Detecting Nasdaq Composite Index Trends with OFNs

2017 ◽  
pp. 195-205 ◽  
Author(s):  
Hubert Zarzycki ◽  
Jacek M. Czerniak ◽  
Wojciech T. Dobrosielski
Keyword(s):  
Composite Index ◽  
Nasdaq Composite Index

scholarly journals Regime-Switching Behaviour In US Equity Indices: Two State Model With Kalman Filter Tracking And Finite State Machine Trading System

2021 ◽  
Author(s):  
Timothy Little
Keyword(s):  
Regime Switching ◽  
Finite State Machine ◽  
Composite Index ◽  
State Machine ◽  
Trading System ◽  
Switching Model ◽  
Nasdaq Composite Index ◽  
Finite State ◽  
Equity Index ◽  
Equity Indices

This thesis presents a time varying regime-switching model for US equity index daily returns. The parameters of the model are estimated recursively with the Kalman lter. We demonstrate our model and parameter estimation technique are effective by demonstrating improvements in model t compared to alternate models. Information from our model is used to build a Finite State Machine trading system with back-tested performance in excess of 15,000% above a buy and hold strategy for the DOW Jones Industrial average from 1928-2012. Similar results are found for both the S&P 500 index and the NASDAQ Composite index over a long period. Our model succeeds at identifying pro table investment opportunities and improving model t with a minimum of parameters.

scholarly journals A Hypothesis Test Method for Detecting Multifractal Scaling, Applied to Bitcoin Prices

2020 ◽  
Vol 13 (5) ◽  
pp. 104
Author(s):  
Chuxuan Jiang ◽  
Priya Dev ◽  
Ross A. Maller
Keyword(s):  
Time Series ◽  
Heavy Tails ◽  
Financial Time Series ◽  
Hypothesis Test ◽  
Composite Index ◽  
Test Method ◽  
Scaling Functions ◽  
Financial Time ◽  
Nasdaq Composite Index ◽  
Multifractal Scaling

Multifractal processes reproduce some of the stylised features observed in financial time series, namely heavy tails found in asset returns distributions, and long-memory found in volatility. Multifractal scaling cannot be assumed, it should be established; however, this is not a straightforward task, particularly in the presence of heavy tails. We develop an empirical hypothesis test to identify whether a time series is likely to exhibit multifractal scaling in the presence of heavy tails. The test is constructed by comparing estimated scaling functions of financial time series to simulated scaling functions of both an iid Student t-distributed process and a Brownian Motion in Multifractal Time (BMMT), a multifractal processes constructed in Mandelbrot et al. (1997). Concavity measures of the respective scaling functions are estimated, and it is observed that the concavity measures form different distributions which allow us to construct a hypothesis test. We apply this method to test for multifractal scaling across several financial time series including Bitcoin. We observe that multifractal scaling cannot be ruled out for Bitcoin or the Nasdaq Composite Index, both technology driven assets.

scholarly journals PORTFOLIO RETURN DISTRIBUTIONS: SAMPLE STATISTICS WITH STOCHASTIC CORRELATIONS

2015 ◽  
Vol 18 (02) ◽  
pp. 1550012 ◽  
Author(s):  
DESISLAVA CHETALOVA ◽  
THILO A. SCHMITT ◽  
RUDI SCHÄFER ◽  
THOMAS GUHR
Keyword(s):  
Normal Distribution ◽  
Multivariate Normal Distribution ◽  
Composite Index ◽  
Multivariate Normal ◽  
Correlation Matrices ◽  
Daily Data ◽  
Nasdaq Composite Index ◽  
Return Distributions ◽  
Portfolio Return ◽  
Good Agreement

We consider random vectors drawn from a multivariate normal distribution and compute the sample statistics in the presence of stochastic correlations. For this purpose, we construct an ensemble of random correlation matrices and average the normal distribution over this ensemble. The resulting distribution contains a modified Bessel function of the second kind whose behavior differs significantly from the multivariate normal distribution, in the central part as well as in the tails. This result is then applied to asset returns. We compare with empirical return distributions using daily data from the NASDAQ Composite Index in the period from 1992 to 2012. The comparison reveals good agreement, the average portfolio return distribution describes the data well especially in the central part of the distribution. This in turn confirms our ansatz to model the nonstationarity by an ensemble average.

