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I make money selling covered calls on FX spot options, and some of my friends want to buy in to this without having to trade their own accounts. One method is for each of them to get an account, and have me trade it, but that doesn't scale well: I really don't want to be trading 10 accounts. The other...
Hedgefund-like behavior for covered call selling account?
Is there a popular curve fitting formula of options skew vs strike price or vs Delta?
If I were you I would be very cautious when playing this mean reversion. For several reasons. 1/ You never know when this spread is going to close, and the contracts on which you enter the trade may have expired. Then you would have rolled. In fact the arbitrage can close without any opportunity to capture it becaus...
Have you considered a Monte Carlo simulation on your returns? Then you could look at the distribution of Maximum Drawdowns. -Ralph Winters
This is probably not the best place to ask this question but the one that seems most appropriate on stack exchange(doesn't seem to be an economics one). Anyways, My question, a serious one and not politically motivated, is about "big oil". Does anyone know why we generally see "big oil" have record profits usuall...
This is probably not the best place to ask this question but the one that seems most appropriate on stack exchange(doesn't seem to be an economics one). Anyways, My question, a serious one and not politically motivated, is about "big oil". Does anyone know why we generally see "big oil" have record profits usuall...
> *demand surely decreases? Maybe this is not true because the high demand for oil?* Demand for oil, like grains, is very inelastic. People have a very hard time changing their energy consumption habits when price shocks happen. Some of this is unwillingness to change, but a lot is that there are very few alternati...
What are the standard methods to price american call/put options on illiquid underlyings (such as a share of a non listed company)?
If you have a bunch of different econometric data (e.g. indexes, FX, commodities, interest rates...) you can try to find a formula to see if there is any relationship in the data - e.g. to forecast it by this discovered pattern. What I am asking here is a little bit different: Is there another way in the se...
What are the most used/mature/promising commercial solutions today which handle backtesting/ automated trading needs? I'm talking about vertical product suites like [QuantFactory][1] or [Deltix][2] which address market data capture, historical data, CEP, backtesting, trading, etc. (I would be more specifically inter...
As of right now, the price of Brent Crude is $\$$111.59/bbl and the price of WTI Crude is $\$$98.36/bbl. I'm well aware that futures markets don't set the spot price for oil, but actual supply/demand does. And, that I don't have access to enough refinery/supplier data to figure out the supply/demand balance for WTI...
Some LinkedIn groups are particularily adequate to post these questions. Your question has already been asked in "Automated Trading Strategies" at this URL: [Seeking input on QuantFactory, Deltix and 4thStory: Professional end-to-end Automated Trading Solutions][1]. Feel free to let us know the state of your resear...
Some LinkedIn groups are particularily adequate to post these questions. Your question has already been asked in "Automated Trading Strategies" at this URL: [Seeking input on QuantFactory, Deltix and 4thStory: Professional end-to-end Automated Trading Solutions][1]. Feel free to let us know the state of your resear...
The current jump in price is because one or more suppliers are dropping out. That shifts the supply curve to the left such that for the same demand for oil, the new price is now further up the steeper part of the curve (see the plots below). The demand for oil will react to that new price, but it takes time. So...
The current jump in price is because one or more suppliers are dropping out. That shifts the supply curve to the left such that for the same demand for oil, the new price is now further up the steeper part of the curve (see the plots below). The demand for oil will react to that new price, but it takes time. So...
The current jump in price is because one or more suppliers are dropping out. That shifts the supply curve to the left such that for the same demand for oil, the new price is now further up the steeper part of the curve (see the plots below). The demand for oil will react to that new price, but it takes time. So...
What are the standard methods to price american call/put options on illiquid underlyings?
Could somebody advise me good literature on the topic? In finance (since people would like to make money there) it is sometimes difficult to find relevant literature because even if the book's title is not "We'll tell you how to earn $10^6" the content of the book still can be bad. On the other hand maybe it is not ...
Below, I see a lot of support and resistance. Here's the code: x <- cumsum(rnorm(1000)) plot(x, type="l", main="Support and Resistance") ![enter image description here][1] [1]: https://i.stack.imgur.com/ZIr74.jpg Edit (03/03/2011) ================================================ Gortau...
If I were you I would be very cautious when playing this mean reversion. For several reasons. 1/ You never know when this spread is going to close, and the contracts on which you enter the trade may have expired. Then you would have rolled. In fact the arbitrage can close without any opportunity to capture it becaus...
Below, I see a lot of support and resistance. Here's the code: x <- cumsum(rnorm(1000)) plot(x, type="l", main="Support and Resistance") ![enter image description here][1] [1]: https://i.stack.imgur.com/ZIr74.jpg Edit (03/03/2011) ================================================ Gortau...
