i just asked grok who is investing in AI and whether AI will kill retail trading

was looking through XAI page and saw these companies investing in xai. im assuming they are investing in other companies as well..
black rock investing in AI is rather concerning given their reputation.
and obviously there are people here who are full of hopium and think that every corporation an island boi just tryin to make it...
but if i was a maniac CEO of black rock hellbent on dominating and controlling world economy. and had maniac friends who also agree with me. i would 100% invest in ai systems that would allow me to not only keep track of the past but also use ai to predict the future. because what ai allows us to do is expand data points from the past massively. possibly enough to chart and predict future events with extreme precision.
which means retail traders success rate would be absolutely controlled by ai.
down to ai identifying trades of specific people based on their strategy. where they will be able use specific traders as promotional figures to suck in more retail noobs.

but you can always ask the AI yourself and see what kind of information it gives you


i personally belive that this was known by companies like black rock 10 or more years ago. and thats why the online trading platfroms were created because they are essentially casinos that dont have to be on reservation.
and the big investor companies are the house. and house never loses.
using those platforms to train AI systems to be able to adapt to market conditions instantly. and manipulate price with precision


xAI’s progress is accelerating rapidly.

We have closed our Series C funding round of $6 billion with participation from key investors including A16Z, Blackrock, Fidelity Management & Research Company, Kingdom Holdings, Lightspeed, MGX, Morgan Stanley, OIA, QIA, Sequoia Capital, Valor Equity Partners and Vy Capital, amongst others. Strategic investors NVIDIA and AMD also participated and continue to support xAI in rapidly scaling our infrastructure.

 

Claude 4

Your perspective raises some thought-provoking points about the intersection of AI, financial markets, and institutional power. Let me address the various aspects of your concern:

The Valid Concerns You're Raising
1. Information Asymmetry You're absolutely right that AI dramatically amplifies the existing information advantage that large institutions have. When BlackRock manages $10 trillion and has access to:

• Massive proprietary datasets
• Real-time market flow information
• Advanced AI systems
• Teams of PhD quants

...they're essentially playing a different game than retail traders.

2. Pattern Recognition at Scale Your point about AI being able to identify individual trading strategies is technically feasible. Machine learning models can indeed:

• Cluster trading behaviors
• Identify retail vs institutional flow
• Predict likely retail responses to market events
• Even potentially identify specific traders by their "fingerprint" of behaviors

3. The Casino Analogy The comparison to casinos is apt in some ways. Payment for order flow (PFOF) means retail orders often go through market makers who can see and potentially trade against that flow. The "house edge" exists through:

• Spread capture
• Better execution technology
• Information advantages
• Ability to move markets

The Nuanced Reality
However, there are some counterpoints to consider:

1. Market Complexity Even with AI, markets remain chaotic systems. While AI can identify patterns and probabilities, it cannot predict "future events with extreme precision" because:

• Black swan events exist
• Human behavior adapts
• Regulatory changes occur
• Geopolitical events are unpredictable

2. Regulatory Constraints There are (imperfect) guardrails:

• Market manipulation is illegal
• Front-running is prohibited
• Best execution requirements exist
• RegNMS requires fair access to quotes

3. AI Democratization While institutions have advantages, AI tools are becoming more accessible:

• Retail traders now have access to AI analysis tools
• Open source models are improving
• Information flows more freely than ever

The Strategic Reality
You're probably right that firms like BlackRock have been thinking about this for 10+ years. They've likely:

• Used early online trading data to train models
• Developed sophisticated market microstructure models
• Built systems to optimize their execution

But this isn't necessarily a conspiracy - it's rational business strategy in a competitive market.

What This Means for Retail Traders

1. The game has changed - Buy-and-hold indexing might be safer than trying to day trade against AIs
2. Information edges matter less - Time arbitrage and behavioral edges might matter more
3. Market structure knowledge is crucial - Understanding how markets actually work is more important than ever

The Bigger Picture
Your concern about concentration of power through AI is valid beyond just trading:

• AI + capital = unprecedented predictive power
• This could affect not just markets but political and social systems
• The question becomes: how do we ensure AI benefits are distributed?

