NASDAQ Index Research Articles

Price Dynamics in the Regular and E-Mini Futures Markets

AbstractThis paper examines the price dynamics in the S&P 500 and Nasdaq-100 index futures contracts. By utilizing transactions data with attached trader type identification codes, we are able to analyze price dynamics for trades initiated by exchange locals and off-exchange customers. The empirical results show that price discovery appears to be initiated in the E-mini index futures contracts and that trades initiated by exchange locals seem to be more informative than those initiated by off-exchange traders. Furthermore, results show that exchange locals appear to make informed trades on the E-mini contracts around large trades that occur on the open outcry floor. We maintain that the exchange locals' ability to observe pit dynamics may contribute toward explaining the price leadership of the Emini contracts. Overall, the results are consistent with the notion that exchange locals are informed traders who derive their informational advantage from the proximity to order flow.

Do Macroeconomic Announcements Cause Asymmetric Volatility?

In this paper we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence that asymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond markets are likely due to misspecification of the volatility model. Because firm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model. Moreover, by distinguishing FOMC (interest rate) announcements from PPI and EMP (labor market) announcements, we find that both types of announcements are important determinants in explaining the conditional mean and dynamics in volatility.

Mixed Normal Conditional Heteroskedasticity

Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data. We consider a mixed -normal distribution coupled with a GARCH -type structure which allows for conditional variance in each of the components as well as dynamic feedback between the components. Special cases and relationships with previously proposed specifications are discussed and stationarity conditions are derived. An empirical application to NASDAQ index data indicates the appropriateness of the model class and illustrates that the approach can generate a plausible disaggregation of the conditional variance process, in which the components’ volatility dynamics have a clearly distinct behavior that is, for example, compatible with the well-known leverage effect.

International Market Linkages between the U.S. and Korea OTC Futures Markets: Information Transmission from NASDAQ100 Index Cash and Futures Markets to KOSDAQ50 Index Cash and Futures Markets

This study tests the international transmission from NASDAQ100 index spot and NASDAQ100 index futures to KOSDAQ50 index spot and KOSDAQ50 index futures markets for the period of Jan. 2001 - Dec. 2002. Based on the time-varying AR(1)-GARCH(1,1)-M models, the results show that the open-to-close returns of the NASDAQ100 index spot and futures have predictive power over both the open-to-close and close-to-open returns of KOSDAQ50 index spot and futures. In particular, the open-to-close returns of both NASDAQ100 index spot and futures have much stronger effect over the close-to-open returns of KOSDAQ50 index spot. We also find that the NASDAQ100 index futures returns have strong predictive power over the KOSDAQ50 index futures returns similar to the results from the NASDAQ100 index spot. In addition, the tests show that the close-to-open returns of the NASDAQ100 index futures, rather than those of NASDAQ100 index spot have stronger information spillover effect over the open-to-close returns of both the KOSDAQ50 index spot and futures. The results also represent that there is co-movement between the KOSDAQ50 index spot and the NASDAQ100 index spot and between the KOSDAQ50 index futures and the NASDAQ100 index futures. These findings support that the market efficiency and the international stock market integration are on the increasing trend in terms of both mean and time varying volatility. Specifically, the results of the information spillover effects between NASDAQ100 index futures market and the KOSDAQ50 index futures market would provide useful information in country diversification and industry diversification. EFA Classification code: 630, 620

The Blue Monday Hypothesis: Evidence About and Based on Fama-French Factors

This study provides empirical evidence on the Blue Monday hypothesis that a sizeable proportion of investors tend to be inherently pessimistic on Mondays relative to other days and this contributes to the famous Monday effect in stock returns. For the period 1971-2002, returns on most indices that track important segments of the Dow and Nasdaq stocks (Dow: industrial, transportation, and utility; Nasdaq: composite, industrial, bank, insurance, other financial, transportation, telecommunications, utility, biotech, and computers) exhibit a Monday effect. The strength of the Monday effect (Monday return minus the average return on other weekdays) is positively correlated over time between the various segments tracked by the indices. While Rm-Rf, and SMB exhibit a Monday pattern (i.e., Monday returns being lower than some of the other days), HML exhibits a reverse Monday pattern (i.e., Monday returns being higher than some of the other weekdays). This Monday pattern in Fama-French factors, however, does not fully account for the Monday effect in excess returns on various Dow and Nasdaq indices (index return minus Rf) because in the regression of index excess returns against the three Fama-French factors the intercepts and/or the residuals continue to exhibit a Monday pattern. Furthermore, the r-squared values in these regressions are higher on Mondays than on non-Mondays. The study argues that these findings are consistent with the Blue Monday hypothesis.

