The Dow Jones Industrial Average is (DJIA) is possibly the most well-known and commonly used stock index in the United States. It is a price-weighted index that assesses the stock prices of 30 prominent companies, whose combined prices are then divided by a regularly-updated divisor (0.15199 in February 2021), which gives the index value. The companies included are rotated in and out on a regular basis; as of mid-2022, the longest mainstay on the list is Procter & Gamble, which was added in 1932; whereas Amgen, Salesforce, and Honeywell were all added in 2020. As one of the oldest indices for stock market analysis, the impact of major events, recessions, and economic shocks or booms can be tracked and contextualized over longer periods of time.

Due to inflation, unadjusted figures appear to be more sporadic in recent years, however the greatest fluctuations came in the earliest years of the index. In the given period, the greatest decline came in the wake of the Wall Street Crash in 1929; by 1932 average values had fallen to just one fifth of their 1929 average, from roughly 314 to 65.

The statistic shows the worst days of the Dow Jones Industrial Average index from 1897 to 2025. The worst day in the history of the index was ****************, when the index value decreased by ***** percent. The largest single day loss in points was on ***********.

This dataset contains several daily features of S&P 500, NASDAQ Composite, Dow Jones Industrial Average, RUSSELL 2000, and NYSE Composite from 2010 to 2017. It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of "CNNpred: CNN-based stock market prediction using a diverse set of variables".

The replication data contain MATLAB and GAUSS codes as well as the data required for replication of the results from the paper

1. Monte Carlo Simulation:

Contains codes and data for simulation study from Section 3.

Data:

• MV.mat, MV.txt- monthly data on market capitalization of the 205 stocks of the S&P500 index obtained from DataStream for the period 01.01.1974-01.05.2015

• sp500_edata.mat - monthly data on close prices of components of S&P500 index for the period 01.01.1974-01.05.2015 processed to obtain excess returns using as a risk free return data on the risk free return from French & Fama database. Description of the price data from DataStream: "The ‘current’ prices taken at the close of market are stored each day. These stored prices are adjusted for subsequent capital actions, and this adjusted figure then becomes the default price offered on all Research programs. " Description of the excess return of the market from French & Fama database : "the excess return on the market, value-weight return of all CRSP firms incorporated in the US and listed on the NYSE, AMEX, or NASDAQ that have a CRSP share code of 10 or 11 at the beginning of month t, good shares and price data at the beginning of t, and good return data for t minus theone-month Treasury bill rate (from Ibbotson Associates)." From the latest file two separate data files were created (see CAPMsim.m):

• sp500_stocks.txt, sp500_stocks.mat - monthly data on close prices of 205 components of S&P500 index for the period 01.01.1974-01.05.2015

• FactorData.txt, FactorData.txt - The Fama & French factors from French & Fama database for a period July 1926 - May 2015.

Codes:

• CAPMsim.m - the main code that replicates the Monte Carlo simulation of the artificial market and proxy indexes subject to different types of the measurement error.

• sure.m- obtains the estimated parameters for the SUR system and performs hypothesis testing of the significance of the coefficients.

2. Empirical Application

Contains codes and data for empirical application from Section 4.

Data:

• data1203.txt - 120 monthly observations on the excess returns on 20 random stocks from S&P500, S&P500 index return, DJIA return from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2005-01/05/2015.

• data1204.txt - 120 monthly observations on the excess returns on 30 stocks from DJIA, S&P500 index return, DJIA return from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2005-01/05/2015.

• DJSTOCKS_60_FF_Z.dat - 60 monthly observations on the excess returns on 30 stocks from DJIA from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2010-01/05/2015.

• DJSTOCKS_60_SP_Z.dat - 60 monthly observations on the excess returns on 30 stocks from DJIA and S&P500 index return from DataStream for a period 01/06/2010-01/05/2015.

  • DJSTOCKS_60_DJ_Z.dat - 60 monthly observations on the excess returns on 30 stocks from DJIA and DJIA return from DataStream for a period 01/06/2010-01/05/2015.
  • STOCKS_60_FF_Z.dat - 60 monthly observations on the excess returns on 20 random stocks from S&P500 from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2010-01/05/2015.
  • STOCKS_60_SP_Z.dat - 60 monthly observations on the excess returns on 20 random stocks from S&P500 and S&P500 index return from DataStream for a period 01/06/2010-01/05/2015.

• STOCKS_60_DJ_Z.dat - 60 monthly observations on the excess returns on 20 random stocks from S&P500 and DJIA return from DataStream for a period 01/06/2010-01/05/2015.

  Description of the variables in the data sets:

• Z_1, Z_2,...,Z_20,..., Z_30 - returns of individual stocks depending on the data set.

• For calculation of the returns adjusted prices from DataStream were used (see data from Monte Carlo simulation part). Risk free return is taken from French & Fama database.