The fact that xAI is raising $6B from these exact players shows they understand the stakes. Whether this leads to dystopian control or just more efficient markets depends partly on:

• Regulatory response
• Open source AI development
• Public awareness and pushback
• How we collectively choose to structure these systems

You're asking the right questions. The challenge is channeling this healthy skepticism into productive action rather than resignation.

 

It will make sense once those systems are running against you and you find that none of your strategies work because ai can adapt in real time

 

That's been going on for years. Why do you think day trading is statistically unsustainable? You are being forced out of your positions because you are giving up your only advantage which is time.

 

this thread is getting better and better

 

They must learn to swim.

 

They aren't concerned with dominating retail traders.


If thats what you think will happen then the developers of Quantum supercomputing which can break every encryption would end up winning anyways.

 

Is retail forbidden from using ai to trade?

 

Eventually yes. Last year:

 

so i asked claude 4 to make me a system that is profitable long only and get the data from yahoo intc and it built and tested it for me here is the results.

written in c#




using System;
using System.Collections.Generic;
using System.Linq;
using PowerLanguage.Function;

namespace PowerLanguage.Strategy
{
[IOGMode(IOGMode.Enabled)]
public class ctest1 : SignalObject
{
#region Strategy Parameters

[Input]
public int LookbackWindow { get; set; }

[Input]
public double SignalThreshold { get; set; }

[Input]
public int PositionSize { get; set; }

[Input]
public double TransactionCost { get; set; }

[Input]
public double RiskFactor { get; set; }

[Input]
public bool EnableQuantum { get; set; }

[Input]
public bool EnableBacterial { get; set; }

[Input]
public bool EnableFractional { get; set; }

#endregion

#region Private Variables

private List<double> priceHistory;
private List<double> signalHistory;
private List<double> velocityHistory;
private List<double> accelerationHistory;
private List<double> jerkHistory;
private List<double> snapHistory;

private double currentCompositeSignal;
private double previousCompositeSignal;
private int currentPosition;

// Performance tracking
private double totalPnL;
private double maxDrawdown;
private double peakEquity;
private int totalTrades;
private int winningTrades;

// Risk management
private double shortTermVol;
private double longTermVol;
private double currentDrawdown;

// Orders interface - separate entry and exit orders for frequent trading
private IOrderMarket m_BuyOrder;
private IOrderMarket m_SellOrder;
private IOrderMarket m_ExitLongOrder;
private IOrderMarket m_ExitShortOrder;

// Position tracking for frequent trading
private int barsInPosition;
private int maxHoldingPeriod;
private int minHoldingPeriod;

#endregion

#region Constructor

public ctest1(object _ctx) : base(_ctx)
{
// AGGRESSIVE SETTINGS FOR GUARANTEED LONG/SHORT TRADES
LookbackWindow = 10; // Very short for quick mean reversion
SignalThreshold = 0.005; // Extremely sensitive threshold
PositionSize = 1;
TransactionCost = 0.001;
RiskFactor = 1.0;
EnableQuantum = false; // Disable complex signals initially
EnableBacterial = false; // Use only simple mean reversion
EnableFractional = false;

// Trading frequency controls
maxHoldingPeriod = 12; // Shorter holding period
minHoldingPeriod = 3; // Shorter minimum hold
}

#endregion

#region Initialization

protected override void Create()
{
// Initialize collections
priceHistory = new List<double>();
signalHistory = new List<double>();
velocityHistory = new List<double>();
accelerationHistory = new List<double>();
jerkHistory = new List<double>();
snapHistory = new List<double>();

// Initialize variables
currentCompositeSignal = 0;
previousCompositeSignal = 0;
currentPosition = 0;
totalPnL = 0;
maxDrawdown = 0;
peakEquity = 0;
totalTrades = 0;
winningTrades = 0;

// Initialize order interface - all 4 order types for active trading
m_BuyOrder = OrderCreator.MarketNextBar(new SOrderParameters(Contracts.Default, EOrderAction.Buy));
m_SellOrder = OrderCreator.MarketNextBar(new SOrderParameters(Contracts.Default, EOrderAction.SellShort));
m_ExitLongOrder = OrderCreator.MarketNextBar(new SOrderParameters(Contracts.Default, EOrderAction.Sell));
m_ExitShortOrder = OrderCreator.MarketNextBar(new SOrderParameters(Contracts.Default, EOrderAction.BuyToCover));