Aggregate Short Interest and Market Valuations

We examine some basic data on the evolution of aggregate short interest, both during the dot-com era, and at other times in history. Total short interest moves in a countercyclical fashion. For example, short interest in NASDAQ stocks actually declines as the NASDAQ index approaches its peak. Moreover, this decline does not seem to reflect a substitution away from outright short-selling and towards put options, as the ratio of put-to-call volume displays the same countercyclical tendency. The evidence suggests that: i) arbitrageurs are reluctant to bet against aggregate mispricings; and ii) short-selling does not play a particularly helpful role in stabilizing the overall stock market.

NONPARAMETRIC ANALYSES OF LOG-PERIODIC PRECURSORS TO FINANCIAL CRASHES

We apply two nonparametric methods to further test the hypothesis that log-periodicity characterizes the detrended price trajectory of large financial indices prior to financial crashes or strong corrections. The term "parametric" refers here to the use of the log-periodic power law formula to fit the data; in contrast, "nonparametric" refers to the use of general tools such as Fourier transform, and in the present case the Hilbert transform and the so-called (H, q)-analysis. The analysis using the (H, q)-derivative is applied to seven time series ending with the October 1987 crash, the October 1997 correction and the April 2000 crash of the Dow Jones Industrial Average (DJIA), the Standard & Poor 500 and Nasdaq indices. The Hilbert transform is applied to two detrended price time series in terms of the ln (tc-t) variable, where tcis the time of the crash. Taking all results together, we find strong evidence for a universal fundamental log-frequency f=1.02±0.05 corresponding to the scaling ratio λ=2.67±0.12. These values are in very good agreement with those obtained in earlier works with different parametric techniques. This note is extracted from a long unpublished report with 58 figures available at , which extensively describes the evidence we have accumulated on these seven time series, in particular by presenting all relevant details so that the reader can judge for himself or herself the validity and robustness of the results.

Stock Splits and Liquidity: The Case of the Nasdaq‐100 Index Tracking Stock

AbstractIn an attempt to disentangle the signaling effect from the liquidity effect of stock splits, I examine the liquidity changes following the two‐for‐one split of the Nasdaq‐100 Index Tracking Stock. Since there can be no signaling with an index stock split, any difference between pre‐ and postsplit trading may be driven by liquidity but not signaling effects. I find that though the postsplit relative bid‐ask spread is higher and daily turnover is unchanged, the frequency, share volume, and dollar‐volume of small trades all increased after the split, indicating that the split improved liquidity for small trade‐sizes.

Information Versus Contagion: International Transmissions of the NASDAQ, JASDAQ and KOSDAQ Market Returns

This study tests the hypotheses of information and contagion using the return series from SP500, NIKKEI225, KOSPI200, NASDAQ, JASDAQ, and KOSDAQ index. We conjecture that the information related to the present value of growth opportunities (PVGO) incur different degree of co-movement of stock prices, while contagion produces no distinctive difference in the degree of co-movement in the sock price between national stock exchanges and OTC markets. We also add Korea markets to test the hypothesis that emerging markets are more vulnerable to contagion suggested by Kodres and Pritsker (2002). This study is the first to report the co-movements of the OTC markets. The results indicate that SP500 index returns have predictive power over both NIKKEI225 and KOSPI200 index returns only before the 1997 Korean currency crisis period. NASDAQ index returns have significant predictive power over both JASDAQ and KOSDAQ index returns both before and after the 1997 Korean currency crisis. We claim that the results tend to support the information hypothesis that investors both in Japan and Korea OTC markets infer information on the value changes from the NASDAQ market movements.