• Time period was shortened from 120 to 60 observations: 01/06/2010-01/05/2015

• Excess returns from the market and indeces:

  • Z_SP - 60 observations on excess return of the S&P500 from DataStream
  • Z_DJ - 60 observations on excess return of the DJIA from DataStream
  • Z_FF - 60 observations on excess return of the market from French & Fama database

Codes:

• load_stocks120.gss - loads the data on the returns of the randomly selected 20 socks of S&P500 and selects last 60 observations
  • load_djstocks120.gss - loads the data on the returns of the 30 socks of the Dow-Jones Industrial Average Index and selects last 60 observations
  • CAPM.prc- contains functions to estimate CAPM model by SUR and Minimum Distance methods
• CAPM.inc- sets the format for the output files from the GAUSS procedures
• CAPM_STOCKS20_FF.gss, CAPM_STOCKS20_DJ.gss, CAPM_STOCKS20_SP.gss, CAPM_DJSTOCKS30_FF.gss,CAPM_DJSTOCKS30_DJ.gss,CAPM_DJSTOCKS30_SP.gss - GAUSS procedures to estimate the CAPM models based on particular data set (20 random stocks or 30 stocks from DJIA as well as different market indexes: S&P500, DJIA, CRSP) and generate separate output files. 2019-03-05 11:51:42.893129 The replication data contain MATLAB and GAUSS codes as well as the data required for replication of the results from the paper

The expense ratio of passive mutual funds is expected to fall more quickly than for active funds between 2010 and 2015. While the former is predicted to fall by around ********** between 2010 and 2025, the latter is only expected to fall by *********. Active mutual funds are funds of pooled money that is invested by a fund manager, who actively researches new investment opportunities and amends the fund's portfolio accordingly. This contrasts to passive funds, where the fund's portfolio is (usually) determined by an external stock market index such as the Dow Jones Industrial Average or the FTSE 100. The less hand-on nature of passive funds means they are cheaper to operate, hence the consistently lower expense ratio.

While passive funds only constituted ** percent of the mutual fund market in the the United States in 2010, it is projected that over **** of all U.S. mutual funds will be passive by 2025. Active mutual funds are funds of pooled money that is invested by a fund manager, who actively researches new investment opportunities and amends the fund's portfolio accordingly. This contrasts to passive funds, where the fund's portfolio is (usually) determined by an external stock market index such as the Dow Jones Industrial Average or the FTSE 100.

While passive funds only accounted for *** trillion U.S. dollars of total assets held by mutual funds in the United States in 2010, this figure will have multiplied by 2025. Active mutual funds are funds of pooled money that is invested by a fund manager, who actively researches new investment opportunities and amends the fund's portfolio accordingly. This contrasts to passive funds, where the fund's portfolio is (usually) determined by an external stock market index such as the Dow Jones Industrial Average or the FTSE 100.

While passively managed index funds only constituted ** percent of the total assets managed by investment companies in the United States in 2010, this share had increased to ** percent by 2024. Active mutual funds are funds of pooled money managed by a fund manager, who actively researches new investment opportunities and amends the fund's portfolio accordingly. This contrasts to passive funds, where the fund's portfolio is (usually) determined by an external stock market index such as the Dow Jones Industrial Average or the FTSE 100.

Wer zum Ende des Jahres 2010 in Dow Jones-Werte investierte und diese Aktien Ende 2024 wieder verkaufte, erzielte in diesem Zeitraum eine jährliche Rendite von im Schnitt etwa *** Prozent. Dies zeigt das vorliegende Renditedreieck, welches die Renditeentwicklung der im Dow Jones notierten Aktien visualisiert. So lesen Sie das Renditedreieck Entlang der Waagerechten des Dreiecks sind die möglichen Jahre des Kaufs und auf der Senkrechten die für den Verkauf der Aktien abgetragen. Im Schnittpunkt von Kauf- und Verkaufsjahr steht die durchschnittliche jährliche Rendite des gewählten Zeitraums.Die Daten in der untersten Zeile geben an, welche jährliche Rendite bei einem Anlageeinstieg im jeweiligen Jahr durchschnittlich erzielt werden konnte. Bei einem Einstieg am Ende des Jahres 2005 erzielten Anleger:innen im Dow Jones beispielsweise jährliche Kursrenditen von durchschnittlich *** Prozent. Über den Dow-Jones-Index Der Dow Jones Industrial Average (DJIA), kurz Dow Jones, stellt nach dem Dow Jones Transportation Average den ältesten noch existierenden Aktienindex der USA dar. Zugleich ist der DJIA das weltweit bekannteste wie auch meistbeachtete Börsenbarometer. Gründer und Namensgeber des Dow Jones waren Charles Henry Dow sowie Edward David Jones, die Ende des 19. Jahrhunderts das Wall Street Journal herausgaben. Der Dow Jones wurde 1896 erstmals veröffentlicht und umfasste damals nur die ***** wichtigsten Unternehmen. Ab 1916 repräsentierte das Barometer ** US-Industriewerte, seit 1928 sind es ** – inzwischen auch bedeutende Aktien anderer Branchen. Im Gegensatz zum DAX, bei dem es sich um einen Performance-Index handelt, wird der Dow Jones als reiner Kursindex berechnet. Der Indexstand des DJIA wird also ausschließlich auf Grund der Aktienkurse ermittelt, Dividendenzahlungen und Kapitalabschläge werden nicht berücksichtigt.