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18

Because of: The (extreme) dominance of noise over signal The prevalence of non-repeating patterns (many of which we know are not going to repeat) A pathetic sample size for cross-validation Regime changes due to exogenous events. These are typically in the cross-val window which makes it even worse. (GFC, financial integration, trade law changes, interest ...


7

I recommend reading Cao, Hansch, and Wang (2004) "The Informational Content of an Open Limit Order Book". They present a simple model for an order-book price called the weighted price ($\mbox{WP}$): $$ \mbox{WP}^{n_1 - n_2} = \frac{\sum_{j=n_1}^{n_2} (Q_j^d P_j^d + Q_j^s P_j^s)}{(Q_j^d + Q_j^s)} $$ Where: $n$ is the order book level $Q_j$ is the size at ...


6

I think one has to distinguish between pricing and fitting/reproducing empirical stock returns. A model might fit the empirical stock returns extremly well but fail to reproduce derivative prices. In my answer I will assume that you are interested in reproducing the empirical stock returns. Mandelbrot and the Stable Paretian Hypothesis The most salient ...


4

My take on the whole issue is as follows: We cannot be sure to find the one and only true model, the only thing we can do is to identify the most prevalent so called stylized facts and try to model them parsimoniously. The following paper was already mentioned in the comments: Empirical properties of asset returns: stylized facts and statistical issues by ...


3

2) Alternative to Fama-MacBeth is Fama-French approach. Explanation of difference see, for example, here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1271935 Fama-French approach was used by Carhart (introduced momentum), Pastor-Stambaugh (introduced liquidity), Fama-French themselves (used it to build 5-factor model), and many other (elsevier or ...


3

I was going to comment but it turned out to be quite elaborate. My experience with certain AI/ML methods is that they're not deterministic. Take RBM for instance, a very wide-spread paradigm. To train such a machine you have two approaches, backpropagation or Kullback-Leibler divergence. Both require you to initialise the machine to a random state. And ...


3

Definitely time series analysis. What you essentially want to do is some form of impact analysis. this can be done naturally using multivariate time series models like Vector Auto Regression models. Also when working with data to model liquidity you might want to use some specialized procedures like GARCH and ACD. Further there are methods to model non ...


3

Your first definition is wrong; I'm not sure where you got that from. Your second definition is correct: the ISO alerts the exchange that the submitting party has taken responsibility for RegNMS and requests a fill at only that venue's price; there is no routing away. Obviously, there is a huge red-tape burden to get permission to do this.


3

There is a major bug when you are getting information from exchanges outside USA. If you get the adjusted prices for BOVESPA (Brazilian Stock Exchange) for example, it will only consider the events that happened using the US Calendar and not the Brazilian calendar of working days, this leads to a lack of information on other exchanges. Be aware of this if ...


3

I can offer an intuitive answer. The limit when your equally weighted portfolio is continuously rebalanced will give you the geometric mean. This is because the excess return of the better performing strategies will be allocated towards the least performing strategies, compounding high returns with low returns.


2

Yahoo data is good enough, but it has its quirks. As people have mentioned, sometimes it does miss out on corporate actions. I remember a while back I was looking at price for Ford (F) around 1999 , and computing my own adjusted close using yahoo's methodology and noticed that yahoo was missing a dividend payment in 1999(which I verified from bloomberg). ...


2

Morningstar is the best one I've found so far. It has all the data required and, as I've recently found, can export it quite easily to CSV. The key is to send the right parameters to /ajax/ReportProcess4CSV.html. In what scenarios scraping this is allowed, I do not know. I will endeavor to find out once I start building this application. For anyone looking ...


2

Marketwatch has financials for a lot of companies, including H&M: Annual Financials for H&M Hennes & Mauritz AB Series B


2

As someone pointed out, most times you do not have a choice because how the order book is disseminated heavily depends on the exchange. In Asia there are exchanges that even show the name of the counter party (though only aggregate volume not each order). Other exchanges provide a full "view", again others price level aggregates. Broadly speaking, some ...


2

The main problem with hypothesis testing is going to be survivorship bias. Any manager with a track record you're looking at is only there because they haven't performed badly -- if they perform badly then investors withdraw their money, they collapse, and you don't have their data to do the hypothesis test on! So even if all the managers were investing in ...


