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38

Visualization should lead to truth and understanding. As such, I find that simple visualizations tend to be the best. My favorite visualization for showing relationships is the scatterplot. Once you start to even introduce a line plot, you are implying continuities between data that may not exist. And trying to introduce more advanced visualizations like ...


16

The Google Motion Chart is a particularly elegant visualization for 'replaying' time series data. There is also an R package to interface with it.


12

Nanex has an interesting way of showing the order-book: The following images show CME's emMni future (S&P 500) depth of book and trades. The images are rainbow (ROYGBIV) color coded by the relative size at each depth level. Red indicates a lot of size, violet indicates size approaching 0. Note that a full minute before each event, the depth starts ...


10

I feel that the best way to answer your question is to first quote your problematic idea and then carefully explain the subtle alternative. :) The derivation of the Black-Scholes PDE is based on the assumption that the price of the option should change in time in such a way that ... And my question is: Why do we assume that the price of the option has ...


8

Shane's advice is good. I think it's worth adding the following two techniques not already mentioned: Self-Organizing Maps (SOMs) Seriation (pdf pertaining to R package seriation, but great intro to the topic). They are not explicit visualize techniques, per se. Instead, they are algos that transform underlying data in ways that aim to lead to ...


8

That's a complicated question. There are many paths. One path is to build a model of the underlying supply/demand relationships. For example, the sudden loss of a power supplier (or transmision corridor) shifts the supply curve to the left spiking the price. The key to the game is data, data, and more data (price, weather/wind, season, power loads, ...


8

Market makers, obviously, have to be willing to short an option. They will delta hedge their positions to limit risk. As for investors, they can aim for a buy-write strategy to collect extra income in lieu of unlimited upside. And lastly, someone who owns a stock he can't sell right away (such as an entrepreneur still under a vesting period after his firm ...


6

Here's a research note devoted to pricing of CMS by means of a stochastic volatility model. The authors indicate in the Introduction that an analysis of the coupon structure leads to the conclusion that CMS contracts are particularly sensitive to the asymptotic behavior of implied volatilities for very large strikes. Market CMS rates actually drive the ...


5

There are many price driven financial data finsualization concepts are available such as candle stick stock charts. However, there is an advanced charting concept, Mano Stick which is supply & demand driven charting concept. Mano Stick is a multidimentional charting concept which is able to display price information along with volume information to show ...


5

Here are a few recent examples: http://stackoverflow.com/questions/4951193/find-largest-5-value-less-than-1-lowest-5-values http://tables2graphs.com/doku.php?id=04_regression_coefficients#figure_6 http://tables2graphs.com/doku.php?id=03_descriptive_statistics#figure_5 http://chartporn.org/category/innovative/


5

Specifically, we have a generic conditional claim, $C$, that is a function of the diffusion process for the underlying, $S(t)$, and time $t$ so $C = C(S(t), t)$. As you pointed out, $C$ is an Ito process becuase it is a function of a stochastic process so we use Ito's Lemma to determine how the contingent claim varies as a function of the diffusion process ...


5

The answer to your first four questions is affirmative. Option-adjusting the spread makes an equivalence between everything theoretically possible, but the quality of results depends significantly on the quality of your interest rate model and its calibration. My personal opinion, though, is that the results need to be treated carefully because the OAS ...


5

This is indeed one of the most difficult tasks to do (if not next to impossible). I would say the standard reference is the following: Expected Returns: An Investor's Guide to Harvesting Market Rewards by Antti Ilmanen An abridged (but still about 170 pages long), yet more current - and free (!) version in different formats (pdf, mobi for the Kindle and ...


4

One could say that a CDS price is determined by the physical default probability and the risk premium. The physical PD (PPD) is the actual probability of company defaulting within the given period of time. It is purely a theoretical concept as no one really knows what this probability is. We could estimate it using some models or credit ratings, but those ...


4

The SABR model has an overly fat right tail. If you do the CMS replication using cash-settled swaptions you find that you need ridiculously high strikes.


