The Sqn Asset Finance Income ($SQN) Rundown (2019-09-13)

REPORTING FOR 2019-09-13 | THEBUNSENBURNER.COM: With the assistance of the Beat The Market Analyzer software and our own in-house methods, we have conducted a deep analysis of how SQN has been trading over the last 2 weeks and the past day especially. On its latest session, Sqn Asset Finance Income ($SQN) opened at 81.32, reaching a high of 82.0 and a low of 81.2 before closing at a price of 81.6. There was a total volume of 297303.0.

VOLUME INDICATORS: We saw an accumulation-distribution index of 110.4, an on-balance volume of -0.9508, chaikin money flow of 1.35294 and a force index of 6472.03378. There was an ease of movement rating of -0.34667, a volume-price trend of 572.98935 and a negative volume index of 1000.0. What do these volume indicators mean for SQN? Click here for an explanation.

VOLATILITY: We noted an average true range of 10.48402, bolinger bands of 154.56491, an upper bollinger band of -72.41411, lower bollinger band of 81.2, a bollinger high band indicator of 1.0, bollinger low band indicator of nan, a central keltner channel of 81.50667, high band keltner channel of 80.82667, low band keltner channel of 82.18667, a high band keltner channel indicator of 1.0 and a low band keltner channel indicator of 1.0. There was a donchian channel high band of 81.2, a donchian channel low band of 81.2, a donchian channel high band indicator of 1.0, and a donchian channel low band indicator of 1.0. What do these volatility indicators mean for SQN? Click here for an explanation.

TREND: We calculated a Moving Average Convergence Divergence (MACD) of -1.80046, a MACD signal of -1.00026, a MACD difference of -0.80021, a fast Exponential Moving Average (EMA) indicator of 81.2, a slow Exponential Moving Average (EMA) indicator of 81.2, an Average Directional Movement Index (ADX) of unknown, an ADX positive of 20.0, an ADX negative of 20.0, a positive Vortex Indicator (VI) of 1.0, a negative VI of 1.0, a trend vortex difference of 0.00864, a trix of 201.72634, a Mass Index (MI) of 1.0, a Commodity Channel Index (CCI) of -66.66667, a Detrended Price Oscillator (DPO) of -44.96015, a KST Oscillator (KST) of 1240.62738 and a KST Oscillator (KST Signal) of 1240.62738 (leaving a KST difference of -553.59777). We also found an Ichimoku rating of 81.66, an Ichimoku B rating of 81.66, a Ichimoku visual trend A of 43.786, an Ichimoku visual trend B of 44.82913, an Aroon Indicator (AI) up of 4.0 and an AI indicator down of 4.0. That left a difference of -4.0. What do these trend indicators mean for SQN? Click here for an explanation.

MOMENTUM: We found a Relative Strength Index (RSI) of 50.0, a Money Flow Index (MFI) of 100.0, a True Strength Index (TSI) of 100.0, an ultimate oscillator of 99.73381, a stochastic oscillator of 117.64706, a stochastic oscillator signal of 117.64706, a Williams %R rating of 17.64706 and an awesome oscillator of -10.73243. What do these momentum indicators mean for SQN? Click here for an explanation.

RETURNS: There was a daily return of 124.06274, a daily log return of -444.73668 and a cumulative return of -98.82906.

What the heck does all of this mean? If you are new to technical analysis, the above may be gibberish to you, and that’s OK (though we do advise learning these things). The bottom line is that AS OF 2019-09-13 (if you are reading this later, the analysis will be out of date), here is what our deep analysis of technical indicators are telling us for Sqn Asset Finance Income ($SQN)…

For a more complete analysis, run all of this through the BTMA software.

DISCLAIMER: We are not registered investment advisers and the above analysis should be taken at face value only. We strongly advise against buying or selling Sqn Asset Finance Income ($SQN) based solely on our analysis above, and are not responsible for any losses that you may incur if you choose make any investment decisions based on the above.

Franco Germanio

I am a PhD in Mathematics and perform comprehensive technical analysis on stocks.

3898 Forest Drive, Mclean VA 22101
Ph: 703-918-6381
franco@thebunsenburner.com
Franco Germanio

Franco Germanio

I am a PhD in Mathematics and perform comprehensive technical analysis on stocks. 3898 Forest Drive, Mclean VA 22101 Ph: 703-918-6381 franco@thebunsenburner.com