2

It's simply the difference between the two values. High-Low gives you an idea about the total price movement over the tick period, Open-Close gives you an indication of the direction of the move. If Open-Close is negative, the price went up, and vice versa. High-Low obviously is always positive.


2

It's probably because of the strong long-standing statistical underpinnings in economics and econometrics, and overall, risk prediction. For example, look at current research with fat-tail distributions and calculations for Expected Tail Loss (ETL), etc. These studies fit Student's t, Normal, Stable, and Pareto probability distributions to data and report ...


2

You are not doing anything wrong. You just need to multiply the absolute return by the currency conversion factor. Example: You trade 200,000,000 yen notional and generate a return of 16% on that notional, then simply multiply 32,000,000 jpy gain by your conversion factor 0.0126 to yield a return of 403,200 USD. The return of 16% was generated on the ...


2

Breakpoint approaches Test based To be well received in a financial econometrics journal, you want test-based approaches. Depending on your question it is common to see a linear regression (least squares) where the parameter suspected of breaking is interacted with an indicator function $I(E)$ where $E$ is the event in question; this function assumes a ...


2

I am not aware about any rule of thumb on market impact during fixing auctions (nothing comparable with the usual square root rule for meta orders market impact). In Navigating Liquidity 6 - A global menu for optimal trading, there is a study about the liquidity during the fixing auctions, you should start from here. Another important point is the data you ...


2

The key assumption is that there is no time-series correlation between the error terms. Fama-MacBeth can deal with cross-sectional correlations. See Samuel Thompson's "Simple formulas for standard errors that cluster by both firm and time" in the Journal of Financial Economics (2011) for a treatment of different regression methods for testing equity ...


2

There are no "fundamental algos" analogous to "technical algos". Instead, quantitative useof fundamental data assumes applying multifactor models to predicting returns and other intrument parameters. That models vary from "academical" (like Fama-French 3-factor or Chen, Roll, Ross) to proprietary models of guys from industry: MSCI Barra, Bloomberg, CSFB, ...


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

I believe historical Reuters data can be downloaded online. Search for Reuters Key Developments Corpus. The author of this paper (http://people.csail.mit.edu/azar/wp-content/uploads/2011/09/thesis.pdf) used data like this.


1

I think your request is too broad. ITUB, for example is an Italian company and has ADRs traded in several stock exchanges. Hence, if you do search in Eikon, you find multiple tickers for it. And I failed to find critea, which could yield single return value for each tickers you supplied. I used request: =RSearch("Equity", "TickerSymbol:" & B3 & ...


1

That's a great question and it is what I always wanted to try to do. I guess I found a solution using PDE approach. Change of numeraire would be more intuitive indeed, but I am not very good in stochastic calculus. The idea is as follows: 1) Let's consider portfolio $\Pi = V(X,Y,t) - \Delta_X X - \Delta_Y Y$. I will found $\Delta_X$ and $\Delta_Y$ such ...


1

No you certainly should not use in simulation any data that you don't know in real environment because simply results will be much different. Simulation should be created in environment as much possible similar to real environment. You basically should use only Open values for making trades, High/Close/Low you can use for indicator calculation of past ...


1

Its a bit of a broad and almost philosophical question to be honest. Just two things that pop in mind are (A) the money supply (& possible inflation) in combination with interest rates - this will drive the major money allocation in the world. As you see now with S&P at record highs on the back of massive quantitative easing and low interest rates. ...


1

I think Hull treats dilution in his book, and it's extensible to this case. For what it's worth, the strike is typically set low enough that there's little doubt about exercise, meaning there's not much point in modeling the optionality. Most people concentrate on the dilution alone -- particularly the question of the change in fully diluted versus ...


1

Beside the lag issue, I do not believe that the negative correlation between Consumer Staples and sentiment is counter-intuitive. The S&P SPDR XLP ETF (Consumer Staples) offers a broad exposure to defensive mega-cap consumer names. Spending on consumer staples is usually characterized by an inelastic demand. Whether the economic climate is strong or ...



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