Hot answers tagged

2

I found what I was looking for at Nasdaq.com. This information wasn't available months ago when I initially built my trading strategy. Basically Nasdaq.com provides a CSV file of all symbols that are ETFs. And its free. http://www.nasdaq.com/investing/etfs/etf-finder-results.aspx?download=Yes


2

The easiest way to think of this is as follows: Settlement Price - Price at which the exchange margins all accounts for those options. Closing Price - Mid/Bid/Ask of Active Market at the exchanges last trade time. E.g. for TY Contracts this is at 5pm EST vs. a Settle Time of 3pm EST. Last Trade Price - Not all options trade every day. This is the price ...


1

Google uses the 1 factor CAPM model developed by Fama French (1974). Its a simple linear regression with the stock as dependent variable and the market portfolio as independent


1

Metastock uses a binary format that you would have to convert to text before exporting it to a SQL table. Also, there is no Python library that could extract data directly from Metastock's end-of-day servers. You may consider quandl which allows Python developers to download pricing data as well as economic indicators. You can download CSV, JSON, or XML. If ...


1

We consider the forward value, which can be employed to estimate the equity value. Let $T_1=0.5$ be the dividend payment time, and $T=1$. Moreover, let $r_1=5\,\%$ be the annualized interest rate to $T_1$, $r=6\,\%$ be the interest rate to $T$, and $d=5$ be the dividend payment. Then, the forward value, under the risk-neutral measure with the deterministic ...


1

The relationship between interest rates and equity prices being at best unstable and weak, I'll assume that the level of interest rate is irrelevant here. So the answer to your question (price of the equity in a year) is 95, everything else being equal. Of course it's unlikely that the equity will actually price at 95 in a year due to market movements, but ...


1

First it would help to know some more details about what you mean by maximum capacity. However here are a few things to consider. Do you have a simulator you use to simulate your strategy with market data? If answer to above is yes then you can clearly see the linear impact due to market liquidity constraints for your increased size. Now 2 is easy only if ...


1

As soon as you're comfortable with Python, let's do this exercise in three steps: Download data and calculate cumulative returns (or value of your position as if you invested $1 in each of the stocks) Define function that will capture stock movements in excess of predefined threshold, 10% in this case. This function is going to be the "indicator" you ...



Only top voted, non community-wiki answers of a minimum length are eligible