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Jul
15
comment Sharpe Ratio - my own calculation differs from Yahoo finance, Morningstar
I would argue that the inclusion of the risk free rate is a bit out-dated. I know of a number of hedge funds that do not include the risk free rate in their computations (albeit they mention it in the disclosure documents). There is no real risk-free rate, sovereign bills or bonds are anything but risk-free, including bills issued by the US Treasury. Imagine short rates were 20% then the Sharpe ratio with inclusion of Rf would be badly skewed. Sharpe is not a comparable risk measure but measures return relative to its own risk.
Jul
15
comment Sharpe ratio in days with no open positions
I disagree, because Sharpe is a measure of excess risk-adjusted, returns. It does not matter whether competing investments generate return during days you are not taking any risks. Sharpe is not a comparable performance measure such as the Information Ratio, its focus is on its own performance relative to its own risk taken, which is why a lot of practitioners actually leave out the risk-free rate altogether. I am not arguing here whether it should be included or not, but I try to make a point that days on which risk is not taken should not be included in the Sharpe ratio computation.
Jul
15
comment Sharpe ratio in days with no open positions
@feetwet, I am not sure I understand what you are trying to say. I mentioned explicitly that Sharpe is a measure of excess risk-adjusted return. Because it is risk-adjusted so you should not include days on which you do not take any risk, hence the exclusion of trading days on which no risk is taken. However, you still need to use business days in the market you trade for annualization purposes else you would not end up with an annualized Sharpe measure. So, I am not sure which part you disagree with.
Jul
14
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
Well, in the real world things are a lot simpler: One makes money, the other loses. Guess who is right? If you happen to derive a model to which market prices almost surely converge then all the power to you, I have not come across such individual in my career so far. Generally market practitioners at the sell-side calibrate their models to market prices and look to extract money through pricing "edge cases".
Jul
14
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
And sorry for my misnomer: I meant to say "closed-form solution" instead of "numerical method". And if you disagree with my general opinion on this topic then I invite you to write up your own answer. That is what this forum is for, different answers to reflect different schools of thought or approaches. But thanks for pointing out my incorrect usage of terminology.
Jul
14
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
Not sure what you are trying to imply with your last comment but I can assure you that this is how it works in real life. You may have a point when it comes to other than no-arbitrage pricing models, apply whatever model you want and see fit, market dynamics will tell you whether the market converges to your model prices or the other way around. But I can assure you that your model is wrong if you get arbed by other market participants. Simple as that.
Jul
14
comment Option based portfolio insurance in practice
I edited my answer.
Jul
14
comment Option based portfolio insurance in practice
are you asking about going practice on the bank or insurance side? Thanks
Jul
14
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
By my own admission I have as prop trader at one bank arbed brokers and extracted millions of dollars within a 2-3 month span for the precise reason that someone on the other side thought they are too smart and priced according to their own model that strongly disagreed with general market prices. Sometimes I let them off the hook if the price was just too off but at other times I held them to the trade because after all it is supposed to be an informed market where professionals trade among themselves. Hope this makes my point clear.
Jul
14
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
Of course must models agree on price. You can implement whatever model you want but if your model under-prices assets your buy-side customers will happily buy from you in size and if you over-price they will sell to you. In either way you will at best be told by your desk head that you mess up and at worst you will find yourself looking for a new job. Keep in mind that most buy side clients request 2 way prices from sell-side desks from a number different competing sources.
Jul
10
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
For most exotic derivatives numerical methods do not exist. You generally end up with some sort of discretization. But in either case taking into account no-arbitrage conditions, a discrete and continuous model must agree on price else the models are not identical and one of the two is wrong. I argue that you can price any derivative with a discrete model but only very few can be priced with continuous models. And to answer your last question (unless I misunderstand your question), absolutely yes, else the models would not agree.
Jul
10
comment What are the main differences between discrete and continuous time models when modeling asset price dynamics?
Sure if you make the steps sufficiently small, else by definition 2 models (1 discrete, 1 continuous) are not exchangeable. And I never questioned the validity of the question itself. Academicians should occupy all their time with this issue, I prefer to have my juniors focus on working the other way around: Pricing is known for assets of specific properties, if a continuous model exists and arrives at such pricing then great, else let's not waste time, wrap up the sleeves and create a discrete model that can properly price the asset at hand.
Jun
10
comment Why parameterize the Black Scholes implied volatility surface?
Very nice answer, and I liked the paper you linked to, thanks. (+1)
Jun
2
comment What is the motivation for index benchmark?
...funds also do not adjust for inflation when they market their return metrics, so why would I care how they perform against the S&P500, just because a fund marketer tells me so. Absolute returns are perfectly comparable and if I lose money on a fund investment I do not go out and celebrate just because the fund performed couple percentage points better than some benchmark. In today's world, where every retail investor can chose to invest in long-short funds, absolute performance should be the core metric and not benchmark performance.
Jun
2
comment What is the motivation for index benchmark?
@user3264325, yes we are interested in risk adjusted returns but the focus should not be on "comparable risk" but on the risk of the very same asset you invest in and it should be about excess returns above the one of "riskless" (or better low-risk) assets. So when I invest I care about expected absolute returns in the context of the risk of its own asset. When you buy house insurance in the MidWest you also do not want to be quoted rates for insurance contracts on earthquake fault lines but want to pay for risk of the very same object you look to insure.
Jun
1
comment What is the motivation for index benchmark?
@user3264325, I am not sure this is a prudent approach. Guess how we all ended up in the midst of the biggest financial crisis since 1929: The "big guy theory" did not work all that great with banks, hedge funds, even money market funds; it does not work well as long as money is involved. We need prudent business practices and regulations, not to limit our freedom but to provide checks and balances because money managers are certainly not holding themselves to fiduciary duties because they truly enjoy doing so.
May
28
comment Volatility of Option
yes as long as you have deterministic r and sigma, as far as I understood the paper.
May
28
comment Volatility of Option
...which then basically sums up most B-S assumptions ;-)
May
28
comment Is there any other way to measure option pricing model performance than proximity to market prices?
..the market, or (b) you derive a model that makes its own asset price level/return prediction in the hope that market prices are dislocated short-term and converge to levels a model predicts.
May
28
comment Is there any other way to measure option pricing model performance than proximity to market prices?
I do not share the same summary of the "academic approach". I do not think that academicians consider market prices as benchmark because they believe in the EMH theory. I can again only repeat that most everyone considers market prices because they function as yardstick against which everything is measures. Even my own models, if market prices do not converge to my model then my model was obviously flawed and not the market. You look to either (a) derive a model as close to market prices as possible in order to price similar assets that may not be traded using inputs that were calibrated to..