Richard Herron
  • Member for 11 years
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How to generate a random price series with a specified range and correlation with an actual price?
1 votes

If you want to make the returns "random", then you will have to generate the whole price paths that meet your correlation criteria and then discard results that don't fit your price criteria. This isn'...

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zero-sum active management riddle
3 votes

@Tal and @Patrick point out that there are more than two subsets of investors. If we divide the active investors into smart and dumb, we can reconcile their results (i.e., they only look at active, ...

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How to check if a timeseries is stationary?
3 votes

The tseries package has GARCH models. Here is some simple code: library(quantmod) library(tseries) getSymbols("MSFT") ret <- diff.xts(log(MSFT$MSFT.Adjusted))[-1] arch_model <- garch(ret, order=...

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Garch modelling on Stata
5 votes

I don't use Stata often, but the help() function is typically very good. Try help(garch). It looks like the command is garch _depvar_ _indepvars_ _options_ Here's the help page on the web.

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Has high frequency trading (HFT) been a net benefit or cost to society?
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23 votes

The lead paper in the January 2011 Journal of Finance (Hendershott, Jones, and Menkveld) addresses algorithmic trading (AT). In short, they find that AT improves liquidity as measured by bid-offer ...

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How many explanatory variables is too many?
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4 votes

“Make things as simple as possible, but not simpler.” The problem you want to avoid is (near) multicollinearity. The tip-off will be that adding/removing a regressor will significantly change the ...

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Indicators and research for stress-based investment strategies
4 votes

Post-crisis there has been some research that uses return series for financial institutions to predict downturns. I think the major ones are CoVaR (Adrian and Brunnermeier) and CATFIN (Allen, Bali, ...

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Is Conditional Value-at-Risk (CVaR) coherent?
9 votes

$VaR^\alpha$ is not a coherent risk measure because it fails sub-additivity (a coherent risk measure is monotonic, sub-additive, positive homogenous, and translation invariant). The expectation ...

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Control for bid/ask bounce in high-frequency trade data?
14 votes

IMO transaction data is a better approach, because you have both sides of the trade agreeing that the price is "right." The literature tends to decompose the transaction price $P$ into a true/...

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What is the unit of the Distance to Default measure?
Accepted answer
10 votes

Distance to default $DD$ should be measured in standard deviations. You convert this into a probability $p_{default}$ using the normal CDF: $p_{default} = N(-DD)$. So if $DD = 2.978$ then the firm is ...

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Debunking risk premium via "hedging" argument? (or why even in the real world $\mu$ should equal $r$)
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5 votes

If you're long the underlying and short the futures contract, then you have no risk and earn the risk-free rate. You get into the position at $S_0$ and will be able to get out of the position at $F_0$ ...

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Using linear regression on (lagged) returns of one stock to predict returns of another
11 votes

A few thoughts. Yes, your return series are autocorrelated (i.e., stocks don't exactly follow a random walk), so you should use Newey-West standard errors. If you do this as a univariate regression $...

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Simulating Returns
4 votes

I have a few thoughts, but no real answers :). You take the returns from the DAX, which isn't normal, then make it normal and apply normal noise to it. It seems that you could be slightly better off ...

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Are two identical time series cointegrated?
9 votes

Let us test that $x$ and $y$ are co-integrated, say that $x_t, y_t \sim I(1)$. In the Engle-Granger we test stationarity of the error term in $$y_t = \alpha + \beta x_t + u_t$$ which we estimate as $$\...

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Mean reverting Indicator
5 votes

I think of mean reversion as more of a single stock phenomenon. In aggregate, these ididosyncratic mean reversions should offset one another and make the market smoother than its component stocks. ...

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data on historical stock price of bankrupt companies
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12 votes

Google and Yahoo finance have a survivorship bias -- they only include firms that are still around. I know of no free source that provides the data you seek. I get my data from Compustat and CRSP via ...

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An equation for European options
Accepted answer
3 votes

I think you provided the two that must be met. Pricing must be linear.$$V(\ldots, 2P) = 2 \cdot V(\ldots, P)$$ And pricing must meet the law of iterated value. Where $\tau \in (t, T)$ $$V_t(\ldots, \...

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Given two portfolios with identical correlation matrices, which one will have a better risk/reward ratio?
6 votes

From a theoretical point of view (you mentioned beta, so assume we're in a CAPM world), you should hold the market portfolio (let's assume S&P500 index) and be long (or short) the risk-free asset ...

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Is statistical arbitrage on FX possible?
4 votes

Disclaimer: I know nothing about FX trading, other than that I've heard something to the effect of "The first rule of FX trading is that you do not trade FX. The second rule..." you know how it goes. ...

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How to perform risk factor calculation?
10 votes

I don't have much to add, but wanted to address the "price of risk" question. APT is kind of "economics"-free and tries to price assets without the utility maximization required in CAPM/ICAPM. Ross's ...

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Can the futures market's open interest predict commodity, treasury, and equity returns?
6 votes

Maybe a better question title is "Can futures market open interest predict commodity, treasury, and equity returns"? I saw this paper in an earlier form and it still baffles me. Superficially, it ...

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Using Black-Scholes equations to "buy" stocks
9 votes

You can look at equity as a call option on the firm. In theory this illustrates the differences between holding equity or debt. The quick and dirty is that equity holders own the firm, but only ...

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Discrete-time model: stock dynamics
2 votes

Have you considered Dynamic Liner Models? I don't know enough about currencies or DLMs to give any more guidance, but it may be worth a few minutes of googling to see if you can apply it.

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How to compute the Value-at-Risk of the sum of two dependent lognormal random variables?
1 votes

For independent random variables the variance of a sum is the sum of the variances. If the random variables are not independent, then there's a covariance term $$Var(X_1 + X_2) = VarX_1 + VarX_2 + 2*...

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Predicting Price Movements on a Betting Exchange
6 votes

Have you looked into "noise trader" models? This seems like a market that is mostly noise. A few betters may have some information on or real knowledge of who might win, but certainly nothing like ...

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Data on US bankruptcy rate vs. standard valuation ratios
Accepted answer
3 votes

I get my stock data from Univ of Chicago's Center for Research in Security Prices (CRSP), which keeps stocks after delisting, so there's no survivorship bias. I assume that Bloomberg and Reuters do ...

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Do low volatility stocks outperform high volatility stocks over the long run?
6 votes

The theory predicts that expected risk and expected return should be positively related. But no one has convincingly proved this. The results are very sensitive to how you determine the expectations ...

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How do I reproduce the cross-sectional regression in "Intraday Patterns in the Cross-section of Stock Returns"?
11 votes

The $R^2$s are usually close to zero for single stock regressions. The big $R^2$s that a lot of asset pricing research shows is by forming portfolios. Forming portfolios cancels a lot of the ...

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How would one price a "credit event binary option"?
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5 votes

I would see if a binomial tree gives reasonable answers (i.e., can you get close to the CEBOs with high volume). You could determine the probability of default over a given interval using the KMV-...

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Supply and Demand of Oil
5 votes

This occurs because the price elasticity of demand for oil is near zero, which is to say the demand curve is nearly vertical. This is partly a limited rate of production story (i.e., in the short term ...

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