# Tag Info

10

I think you are interpreting too much into the matter. The $-\frac12\sigma^2$ is just a correction term that comes from Jensen's inequality. You need this when switching from supposedly symmetric returns (normal distribution) to the skewed price process (log-normal distribution). I think there are no deeper truths to be found here.

6

You can get quite a bit of structured data for free from the SEC's Edgar system via XML: http://www.sec.gov/edgar/quickedgar.htm http://xbrl.sec.gov/ Even the older stuff that's not xml based, is fairly readily parsable. Another source that is easier to deal with, but not free, and possibly expensive, is CapitalIQ (where Yahoo Finance gets their data ...

5

Proof: Recall that $$\beta_{i} = \frac{\mathrm{Cov}(r_{i},r_{m})}{\mathrm{Var}(r_{m})}.$$ Now, the returns on unlevered and levered equity are given by $$r_{U} = \frac{\mathrm{EBIT}(1-\tau) - \mathrm{CAPEX} + \mathrm{Depreciation}}{E_{U}}$$ $$r_{L} = \frac{\mathrm{EBIT}(1-\tau) - \mathrm{CAPEX} + \mathrm{Depreciation} + \mathrm{Net\ Debt} - \mathrm{... 3 Compustat supports unlimited data export keeps the history of disbanded entities provides restatements since 1950 + point-in-time data since 1986 coverage since 1950 list of variables (data guide) Compustat is a S&P subsidiary. It goes as a plugin for CapitalIQ (also S&P), WRDS, CRSP, and other platforms. Pricing starts from \3k. A platform ... 3 You can use refined methodologies but if you just need a rough estimation of liquidity, you can simply use an average of daily volume over N days. In practice, for equities, people tend to use N = 20 or 30. Once you have the average daily volume (say 100,000 shares), you compare it to your holding (say 50,000 shares) to determine the the size of your ... 3 You can download the company list csvs from nasdaq.com, it has the mapping you need. 3 This is a very subjective question. One thing you need to understand is that there are many types of quants and it is not always about predicting the future returns. Many quantitative analysts are involved in market-making, this is where you sell products at a slight cost to customers and try to stay more or less neutral to market moves. When you read about ... 3 One thing to keep in mind here is that the world of risk-free/arbitrage-free models is not necessarily the real world. Specifically, this equation$$ \mu = r - \frac{1}{2}\sigma^2  occurs not because this is the way stocks behave in reality (they don't! For S&P 500, long-run $\mu$ is closer to 6-9%, if I recall correctly), but because using any ...

3

If you have a friend studying at almost any university you can get access to WRDS. Inside WRDS just go to Compustat which has all the info you need for dates since 1950.

3

Quantopian provides both the fundamental data (from Morningstar), as well as the backtest platform to reproduce results from the books you mentioned. Here's the introduction to our fundamentals offering: https://www.quantopian.com/posts/fundamental-data-from-morningstar-now-available-for-backtesting (disclosure: I'm the ceo of quantopian)

2

Examples for cash-settled futures are: Interest Rate futures Futures on implied Volatility (e.g. on VIX) Futures on Commodity Indices: Indices such as the Dow Jones UBS consist of futures themselves. Furthermore in asset management you usually don't want physical delivery of the underlying (oil, gas, coal, pig, ... ;) Futures on Equity Indices The ...

2

It's just cash settled, like a bet on a sports game. This was somewhat controversial when the financial index futures were first invented.

2

Let's start with question (2). If you are not obtaining $S=1.5295e+009$ after backwardation, then you have a bug in your binomial tree code. You may wish to find and eliminate that before proceeding. One simple check is to make all the terminal nodes have value 1.0. You should obtain that the initial node has value $e^{-rT}$. This assumes, of course, ...

2

There are two mainly (good) free sources available online: wolphramalpha.com Quandl They report the mainly market and fundamental data, so you will not find any particular fundamental accounting ratio. In the case you need particular ratio or data, you should get some better financial data provider, as, for instance, Bloomberg or Thompson Reuters.

2

It turns out that GBM with constant drift and constant volatility is not really used in real life. It is well known that volatility as well as drift may vary over time. Hence, if you want to use a model with time-varying parameters, you need to come up with a model to define $\mu_t$ and $\sigma_t$. There are classic models that use some mean-reverting ...

1

Morningstar Morningstar partnered with Quantopian, and the latter published the structure of Morningstar's equity fundamentals database: https://www.quantopian.com/help/fundamentals Quantopian users can use this data for free.

1

You can pull Financial Statement (Income Statement, Balance Sheet, and Statement of Cash Flows) data from Google Finance with the getFinancials function in the quantmod R package. > library(quantmod) > getFinancials('IBM') > head(viewFin(IBM.f, type = 'IS')) Annual Income Statement for IBM 2014-12-31 2013-12-...

1

I think one of the main liquidity measures is the one from Pastor and Stambaugh (2003). You can use it for both individual stocks or indexes. Just run the following intra-month regression with daily data: $r^e_{i,d+1,t} = \theta_{i,t}+\phi_{i,t}r_{i,d,t}+\gamma_{i,t}sign(r^e_{i,d,t}) \times v_{i,d,t}+\epsilon_{i,d+1,t}$. Where $r^e_{i,d+1,t}$ is the ...

1

I would consider Amihud (2002) as a good first approximation with that level of data.

1

According to this reference there are indeed several types of P/E-Ratios (trailing P/E that is based on previous earnings and forward P/E which is based on projected earnings) Also several books calculate the P/E according to the following formula $P/E-Ratio = \frac{Average Common Stock Price}{Net Income Per Share}$ (Confer source1, source2 and source3) ...

1

There a likely multiple source of this indicator becoming negative in general. In this particular case this is probably related to the investment of Japanese monies in foreign bonds. Which in turn looks to be an effect of the quantitative easing by the Bank of Japan.

1

I see the question and answers are rather old here but I just ran across quandl which provides access to a variety of SEC data with a free API key.

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