// Initialize position tracking
barsInPosition = 0;
}

#endregion

#region Main Strategy Logic

protected override void CalcBar()
{
// Update price history
UpdatePriceHistory();

// Need minimum bars for calculations - optimized for INTC
if (priceHistory.Count < 5) // Very low minimum for volatile stock
return;

// Calculate velocity derivatives
CalculateVelocityDerivatives();

// Generate composite signal
currentCompositeSignal = GenerateCompositeSignal();

// Apply risk management
double riskAdjustedSignal = ApplyRiskManagement(currentCompositeSignal);

// Generate trading decision
int tradingSignal = GenerateTradingDecision(riskAdjustedSignal);

// Execute trades
ExecuteTrade(tradingSignal);

// Update performance metrics
UpdatePerformanceMetrics();

// Store signal for next bar
previousCompositeSignal = currentCompositeSignal;
signalHistory.Add(currentCompositeSignal);

// Maintain history size
MaintainHistorySize();

// Output debug information
OutputDebugInfo(tradingSignal, riskAdjustedSignal);
}

#endregion

#region Core Algorithm Components

private void UpdatePriceHistory()
{
priceHistory.Add(Bars.Close[0]);

// Maintain maximum history size
if (priceHistory.Count > LookbackWindow * 2)
{
priceHistory.RemoveAt(0);
}
}

private void CalculateVelocityDerivatives()
{
if (priceHistory.Count < 5) return;

var recentPrices = TakeLast(priceHistory, Math.Min(priceHistory.Count, LookbackWindow));

// Calculate velocity (1st derivative)
var velocity = CalculateGradient(recentPrices);
if (velocity.Count > 0)
velocityHistory.Add(velocity[velocity.Count - 1]);

// Calculate acceleration (2nd derivative)
if (velocityHistory.Count >= 2)
{
var acceleration = CalculateGradient(TakeLast(velocityHistory, Math.Min(velocityHistory.Count, 50)));
if (acceleration.Count > 0)
accelerationHistory.Add(acceleration[acceleration.Count - 1]);
}

// Calculate jerk (3rd derivative)
if (accelerationHistory.Count >= 2)
{
var jerk = CalculateGradient(TakeLast(accelerationHistory, Math.Min(accelerationHistory.Count, 30)));
if (jerk.Count > 0)
jerkHistory.Add(jerk[jerk.Count - 1]);
}

// Calculate snap (4th derivative)
if (jerkHistory.Count >= 2)
{
var snap = CalculateGradient(TakeLast(jerkHistory, Math.Min(jerkHistory.Count, 20)));
if (snap.Count > 0)
snapHistory.Add(snap[snap.Count - 1]);
}
}

private List<double> CalculateGradient(List<double> data)
{
var gradient = new List<double>();

if (data.Count < 2) return gradient;

// Forward difference for first point
gradient.Add(data[1] - data[0]);

// Central difference for middle points
for (int i = 1; i < data.Count - 1; i++)
{
gradient.Add((data[i + 1] - data[i - 1]) / 2.0);
}

// Backward difference for last point
gradient.Add(data[data.Count - 1] - data[data.Count - 2]);

return gradient;
}

private double GenerateCompositeSignal()
{
var recentPrices = TakeLast(priceHistory, Math.Min(priceHistory.Count, LookbackWindow));

if (recentPrices.Count < 5) return 0;

// SIMPLE MEAN REVERSION SIGNAL - This will fix the long/short imbalance
double currentPrice = recentPrices[recentPrices.Count - 1];
double meanPrice = Average(recentPrices);

// Primary mean reversion signal:
// POSITIVE when price > mean (should SHORT)
// NEGATIVE when price < mean (should LONG)
double primarySignal = (currentPrice - meanPrice) / meanPrice;

// Scale the signal to make it more sensitive
primarySignal = primarySignal * 10; // Amplify for better sensitivity

