Tag Info

Hot answers tagged

14

To explain why a negative sloping yield curve is bad, you have to start with a theory of the yield curve. The dominant theories for the term structure of interest rates are the rational expectations, liquidity preference, and market segmentation. (The first two theories are quite compatible with each other and have more standing so let's assume that view.) ...


12

Short Version : Two main uses I'm doing an arbitrage/statarb strategy (volatility for instance) which should not be dependant on the Delta (I'm an arbitragist). I HAVE to keep a product in my portfolio, but I don't want to be EXPOSED to it (I'm a market maker). Long Version : The goal of Dynamic Hedging is not down the line to earn risk free rate of ...


12

Weak form market efficiency says that you can't predict prices based on past prices. Or that technical analysis doesn't work. I think that the tests of weak form market efficiency are pretty conclusive and show that the US stock market is weak-form efficient; at least on a a timeline longer than a few minutes. That's not to say that markets are "efficient". ...


7

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 you to compare. This probably means they ...


6

General answer to a very general question: If you find a significant pattern which distinguishes between structure and noise you understand something about that system. You have a model about it so you can extrapolate and forecast. On that basis you can use this model to make money. In that sense mean-reversion and trend-following are also "only" ...


6

A discrete-time model only works in no-arbitrage land with discrete asset values. Furthermore, the number of allowable asset values per timestep is limited by the number of available securities. The tree is the classic example of this. Binomial trees "work", but if you make a one-step trinomial tree, you will find that you can no longer form a risk-free ...


6

If you look in the portfolio management sections of the CFA (chartered financial analyst) curriculum, you'll find a listing of commonly used portfolio management techniques. It is by no means exhaustive, but the content in the CFA curriculum comes directly from industry professionals, so it is reasonable current and applicable. CFA Candidate Body of ...


5

For the binary tree model the full replication property of all possible options can be shown using basic algebra and the no-arbitrage argument. It's beautiful how simple it is actually. You can find the complete derivation in Shreve's Stochastic Calculus for Finance I: The Binomial Asset Pricing Model.


5

Some of the used heavy-tail distributions are: Log-Cauchy and Log-Gamma Lévy Burr and Weibull Mixed normal Here two papers that cover some of them and others: http://ect-pigorsch.mee.uni-bonn.de/data/research/papers/Financial_Economics,_Fat-tailed_Distributions.pdf http://www.rff.org/RFF/Documents/RFF-DP-11-19-REV.pdf


5

You have to differentiate here between the risk-taking and the market-making side. As a risk-taker, like e.g. a hedge-fund, you are right, you could just buy the bond! But as a market-maker you sell these options but don't want to bear the risk, so you have to counterbalance it. You could of course counterbalance it with another option which would be the ...


4

I think there is an error implicit in your question. Dynamic delta hedging, even assuming the underlying process is a continuous martingale and trading entails zero transaction costs, only eliminates the directional risk. A number of residual risks remain, most notably volatility risk, embodied in both the gamma and vega. A dynamically hedged portfolio of ...


4

This is the equity premium puzzle. (See that article for references.) My thoughts are that individual investors are rational to be risk-averse and demand a premium for bearing a type of market risk that cannot be diversified away. This risk is actually worse and more insidious than it appears, because "personal" circumstances tend to correlate in ...


4

Orthogonality and independence are different concepts. The concepts are the same for Wiener processes because in the context of normal random variables, independence is equivalent to orthogonality (i.e. uncorrelatedness) Independence is the standard definition for probability. Let $\mathcal{F}, \mathcal{G}$ be the sigma algebras generated by two ...


3

I have asked myself the very same question when I first read the book. As far as I can tell, the "scalability" condition is only imposed for technical reasons. It simplifies the subsequent proof of the Fundemental Theorem of Asset Pricing in constrained markets. There are several papers that have shown that the theorem is valid for conic constraints. ...


