Paper: HFT y su impacto

High Frequency Trading and its Impact on Market Quality

Abstract:
This paper examines the impact of high frequency traders (HFTs) on equities markets. I analyze a unique data set to study the strategies utilized by HFTs, their profitability, and their relationship with characteristics of the overall market, including liquidity, price efficiency, and volatility. I find that in my sample HFTs participate in 77% of all trades and that they tend to engage in a price-reversal strategy. I find no evidence suggesting HFTs withdraw from markets in bad times or that they engage in abnormal front-running of large non-HFTs trades. The 26 high frequency trading (HFT) firms in the sample earn approximately $3 billion in profits annually. HFTs demand liquidity for 50.4% of all trades and supply liquidity for 51.4% of all trades. HFTs tend to demand liquidity in smaller amounts, and trades before and after a HFT demanded trade occur more quickly than other trades. HFTs provide the inside quotes approximately 50% of the time. In addition if HFTs were not part of the market, the average trade of 100 shares would result in a price movement of $.013 more than it currently does, while a trade of 1000 shares would cause the price to move an additional $.056. HFTs are an integral part of the price discovery process and price efficiency. Utilizing a variety of measures introduced by Hasbrouck (1991a, 1991b, 1995), I show that HFTs trades and quotes contribute more to price discovery than do non-HFTs activity. Finally, HFT reduces volatility. By constructing a hypothetical alternative price path that removes HFTs from the market, I show that the volatility of stocks is roughly unchanged when HFT initiated trades are eliminated and significantly higher when all types of HFT trades are removed.

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Paper: Correlación y el SPY

Intraday Correlation Patterns between the S&P 500 and Sector Indices

Abstract:
In this brief research note, I explore recent patterns in intraday return and volume correlation between the S\&P 500 and sector indices, as represented by minutely data from Aug. 23 to Sep. 10 for the SPDR exchange-traded funds. Notably, there appears to be evidence of two previously unreported patterns in intraday correlation. First, there is a “U-shaped” trend in return correlation, characterized by higher correlation at open and close and lower correlation during mid-day hours. Second, volume correlation is marked by lower values in the morning and increasing values in the afternoon. In some cases, this trend even takes the infamous “hockey-stick” shape, exhibiting stable values in the morning but sharply increasing values in the late afternoon. To ensure that these patterns are not a function of the choice of correlation window size, I confirm that these patterns are qualitatively stable over correlation windows ranging from 10 minutes to 90 minutes. These findings indicate that non-time-stationary patterns exist not only for volume and volatility, as previously reported, but also for the correlation of return and volume between the market and sector indices. These results have possible implications for intraday market efficiency and for trading strategies that rely on intraday time-stationarity of return or volume correlation.

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Paper: Instrumentos de volatilidad como hedge

Using Volatility Instruments as Extreme Downside Hedges

Abstract:
“Long volatility” is thought to be an effective hedge against a long equity portfolio, especially during periods of extreme market volatility. This study examines using volatility futures and variance futures as extreme downside hedges, and compares their effectiveness against traditional “long volatility” hedging instruments such as out-of-the-money put options. Our results show that CBOE VIX and variance futures are more effective extreme downside hedges than out-of-the-money put options on the S&P 500 index, especially when reasonable actual and/or estimated costs of rolling contracts have taken into account. In particular, using 1-month rolling as well as 3-month rolling VIX futures presents a cost-effective choice as hedging instruments for extreme downside risk protection as well as for upside preservation.

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Convexidad y el Flattening Trade

Minyanville tiene un interesante post y una buena razon para seguir pensando que las yields de la parte larga puede seguir bajando.

So long as there are convexity gains to be made in duration-neutral yield curve flatteners, long-term yields can continue to fall.

Si entendiste esto, bien. Y si no, Minyanville lo explica muy bien.

Whoa, that’s a mouthful. But it’s not all that complex once we dissect it from back to front for a 5-10 year Treasury trade. The flattening trade is borrowing a shorter maturity, here the 5-year, and lending at a longer-maturity, here the 10-year. The duration-neutral aspect is simply a hedge ratio to neutral overall interest rate exposure; we’d need to trade about 1.8 5-years for every 10-year at last count.

