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Archive for the ‘Trading ideas’ Category

VIX Futures Sets Record, Volatility Trading on the Rise

19 Nov

Article by: Daniel P. Collins
Published by: Futures Magazine
Date: 17 Nov 2010

“The Chicago Board Options Exchange’s (CBOE) volatility complex has been a successful franchise stemming from its benchmark CBOE volatility index (VIX). But since launching futures and options on the benchmark VIX, options volume has been more impressive than the futures contract which is offered through CBOE Futures Exchange (CFE). But in November VIX futures has set a series of volume records culminating on Tuesday Nov. 16 with record volume of 70,754, which surpassed a two-week old record by 50%”

Full article: Link

 
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Posted in Trading ideas

 

Volatility and its Impact on Your Portfolio

21 Oct

Published by: Direxionfunds
Date: 13 Nov 2007

“Assessing risk is an important part of investing. One commonly
used measure of risk is volatility, which measures
the variability of a security’s return through time. If
Security A and Security B have the same expected return
but Security B has greater variability of return, Security B
is more volatile than Security A. Given an equal return
most investor’s would prefer a security with less volatility,
which means that investors expect a higher return on an
investment when it carries a higher level of volatility.
This paper takes a close look at the basics of volatility, discusses
why it matters in relation to portfolio management,
and suggests some methods for managing and controlling
the impact of volatility. In highly volatile markets,
heightened emotions can lead to clouded judgment.
Controlling the amount of volatility within your portfolio
can allow for more prudent decisions.”

Full article (PDF): Link

 
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Posted in Hedging, Investing ideas, Trading ideas

 

Variance Swaps on Time-Changed Levy Processes

16 Oct

Article by: Peter Carr, Roger Lee, and Liuren Wu
Published by: NYU
Date: 6 Apr 2009

“We prove that a multiple of a log contract prices a variance swap, under arbitrary exponential Levy dynamics, stochastically time-changed by an arbitrary continuous clock having arbitrary correlation with the driving Levy process, subject to integrability conditions. We solve for the multiplier, which depends only on the Levy process, not on the clock. In the case of an arbitrary continuous underlying returns process, the multiplier is 2, which recovers the standard no-jump variance swap pricing formula as a special case of our framework. In the presence of negatively- skewed jump risk, however, we prove that the multiplier exceeds 2, which agrees with calibrations of time-changed Levy processes to equity options data. Finally we show that discrete sampling increases variance swap values, under an independence condition; so if the commonly-quoted 2 multiple undervalues the continuously-sampled variance, then it undervalues furthermore the discretely-sampled variance.”

Full article (PDF): Link

 
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Posted in Hedging, Realized volatility, Trading ideas

 

Risk and Volatility: Econometric Models and Financial Practice

14 Oct

Article by: Robert F. Engle III
Nobel lecture
Date: 8 Dec 2003

“The advantage of knowing about risks is that we can change our behavior to
avoid them. Of course, it is easily observed that to avoid all risks would be impossible;
it might entail no flying, no driving, no walking, eating and drinking
only healthy foods and never being touched by sunshine. Even a bath could
be dangerous. I could not receive this prize if I sought to avoid all risks. There
are some risks we choose to take because the benefits from taking them exceed
the possible costs. Optimal behavior takes risks that are worthwhile. This
is the central paradigm of finance; we must take risks to achieve rewards but
not all risks are equally rewarded. Both the risks and the rewards are in the future,
so it is the expectation of loss that is balanced against the expectation of
reward. Thus we optimize our behavior, and in particular our portfolio, to
maximize rewards and minimize risks.

“This simple concept has a long history in economics and in Nobel citations.
Markowitz (1952) and Tobin (1958) associated risk with the variance in
the value of a portfolio. From the avoidance of risk they derived optimizing
portfolio and banking behavior. Sharpe (1964) developed the implications
when all investors follow the same objectives with the same information. This
theory is called the Capital Asset Pricing Model or CAPM, and shows that
there is a natural relation between expected returns and variance.”

Full article (PDF): Link

 
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Posted in Hedging, Implied volatility, Investing ideas, Trading ideas

 
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