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1

You could also try using Bloomberg's screener (EQS <GO>). You need to clarify your idea of a stock, are dual-listings of the same issue two stocks or one? What about company issues whose trading is currently suspended? Anyway, running the screener on just active stocks that are public companies, as of now, gives 354283 equity stocks. Edit: More in ...


6

Per the factsheet for MSCI ACWI All Cap Index (as of May 31, 2019): The MSCI ACWI All Cap Index captures large, mid, small and micro cap representation across 23 Developed Markets (DM) countries and large, mid and small cap representation across 26 Emerging Markets (EM) countries. With 14,752 constituents, the index is comprehensive, covering ...


0

Even when predicting asset returns with classical CAPM or Fama-French 3, 4, or 5 factor models, estimates will tend to have significant estimation error, and as explained by the others, univariate vs multivariate are equivalent. The difficulty of predicting asset means has been well known since Merton (1980) and that's why most people, at least in asset ...


1

You can use the company specific yield gap( dividend yield / company's long term debt yield) as an indicator to switch between debt and equity. Larger yield gap indicates equity is cheaper compared to debt.Tons of such indicators are available which compare the relative valuation of debt and equity. You can overlay it with momentum also. Someone suggested ...


1

I answer from the point of view of a small price-taker investor. Investing in debt and equity depends on very different analysis. If on one side you have the ability and willingness to repay depending on the credit quality of an issuer, on the other you have the ability of generating consistent cashflows with a well managed liquidity and long-term growth. ...


0

They say historical returns are no indication of guaranteed future profits for liability reasons so companies cover their asses.


0

Here is a short python3 script that will parse the info that you're looking for from Yahoo Finance: import requests import json import pprint symbol='T' url='https://finance.yahoo.com/quote/' + symbol resp=requests.get(url) r=resp.text i1=0 i1=r.find('root.App.main', i1) i1=r.find('{', i1) i2=r.find("\n", i1) i2=r.rfind(';', i1, i2) jsonstr=r[i1:i2] ...


-1

Under Efficient Market Hypothesis, future prices are nothing but the expected value of historical prices, given a probability and an information structure. Looking at historical prices can be useful. Indeed, a lot of the financial literature, spanning from Risk Management to Portfolio Management uses historical values. As you suggest, however, in case of ...


1

Lots of different ways to do it that typically involve the following: (1) Identify starting universe. (2) Source and process underlying attribute data for each holding (for instance, for a low vol factor, possibly ST and LT vol for each security). (3) At this point, there is tons of variability. Once you have your factor data, some simply use it for ...


1

First you need to start with an investible universe of securities that can be used to retrieve data on. From there, you'll need to compile a list of each individual factor that you'd like to screen for (Momentum, Value, Growth, Div Payers, High Multiple, Asset Quality etc...) and create a metric of measurement for each factor. Enter into some sort of ...


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