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9

The idea of regime switching in volatility is rooted in the observation that volatility is usually fairly consistent and "mild", and occasionally very high, say during a market crash. The concept goes further, though. Not only does the volatility level differ markedly in different regimes, but the behavior of volatility does as well (degree of mean reversion,...


8

Regime switching is another way to describe structural changes in a data series. For example, an inflation timeseries may change states from ARMA to linear as the economy moves from a period of cyclical growth to prolonged recession. A stock price may, say, be determined by and correlated to the main equity index when it has a large market capitalisation ...


7

The only "indicators" that I believe add value in academic research are time series smoothing functions. ( I don't call them indicators because they are all lagging thus do not indicate anything into the future). There is clear empirical evidence and a number of academic papers have been published that show that none of the common indicators (common defined ...


7

I think the answer to your question is very dependent on the respective indicators. It can be argued for example that moving averages not only smooth out time series but because they are a shifted version of the original series signals on crossovers make use of the momentum factor. In general you might want to check out the book Evidence Based Technical ...


6

Concur with Thomas for most part, though I would recommend you to sign up for a trial with Dow Jones Newswire. I like the API and app that Newsware ( http://www.newsware.com/) makes available. It is not suitable for hft but I use it in order to stay informed and look up often used mnemonics. I think they have a pretty capable API and I remember they offer ...


6

Intuition : Lets observe the U.S. ex post real interest rates from 1961 to 1986 : At first look it is not easy to identify different states of the economy. Now lets apply an econometric model that will try to identify those different states and observe the result: The econometric model identifies 3 different states of the economy, this is what we call ...


5

One of the most famous definition of Regimes and Regime Switching in Financial Markets comes from Wyckoff Cycle Wyckoff believed that prices judged by supply and demand, go through periods of advance, accumulation, decline an distribution based on the movement of smart money. In the quantitative world one can use state space models to model such regime ...


5

It would be relatively trivial to implement a web scraper for any website you were interested in gathering news from - see Beautiful Soup for Python. This would allow you to gather and analyse news data from multiple sources in a way that may be more robust than relying on a single service. For example, you could screen scrape a certain website for the news ...


5

The typical approach is: you only use option data from the last day. Furthermore, you only include those points that are liquid enough. One approach to this is to weigh the modelling error of an option by its bid-ask spread and vega. Using data from multiple days is not a good approach, because you might have options with the same strike but different ...


5

I know two papers explaining how to calibrate this kind of models, and one of them explain the impact of the quality of the fit on a pricing model: Aït-Sahalia, Y. (2002, January). Maximum likelihood estimation of discretely sampled diffusions: A closed-form approximation approach. Econometrica 70 (1), 223-262. Azencott, R., Y. Gadhyan, and R. Glowinski (...


4

I used https://newsapi.org/ for one of my last projects. free access to over 30,000 news sources world wide (US, Germany, India, Japan, etc.) RESTful API returning JSON excellent API documentation no throttling Example: Top Headlines Request: https://newsapi.org/v2/top-headlines?country=us&apiKey=YOUR_API_KEY Response: { status: 'ok', ...


3

You are right. In the CIR++, $\alpha$ parameter is absorbed into $\phi$. With the CIR++, $\phi(t)$ will allow you to have to have negative rates. You will calibrate your $\phi$ to fit the discount factors. The shifted idea is the one used to handle negative rates problem in caplet, swaption...


3

I would argue that there is some path-dependency involved. The BS model is considered the big breakthrough and it presented the world with some kind of tractable toy model. After that people saw that you had to adjust the model to account for all kinds of stylized facts (e.g. non-constant volatility for different strikes, over time and so on). Yet finite ...


3

News is not free, and hence you won't find a company offering machine readable news services for free. My best suggestion is to ask a machine readable news company for a day's worth of historical data. Even that might not work, however, as they won't waste their time if they don't think you're going to buy their service.


3

Typically "average" lines are used to get rid of noise in the original data. It seems pretty logical to smooth intra week fluctuations when working with a year of data.


