# Tag Info

9

There is certainly much more to quantitative finance than technical analysis, and a previous question does a decent job of outlining the different areas, as does the wikipedia on "quantitative analyst". Even for what wikipedia terms an "algorithmic trading quant" or what Mark Joshi terms a "statistical arbitrage quant", technical analysis is just one tool ...

7

Second Joshi guide but yout you can do better than that. We have a list for all level, some of them are free to download (just like Joshi), others are books and websites that for beginner level http://www.quantnet.com/master-reading-list-for-quants/ As for websites and blogs, there are only a handful of them out there (this is a niche field after all). I ...

7

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 the Wharton Resource Data Service, but these (or Bloomberg or Reuters) are likely too expensive for an individual. Have you asked your broker if they will sell ...

7

Have a look here: http://www.climatelogic.com/ The method is based on a sequential F-test, see also this paper: Rodionov, S.N., 2005b: Detecting regime shifts in the mean and variance: Methods and specific examples. In: Large-Scale Disturbances (Regime Shifts) and Recovery in Aquatic Ecosystems: Challenges for Management Toward Sustainability, V. Velikova ...

6

This is the canonical Arrow-Pratt "portfolio" model. Couple of points on terminology: For a function $u$, we define the risk aversion function by $r_u(x):=-\frac{u''(x)}{u'(x)}$. In your utility function, $r_u(x) = \lambda$; hence, it is a constant absolute risk aversion utility and $\lambda$ is the "coefficient of risk aversion," not the "risk ...

6

Natural experiments are good working material for MA-thesis (less issue statistically speaking, quicker path to results,...). A good one recently in finance deals with short selling ban: in many countries in the euro-zone, in 2008, short sales were banned on some banks/financial corporations in some countries (Greece, France, Belgium, Germany) while still ...

5

Hi Quantitative Finance has in my opinion two main streams. The first is about of valuation of some derivative contracts in a consistent way. This is a theory and once paradigms accepted it is coherent, it can considered as science at the same level as economy can pretend to this kind of terminology. The second is about making (or trying to) prediction(s) ...

5

One simple way to approach this question is to look at what quantitative hedge funds did well during the crisis, and try to understand what strategies they employed. As an example, you can look at the Barron's 100 from 2009. The top performing fund was RenTech's Medallion. Their strategy is not publicly known. There were only two broad hedge fund ...

5

There is a very cheap, i.e. free, way of obtaining the list of companies included in the S&P 500 at any given time. Check the revision history for the S&P 500 List updates on Wikipedia. It is ugly and unreliable but you usually get what you pay for :) ... it should be okay if you are just playing around with your own strategies. This doesn't ...

5

The general idea is to bootstrap the discount factors in the correct order, based on the data you have given. I'm going to make some assumptions that your bonds are paying annual coupons. The longest maturity is 2.5 years, meaning you need discount factors for 6M, 1.5Y and 2.5Y. The 6M deposit has a rate of 5%, this tells you that you should use the 5% rate ...

4

This looks like a general equilibrium model in Economics. It should be described in most of microeconomics textbooks (e.g. this). Yes, you need a budget constraint here for$\ a$, otherwise your optimization problem makes no sense. Moreover, the household prefers consumption today to consumption tomorrow and, hence, you may want to enhance your model by ...

4

Correct. All outstanding issues are held. Money only flows into an asset class via the primary market (such as an IPO, secondary offering, etc.) not on the secondary markets which are publicly traded. What is actually changing is people's willingness to buy and sell securities at various prices. When market commentators talk about money flowing into or out ...

4

Quant in trading creates system that can be backtested, has a certain risk valuation. It is more like playing chess when you need to calculate multistep strategy. Let say certain instrument moves 1% a day. Our goal is to create strategy for one year (250 step strategy). If we use stock + options we get 50 or more entries a day into our system for analysis. ...

4

Wilmott and NuclearPhynance are two fairly popular forums, although quant.stackexchange.com will hopefully serve as a better resource in the future.

4

This might be a surprise to you, you can evaluate the option using Black Scholes. The key concept is change your numéraire from dollar to the asset associated with $V$. The $V$ in your payout $\max(U_t-V_t,0)$ will effectively get replaced by a constant, the par forward of asset $V$ at maturity $t$. Since $U_t$ and $V_t$ are independent, you can ...