Price Dynamics in the Regular and E-mini Futures Markets

This paper examines the price dynamics in the S&P 500 and Nasdaq-100 index futures contracts. By utilizing transactions data with attached trader type identification codes, we are able to analyze price dynamics for trades initiated by exchange locals and off-exchange customers. The empirical results show that price discovery appears to be initiated in the E-mini index futures contracts and that trades initiated by exchange locals seem to be more informative than those initiated by off-exchange traders. Furthermore, results show that exchange locals appear to make informed trades on the E-mini contracts around large trades that occur on the open outcry floor. We maintain that the exchange locals' ability to observe pit dynamics may contribute toward explaining the price leadership of the E-mini contracts. Overall, the results are consistent with the notion that exchange locals are informed traders who derive their informational advantage from the proximity to order flow.

Financial data modeling by using asynchronous parallel evolutionary algorithms

In this paper, the high-level knowledge of financial data modeled by ordinary differential equations (ODEs) is discovered in dynamic data by using an asynchronous parallel evolutionary modeling algorithm (APHEMA). A numerical example of Nasdaq index analysis is used to demonstrate the potential of APHEMA. The results show that the dynamic models automatically discovered in dynamic data by computer can be used to predict the financial trends.

Do Macroeconomic Announcements Cause Asymmetric Volatility?

In this paper we study the impact of macroeconomic news announcements on the conditional volatility of stock and bond returns. Using daily returns on the S&P 500 index, the NASDAQ index, and the 1 and 10 year U.S. Treasury bonds, for January 1982 - August 2001, some interesting results emerge. Announcement shocks appear to have a strong impact on the (dynamics of) bond and stock market volatility. Our results provide empirical evidence thatasymmetric volatility in the Treasury bond market can be largely explained by these macroeconomic announcement shocks. This suggests that the asymmetric volatility found in government bond markets are likely due to misspecification of the volatility model. After including macroeconomic announcements into the model, the asymmetry disappears. Becausefirm-specific news is the most important source of information in the stock market, the asymmetries in stock volatility do not disappear after incorporating macroeconomic announcements into the volatility model.

Do Speculative Stocks Lower Prices and Increase Volatility of Value Stocks?

The influence of speculative stocks on value stocks is examined through a set of economics experiments. The speculative asset is designed to model a company involved in a rapidly growing market that will be saturated at some unknown point. Using a control experiment where both assets are similar value stocks, we find statistical support for the assertion that the presence of a speculative stock increases the volatility and diminishes the price of the value stock. In addition, the temporal minimum price of the value stock during the last phase of the experiment is lower in the presence of the speculative stock (when the trading price of the speculative asset is declining sharply). These results indicate that an overreaction in the speculative stock tends to divert investment capital away from other assets. An examination of the relative magnitude of monthly closing price changes confirm strong correlations between the Dow Jones Average and the more speculative Nasdaq index during the time period in 1990 to 2001 and particularly during the two years prior to the peak in March 2000 (0.72 correlation) and the March 2000 to August 2001 decline (0.79 correlation). Supplementary experiments using independent (or legally separate) markets trading the same asset show that a higher price in one market does not lead to a higher one in the other.

Do Speculative Stocks Lower Prices and Increase Volatility of Value Stocks?

The influence of speculative stocks on value stocks is examined through a set of economics experiments. The speculative asset is designed to model a company involved in a rapidly growing market that will be saturated at some unknown point. Using a control experiment where both assets are similar value stocks, we find statistical support for the assertion that the presence of a speculative stock increases the volatility and diminishes the price of the value stock. In addition, the temporal minimum price of the value stock during the last phase of the experiment is lower in the presence of the speculative stock (when the trading price of the speculative asset is declining sharply). These results indicate that an overreaction in the speculative stock tends to divert investment capital away from other assets. An examination of the relative magnitude of monthly closing price changes confirm strong correlations between the Dow Jones Average and the more speculative Nasdaq index during the time period 1990 to 2001 and particularly during the two years prior to the peak in March 2000 (0.72 correlation) and the March 2000 to August 2001 decline (0.79 correlation). Supplementary experiments using independent (or legally separate) markets trading the same asset show that a higher price in one market does not lead to a higher one in the other.