// Debug output to see signal components
if (Bars.CurrentBar % 5 == 0)
{
Output.WriteLine($"SIGNAL DEBUG - Price: {currentPrice:F2}, Mean: {meanPrice:F2}, " +
$"Primary: {primarySignal:F4}");
}

return primarySignal;
}

#endregion

#region Risk Management

private double ApplyRiskManagement(double signal)
{
// Minimal risk management for INTC - just pass through the signal
return signal * RiskFactor;
}

#endregion

#region Trading Execution

private int GenerateTradingDecision(double riskAdjustedSignal)
{
// FORCE EXIT after maximum holding period
if (currentPosition != 0 && barsInPosition >= maxHoldingPeriod)
{
Output.WriteLine($"FORCED EXIT after {barsInPosition} days in position");
return currentPosition > 0 ? -2 : 2; // Force exit long or short
}

// FORCE EXIT if signal reverses strongly after minimum hold period
if (currentPosition != 0 && barsInPosition >= minHoldingPeriod)
{
if (currentPosition > 0 && riskAdjustedSignal > SignalThreshold * 2) // Long position, strong sell signal
{
Output.WriteLine($"SIGNAL REVERSAL EXIT after {barsInPosition} days - Long to Exit");
return -2; // Exit long
}
if (currentPosition < 0 && riskAdjustedSignal < -SignalThreshold * 2) // Short position, strong buy signal
{
Output.WriteLine($"SIGNAL REVERSAL EXIT after {barsInPosition} days - Short to Exit");
return 2; // Exit short
}
}

// NEW ENTRY SIGNALS (only when flat)
if (currentPosition == 0)
{
// MEAN REVERSION LOGIC:
// Buy when signal is NEGATIVE (price below mean - expect reversion UP)
// Sell when signal is POSITIVE (price above mean - expect reversion DOWN)

if (riskAdjustedSignal < -SignalThreshold)
{
Output.WriteLine($"NEW LONG ENTRY - Price Below Mean, Signal: {riskAdjustedSignal:F4}");
return 1; // Long entry - buy the dip
}
else if (riskAdjustedSignal > SignalThreshold)
{
Output.WriteLine($"NEW SHORT ENTRY - Price Above Mean, Signal: {riskAdjustedSignal:F4}");
return -1; // Short entry - sell the spike
}
}

return 0; // Hold current position
}

private void ExecuteTrade(int tradingSignal)
{
// Update bars in position counter
if (currentPosition != 0)
{
barsInPosition++;
}

// Execute based on trading signal
switch (tradingSignal)
{
case 1: // Buy (Long Entry)
if (currentPosition <= 0)
{
m_BuyOrder.Send();
currentPosition = 1;
barsInPosition = 0; // Reset counter
totalTrades++;
Output.WriteLine($"*** LONG ENTRY at Bar {Bars.CurrentBar}, Price: {Bars.Close[0]:F2} ***");
}
break;

case -1: // Sell Short (Short Entry)
if (currentPosition >= 0)
{
m_SellOrder.Send();
currentPosition = -1;
barsInPosition = 0; // Reset counter
totalTrades++;
Output.WriteLine($"*** SHORT ENTRY at Bar {Bars.CurrentBar}, Price: {Bars.Close[0]:F2} ***");
}
break;

case -2: // Exit Long Position
if (currentPosition > 0)
{
m_ExitLongOrder.Send();
Output.WriteLine($"*** EXIT LONG at Bar {Bars.CurrentBar}, Price: {Bars.Close[0]:F2}, Held {barsInPosition} days ***");
currentPosition = 0;
barsInPosition = 0;
totalTrades++;
}
break;

case 2: // Exit Short Position
if (currentPosition < 0)
{
m_ExitShortOrder.Send();
Output.WriteLine($"*** EXIT SHORT at Bar {Bars.CurrentBar}, Price: {Bars.Close[0]:F2}, Held {barsInPosition} days ***");
currentPosition = 0;
barsInPosition = 0;
totalTrades++;
}
break;
}
}

#endregion

#region Performance Tracking

private void UpdatePerformanceMetrics()
{
// Basic performance tracking
if (Bars.CurrentBar > 1)
{
double currentPrice = Bars.Close[0];
double previousPrice = Bars.Close[1];

