Yes. I generally exit a credit spread at 50% profit. Then reenter selling a 15Δ Call and/or Put and buying $10 wings usually 35-50 DTE. I have found that, on average, I am looking for an exit in 11-15 days. As an aside, I agree with others that carrying a trade to expiration carries additional, and for me, unacceptable risk. Best
The close is in place and will be adjusted according to market conditions. i'm looking for the simplest solutions. Thanks!
Haters will be haters. I've been using credit spreads like this for a while. And like the %^&** above.. I also use charts with indicators to show me "when" to place the trade. Take the profit... and look for the next opportunity.
I used to use Technical Analysis to make trading decisions. Trouble is nothing seemed to work. When Bollinger Bands said BUY, Stochastics said SELL. Then I realized I couldn't see the forest because of the trees. So I eliminated all these indicators from my chart and now all is well. Acceleration Bands (ABANDS) Accumulation/Distribution (AD) Average Directional Movement (ADX) Adaptive Moving Average (AMA) Absolute Price Oscillator (APO) Aroon (AR) Aroon Oscillator (ARO) Average True Range (ATR) Volume on the Ask (AVOL) Volume on the Bid and Ask (BAVOL) Bollinger Band (BBANDS) Bar Value Area (BVA) Bid Volume (BVOL) Band Width (BW) Commodity Channel Index (CCI) Chande Momentum Oscillator (CMO) Double Exponential Moving Average (DEMA) Directional Movement Indicators (DMI) Exponential (EMA) Fill Indicator (FILL) Ichimoku (ICH) Keltner Channel (KC) Linear Regression (LR) Linear Regression Angle (LRA) Linear Regression Intercept (LRI) Linear Regression Slope (LRM) Moving Average Convergence Divergence (MACD) Max (MAX) Money Flow Index (MFI) Midpoint (MIDPNT) Midprice (MIDPRI) Min (MIN) MinMax (MINMAX) Momentum (MOM) Normalized Average True Range (NATR) On Balance Volume (OBV) Price Channel (PC) PLOT (PLT) Percent Price Oscillator (PPO) Price Volume Trend (PVT) Rate of Change (ROC) Rate of Change (ROC100) Rate of Change (ROCP) Rate of Change (ROCR) Relative Strength Indicator (RSI) Session Volume (S_VOL) Parabolic Sar (SAR) Session Cumulative Ask (SAVOL) Session Cumulative Bid (SBVOL) Simple Moving Average (SMA) Standard Deviation (STDDEV) Stochastic (STOCH) Stochastic Fast (StochF) T3 (T3) Triple Exponential Moving Average (TEMA) Triangular Moving Average (TRIMA) Triple Exponential Moving Average Oscillator (TRIX) Time Series Forecast (TSF) TT Cumulative Vol Delta (TT CVD) Ultimate Oscillator (ULTOSC) Volume At Price (VAP) Volume (VOLUME) Volume Delta (Vol ?) Volume Weighted Average Price (VWAP) Williams % R (WillR) Weighted Moving Average (WMA) Welles Wilder's Smoothing Average (WWS) Now I just use volume, open interest, Delta, Theta, implied volatility, and standard deviation to make my trades. And it works. No more Swinging Tops or Dojis for me. Best
If you believe in the Efficient Market Hypotheses all those indicators and even fundamental information, while interesting for sure, do nothing for your actual trades' results. What does? Strategies, probabilities and an understanding of implied volatility
You cannot take the efficient market hypothesis to extremes as you are doing there because there is a legal ban on insider information sharing. Therefore by definition all information is not available in the market and therefore the market CANNOT be totally efficient at all times and under all circumstances. Insider information can possible be guessed at by a number of the indicators noted above or some kind of analysis and thereby give you an edge. I would say its more truthful that no indicator is 100% correct all of the time - there has been extensive scientific back-testing of theories over long periods and it can be shown that almost none show any edge over the market if you go back to say 1900 to today. I think an interesting analogy can be found in weather prediction - which we also know to be somewhat subject to error. Weather prediction is done in two main ways: Take technical indicators like pressure, wind and temperature and so forth and deduce on physical modelling where the weather is going; Building a gigantic database of all weather patterns in the world with as many data points on temperature and yada yada as you can. When you see any specific set of measurements of data points you look in your data base for an identical one and predict the weather will develop in the same way as it did after that similar entry.