Blockchain ETFs: dynamic correlations and hedging capabilities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ivelina Pavlova
Keyword(s):  
Composite Index ◽  
Exchange Traded Funds ◽  
Financial Assets ◽  
Content Type ◽  
Dynamic Correlations ◽  
Dynamic Relationship ◽  
Nasdaq Composite Index ◽  
Hedge Ratios ◽  
Relationship Of ◽  
High Degree

PurposeIn this paper, the authors examine the interconnectedness of four blockchain exchange-traded funds (ETFs) with other financial markets, such as stocks and cryptocurrencies.Design/methodology/approachA multivariate dynamic conditional correlation model is used to model the relationship of blockchain ETFs with equity and cryptocurrency markets. Risk-minimizing hedge ratios are calculated following the methods used in studies by Kroner and Sultan (1993) and Sadorsky (2012).FindingsThe empirical results show a high degree of correlation of blockchain ETF returns with returns of the NASDAQ Composite Index, while the level of comovement with Bitcoin is relatively low.Research limitations/implicationsThe results imply that blockchain ETFs may be suitable for hedging purposes in a portfolio holding Bitcoin. Furthermore, investing in blockchain ETFs appears similar to investing in NASDAQ.Originality/valueTo the best of the authors’ knowledge, no studies have investigated the dynamic relationship of blockchain ETFs and other financial assets.

scholarly journals Risk and Policy Uncertainty on Stock–Bond Return Correlations: Evidence from the US Markets

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 58
Author(s):  
Thomas Chiang
Keyword(s):  
Composite Index ◽  
Correlation Coefficients ◽  
Stock Index ◽  
Policy Uncertainty ◽  
Dynamic Correlations ◽  
Nasdaq Composite Index ◽  
Bond Returns ◽  
The Us ◽  
Bond Return ◽  
Index Value

This paper investigates dynamic correlations of stock–bond returns for different stock indices and bond maturities. Evidence in the US shows that stock–bond relations are time-varying and display a negative trend. The stock–bond correlations are negatively correlated with implied volatilities in stock and bond markets. Tests show that stock–bond relations are positively correlated with economic policy uncertainty, however, are negatively correlated with the monetary policy and fiscal policy uncertainties. Correlation coefficients between stock and bond returns are positively related to total policy uncertainty for returns of the Dow-Jones Industrial Average (DJIA) and the S&P 500 Value stock index (VALUE), but negatively correlated with returns of S&P500 (Total market), the NASDAQ Composite Index (NASDAQ), and the RUSSELL 2000 (RUSSELL).

scholarly journals Moving Average Trading Rules for NASDAQ Composite Index

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Chien-Ping Chen
Keyword(s):  
Transaction Costs ◽  
Predictive Power ◽  
Moving Average ◽  
Composite Index ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Nasdaq Composite Index

This paper tests a few moving average technical trading rules for the NASDAQ Composite and Goldman Sack commodity indexes from 1972 to 2015. Our results indicate that moving average rules do exhibit strong predictive power for NADSAQ composite index but much weaker predictive power for GSCI. Can a trader use this predictive to beat the B&H strategy? We show that MA-100 days could most of the time make an abnormal profit in the case of NASDAQ composite index by considering both transaction costs and risk. 

scholarly journals THE ECONOMETRIC ANALYSIS OF THE DYNAMICS OF ETHEREUM IN THE SHORT-TERM PERIOD

2018 ◽  
Author(s):  
Олег Кудрявцев ◽  
Oleg Kudryavtsev ◽  
Кирилл Мозолев ◽  
Kirill Mozolev ◽  
Артур Чивчян ◽  
...  
Keyword(s):  
Composite Index ◽  
Econometric Analysis ◽  
Short Term ◽  
Price Changes ◽  
Nasdaq Composite Index ◽  
Dow Jones Industrial Average ◽  
Survey Results ◽  
Index Changes ◽  
Gold Futures ◽  
Average Index

