Tag Info

27

quandl is a new data source for all kind of econometric time series.

18

I don't know how interested you are in the CME data, but I have been learning about options and volatility modeling. I have been working with delayed CME data. I have been able to extract the JSON queries and now have been able to run them in my .NET application to get data for every asset type. Exmaple of ES options data: Run the query below in Chrome ...

16

Academic access to Thomson Reuters Tick History: www.sirca.org.au The Thomson Reuters Tick History database provides millisecond-timestamped tick data going back to January 1996, covering 45 million OTC and exchange-traded instruments worldwide. The database currently updates at a rate of 1 million messages per second and is around 3 Petabytes uncompressed....

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To get a consolidated feed of most of the data feeds here use Quandl. This is free for limited amount of requests per day.

10

This is the canonical Arrow-Pratt "portfolio" model. Couple of points on terminology: For a function $u$, we define the risk aversion function by $r_u(x):=-\frac{u''(x)}{u'(x)}$. In your utility function, $r_u(x) = \lambda$; hence, it is a constant absolute risk aversion utility and $\lambda$ is the "coefficient of risk aversion," not the "risk ...

10

Somewhat more economic data can be found at e.g.: The World Bank The United Nations The OECD More financial: The IMF European Union / EFTA / EMU data: Eurostat European Central Bank (financial) Data from these sources is all freely available. You can also play with data from many of these sources using the Google Public Data Explorer.

9

Quandl is a free one, with good economic and market data and an API http://www.quandl.com/

7

I did a fair amount of searching for a good source of historical data and I came across Norgate Investor Services. They provide the data in MetaStock format. I used the data for analysis in MATLAB via Metastockread. They have data for the US, Australia and Singapore.

6

I basically agree with @John, let me expand: We want to model $y$ using a simple linear model, the most basic setup is $$y = c + \mathbf{X}\beta$$ with $y$ the $N$ observations, $c$ a constant, $\mathbf{X}$ the $N \times M$ matrix of regressors and $\beta$ a $M$-dimensional vector of coefficients. This model has $M$ parameters, the elements of $\beta$. ...

6

Financial economics is what economics calls finance. Finance is what finance calls finance. Less flippantly though, there's a long debate on whether finance is a subfield of economics, and this debate goes back at least to the PhD thesis of Markowitz. Prof. Milton Friedman famously opposed awarding Markowitz a PhD in economics from the University of Chicago ...

6

What you describe is known as the Equity Premium Puzzle - and it really is, as the name says, a real enigma: "The equity premium puzzle (EPP) is a phenomenon that describes the anomalously higher historical real returns of stocks over government bonds." Source: https://www.investopedia.com/terms/e/epp.asp#ixzz5HlCdHS2Z A good first introduction can be ...

5

This looks like a general equilibrium model in Economics. It should be described in most of microeconomics textbooks (e.g. this). Yes, you need a budget constraint here for$\ a$, otherwise your optimization problem makes no sense. Moreover, the household prefers consumption today to consumption tomorrow and, hence, you may want to enhance your model by ...

5

Information on the FOMC Meeting dates can be in the tables of this article and on the FED website but one would need to manually retype the data which takes time and is error prone. Here's a Python script to parse the meeting dates from the federalreserve.gov page that you linked: pastie.org/2566958. It pulls the dates from the url of the "Minutes" link for ...

5

Miscellaneous data, extending back hundreds of years in some cases, is available from Global Financial Data

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Futures and Forex: http://www.tradingblox.com/?page_id=218 Indicies, Forex, Futures: http://pitrading.com/free_market_data.htm Commodities, Forex, Stocks, Interest Rates, Mutual Funds, Hedge Funds and more: http://www.wikiposit.com

4

Mostly (macro-)economic but also stuff from xignite free (as of 2011-11-15): http://datamarket.com

4

Whether you are an institution or individual you if you want to find some data related to finance, you can check out from here: http://fundamentals.morningstar.com/ http://equityapi.morningstar.com/

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General data source: WRDS Fixed Income: Fed historical daily rates

4

I have yet to see Bloombergs open API in this thread... Bloombergs API This is the link to the actual API on that page. The second link is the actual link to the latest api

4

I have used both Xignite and FinancialContent for economic data and stock quote data feeds. The plus side of FinancialContent is that they have JavaScript widgets (free with ads or paid with no ads). Both companies offer JSON, XML and CSV formatted feeds.

4

What you are talking about is called regression using fractional polynomials and it has its merits. The canonical reference is this one: Regression Using Fractional Polynomials of Continuous Covariates: Parsimonious Parametric Modelling by Royston and Altman (1994) From the abstract: The relationship between a response variable and one or more ...

4

First, your statement that your utility function goes to infinity is wrong. It's minus exponenta. You can think of it as a minimum of $e^{f(x)}$ which is bounded below by zero whatever $f(x)$ is. In other words, your utility function is bounded above by 0. Second, maximizing expected value, you need to calculate it before deploying maximization techniques. ...

4

The master list already has dukascopy listed for forex historical tick data. Dukas also now has selected CFDs of indices, metal/energy, and individual stocks. The forex data for the majors go back to 1997 or so. It's free, so you get what you pay for. The data that is more recent (last 5 years) has almost 0 gaps on the majors and crosses. What was also ...

4

There is not a single 'interest-rate' to reduce, there are various interest rates in play. The central bank mandate is usually to control CPI or a similar measure of inflation (e.g. Bank of England's 2% inflation target for GBP). There are various tools for them to do this, including QE and setting the central bank rate. However, at the moment, the central ...

4

U.S. Government DID save American International Group (AIG) from bankruptcy, since it was considered too big to fail, actually: a lot of financial institutions were insured by AIG. This Investopedia page is a nice summary on the topic about AIG's bailout. Here (Investopedia again) about Lehman Brothers, that became really too much leveraged and exposed to ...

4

The general formula for conversion of "a to b" odds to a probability is $p=\frac{b}{a+b}$ http://www.calculatorsoup.com/calculators/games/odds.php So 8/15 remain implies remain with probability 0.652 8/4 for leave implies leave with probability 0.333 The amount 1-0.652-0.333 = 0.0145 represents the bid-ask spread or loss that you suffer (and the other ...

4

Suppose markets are perfectly efficient and asset prices reflect all available information. Under this assumption one expects current prices to be non-biased estimators of future prices. It is a common mistake to think that market efficiency implies $P_t = E_t[P_{t+1}]$! In general, the correct statements are: $P_t = \frac{E_t^Q[P_{t+1}]}{R_f}$ where $Q$ ...

3

Here's a snippet of a detailed list of data sources and tools which available on my blog at http://the-world-is.com/blog/resources/general-investor-resources/. Fundamental Financial Data Institutional: CompuStat (S&P Capital IQ) – Compustat offers what I believe to be the highest value instutional-level fundamental financial data. The data ...

3

Our startup SimFin, provides both historical and actual data for free, since we couldn't afford the pricey premium solutions back when we were students and wanted to overcome the hegemony of the data market. To this date, we have 70+ financial ratios, Financial statements (directly sourced from the SEC's XBRL data and up to 10y back; quarterly, H1 and 9M) ...

3

Volatility changes over time. Even if daily returns are normal, assuming the conditional volatility each day is known, the unconditional distribution of daily returns will have excess kurtosis. For example, if daily returns have a standard deviation of 1%, 90% of the time, and a standard deviation of 3%, 10% of the time, the presence of the high-volatility 3%...

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