winner of the National Young Arts Foundation Competition.
At the Young Concert Artists 2016 International Auditions, Trionfo received additional prizes, including the Saint Vincent College Concert Series Prize, the Ruth Laredo Award, the Lied Center of Kansas Prize and the Michaels Award. He received the further distinction of being the first YCA artist to win the inaugural LP Classics Debut Recording Prize, granting him a commercial recording.
In addition to performing, Trionfo is committed to community outreach, teaching through the Jumpstart program in Los Angeles.
Trionfo is pursuing his master's degree under the tutelage of James Walker at the Colburn Conservatory of Music, where he has been a Teaching Fellow. He graduated from the Interlochen Arts Academy, having studied with Nancy Stagnitta. He has performed in master classes with Emmanuel Pahud, Mimi Stillman and Paula Robison.


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Merkel has given political backing to the Nord Stream 2 pipeline to import more gas, despite criticism from other European Union governments. Trump wants Europeans to pay up more for their own defence instead of making deals with Moscow. "They pay billions of dollars to Russian Federation and we have to defend them against Russian Federation", the U.S. president said at a breakfast with North Atlantic Treaty Organisation chief Jens Stoltenberg.
Germany is "totally controlled by Russia" due to its Nord Stream gas pipeline deal with Moscow, U.S. President Donald Trump said Wednesday ahead of a North Atlantic Treaty Organisation summit in Brussels, calling the deal "inappropriate".
Trump said Germany had become Russia's "captive" after it got rid of its coal plants and nuclear energy.
The Commander-in-Chief called-out the Chancellor at the onset of the global summit in Brussels; saying "It's very sad when Germany makes a massive oil and gas deal with Russian Federation where we're supposed to be guarding against Russian Federation".
PHOTO: President Donald Trump meets with Russian President Vladimir Putin at the G-20 Summit in Hamburg, July 7, 2017.
As Trump was set to travel to Brussels for a North Atlantic Treaty Organisation summit, Tusk said, "I would like to address President Trump directly, who for a long time now has been criticizing Europe nearly daily for, in his view, insufficient contributions to the common defense capabilities, and for living off the U.S".
He then contrasted the summit ahead to his very private meeting with Vladimir Putin, which is set for July 16 in Helsinki, days after the North Atlantic Treaty Organisation summit. "And I think that leaders are also looking forward to your thoughts about the meeting with President Putin later on".
Later, Trump told NATO Secretary General Jens Stoltenberg that Germany should have to pay more than "just over 1%" in comparison to the United States' 4.2% to NATO.
Of Nato's 29 members, just five meet that target this year: the US, Greece, Estonia, the United Kingdom and Latvia.
TRT World's Simon McGregor-Wood has more details.
The two leaders had a one-on-one meeting later on Wednesday, after which Trump claimed: "We have a tremendous relationship with Germany". "We're discussing military expenditure. talking about trade", Trump told reporters who were allowed in to the meeting room.
US President Donald Trump insisted Wednesday that he gets on well with Chancellor Angela Merkel, despite earlier savaging Germany's trade and defence policies.
Berlin has argued the pipeline is a private project, not state-funded.


I am running as administrator and syncing over a serial port.
I have searched the entire disk for the hddbg.log and not found it, so I am not sure if debug40.exe works on Windows 10.
Wow, I have not seen anyone using HanDBase for Palm on Windows 10, or even Windows 8. Glad to see you still have a working Palm OS device!
Unfortunately, I don't, so I have no way to test and see if its still compatible with Windows 10. I wonder if anyone else has tried this?
I am suspecting a driver issue, although all my Palm devices have gone to the electronic recycler years ago.
Going from XP to Windows 10, I am pretty sure that you will need 64-bit drivers.


1. Sew together four assorted print 2-1⁄2" squares in pairs (Diagram 1). Press the seam allowances in opposite directions, then join the pairs to make a Four-Patch unit. Press the seam allowance in one direction. Repeat to make a second Four-Patch unit.
2. Sew together the two Four-Patch units and two cream print squares in pairs (Diagram 2). Press the seam allowances toward the cream print squares. Then join the pairs to make a block (Block Assembly Diagram). Press the seam allowance in one direction.


"Frontiers in CNS Drug Discovery" is an eBook series devoted to publishing the latest and the most important advances in Central Nervous System (CNS) drug design and discovery. Eminent scientists write contributions on all areas of rational drug design and drug discovery including medicinal chemistry, in-silico drug design, combinatorial chemistry, high-throughput screening, drug targets, recent important patents, and structure-activity relationships. The eBook series should prove to be of interest to all pharmaceutical scientists involved in research in CNS drug design and discovery. Each volume is devoted to the major advances in CNS drug design and discovery. The eBook series is essential reading to all scientists involved in drug design and discovery who wish to keep abreast of rapid and important developments in the field.
- Patents involving the use of different factors that promote axonal regeneration.
- Patents aimed at overcoming the activity of glial scar inhibitory molecules that hinder axonal regeneration. These approaches can be further subdivided into those that block Nogo and other myelin components, and those that involve the use of chondroitinase against glial scar chondroitin sulphate proteoglycans.
- Patents concerning glial cell therapy, in which glial cells are used to mediate axonal repair in the spinal cord (Schwann cells, olfactory ensheathing cells or astrocytes).
Centro de Biologia Molecular "Severo Ochoa" (C.S.I.C.-U.A.M.), C/ Nicolas Cabrera 1, Universidad Autonoma de Madrid, 28049 Madrid, Spain.