The article presents an econometric analysis of the effect of stock indicators, such as Comex Gold futures, Dow Jones Industrial Average index and NASDAQ Composite, on the Ethereum cryptocurrency dynamics in the 100-day period. As part of the study, an econometric model of the dynamics of e-currency was built. The survey results show that when the Comex gold futures price changes by 1% on average, the Ethereum price changes by 5.01% in the same direction, when the Dow Jones Industrial Average index changes by 1%, the Ethereum price is 10.897%, and when the NASDAQ Composite index changes, the Ethereum price will change in the opposite direction to 3.59%

scholarly journals Regime-Switching Behaviour In US Equity Indices: Two State Model With Kalman Filter Tracking And Finite State Machine Trading System

2021 ◽  
Author(s):  
Timothy Little
Keyword(s):  
Regime Switching ◽  
Finite State Machine ◽  
Composite Index ◽  
State Machine ◽  
Trading System ◽  
Switching Model ◽  
Nasdaq Composite Index ◽  
Finite State ◽  
Equity Index ◽  
Equity Indices

This thesis presents a time varying regime-switching model for US equity index daily returns. The parameters of the model are estimated recursively with the Kalman lter. We demonstrate our model and parameter estimation technique are effective by demonstrating improvements in model t compared to alternate models. Information from our model is used to build a Finite State Machine trading system with back-tested performance in excess of 15,000% above a buy and hold strategy for the DOW Jones Industrial average from 1928-2012. Similar results are found for both the S&P 500 index and the NASDAQ Composite index over a long period. Our model succeeds at identifying pro table investment opportunities and improving model t with a minimum of parameters.

scholarly journals COULD SHORT SELLING MAKE FINANCIAL MARKETS TUMBLE?

2005 ◽  
Vol 08 (04) ◽  
pp. 509-521 ◽  
Author(s):  
JØRGEN VITTING ANDERSEN
Keyword(s):  
Financial Markets ◽  
Hedge Funds ◽  
Composite Index ◽  
Sustainable Growth ◽  
Broken Symmetry ◽  
Steady Increase ◽  
Nasdaq Composite Index ◽  
Growth Phenomenon ◽  
Recent Arrival

It is suggested to consider long term trends of financial markets as a growth phenomenon. The question is what conditions are needed for a long term sustainable growth or contraction in a financial market? The paper discusses the role of traditional market players of long only mutual funds versus hedge funds which take both short and long positions. It will be argued that financial markets since their very origins and only till very recently, have been in a state of "broken symmetry" which favored long term growth instead of contraction. The reason for this "broken symmetry" in a long term "bull phase" is the historical almost complete dominance by long only players in financial markets. Only with the recent arrival of investors that take up short positions is the symmetry slowly being restored, with the implications, as will be argued, of an increased probability for lasting decline of the markets, i.e., appearance of a long term "bear phase". Recent short trade data of the Nasdaq Composite index show an increase in the short activity prior to or at the same time as dips in the market, and reveal an steady increase in short trading activity, reaching levels never seen before.

scholarly journals Multivariate Option Pricing with Pair-Copulas

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Anna Barban ◽  
Luca Di Persio
Keyword(s):  
Option Pricing ◽  
Decomposition Method ◽  
General Procedure ◽  
Composite Index ◽  
Simulated Data ◽  
Dependence Structure ◽  
Main Difficulty ◽  
Comparison Analysis ◽  
Nasdaq Composite Index ◽  
Proposed Model

We propose a copula-based approach to solve the option pricing problem in the risk-neutral setting and with respect to a structured derivative written on several underlying assets. Our analysis generalizes similar results already present in the literature but limited to the trivariate case. The main difficulty of such a generalization consists in selecting the appropriate vine structure which turns to be of D-vine type, contrary to what happens in the trivariate setting where the canonical vine is sufficient. We first define the general procedure for multivariate options and then we will give a concrete example for the case of an option written on four indexes of stocks, namely, the S&P 500 Index, the Nasdaq 100 Index, the Nasdaq Composite Index, and the Nyse Composite Index. Moreover, we calibrate the proposed model, also providing a comparison analysis between real prices and simulated data to show the goodness of obtained estimates. We underline that our pair-copula decomposition method produces excellent numerical results, without restrictive assumptions on the assets dynamics or on their dependence structure, so that our copula-based approach can be used to model heterogeneous dependence structure existing between market assets of interest in a rigorous and effective way.

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