Convexity is the rate at which duration — the sensitivity of bonds to interest rates — changes as a function of yields. Convexity is valuable: The higher it is, the more the bond gains as rates fall and the less the bond loses as rates rise. For those of you comfortable with option Greeks, think of duration and convexity as you might delta and gamma.

No se porque, pero todo este tema me hizo acordar a una vieja cancion que dice asi en su estribillo.

I’m forever blowing bubbles,

Pretty bubbles in the air.

They fly so high,

Nearly reach the sky,

Then like my dreams,

They fade and die.

Fortune’s always hiding,

I’ve looked everywhere,

I’m forever blowing bubbles,

Pretty bubbles in the air.

¿inversor o trader de moneda?

Adam Kritzer, en un post en Forex Blog, plantea muy bien los diferentes horizontes temporales que manejan los inversores y los traders (en este caso de moneda), haciendo foco en el Euro.

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But seriously, currency traders must adapt to the zero-sum nature of forex markets by shortening their time horizon. Stock market investors, on the other hand, are not bound by this constraint. In fact, by holding stocks for a long enough time period, investors can actually turn this into an advantage.

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Simply, currencies fluctuate. Since its introduction 10 years ago, the Euro has fallen, then risen, then fallen, then risen, then fallen again to its current level. If you initially invested in Europe 2 years ago, the exchange rate would erode your returns if you tried to sell now. If you invested 5 years ago, you would break even. If you invested 10 years ago, you would come out ahead. In the end, it’s only a question of perspective. Still, if you maintain your positions for long enough, either you will break-even from the exchange rate or it will only marginally affect your returns (on an annualized basis).

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In short, unless you deliberately want to speculate on exchange rates, don’t worry about them! If your investing horizon is long enough, their fluctuations will neither help nor hurt you in a meaningful way.

un poquito de leverage…

CSS Analytics tiene un post donde muestra la relación entre fundamentals y análisis técnico vía el Efecto Apalancamiento.

The “leverage effect”  and subsequent theory originated from early studies done by Fisher Black (of Black-Scholes fame). Black  found  that stock volatility tended to rise when stock prices went down and that volatility fell when prices went up. The economic rationale behind this effect is rooted in the firm’s capital structure. As a stock rises, the percentage of equity to debt rises, and the firm becomes less risky since the debt holders claims to the company value are more limited. Conversely, as the stock falls, the percentage of equity to debt falls, and the increased share of debt holder claims make the firm’s equity more risky. Thus a falling stock price should lead to an increase in future volatility.

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Well most educated finance students understand first of all the principle of balance sheet leverage: when you add debt to the balance sheet, a given % increase in sales has a disproportionately larger increase in the % increase in earnings because you are netting out a fixed interest cost. If we all agree that 1) the market tends to discount future GDP and hence revenues, and 2) that firm value is also a function of earnings growth and total earnings, then the firms that will experience the greatest percentage change in firm value when the market forecasts a recovery should mathematically be the most leveraged firms.

This affects the technical trader in many ways whether you trade short-term or not. It means that the biggest winning stocks will have strong velocity relative to volatility (think sharpe ratio) only while the market is rising. When the market peaks, in fact, their velocity relative to volatility will have peaked at extraordinary levels. At this point the firm’s debt to equity is often at unsustainable  levels–leaving it vulnerable to the largest proportionate changes in firm leverage–and hence future volatility/downside risk.

Paper: timing para operar

Paying Attention: Overnight Returns and the Hidden Cost of Buying at the Open

Abstract:
Using 13 years of intraday data for U.S. stocks, we find a strong tendency for positive returns during the overnight period followed by reversals during the trading day. This behavior is driven by an opening price that is high relative to intraday prices. We find this temporary price inflation at the open is concentrated among stocks that have recently attracted the attention of retail investors, and these high attention stocks have high levels of net retail buying at the start of the trading day. In addition, we document that the sensitivity of opening prices to retail investor attention is more pronounced for stocks that are difficult to value and costly to arbitrage, and is greater during periods of high retail investor sentiment. The additional implicit transaction costs for retail traders who buy high attention stocks near the open frequently exceed the effective half spread.