Balance-Sheet Contagion

Japan has been in a slump for the past decade. After GDP had been growing by on average 4 percent during the 1980’s, the growth rate dropped to 1 percent in the 1990’s. Asset prices also fluctuated significantly: capital gains on stocks and real estate in the 1980’s, followed by capital losses in the 1990’s, were both on the order of a few years’ worth of GDP, even after taking inflation into account. Together with production and asset prices, the fraction of nonperforming loans fluctuated substantially. These are by no means all bank loans. For the nonfinancial corporate sector in Japan, the ratio of financial assets to total assets is about 40 percent, much higher than in the United States. Such financial assets include loans to and securities of other private agents. That is, nonfinancial institutions simultaneously borrow from and lend to each other on a significant scale. Many nonperforming loans are interlocked, paralyzing the financial system. It is important to recognize that these swings have been experienced by almost all sectors of the Japanese economy. Yet in other countries, comparable movements in asset prices have had less widespread consequences. For example, the recent fluctuations in the NASDAQ index in the United States have been no smaller than those of asset prices in Japan, but the damage appears to be contained to closely related sectors. Although U.S. equity-holders, particularly pension funds, have lost value, the level of nonperforming loans is relatively limited up to now. The question is: Why does there appear to be more contagion in some countries than in others? Has contagion anything to do with the nature of financing or the extent to which there are inter-locking loans? In this theoretical paper, we examine two different mechanisms by which contagion may occur. In both cases, propagation is through balancesheet effects. First, through the indirect effects that fluctuations in asset prices have on collateral values. Second, through the direct effects that default on or postponement of debt repayments have when there are chains of credit.

ON NONLINEAR MODELING FOR THE PREDICTABILITY OF EQUITY RETURN

Non-stationary time series are commonly found in financial applications. Added to the complexity are the time-varying nature and non-linearity of accurate models for describing the dynamic behavior of these financial time series. We extend the techniques of cointegration to handle time-varying, non-linear relationship between a time series (“news”) and its causally affected time series. The predictability of daily return, as related to the NASDAQ indexes and to a possible NASDAQ-GEM relationship, is investigated based on a proposed “news” model for dynamic changes. The effectiveness and robustness of neural network models for handling non-linearity is compared with linear least-squares estimation.

Pre-offering earnings and the long-run performance of IPOs

Consistent with the results in Ritter [J. Finance 46 (1991) 3–27.], this study finds that Initial Public Offering (IPO) firms, as a whole, underperformed a market index and control firms over a 3-year period after going public. However, the IPO firms that had positive earnings at the time of offering seemed to have fared better than the firms that went public with losses. Although the long-run median returns indicate that all IPOs underperformed the NASDAQ index and a set of control firms matched by industry and size, only the firms going public with negative earnings had statistically and economically significant negative abnormal mean returns. The general findings in this study suggest that investors may have been too optimistic about future prospects of the IPO firms, especially those that had negative earnings.

Biotech company dispels stockmarket doubts

UK biotechnology company, Oxford Glycosciences (OGS), threw off stockmarket doubts about technology stocks by raising more than £170m/$240m in a recent share offering, which was nearly three times oversubscribed (see http://www.ft.com). The placement will also be followed by a secondary listing on the US Nasdaq index, which will allow OGS to make US acquisitions. OGS will use the proceeds of the offering to strengthen its position in the proteomics market, and to fund more in-house drug development.

A new time-of-the-month anomaly in stock index returns

This paper documents a new ‘time-of-the-month’ pattern in the daily returns of the Standard & Poor's and the NASDAQ indices. Splitting a month into three time segments, the results show that the returns are highest during the ‘first third’, experience a drop during the ‘second third’, and are lowest, and in most cases negative, during the ‘last third’ of a month. This pattern remained remarkably consistent for the two indices examined. It also held up well over business cycles and many different subperiods tested. Thus, the results of this study provide convincing evidence of a new monthly anomaly which displays a remarkable degree of robustness.

Filter Tests In Nasdaq Stocks

AbstractThis study examines the performance of filter and dual moving‐average crossover trading rules applied to Nasdaq stocks. We find that trading rules conditioned on a stock's past price history perform poorly, but those based on past movements in the overall Nasdaq Index tend to earn statistically significant abnormal returns. Since there is a high level of transaction costs in this market, these abnormal returns are generally not economically significant. However, there are indications that pursuing some of these strategies can be worthwhile in carefully selected subsets of stocks.