4

The common approach to temperature derivatives in their first run of popularity (in the late 1990's) was to use an Ornstein-Uhlenbeck process to describe deviations of temperature from a seasonal average. So far as I know, no major innovations have arisen since then. Calibrating such a model is very simple, and so is valuing certain quantities such as ...


4

A swap does not require a model because its price can be derived from the yield curve without any assumptions about how the yield curve may move in the future. The PFE however is an indication of by how much the swap's mark-to-market may move between now and a moment in the future. It is of course influenced by how volatile rates are. The more volatile ...


4

As a complement to chrisaycock's answer, I would also say that shorting options is useful when you want to create option strategies. Buying and shorting options on the same underlying with different strike prices allows the investor to create products with elaborate payoff which allows them to be more on a range of the underlying's price rather than on its ...


4

You can ask for a quote from a bank as I am sure they will create it for you. If you want to create this kind of payoff yourself, you can use the following paper from Peter Carr where he introduces the spanning formula for replicating any twice differentiable payoff. http://www.math.nyu.edu/research/carrp/papers/pdf/twrdsfig.pdf


4

Just take something like $$ \frac{\log{\frac{F_j}{F_i}}}{t_j - t_i} * 365 $$ where $t_i$ denotes the expiry (or alternatively delivery) date of future $i$. The annualization is so you can compare different futures.


4

First of all, I must say that it's a very general question, and the answer can vary depending on type of assets you model. In quant finance real world probabilities are generally used for risk management. It can be said, that in order to use real-world probabilities you have to calibrate your models to history. In order to obtain risk-neutral probabilities, ...


4

You may want to consider splitting two important, yet very different concepts: Pricing a derivative security with contingent payoff and forecasting an asset. Pricing a derivative can be achieved through setting up a hedge portfolio and track its evolution and "value" at any point in time before the derivative security pays off. Risk-neutral pricing is a ...


4

This looks like a binary option. Following this wikipedia article it is called an "asset or nothing call". The pricing formula in the Black-Scholes world is $$ S e^{-q T} \Phi(d_1), $$ where $S$ is the current spot price, $q$ is the dividend yield, $\Phi$ the cdf of a standard normal and $d_1$ is as usual in BS. To my knowledge such options are much less ...


4

It is incorrect to use 1m euribor or O/N euribor in a 6m Euribor forward curve. You should only use instruments based on 6M euribor, such as 1x7 FRA, 6x12 FRA or swaps v 6m Euribor, as you have done in your second example. The actual 6m euribor fixing itself can be thought of as a 0x6 FRA out of spot. Before the financial crisis basis between different ...


3

You are quite correct that there are further assumptions in the replicating argument. Once you are assuming your equation (2), that is, that $$ dS = S(\mu dt + \sigma dW) $$ along with the determinism of interest rates, the rest of the replication argument necessarily follows because you have constructed a mathematical world with nothing else in it. Hence ...


3

This guy listed a list of key papers relative to commodities price modeling. That could perhaps help you get started.


3

Best approach is to model each contract separately, or to develop an equilibrium model that constrains the relationship among the various spot and futures contracts. So if you estimate you can make inferences about the other contracts. The term structure of interest rates or covered interest parity would be examples of the latter.


3

1) Instead of asking why the portfolio is equal to the premium, ask why create it at all? I say that because it actually isn't equal to the premium, since that would just be D, and also because the actual value isn't as important as what the portfolio represents. We form this particular portfolio because the laws of no-arbitrage guarantee it has a certain ...


3

It might not work the way you think. Note first that nobody sells options for free so at least one of your integers ($a,b,c$) is negative, meaning you will have nonzero risk of losing money on your short option leg. More specifically, let's pretend $b \geq |c|$. Then since the value of a forward contract is the same as the call minus the put plus strike ...


3

The basic difference is that CFDs are over-the-counter products and SSF are exchange listed products. This does not, however, hold entirely true anymore as some CFDs are listed (example, http://www.asx.com.au/products/asx-listed-cfds.htm ). But the historical reason for CFD's origin was that over-the-counter products could provide more leverage and such ...



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