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Paper: Valor predictivo de las recomendaciones

Projected Earnings Accuracy and the Profitability of Stock Recommendations

Abstract:
We find that while analyst characteristics have economically small predictive power for the accuracy of earnings forecasts, they have economically significant predictive power for the profitability of stock recommendations. Analyst characteristics can be used to identify ex ante more profitable stock recommendations and therefore they are helpful for identifying profit opportunities. Taking an investor-oriented, calendar-time approach, we project the firm-specific earnings accuracy of analysts based on their individual characteristics. We show that analysts with higher projected earnings accuracy issue significantly more profitable recommendations than analysts with lower projected earnings accuracy. The long portfolio based on the recommendations of the analysts within the highest projected accuracy quintile earns excess returns of up to 7.53% per year (before transactions costs) in the 1994 to 2007 time period. Analysts with characteristics that are related to higher earnings accuracy also issue more profitable stock recommendations.

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Mr. Roboto, machine or mannequin

Ayer hubo Crash en el Dow, al principio el mundo blog hablo de ordenes abultadas debido a “dedos gordos”

Here’s what I am hearing. There was a “fat finger” that caused someone to execute a large order for PG, a Dow component at a price in the high 30s when it was trading above 60.  Another word out is that someone entered a $16 BILLION trade instead of a $16 million trade – talk about fat fingers. This triggered a lot of stop loss orders in Dow Futures and caused a cascade of losses that at one point reached more than 1000 points on the Dow.

Creditwritedowns.com

Pero hoy, la responsabilidad del hecho se la adjudican a Mr. Roboto y co.

Here’s the COO of NYSE Euronext speaking to Bloomberg:

May 6 (Bloomberg) — Computerized trades sent to electronic networks turned an orderly stock market decline into a rout, according to Larry Leibowitz, the chief operating officer of NYSE Euronext. Nasdaq OMX Group Inc. canceled trades in 286 securities that rose or fell 60 percent or more.

While the first half of the Dow Jones Industrial Average’s 998.5-point intraday plunge probably reflected normal trading, the selloff snowballed because of orders sent to venues with no investors willing to match them, Leibowitz said in an interview on Bloomberg Television.

“If you look at the charts you can see fairly clearly where the trades came in,” he said from New York. “It’s that V-shaped drop where it came down and snapped right back up. You had some very high-cap stocks trading down 50 percent or large percentages in a split-instant because there really was no liquidity in electronic markets.”

FT Alphaville

Quien mejor para pegarle a los bots que Zero Hedge (Audio Incluido)

“Guys this is probably the craziest I have seen it down here ever.” Here it is, memorialized for the generations and away from the now openly ridiculous disinformation propaganda of the mainstream media, just what a full market meltdown panic sounds like: straight from the epicenter, the S&P 500 pits. Luckily open ouctry still exists, if at least for shock value. Click here for a first hand account of the most shocking 15 minutes in recent market history. Fat finger my ass.

Por ultimo, FT Alphaville postea: una declaración de NASDAQ desligándose de lo ocurrido; y una lista con las acciones afectadas.

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UPDATE:

Kid Dynamite tiene 3 post que vale la pena leer:

holy cow wtf stocks heres what im hearing

more on crash possible trigger and high frequency trading

does anyone want to defend decision to cancel trades

Consejos de traders para traders

Brett Steenbarger y Mark Wolfinger -desde sus respectivos blogs- hacen recomendaciones de formación (Steenbarger) y de manejo de riesgo (Wolfinger) basándose en sus experiencias personales.

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In general, I would highlight three areas of learning that I would want to have if I were looking to start out as a trader today:

1) Macroeconomics – I would want to have a grasp of intermarket relationships and how monetary policy affects interest rates, currencies, and economic growth. This information may not determine the trade over the next half-hour, but it does govern the market’s longer time frame picture and help determine market trends. A lack of understanding of macroeconomics and intermarket relationships has been a major reason many short-term traders have lost money fighting the market over the last few months.

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It’s very important to understand the difference between trades that are well-managed and those that luckily end well.  This is a subtlety lost on too many.  The ‘obvious’ but inaccurate conclusion is often: ‘If I made a profit then it was a good trade and I must have handled it well.’

To understand the risk of any given position (or portfolio), it’s essential to know

• How much can be lost, if the worst case scenario occurs
• How much can be lost today, under unusual market conditions
• What you have to gain by holding the position; i.e., potential profits
• The probability of earning a profit from the position as it exists now
• How theta (the passage of time) affects the position
• The effect of a large change in implied volatility (vega risk)

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