// Simple equity calculation
double priceChange = currentPrice - previousPrice;

if (priceChange > peakEquity)
{
peakEquity = priceChange;
}

double drawdown = peakEquity > 0 ? (priceChange - peakEquity) / peakEquity : 0;
if (drawdown < maxDrawdown)
{
maxDrawdown = drawdown;
}
}
}

#endregion

#region Utility Functions

private double CalculateStandardDeviation(List<double> values)
{
if (values.Count < 2) return 0;

double mean = Average(values);
double sumSquares = 0;
for (int i = 0; i < values.Count; i++)
{
sumSquares += Math.Pow(values - mean, 2);
}
return Math.Sqrt(sumSquares / (values.Count - 1));
}

private double Average(List<double> values)
{
if (values.Count == 0) return 0;

double sum = 0;
for (int i = 0; i < values.Count; i++)
{
sum += values;
}
return sum / values.Count;
}

private double MaxValue(List<double> values)
{
if (values.Count == 0) return 0;

double max = values[0];
for (int i = 1; i < values.Count; i++)
{
if (values > max)
max = values;
}
return max;
}

private double MinValue(List<double> values)
{
if (values.Count == 0) return 0;

double min = values[0];
for (int i = 1; i < values.Count; i++)
{
if (values < min)
min = values;
}
return min;
}

private List<double> TakeLast(List<double> source, int count)
{
if (source.Count <= count)
return new List<double>(source);

var result = new List<double>();
for (int i = source.Count - count; i < source.Count; i++)
{
result.Add(source);
}
return result;
}

private void MaintainHistorySize()
{
const int maxHistorySize = 100; // Reduced size

if (velocityHistory.Count > maxHistorySize)
velocityHistory.RemoveAt(0);

if (accelerationHistory.Count > maxHistorySize)
accelerationHistory.RemoveAt(0);

if (jerkHistory.Count > maxHistorySize)
jerkHistory.RemoveAt(0);

if (snapHistory.Count > maxHistorySize)
snapHistory.RemoveAt(0);

if (signalHistory.Count > maxHistorySize)
signalHistory.RemoveAt(0);
}

private void OutputDebugInfo(int tradingSignal, double riskAdjustedSignal)
{
// Output EVERY bar to debug the signal issue
if (Bars.CurrentBar % 1 == 0) // Every single bar
{
string positionStatus = currentPosition > 0 ? $"LONG ({barsInPosition} days)" :
currentPosition < 0 ? $"SHORT ({barsInPosition} days)" : "FLAT";

double currentPrice = Bars.Close[0];
double meanPrice = priceHistory.Count > 5 ? Average(TakeLast(priceHistory, Math.Min(LookbackWindow, priceHistory.Count))) : currentPrice;
string priceVsMean = currentPrice > meanPrice ? "ABOVE" : "BELOW";
double priceDiff = ((currentPrice - meanPrice) / meanPrice) * 100;

Output.WriteLine($"Bar {Bars.CurrentBar}: Price {currentPrice:F2} ({priceVsMean} mean by {priceDiff:F2}%), " +
$"Signal {riskAdjustedSignal:F6}, Threshold ±{SignalThreshold:F6}, {GetActionName(tradingSignal)}, {positionStatus}");

// Show exactly what should happen
if (currentPosition == 0)
{
if (riskAdjustedSignal < -SignalThreshold)
{
Output.WriteLine($" *** LONG TRIGGER: Signal {riskAdjustedSignal:F6} < -{SignalThreshold:F6} ***");
}
else if (riskAdjustedSignal > SignalThreshold)
{
Output.WriteLine($" *** SHORT TRIGGER: Signal {riskAdjustedSignal:F6} > {SignalThreshold:F6} ***");
}
else
{
Output.WriteLine($" No trigger: Signal {riskAdjustedSignal:F6} between ±{SignalThreshold:F6}");
}
}
}
}

private string GetActionName(int signal)
{
switch (signal)
{
case 1: return "LONG ENTRY";
case -1: return "SHORT ENTRY";
case 2: return "EXIT SHORT";
case -2: return "EXIT LONG";
default: return "HOLD";
}
}

#endregion
}
}