4

I found these nice lecture note by Karl Sigman on the web. On page three you see if $X\sim N(\mu,\sigma)$ then the moment generating function (mgf) of $X$ is given by $$M_X(s) = E(exp(sX)) = \exp( \mu s + \sigma^2 s^2 /2)$$ Thus for Brownian motion with drift $X_t$ you get $$M_{X_t}(s) = E(exp(s X_t)) = \exp( \mu t s + \sigma^2 s^2 t /2).$$ Finally for ...

3

Quantnet provided a rankings of MS in Financial Engineering programs, which can be used for reference. More generally, this really depends on what area of quantitative finance that interests you: If you want to work in developing valuation and pricing models, than one of these programs will be very useful. If you want to work in quantitative trading, it's ...

3

One that I found via google that seems promising (for beginners though) is. Numerical methods in finance and Economics

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Options, Futures, and Other Derivatives Analysis of Financial Time Series Inside the Black Box: The Simple Truth About Quantitative Trading Trading and Exchanges: Market Microstructure for Practitioners

3

Well I guess as pure programmer, you could be looking to "evolve" to: An algorithmic trader which is in a nutshell a programmer designing algorithms which automatically trade in the market. or a Quantitative developper A quant is basically a person with strong quantitative background looking, for example, to find models to apply to the financial markets. ...

3

This is usually called Pin Risk. It's difficult because there is a high degree of uncertainty regarding the whether the options you sold are exercised or not. If you don't hedge, your short options could be exercised and you are left with risky net short position in the underlying. If you hedge and your short options are not exercised, then you have a long ...

3

The essence of discounting is that now is less risky than later. So a contract to deliver £1 in 1 year is more risky than one to deliver £1 tomorrow, (the counterparty could suffer a credit event) so it is worth less. Discount factors multiply; if I know that £1 at 1y is worth £0.98 today, and £1 at 2y is worth £0.98 at 1y (i.e. equal rates for both ...

3

If you allow $X_t$ to be two dimensional then a model with a stock price $X_t^1$ and its variance process $X_t^2$ (stochastic volatility) would fit your definition. In such cases to my knowledge we often don't have a closed form of the density of $X_T^1$ but in some cases we have a closed form of the Laplace transform. An example is the Heston model.

3

I would answer your question with no. First: what do you need the risk free rate for? If you want to price equity derivatives then probably a short money market rate would better fit this purpose. Second: the maturity. Look at yield curves. The short end is usually at a very different level than the 10 year rate. So two times no. A small "no" for ...

3

Following Daniel, Grinblatt, Titman, and Wermers (1997) "D.G.T.W.!", DGTW subtracts from each stock return the return on a portfolio of ﬁrms matched on market equity, market-book, and prior one-year return quintiles. Daniel, K., Grinblatt, M., Titman, S., Wermers, R., 1997. Measuring mutual fund performance with characteristic-based benchmarks, Journal of ...

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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 ...

2

This is an example of minimum price variation (also known as the minimum price increment or the minimum price fluctuation). All public quotes for US equities are displayed to the nearest penny. (Hidden quotes may be entered at sub-penny increments.) US stock indices follow this convention and thus quote to the nearest penny. The oil listing is odd indeed. ...

2

Adding onto Quant Guy, money can technically flow in and out with dividends and secondary issues. In the case of a cash dividend, money flows out without any shares trading(depending on outstanding shares obviously). While secondary issues can basically be thought of as a followup IPO if you will.

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Log returns are additive. Just add the daily returns together. If you only have one average daily return you annualize simply by multiplying with an annualization factor. Often 252 is used but it depends on your specific use case. In your case you may want to multiply by (days per year / days in 10 months period) Make sure you do not apply the same to ...

2

First, your statement that your utility function goes to infinity is wrong. It's minus exponenta. You can think of it as a minimum of $e^{f(x)}$ which is bounded below by zero whatever $f(x)$ is. In other words, your utility function is bounded above by 0. Second, maximizing expected value, you need to calculate it before deploying maximization techniques. ...

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