Can anyone provide a simple example of picking from two distributions, such that the two generated time series give a specified value of Pearson's correlation coefficient? I would like to do this in a simple monte-carlo risk assessment. Ideally, the method should take two arbitrary CDFs and a correlation coefficient ...
Has anybody else out there made this switch? I'm considering it right now. What were the negatives and positives of the switch?
What is a persistent varriable?
What is a persistent variable in the context of regression analysis? For example, dividend to price ratio (D/P) is considered to be persistent variable when used to model future returns (Stambaugh Bias literature).
What is a persistent variable?
Maybe I completely misunderstood the question, but it seems to me that you are looking to find a model structure as opposed to fit a specified/known model. In your context the model specification (the trading rules) are unknown... Am I right? If that Is the case, maybe genetic programming: http://en.wikipedia.org...
Does anyone know of a python library/source that is able to calculate the traditional mean-variance portfolio? To press my luck, any resources where the library/source also contains functions such as alternative covariance functions (etc. shrinkage), Lower partial moment portfolio optimization, etc... I have deve...
To the degree in which it's possible, I'd like to know what the community believes are the objective skills/knowledge required to run a successful Quant book. I'm not interested in strategies, obscure maths or programming languages here. I'm interested in the practical realities of successfully managing/executing...
What is the varswap basis? I am not completely sure what this number represents. Is it the basis between the estimated future realized volatility and the vol surface implied volatilty at a specified tenor?
Varswap Basis - What is it in practice?
CBOE has introduced [credit event binary options][1], kind of as a retail trader's CDS. These binary options are worth **$1** if there is a credit event (ie, bankruptcy) before expiration, and **$0** if there is no credit event (ie, solvency) at expiration. The option's premium is quoted in pennies and indicates the ch...
How would one price a "credit event binary option"?
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-Merton model. Then use the probability over each of these intervals to determine the probabilities for each of the branches ...
Persistent autocorrelations in volatility processes are due to long term memory only. I cannot help but sigh at the hundreds of papers which work under this assumption. Haven't people heard about regime shifts?
How do bond pricing formulae differ between the US, UK and the Euro zone?
This question is inspired by the remark due to Vladimir Piterbarg made in a related [thread][1] on Wilmott back in 2004: >Not to be a party-pooper, but Malliavin calculus is essentially useless in finance. Any practical result ever obtained with Malliavin calculus can be obtained by much simpler methods by eg differ...
How do practitioners use the Malliavin calculus (if at all)?
I'm looking at doing some research drawing comparisons between various methods of approaching option pricing. I'm aware of the Monte Carlo simulation for option pricing, Black-Scholes, and that dynamic programming has been used too. Are there any key (or classical) methods that I'm missing? Any new innovations? Reco...
Here are a few links: http://www.economagic.com/ http://www.eia.doe.gov/electricity/data.cfm http://www.drought.unl.edu/dm/source.html http://gcmd.nasa.gov/KeywordSearch/Home.do?Portal=GCMD&MetadataType=0
I'm looking at doing some research drawing comparisons between various methods of approaching option pricing. I'm aware of the Monte Carlo simulation for option pricing, Black-Scholes, and that dynamic programming has been used too. Are there any key (or classical) methods that I'm missing? Any new innovations? Reco...
I'm currently studying for my undergrad in CS, and considering to do a grad in both CS and Math. I would like to see what you guys would recommend to prepare myself for a field as a Quant. I am specifically interested in Algotrading (algorithmic quant) position. To be able to write models and software to do automate...
Does the gamma function have any application in quantitative finance?
Here is a recent article from Forbes which seems to indicate this. Does anyone have any supporting or contradicting evidence to this claim? http://www.forbes.com/forbes/2011/0314/investing-malcolm-baker-stocks-google-harvard-low-risk.html -Ralph Winters
Do low volatility stocks perform better over the long run than high volatility stocks ?
recently, I was trying to reproduce the results of this research: ["Intraday Patterns in the Cross-section of Stock Returns"][1]. The authors used cross-sectional regression to determine which intra-day lags have predictive power. From my understanding by doing cross-sectional regression I have to use all variables...
Here is a [recent article from Forbes][1] that seems to indicate this. Does anyone have any supporting or contradicting evidence to this claim? [1]: http://www.forbes.com/forbes/2011/0314/investing-malcolm-baker-stocks-google-harvard-low-risk.html
Do low volatility stocks perform better over the long run than high volatility stocks?
Recently I was trying to reproduce the results of this research: ["Intraday Patterns in the Cross-section of Stock Returns"][1]. The authors used cross-sectional regression to determine which intra-day lags have predictive power. From my understanding by doing cross-sectional regression I have to use all variables ...
On a betting exchange the price (the odds that an event will happen expressed as a decimal, 1/(percentage chance event occurring) of a runner can experience a great deal of volatility before the event in question begins. Since very little about the event in question actually changes before it starts the movement in pri...
