Retail investors are jumping into the markets in record numbers. Less certain is whether a majority of these new retail investors have the tools and the experience needed to do well over time. Tickeron's platform of Artificial Intelligence-generated can help.
According to Piper Sandler analysts, retail trading volume that goes through wholesale market makers accounted for nearly half of all trading in the first 11 days in January. For some wealth managers and trading platforms, this has been welcome news. Morgan Stanley just completed its takeover of E*Trade, reporting 900,000 new self-directed accounts over the last two quarters. Charles Schwab, which is now combined with TD Ameritrade, has seen daily trading volumes of close to 8 million trades, which is well higher than volume last year. Schwab has also reported a 16% uptick in average margin loan balances over the past two quarters, suggesting that investors are growing more comfortable with risk-taking.
It's good to see that new investors are showing interest in trading and investing, but more concerning to me is whether investors are taking on too much risk and making trades without having strong fundamental and technical research to back those trades. In my view, it won't take long for many investors to lose money - that's what the market almost always does to blind risk-takers.
Tickeron has several Artificial-Intelligence driven platforms, and if you're new to retail trading and investing, it could be helpful to have A.I. help you drive your investment-decision making. Below, Tickeron's A.I. analyzes major banks that could benefit from the wave of retail investor interest.
XLF saw its Momentum Indicator move above the 0 level on June 24, 2025. This is an indication that the stock could be shifting in to a new upward move. Traders may want to consider buying the stock or buying call options. Tickeron's A.I.dvisor looked at 84 similar instances where the indicator turned positive. In of the 84 cases, the stock moved higher in the following days. The odds of a move higher are at .
Following a 3-day Advance, the price is estimated to grow further. Considering data from situations where XLF advanced for three days, in of 349 cases, the price rose further within the following month. The odds of a continued upward trend are .
The Aroon Indicator entered an Uptrend today. In of 332 cases where XLF Aroon's Indicator entered an Uptrend, the price rose further within the following month. The odds of a continued Uptrend are .
The 10-day RSI Indicator for XLF moved out of overbought territory on July 07, 2025. This could be a bearish sign for the stock. Traders may want to consider selling the stock or buying put options. Tickeron's A.I.dvisor looked at 54 similar instances where the indicator moved out of overbought territory. In of the 54 cases, the stock moved lower in the following days. This puts the odds of a move lower at .
The Stochastic Oscillator may be shifting from an upward trend to a downward trend. In of 67 cases where XLF's Stochastic Oscillator exited the overbought zone, the price fell further within the following month. The odds of a continued downward trend are .
The Moving Average Convergence Divergence Histogram (MACD) for XLF turned negative on July 14, 2025. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 45 similar instances when the indicator turned negative. In of the 45 cases the stock turned lower in the days that followed. This puts the odds of success at .
Following a 3-day decline, the stock is projected to fall further. Considering past instances where XLF declined for three days, the price rose further in of 62 cases within the following month. The odds of a continued downward trend are .
XLF broke above its upper Bollinger Band on June 24, 2025. This could be a sign that the stock is set to drop as the stock moves back below the upper band and toward the middle band. You may want to consider selling the stock or exploring put options.
The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
Category Financial