3

A very good book covering such fundamentals with no or only a minimal amount of maths — highly recommended! Puzzles of Finance: Six Practical Problems and Their Remarkable Solutions by Mark P. Kritzman The topics that are covered here are: Siegel's Paradox Likelihood of Loss Time Diversification Why the Expected Return Is Not To Be Expected Half Stocks ...


3

Theoretically, a rising yield curve is compensation for the additional duration risk. An inverted yield-curve is saying that the market thinks that: Next-year's figures for: growth plus inflation is less than Ten years' time's figures for: growth plus inflation Which means that expectations are either of a recession (some negative economic growth; and ...


3

To my point of view there are never any reason that a pattern or anything else would repeat in the futur. Actualy I don't see any difference between pattern recognition and mean reversion/Trend Following in term of theoretical proof. One can read Pr Andrew Lo : "Foundations of Technical Analysis". It tries to give a theoretical background to TA by studying ...


3

Exact Discretization of the Solution to the Geometric Brownian Motion Stochastic Differential Equation Let $P_{t}$ represent the time series of market prices of the underlying, $\mu$ be its mean continuous log-return, $\sigma$ be its instantaneous volatility and $W_{t}$ be a Wiener process. Here is the stochastic differential equation for the geometric ...


2

Fractal spectra are covered in Multifractal Volatility: Theory, Forecasting, and Pricing. Also note that your run-of-the-mill moving average of a price series is a low-pass filter (filters out the higher frequencies), and moving averages are very used in basic financial analysis.


2

Samuelson once quipped that the yield curve had successfully predicted 9 of the last 5 recessions. Explanations for why the yield curve inverts have been covered adequately above. But what does it mean for the economy? For the yield curve inversion to predict stock market performance enough to make an actual decision, the bond market would have to be more ...


2

An inverted yield curve basically means that interest rates will be higher for the coming year than for the years following. That means that entities that need do borrow for short term purposes will do so at a greater cost that those borrowing for the long term. That is an unusual and "unnatural" relationship. All other things being equal, that will dampen ...


2

If you have the mathematical sophistication, you should review the original papers referenced on the Equity Premium Puzzle page, particularly Mehra and Prescott (1985). Note, however, that contrary to other opinions on this page, the puzzle is NOT that there is an equity risk premium. On the contrary, the puzzle is that the premium had been so high, at ...


1

Sure, the variance of the total wealth can be expressed in terms of the variances and covariances of the prices of the assets. If $$ W = \sum_{i} \pi_i P_i $$ where $\pi_i$ is the total dollar amount invested in asset $i$ with price $P_i$. The variance of total wealth is then $$ Var(W) = \sum_i \pi_i Var(P_i) + \sum_i \sum_{j, j\neq i} \pi_i \pi_j Cov(P_i, ...


1

Another observation that the connection between return and risk is not that straightforward (and in contradiction to modern portfolio theory!) is the low-volatility anomaly. It turns out empirically that stocks that have low-volatility or low-beta show higher returns than high-volatility or high-beta stocks. See also this question and answers: Why does ...


1

In the academic literature it is extremely widely applied in the last 20 years. I would estimate maybe 200 empirical papers, or more. For example a common finding is that higher frequency (daily) wavelet correlations have been high since 2007, attributable either to increasing financial interation or the financial crisis. It is also popular to estimate the ...


1

Something like a moving average smoother is akin to a low pass filter, the 'stochastics' of technical analysis crudely akin to a band pass filter. Going up the ladder of sophistication, you can see something like http://www.jstor.org/pss/3592665 or applications of wavelet decomposition. This paper from 1963 by GRANGER, CLIVE W. J., and MORGENSTERN, 0. ...


1

Is the management fee deducted daily or annually? Or perhaps are you trying to quantify the difference between the two? If annually, are fees in this example deducted based on average daily balance, or ending balance? I think you are also confusing yourself regarding economic vs. accounting cost. Look at how much money is left in the fund after fees ...



Only top voted, non community-wiki answers of a minimum length are eligible