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 idiosyncratic returns, which has a smoothing effect. The $R^2$s should be low here, although I don't see any in the paper for ...
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 idiosyncratic returns, which has a smoothing effect. The $R^2$s should be low here, although I don't see any in the paper for ...
If orders are filled pro rata, is there still incentive to engage in HFT? Because pro rata nullifies the time precedence rule, my intuition is no, but I figure there could be other aspects to it I'm unaware of.
Does HFT make sense in a pro-rata market?
Here is a [recent article from Forbes][1] that seems to indicate this. Does anyone have any supporting or contradicting evidence to this claim? The study cited studied returns for the entire stock market and the 1,000 largest stocks from 1968 to 2008. Note that the answer to this question is really a simple yes or n...
This current paper is highly relevant to your question:<br> [Risk and Return in General: Theory and Evidence (Eric G. Falkenstein)][1] > Empirically, standard, intuitive measures of risk like volatility and beta do not generate a positive correlation with average returns in most asset classes. It is possible that r...
At work we were talking about currency hedging our equity index exposures but I am struggling to understand how this happens in a typical iShares ETF. If we take the [Japan ETF IJPN][1] then we see this index is against the Japanese index. However it is priced in GBP and its base and benchmark currency is USD. ...
Most brokers compute rollover once a day (2200 GMT), but OANDA calculates it continuously. I thought I'd cleverly found an arbitrage opportunity, but it turns out OANDA knows about this *and* advertises it. Quoting from http://www.oanda.com/corp/story/innovations Professional traders can exploit ...
This current paper is highly relevant to your question:<br> [Risk and Return in General: Theory and Evidence (Eric G. Falkenstein)][1] > Empirically, standard, intuitive measures of risk like volatility and beta do not generate a positive correlation with average returns in most asset classes. It is possible that r...
On a betting exchange the price (the odds that an event will happen expressed as a decimal, 1/(percentage chance event occurring) of a runner can experience a great deal of volatility before the event in question begins. Since very little about the event in question actually changes before it starts the movement in pri...
Can someone explain to me the rationale for why the market may be moving towards OIS discounting for fully collateralized derivatives?
Rationale for OIS discounting for collateralized derivatives?
The OIS rate is more stable than Libor, right? And according to [this article][1] from *Risk Magazine*: > The party that is owed money at the end of the swap will have been paying an OIS rate on the collateral it has been holding, and so the ultimate value of the cash it will receive will be the sum it is owed minus...
Does anyone know of any research or data on US corporate bankruptcy rates as a function of standard valuation ratios, such as P/B, P/E, etc.? I'm trying to adjust the results of backtests to account for survivorship bias. My first thought was to put an upper bound on the impact of survivorship bias by assuming a ce...
I've only recently begun exploring and learning *R* (especially since *Dirk* recommended *RStudio* and a lot of people in here speak highly of *R*). I'm rather *C(++)* oriented, so it got me thinking - **what are the limitations of R**, in particular in terms of performance? I'm trying to weigh the *C++/Python/R* al...
I try to implemente the LSM method with this algorithm: but my price are always too low. By example for a american put with follow parameter : S0 = 36, Strike = 40 , rate = 6%, T = 1 year, discret path = 50, volatility = 20% I found 4 $\dollar$ but in their article Longstaff and Schwartz found 4,7 dollar. With a v...
I try to implemente the LSM method with this algorithm but my price is always too low. By example for an American put option with the following parameters: > S0 = 36, Strike = 40, rate = 6%, T = 1 year, discrete path = 50, volatility = 20% I got 4 dollars, but the Longstaff and Schwartz article lists 4.7 dollars....
I'm having a hard time getting my expected loss calculations to tie out with the standard recursion method when implementing the proxy distribution algorithm described by the Back To Normal CDO paper by Shelton. Anyone have working code examples for this?
Any example code implementing the Shelton CDO 'Back To Normal' Paper?
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 equity markets where there are a lot of people who really know the ins and outs of the firms they're trading. The classi...
Do you think Walk Forward Analysis is a good method to estimate the predictability or edge of a trading system? Are there similar methods to know (estimate) how much alpha can capture an algo (in the future)?
I built risk models using cluster analysis in a previous life. Years ago I learned about principal component analysis and I've often wondered whether that would have been more appropriate. What are the pros and cons of using PCA as opposed to clustering to derive risk factors? If it makes a difference, I'm using the...
Cluster analysis vs PCA for risk models?
The nice list of free online data sources http://quant.stackexchange.com/questions/141/data-sources-online does not mention any data from ratings agencies. > Are historical time series available for sovereign credit ratings (other than as proprietary datasets)? I realise that the ratings agencies probably would c...
Are public historical time series available for ratings of sovereign debt?
