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First, let us formulate the problem mathematically: A symmetric random walk starts at 0 and moves up or down one unit (with equal probability) every 1 second. The are two absorbing barriers located at H and -L, with $H,L>0$. Given infinite time, what is the probability $p_H$ that H will be hit before -L is hit and what is the probability $p_L$ that -L ...

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You might want to measure the resiliency of a limit order book. http://users.iems.northwestern.edu/~armbruster/2007msande444/large-06.pdf https://hal.archives-ouvertes.fr/hal-00166969/PDF/OE19.pdf

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As a standard reference (in the back of my head) I use for Swedish and U.S. equities, 7% real return assuming no growth rate in FCFE. So if we assume the entity will produce \$100m per year in fcfe going forward with no growth rate, then the market value of equity is 100/0.07 = 1729. The 7% comes from 2% risk free rate + 5% risk premium (adjusted for ...

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It should be related to your specific valuation model. The most common earnings related models use a risk free rate minus 3%.

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In a few words. The CAPM assume the concave utility function because its, implicitly, assume the validity of mean-variance approach. In utility function way the concavity is related with the concept of risk aversion and risk=variance of return. If utility function is convex the investor is prone to risk and CAPM is not valid and mean-variance as well. If as ...

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First, if you are using python for this, I would recommend that you take a look at pandas in general and the pandas data reader package If data reliability is a concern, I recommend that you self-verify by randomly selecting dates and assets, pulling data from multiple sources (like say yahoo, google, and Quandl) and checking them against each other and ...

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Pretty much agree with what everyone is saying above. Just want to add one more comment. The sad truth of not advocating a lot on the usage of ML in Asset Management is the difficulty to marketing it. Most of the pitches on the quant portfolios are trying to make a systematic fundamental (these days called quantamenal) story. ML methods are apparently not ...

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The dividend yield can be computed from the forward prices. However, in practice (e.g., in Bloomberg), the realized dividend yield is computed as the sum of the dividend payments from the whole past year divided by the current equity (stock or index) price, while the implied dividend yield is computed as the sum of the forecast dividend payments, over the ...

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I am sure that some people do this. Generally, there is some evidence that informed traders choose to trade in the option markets first (Easley et.al, 1998). This is especially true if an informed trader has bad news about a short-sale constrained stock. In this case the option market leads the equity market. Moreover, I was told that there are some people ...

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