JonathanBlack Scholes, Options, Straddles, Strangles, Volatility, Volatility ModelingBlack-Scholes, Implied Volatility, Options, Straddles, Strangles, Volatility

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Home Posts Tagged "Volatility"

JonathanConvexity, Correlation, Factor Risk, Higher Moments, Multifactor Models, Risk Management, S&P500 Index, Strategy Robustness, Tail Risk, VIX Index, VIX Index, Volatility, Volatility ETF Strategy, Volatility ModelingConvexity, Correlation, Factor Risk, Kurtosis, Leveraged ETFs, MultiFactor Models, Sem--deviation, Skewness, Sortino, Tail Risk, Volatility

As markets continue to make new highs against a backdrop of ever diminishing participation and trading volume, investors have legitimate reasons for being concerned about prospects for the remainder of 2016 and beyond, even without consideration to the myriad of economic and geopolitical risks that now confront the US and global economies. Against that backdrop,…

JonathanETFs, Hedge Funds, VIX Index, Volatility ETF Strategy, Volatility ModelingETFs, Hedge Funds, Volatility

Grace Kim, Brand Director at DarcMatter, does a good job of setting out the pros and cons of ETFs vs hedge funds for the family office investor in her LinkedIn post. She points out that ETFs now offer as much liquidity as hedge funds, both now having around $2.96 trillion in assets. So, too, are her…

JonathanETFs, Hedge Funds, Relative Value, VIX Index, Volatility ETF Strategy, Volatility ModelingLong/Short, Relative Value, Volatility, Volatility ETFs

The popular VIX blog Vix and More evaluates the performance of the VIX ETFs (actually ETNs) and concludes that all of them lost money in 2015. Yes, both long volatility and short volatility products lost money! Source: Vix and More By contrast, our Volatility ETF strategy had an exceptional year in 2015, making money in…

JonathanEconometrics, Machine Learning, Mean Reversion, Momentum, Performance Testing, Strategy Development, Systematic Strategies, Volatility ModelingMean Reversion, Momentum, Strategy Performance, Volatility

Building a winning strategy, like the one in the e-Mini S&P500 futures described here is only half the challenge: it remains for the strategy architect to gain an understanding of the sources of strategy alpha, and risk. This means identifying the factors that drive strategy performance and, ideally, building a model so that their relative…

LEARNING TO TRUST A TRADING SYSTEM One of the most difficult decisions to make when running a systematic trading program is knowing when to override the system. During the early 2000’s when I was running the Caissa Capital fund, the models would regularly make predictions on volatility that I and our head Trader, Ron Henley,…

JonathanHedge Funds, VIX Index, Volatility ETF Strategy, Volatility ModelingHedge Funds, SVXY, UVXY, VIX, Volatility, Volatility ETFs, VXX, XIV

Volatility as an asset class has grown up over the fifteen years since I started my first volatility arbitrage fund in 2000. Caissa Capital grew to about $400m in assets before I moved on, while several of its rivals have gone on to manage assets in the multiple billions of dollars. Back then volatility was…

JonathanFactor Models, Mean Reversion, Mean Reversion Strategies, Momentum, Momentum Strategies, VIX Index, Volatility ModelingEBIT, Mean Reversion, Momentum, Value, Volatility

The Fama-French World For many years now the “gold standard” in factor models has been the 1996 Fama-French 3-factor model: Here r is the portfolio’s expected rate of return, Rf is the risk-free return rate, and Km is the return of the market portfolio. The “three factor” β is analogous to the classical β but not equal to it, since there are now…

JonathanFutures, Mathematca, Mathematica, Scalping, Trading, Volatility ModelingComputable Document Format, Dynamic model, E-min, Execution, Extreme Value Distribution, Futures, Gaussian, High Frequency, IOC orders, Latency, Limit order book, Mathematica, Mote Carlo Simulation, Non-Gaussian, Scalping, Trade Expression, Volatility

NOTE: if you are unable to see the Mathematica models below, you can download the free Wolfram CDF player and you may also need this plug-in. You can also download the complete Mathematica CDF file here. In this post I want to explore aspects of scalping, a type of strategy widely utilized by high frequency trading…

JonathanOptions, Stochastic Differential Equations, Volatility ModelingJump Diffusion, Options, Smile, Volatility

The “implied volatility” corresponding to an option price is the value of the volatility parameter for which the Black-Scholes model gives the same price. A well-known phenomenon in market option prices is the “volatility smile”, in which the implied volatility increases for strike values away from the spot price. The jump diffusion model is a…

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