I am seeing a regression model which is regressing Year-on-Year stock index returns on lagged (12 months) Year-on-Year returns of the same stock index, credit spread (difference between monthly mean of risk-free bonds and corporate bond yields), YoY Inflation rate and YoY index of industrial production. It looks thu...
The nice list of free online data sources http://quant.stackexchange.com/questions/141/data-sources-online does not mention any data from ratings agencies. > Are historical time series available for sovereign credit ratings (other than as proprietary datasets)? I realise that the ratings agencies probably would c...
**Fitch** should be available right here: *[Sovereign Ratings History][1]* With **Moody's** it's not so easy, I don't know if there's a complete source available free of charge. But *[Sovereign Default and Recovery Rates, 1983-2007][2]* has some data in the appendix III, though not so up to date and in a not that co...
I am implementing a program in Java that needs the Bank of England base rate. Rather than the user inputting this into the system, I have heard that there is a way to get a **live feed** of the base rate directly from (I am guessing) the Bank of England (i.e. gets automatically updated). Has anyone heard of or used som...
As suggested by *Owe*, you could use the *Statistics* part of the *BoE* website. It's not like the rate is changing every second, so you don't really need a **live** feed, I suppose. You could update it on every start - for example using the [Interest and Exchange Rates tables][1]. Just generate the format you like,...
If one wants to smooth a time series using a window function such as Hanning, Hamming, Blackman etc. what are the considerations for favouring any one window over another?
Hy I posted this question first at mathflow.net they suggested me this page, which I was not aware of. Question: Let $(X_1,X_2)$ be a multivariate normal random vector ($X_1$ and $X_2$ need not be independent). Is it possible to calculate $$VaR_{\alpha}(e^{X_1}+e^{X_2})$$ analyticaly? Or is it even pos...
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 $$Var(X_1 + X_2) = VarX_1 + VarX_2 + 2*Cov(X_1, X_2)$$ Exponentiating doesn't change this relation; it just makes your random variable log-normal. Maybe y...
There is a large literature covering volatility forecasts with high-frequency tick data. Much of this has surrounded the concept of "realized volatility", such as: - ["Realized Volatility and Correlation"][1] (Andersen, Bollerslev, Diebold, and Labys 1999) - ["Modeling and Forecasting Realized Volatility"][2] (A...
How to forecast volatility using high-frequency data?
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.
Suppose I have trend following strategy(on close to close data) that is not getting acceptable returns for some time. When should I start thinking about shutting it down?
When to shut down a trend following strategy?
I am implementing a Mersenne twister random number generator in Java for a Monte Carlo Simulation. I need a uniform distribution of values between -1 and 1. My code is below (I am importing org.apache.commons.math.random.MersenneTwister which is a Apache Commons library that contains the methods I am calling - http://c...
I came across this reference, and I became curious. can the opening futures market really predict market action for the rest of the day? http://historysquared.com/2011/01/31/open-interest-in-futures-markets-predicts-stock-bond-commodity-and-currency-prices-says-study/
Can the opening futures market really predict market action for the rest of the day?
From what I understand, Black-Scholes equation in finance is used to price options which are a contract between a potential buyer and a seller. Can I use this mathematical framework to "buy" a stock? I do not have the choice using options in the market I am dealing with -- I either buy something or I don't. So I was wo...
Proxy integration is just an approximation which can deviate pretty strongly from the recursion algorithm for thin tranches or extremely large/small loss variances. Proceed with caution. Also: when you integrate the Gaussian proxy, do you start from $-\infty$ or from 0? Counter-intuitively, you should start from $-\...
There are really a few issues here: 1) When do I turn off a model because I believe the model is **invalid**? This is a subjective call and depends on many things such as how strong the economic reasoning behind the model is, how crowded the space is, and how poorly the model is performing relative to backtest. ...
Piterbarg (who's a very smart and no-nonsense guy) looks at the problem from the practitioner's perspective, i.e. "will this make the traders happy?". Academicians tend to answer the question "will this make the journal referees happy?". Two different goals.
There are really a few issues here: 1) When do I turn off a model because I believe the model is **invalid**? This is a subjective call and depends on many things such as how strong the economic reasoning behind the model is, how crowded the space is, and how poorly the model is performing relative to backtest. ...
I came across this [article][1] and became curious. Can the opening futures market really predict market action for the rest of the day? [1]: http://historysquared.com/2011/01/31/open-interest-in-futures-markets-predicts-stock-bond-commodity-and-currency-prices-says-study/
I came across this [article][1] and became curious. Can the opening futures market really predict market action for the rest of the day? By "opening futures market" I mean not only price action at open, but anything pre-market which includes price action, fair value, change in open interest, competing markets, or bid-...
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 makes sense that price*quantity holds more information than just price _when_ quantity can change quickly (i.e., outsta...