3

The hypothesis $H_0: β_1=β_2=\dots =β_{k−1}=0$ is normally tested by the $F$-test for the regression. You are carrying out 3 independent tests of your coefficients (Do you also have a constant in the regression or is the constant one of your three variables?) If you do three independent tests at a 5% level you have a probability of over 14% of finding one ...


3

The risk neutral measure is used to price assets (e.g. derivatives) and not to base your investment decisions on. In the first part of you question your simulation gives you the Risk-Neutral expectation of the stock at time $T$. If you want the expectation at time $t$, then why don't you just simulate from time 0 up to time $t$? (I might have misunderstood ...


2

These are independent variables so the hypothesis applies to each parameter independently.


2

If you are an academic interested in this field I would suggest contacting Sirca. Thomson Reuters is active with academics through their partnership with Sirca in Australia (www.sirca.org.au). Sirca has other machine readable text products available.


2

Just a quick fix. Looking at the wikipedia entry of EGARCH: $g(\zeta_t)$ (the unit-scale random variable) seems correct - as you say.


2

To get it out the way: you cannot ask 'what model is better' without a reference to what its use is. Do you want to test for the mean or the AR parameter to trade it? Do you want to calculate VaR? Do you want to forecast volatility over one period? Or over 1000 periods? Or higher moments? Do you want to simulate volatility over one period? Or longer? For ...


2

One does not estimate the local volatility at a given $T$ and $K$. Instead, Dupire's formula actually gives $\sigma(T,K)$ for all $T$ and $K$. $$ \sigma^2(t_0,S_0;T,K)= \frac{\frac{\partial C}{\partial T} + (r - q)K \frac{\partial C}{\partial K} + qC}{\frac{1}{2} K^2 \frac{\partial^2C}{\partial K^2}} $$ where $C(t_0,S_0;T,K)$ are the call prices for ...


2

Please look up goodness of fit measures such as MSE (mean squared error) , R-squared , and adjusted R squared. There are also a number of others measures that have been developed to penalise complex model to avoid overfitting. These include mallow $C_P$, AIC, and BIC. This note would be a good start: https://people.duke.edu/~rnau/compare.htm


2

When the required conditions are fulfilled ( a storeable commodity, an observable spot price, no "convenience yield") the cost of carry model determines the futures price by arbitrage. Otherwise, to my knowledge, there is no alternative model. The futures price will just be the market's expectation (possibly plus or minus a risk premium) of what the ...


1

After some research, I found that PIIs are used in the modelling of Default Risk. See for example : http://www.tandfonline.com/doi/abs/10.1080/13504860903357292 In this paper, the authors also use "Sato processes" which the authors define as a PII with self-similarity.


1

For reporting outputs, you should certainly use the proper market convention (e.g., 30/360 and simple interest for USD Libor). However, internal model convention is a different matter. Many quants use Actual/365.25 or Actual/365, combined with continuous compounding. The day count convention only needs to ensure 1-to-1 mapping between date and rate/discount ...


1

For example if you think the volatility of short term rates is 0.1 during economic exapansions and 0.15 during recessions, then that would be a very simple regime switch model. The parameters of the model (in this case just the vol) change from time to time. Specifically it 'switches' at certain times from one value to another. (And that is different from a ...


1

In the industry the model I have used is the 'shifted Sabr' where: $dx(t) = \sigma(t) [x(t)-c]^\beta dW(t)$ $d\sigma(t) = \alpha \sigma(t) dZ(t)$ $dW(t)\ dZ(t) = \rho\ dt$ This allows for rates down to the parameter $c$. If you set, for example, $c=-200bp$ then you can have negative rates. You can define a CIR variant in an analogous way. I have used ...


1

t.f thanks for the answer. You say that yields can't go negative in CIR. But if r0 (say 1d rate) is negative (which is the case in many govies today), I guess yields can be negative? And you will in this case be able to actually calibrate a CIR, which gives negative yields in the short end? My question might seem a bid odd, but I was just wondering? But ...


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